program(1.3)
[buildInfo = dict<string, string>({{"coremlc-component-MIL", "3600.16.1"}, {"coremlc-version", "3600.25.1"}})]
{
    func L16<ios18>(tensor<fp16, [1, 16, 352]> ids, tensor<fp16, [1, 16]> mask) {
            tensor<int32, [2]> reshape_0_shape_0 = const()[name = string("reshape_0_shape_0"), val = tensor<int32, [2]>([16, 352])];
            tensor<fp16, [16, 352]> reshape_0 = reshape(shape = reshape_0_shape_0, x = ids)[name = string("reshape_0")];
            tensor<fp16, [16, 352]> mul_0 = mul(x = reshape_0, y = reshape_0)[name = string("mul_0")];
            tensor<int32, [1]> reduce_mean_0_axes_0 = const()[name = string("reduce_mean_0_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_0_keep_dims_0 = const()[name = string("reduce_mean_0_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_0 = reduce_mean(axes = reduce_mean_0_axes_0, keep_dims = reduce_mean_0_keep_dims_0, x = mul_0)[name = string("reduce_mean_0")];
            fp32 rsqrt_0_epsilon_0 = const()[name = string("rsqrt_0_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_0 = rsqrt(epsilon = rsqrt_0_epsilon_0, x = reduce_mean_0)[name = string("rsqrt_0")];
            tensor<fp16, [16, 352]> mul_1 = mul(x = reshape_0, y = rsqrt_0)[name = string("mul_1")];
            tensor<fp16, [352]> mul_2_y_0 = const()[name = string("mul_2_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(64)))];
            tensor<fp16, [16, 352]> mul_2 = mul(x = mul_1, y = mul_2_y_0)[name = string("mul_2")];
            fp16 sub_0_y_0 = const()[name = string("sub_0_y_0"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 16]> sub_0 = sub(x = mask, y = sub_0_y_0)[name = string("sub_0")];
            fp16 mul_3_y_0 = const()[name = string("mul_3_y_0"), val = fp16(0x1.388p+13)];
            tensor<fp16, [1, 16]> mul_3 = mul(x = sub_0, y = mul_3_y_0)[name = string("mul_3")];
            tensor<int32, [3]> reshape_1_shape_0 = const()[name = string("reshape_1_shape_0"), val = tensor<int32, [3]>([1, 1, 16])];
            tensor<fp16, [1, 1, 16]> reshape_1 = reshape(shape = reshape_1_shape_0, x = mul_3)[name = string("reshape_1")];
            tensor<fp16, [16, 352]> mul_4 = mul(x = mul_2, y = mul_2)[name = string("mul_4")];
            tensor<int32, [1]> reduce_mean_1_axes_0 = const()[name = string("reduce_mean_1_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_1_keep_dims_0 = const()[name = string("reduce_mean_1_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_1 = reduce_mean(axes = reduce_mean_1_axes_0, keep_dims = reduce_mean_1_keep_dims_0, x = mul_4)[name = string("reduce_mean_1")];
            fp32 rsqrt_1_epsilon_0 = const()[name = string("rsqrt_1_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_1 = rsqrt(epsilon = rsqrt_1_epsilon_0, x = reduce_mean_1)[name = string("rsqrt_1")];
            tensor<fp16, [16, 352]> mul_5 = mul(x = mul_2, y = rsqrt_1)[name = string("mul_5")];
            tensor<fp16, [352]> mul_6_y_0 = const()[name = string("mul_6_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(832)))];
            tensor<fp16, [16, 352]> mul_6 = mul(x = mul_5, y = mul_6_y_0)[name = string("mul_6")];
            tensor<fp16, [352, 352]> linear_0_weight_0 = const()[name = string("linear_0_weight_0"), val = tensor<fp16, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1600)))];
            tensor<fp16, [352]> linear_0_bias_0 = const()[name = string("linear_0_bias_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(249472)))];
            tensor<fp16, [16, 352]> linear_0 = linear(bias = linear_0_bias_0, weight = linear_0_weight_0, x = mul_6)[name = string("linear_0")];
            tensor<int32, [3]> reshape_2_shape_0 = const()[name = string("reshape_2_shape_0"), val = tensor<int32, [3]>([16, 8, 44])];
            tensor<fp16, [16, 8, 44]> reshape_2 = reshape(shape = reshape_2_shape_0, x = linear_0)[name = string("reshape_2")];
            tensor<int32, [3]> transpose_0_perm_0 = const()[name = string("transpose_0_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [88, 352]> linear_1_weight_0 = const()[name = string("linear_1_weight_0"), val = tensor<fp16, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(250240)))];
            tensor<fp16, [88]> linear_1_bias_0 = const()[name = string("linear_1_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [16, 88]> linear_1 = linear(bias = linear_1_bias_0, weight = linear_1_weight_0, x = mul_6)[name = string("linear_1")];
            tensor<int32, [3]> reshape_3_shape_0 = const()[name = string("reshape_3_shape_0"), val = tensor<int32, [3]>([16, 2, 44])];
            tensor<fp16, [16, 2, 44]> reshape_3 = reshape(shape = reshape_3_shape_0, x = linear_1)[name = string("reshape_3")];
            tensor<int32, [3]> transpose_1_perm_0 = const()[name = string("transpose_1_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [88, 352]> linear_2_weight_0 = const()[name = string("linear_2_weight_0"), val = tensor<fp16, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312512)))];
            tensor<fp16, [88]> linear_2_bias_0 = const()[name = string("linear_2_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [16, 88]> linear_2 = linear(bias = linear_2_bias_0, weight = linear_2_weight_0, x = mul_6)[name = string("linear_2")];
            tensor<int32, [3]> reshape_4_shape_0 = const()[name = string("reshape_4_shape_0"), val = tensor<int32, [3]>([16, 2, 44])];
            tensor<fp16, [16, 2, 44]> reshape_4 = reshape(shape = reshape_4_shape_0, x = linear_2)[name = string("reshape_4")];
            tensor<int32, [3]> transpose_2_perm_0 = const()[name = string("transpose_2_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 16, 44]> transpose_0 = transpose(perm = transpose_0_perm_0, x = reshape_2)[name = string("transpose_63")];
            tensor<fp16, [8, 16, 44]> mul_7 = mul(x = transpose_0, y = transpose_0)[name = string("mul_7")];
            tensor<int32, [1]> reduce_mean_2_axes_0 = const()[name = string("reduce_mean_2_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_2_keep_dims_0 = const()[name = string("reduce_mean_2_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 16, 1]> reduce_mean_2 = reduce_mean(axes = reduce_mean_2_axes_0, keep_dims = reduce_mean_2_keep_dims_0, x = mul_7)[name = string("reduce_mean_2")];
            fp32 rsqrt_2_epsilon_0 = const()[name = string("rsqrt_2_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 16, 1]> rsqrt_2 = rsqrt(epsilon = rsqrt_2_epsilon_0, x = reduce_mean_2)[name = string("rsqrt_2")];
            tensor<fp16, [8, 16, 44]> mul_8 = mul(x = transpose_0, y = rsqrt_2)[name = string("mul_8")];
            tensor<fp16, [44]> mul_9_y_0 = const()[name = string("mul_9_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374528)))];
            tensor<fp16, [8, 16, 44]> mul_9 = mul(x = mul_8, y = mul_9_y_0)[name = string("mul_9")];
            tensor<int32, [3]> slice_by_index_0_begin_0 = const()[name = string("slice_by_index_0_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_0_end_0 = const()[name = string("slice_by_index_0_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_0_end_mask_0 = const()[name = string("slice_by_index_0_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 16, 22]> slice_by_index_0 = slice_by_index(begin = slice_by_index_0_begin_0, end = slice_by_index_0_end_0, end_mask = slice_by_index_0_end_mask_0, x = mul_9)[name = string("slice_by_index_0")];
            tensor<int32, [3]> slice_by_index_1_begin_0 = const()[name = string("slice_by_index_1_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_1_end_0 = const()[name = string("slice_by_index_1_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_1_end_mask_0 = const()[name = string("slice_by_index_1_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 16, 22]> slice_by_index_1 = slice_by_index(begin = slice_by_index_1_begin_0, end = slice_by_index_1_end_0, end_mask = slice_by_index_1_end_mask_0, x = mul_9)[name = string("slice_by_index_1")];
            int32 concat_0_axis_0 = const()[name = string("concat_0_axis_0"), val = int32(-1)];
            bool concat_0_interleave_0 = const()[name = string("concat_0_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 16, 44]> concat_0 = concat(axis = concat_0_axis_0, interleave = concat_0_interleave_0, values = (slice_by_index_1, slice_by_index_0))[name = string("concat_0")];
            tensor<fp16, [44]> mul_10_y_0 = const()[name = string("mul_10_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 16, 44]> mul_10 = mul(x = concat_0, y = mul_10_y_0)[name = string("mul_10")];
            tensor<fp16, [1, 16, 44]> mul_11_y_0 = const()[name = string("mul_11_y_0"), val = tensor<fp16, [1, 16, 44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16047488)))];
            tensor<fp16, [8, 16, 44]> mul_11 = mul(x = mul_9, y = mul_11_y_0)[name = string("mul_11")];
            tensor<fp16, [1, 16, 44]> mul_12_y_0 = const()[name = string("mul_12_y_0"), val = tensor<fp16, [1, 16, 44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16048960)))];
            tensor<fp16, [8, 16, 44]> mul_12 = mul(x = mul_10, y = mul_12_y_0)[name = string("mul_12")];
            tensor<fp16, [8, 16, 44]> add_0 = add(x = mul_11, y = mul_12)[name = string("add_0")];
            tensor<fp16, [2, 16, 44]> transpose_1 = transpose(perm = transpose_1_perm_0, x = reshape_3)[name = string("transpose_62")];
            tensor<fp16, [2, 16, 44]> mul_13 = mul(x = transpose_1, y = transpose_1)[name = string("mul_13")];
            tensor<int32, [1]> reduce_mean_3_axes_0 = const()[name = string("reduce_mean_3_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_3_keep_dims_0 = const()[name = string("reduce_mean_3_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 16, 1]> reduce_mean_3 = reduce_mean(axes = reduce_mean_3_axes_0, keep_dims = reduce_mean_3_keep_dims_0, x = mul_13)[name = string("reduce_mean_3")];
            fp32 rsqrt_3_epsilon_0 = const()[name = string("rsqrt_3_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 16, 1]> rsqrt_3 = rsqrt(epsilon = rsqrt_3_epsilon_0, x = reduce_mean_3)[name = string("rsqrt_3")];
            tensor<fp16, [2, 16, 44]> mul_14 = mul(x = transpose_1, y = rsqrt_3)[name = string("mul_14")];
            tensor<fp16, [44]> mul_15_y_0 = const()[name = string("mul_15_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(376448)))];
            tensor<fp16, [2, 16, 44]> mul_15 = mul(x = mul_14, y = mul_15_y_0)[name = string("mul_15")];
            tensor<int32, [3]> slice_by_index_2_begin_0 = const()[name = string("slice_by_index_2_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_2_end_0 = const()[name = string("slice_by_index_2_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_2_end_mask_0 = const()[name = string("slice_by_index_2_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 16, 22]> slice_by_index_2 = slice_by_index(begin = slice_by_index_2_begin_0, end = slice_by_index_2_end_0, end_mask = slice_by_index_2_end_mask_0, x = mul_15)[name = string("slice_by_index_2")];
            tensor<int32, [3]> slice_by_index_3_begin_0 = const()[name = string("slice_by_index_3_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_3_end_0 = const()[name = string("slice_by_index_3_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_3_end_mask_0 = const()[name = string("slice_by_index_3_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 16, 22]> slice_by_index_3 = slice_by_index(begin = slice_by_index_3_begin_0, end = slice_by_index_3_end_0, end_mask = slice_by_index_3_end_mask_0, x = mul_15)[name = string("slice_by_index_3")];
            int32 concat_1_axis_0 = const()[name = string("concat_1_axis_0"), val = int32(-1)];
            bool concat_1_interleave_0 = const()[name = string("concat_1_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 16, 44]> concat_1 = concat(axis = concat_1_axis_0, interleave = concat_1_interleave_0, values = (slice_by_index_3, slice_by_index_2))[name = string("concat_1")];
            tensor<fp16, [44]> mul_16_y_0 = const()[name = string("mul_16_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 16, 44]> mul_16 = mul(x = concat_1, y = mul_16_y_0)[name = string("mul_16")];
            tensor<fp16, [2, 16, 44]> mul_17 = mul(x = mul_15, y = mul_11_y_0)[name = string("mul_17")];
            tensor<fp16, [2, 16, 44]> mul_18 = mul(x = mul_16, y = mul_12_y_0)[name = string("mul_18")];
            tensor<fp16, [2, 16, 44]> add_1 = add(x = mul_17, y = mul_18)[name = string("add_1")];
            tensor<int32, [4]> reshape_5_shape_0 = const()[name = string("reshape_5_shape_0"), val = tensor<int32, [4]>([2, 1, 16, 44])];
            tensor<fp16, [2, 1, 16, 44]> reshape_5 = reshape(shape = reshape_5_shape_0, x = add_1)[name = string("reshape_5")];
            tensor<int32, [4]> tile_0_reps_0 = const()[name = string("tile_0_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 16, 44]> tile_0 = tile(reps = tile_0_reps_0, x = reshape_5)[name = string("tile_0")];
            tensor<int32, [3]> reshape_6_shape_0 = const()[name = string("reshape_6_shape_0"), val = tensor<int32, [3]>([8, 16, 44])];
            tensor<fp16, [8, 16, 44]> reshape_6 = reshape(shape = reshape_6_shape_0, x = tile_0)[name = string("reshape_6")];
            tensor<int32, [4]> reshape_7_shape_0 = const()[name = string("reshape_7_shape_0"), val = tensor<int32, [4]>([2, 1, 16, 44])];
            tensor<fp16, [2, 16, 44]> transpose_2 = transpose(perm = transpose_2_perm_0, x = reshape_4)[name = string("transpose_61")];
            tensor<fp16, [2, 1, 16, 44]> reshape_7 = reshape(shape = reshape_7_shape_0, x = transpose_2)[name = string("reshape_7")];
            tensor<int32, [4]> tile_1_reps_0 = const()[name = string("tile_1_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 16, 44]> tile_1 = tile(reps = tile_1_reps_0, x = reshape_7)[name = string("tile_1")];
            tensor<int32, [3]> reshape_8_shape_0 = const()[name = string("reshape_8_shape_0"), val = tensor<int32, [3]>([8, 16, 44])];
            tensor<fp16, [8, 16, 44]> reshape_8 = reshape(shape = reshape_8_shape_0, x = tile_1)[name = string("reshape_8")];
            fp16 mul_19_y_0 = const()[name = string("mul_19_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 16, 44]> mul_19 = mul(x = add_0, y = mul_19_y_0)[name = string("mul_19")];
            bool matmul_0_transpose_y_0 = const()[name = string("matmul_0_transpose_y_0"), val = bool(true)];
            bool matmul_0_transpose_x_0 = const()[name = string("matmul_0_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 16, 16]> matmul_0 = matmul(transpose_x = matmul_0_transpose_x_0, transpose_y = matmul_0_transpose_y_0, x = mul_19, y = reshape_6)[name = string("matmul_0")];
            tensor<fp16, [8, 16, 16]> add_2 = add(x = matmul_0, y = reshape_1)[name = string("add_2")];
            int32 softmax_0_axis_0 = const()[name = string("softmax_0_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 16, 16]> softmax_0 = softmax(axis = softmax_0_axis_0, x = add_2)[name = string("softmax_0")];
            bool matmul_1_transpose_x_0 = const()[name = string("matmul_1_transpose_x_0"), val = bool(false)];
            bool matmul_1_transpose_y_0 = const()[name = string("matmul_1_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 16, 44]> matmul_1 = matmul(transpose_x = matmul_1_transpose_x_0, transpose_y = matmul_1_transpose_y_0, x = softmax_0, y = reshape_8)[name = string("matmul_1")];
            tensor<int32, [3]> transpose_3_perm_0 = const()[name = string("transpose_3_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_9_shape_0 = const()[name = string("reshape_9_shape_0"), val = tensor<int32, [2]>([16, 352])];
            tensor<fp16, [16, 8, 44]> transpose_3 = transpose(perm = transpose_3_perm_0, x = matmul_1)[name = string("transpose_60")];
            tensor<fp16, [16, 352]> reshape_9 = reshape(shape = reshape_9_shape_0, x = transpose_3)[name = string("reshape_9")];
            tensor<fp16, [352, 352]> linear_3_weight_0 = const()[name = string("linear_3_weight_0"), val = tensor<fp16, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(376640)))];
            tensor<fp16, [16, 352]> linear_3 = linear(bias = linear_0_bias_0, weight = linear_3_weight_0, x = reshape_9)[name = string("linear_3")];
            tensor<fp16, [16, 352]> add_3 = add(x = mul_2, y = linear_3)[name = string("add_3")];
            tensor<fp16, [16, 352]> mul_20 = mul(x = add_3, y = add_3)[name = string("mul_20")];
            tensor<int32, [1]> reduce_mean_4_axes_0 = const()[name = string("reduce_mean_4_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_4_keep_dims_0 = const()[name = string("reduce_mean_4_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_4 = reduce_mean(axes = reduce_mean_4_axes_0, keep_dims = reduce_mean_4_keep_dims_0, x = mul_20)[name = string("reduce_mean_4")];
            fp32 rsqrt_4_epsilon_0 = const()[name = string("rsqrt_4_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_4 = rsqrt(epsilon = rsqrt_4_epsilon_0, x = reduce_mean_4)[name = string("rsqrt_4")];
            tensor<fp16, [16, 352]> mul_21 = mul(x = add_3, y = rsqrt_4)[name = string("mul_21")];
            tensor<fp16, [352]> mul_22_y_0 = const()[name = string("mul_22_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(624512)))];
            tensor<fp16, [16, 352]> mul_22 = mul(x = mul_21, y = mul_22_y_0)[name = string("mul_22")];
            tensor<fp16, [960, 352]> linear_4_weight_0 = const()[name = string("linear_4_weight_0"), val = tensor<fp16, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(625280)))];
            tensor<fp16, [960]> linear_4_bias_0 = const()[name = string("linear_4_bias_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1301184)))];
            tensor<fp16, [16, 960]> linear_4 = linear(bias = linear_4_bias_0, weight = linear_4_weight_0, x = mul_22)[name = string("linear_4")];
            tensor<fp16, [960, 352]> linear_5_weight_0 = const()[name = string("linear_5_weight_0"), val = tensor<fp16, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1303168)))];
            tensor<fp16, [16, 960]> linear_5 = linear(bias = linear_4_bias_0, weight = linear_5_weight_0, x = mul_22)[name = string("linear_5")];
            fp16 mul_23_y_0 = const()[name = string("mul_23_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [16, 960]> mul_23 = mul(x = linear_4, y = mul_23_y_0)[name = string("mul_23")];
            tensor<fp16, [16, 960]> tanh_0 = tanh(x = mul_23)[name = string("tanh_0")];
            fp16 mul_24_x_0 = const()[name = string("mul_24_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [16, 960]> mul_24 = mul(x = mul_24_x_0, y = tanh_0)[name = string("mul_24")];
            fp16 add_4_x_0 = const()[name = string("add_4_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [16, 960]> add_4 = add(x = add_4_x_0, y = mul_24)[name = string("add_4")];
            tensor<fp16, [16, 960]> mul_25 = mul(x = linear_4, y = add_4)[name = string("mul_25")];
            tensor<fp16, [16, 960]> mul_26 = mul(x = mul_25, y = linear_5)[name = string("mul_26")];
            tensor<fp16, [352, 960]> linear_6_weight_0 = const()[name = string("linear_6_weight_0"), val = tensor<fp16, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1979072)))];
            tensor<fp16, [16, 352]> linear_6 = linear(bias = linear_0_bias_0, weight = linear_6_weight_0, x = mul_26)[name = string("linear_6")];
            tensor<fp16, [16, 352]> add_5 = add(x = add_3, y = linear_6)[name = string("add_5")];
            tensor<fp16, [16, 352]> mul_27 = mul(x = add_5, y = add_5)[name = string("mul_27")];
            tensor<int32, [1]> reduce_mean_5_axes_0 = const()[name = string("reduce_mean_5_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_5_keep_dims_0 = const()[name = string("reduce_mean_5_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_5 = reduce_mean(axes = reduce_mean_5_axes_0, keep_dims = reduce_mean_5_keep_dims_0, x = mul_27)[name = string("reduce_mean_5")];
            fp32 rsqrt_5_epsilon_0 = const()[name = string("rsqrt_5_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_5 = rsqrt(epsilon = rsqrt_5_epsilon_0, x = reduce_mean_5)[name = string("rsqrt_5")];
            tensor<fp16, [16, 352]> mul_28 = mul(x = add_5, y = rsqrt_5)[name = string("mul_28")];
            tensor<fp16, [352]> mul_29_y_0 = const()[name = string("mul_29_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2654976)))];
            tensor<fp16, [16, 352]> mul_29 = mul(x = mul_28, y = mul_29_y_0)[name = string("mul_29")];
            tensor<fp16, [16, 352]> mul_30 = mul(x = mul_29, y = mul_29)[name = string("mul_30")];
            tensor<int32, [1]> reduce_mean_6_axes_0 = const()[name = string("reduce_mean_6_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_6_keep_dims_0 = const()[name = string("reduce_mean_6_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_6 = reduce_mean(axes = reduce_mean_6_axes_0, keep_dims = reduce_mean_6_keep_dims_0, x = mul_30)[name = string("reduce_mean_6")];
            fp32 rsqrt_6_epsilon_0 = const()[name = string("rsqrt_6_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_6 = rsqrt(epsilon = rsqrt_6_epsilon_0, x = reduce_mean_6)[name = string("rsqrt_6")];
            tensor<fp16, [16, 352]> mul_31 = mul(x = mul_29, y = rsqrt_6)[name = string("mul_31")];
            tensor<fp16, [352]> mul_32_y_0 = const()[name = string("mul_32_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2655744)))];
            tensor<fp16, [16, 352]> mul_32 = mul(x = mul_31, y = mul_32_y_0)[name = string("mul_32")];
            tensor<fp16, [352, 352]> tern_1_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2656512))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_1_q_weight_0_palettized")];
            tensor<fp16, [16, 352]> tern_1_q = linear(bias = linear_0_bias_0, weight = tern_1_q_weight_0_palettized, x = mul_32)[name = string("tern_1_q")];
            tensor<fp16, [352]> mul_33_y_0 = const()[name = string("mul_33_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2687552)))];
            tensor<fp16, [16, 352]> mul_33 = mul(x = tern_1_q, y = mul_33_y_0)[name = string("mul_33")];
            tensor<int32, [3]> reshape_10_shape_0 = const()[name = string("reshape_10_shape_0"), val = tensor<int32, [3]>([16, 8, 44])];
            tensor<fp16, [16, 8, 44]> reshape_10 = reshape(shape = reshape_10_shape_0, x = mul_33)[name = string("reshape_10")];
            tensor<int32, [3]> transpose_4_perm_0 = const()[name = string("transpose_4_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_36_y_0 = const()[name = string("mul_36_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2688320)))];
            tensor<fp16, [16, 352]> mul_36 = mul(x = mul_31, y = mul_36_y_0)[name = string("mul_36")];
            tensor<fp16, [88, 352]> tern_1_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2689088))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_1_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_1_k_bias_0 = const()[name = string("tern_1_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [16, 88]> tern_1_k = linear(bias = tern_1_k_bias_0, weight = tern_1_k_weight_0_palettized, x = mul_36)[name = string("tern_1_k")];
            tensor<fp16, [88]> mul_37_y_0 = const()[name = string("mul_37_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2696896)))];
            tensor<fp16, [16, 88]> mul_37 = mul(x = tern_1_k, y = mul_37_y_0)[name = string("mul_37")];
            tensor<int32, [3]> reshape_11_shape_0 = const()[name = string("reshape_11_shape_0"), val = tensor<int32, [3]>([16, 2, 44])];
            tensor<fp16, [16, 2, 44]> reshape_11 = reshape(shape = reshape_11_shape_0, x = mul_37)[name = string("reshape_11")];
            tensor<int32, [3]> transpose_5_perm_0 = const()[name = string("transpose_5_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_40_y_0 = const()[name = string("mul_40_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2697152)))];
            tensor<fp16, [16, 352]> mul_40 = mul(x = mul_31, y = mul_40_y_0)[name = string("mul_40")];
            tensor<fp16, [88, 352]> tern_1_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2697920))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_1_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_1_v_bias_0 = const()[name = string("tern_1_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [16, 88]> tern_1_v = linear(bias = tern_1_v_bias_0, weight = tern_1_v_weight_0_palettized, x = mul_40)[name = string("tern_1_v")];
            tensor<fp16, [88]> mul_41_y_0 = const()[name = string("mul_41_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2705728)))];
            tensor<fp16, [16, 88]> mul_41 = mul(x = tern_1_v, y = mul_41_y_0)[name = string("mul_41")];
            tensor<int32, [3]> reshape_12_shape_0 = const()[name = string("reshape_12_shape_0"), val = tensor<int32, [3]>([16, 2, 44])];
            tensor<fp16, [16, 2, 44]> reshape_12 = reshape(shape = reshape_12_shape_0, x = mul_41)[name = string("reshape_12")];
            tensor<int32, [3]> transpose_6_perm_0 = const()[name = string("transpose_6_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 16, 44]> transpose_4 = transpose(perm = transpose_4_perm_0, x = reshape_10)[name = string("transpose_59")];
            tensor<fp16, [8, 16, 44]> mul_42 = mul(x = transpose_4, y = transpose_4)[name = string("mul_42")];
            tensor<int32, [1]> reduce_mean_9_axes_0 = const()[name = string("reduce_mean_9_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_9_keep_dims_0 = const()[name = string("reduce_mean_9_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 16, 1]> reduce_mean_9 = reduce_mean(axes = reduce_mean_9_axes_0, keep_dims = reduce_mean_9_keep_dims_0, x = mul_42)[name = string("reduce_mean_9")];
            fp32 rsqrt_9_epsilon_0 = const()[name = string("rsqrt_9_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 16, 1]> rsqrt_9 = rsqrt(epsilon = rsqrt_9_epsilon_0, x = reduce_mean_9)[name = string("rsqrt_9")];
            tensor<fp16, [8, 16, 44]> mul_43 = mul(x = transpose_4, y = rsqrt_9)[name = string("mul_43")];
            tensor<fp16, [44]> mul_44_y_0 = const()[name = string("mul_44_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2705984)))];
            tensor<fp16, [8, 16, 44]> mul_44 = mul(x = mul_43, y = mul_44_y_0)[name = string("mul_44")];
            tensor<int32, [3]> slice_by_index_4_begin_0 = const()[name = string("slice_by_index_4_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_4_end_0 = const()[name = string("slice_by_index_4_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_4_end_mask_0 = const()[name = string("slice_by_index_4_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 16, 22]> slice_by_index_4 = slice_by_index(begin = slice_by_index_4_begin_0, end = slice_by_index_4_end_0, end_mask = slice_by_index_4_end_mask_0, x = mul_44)[name = string("slice_by_index_4")];
            tensor<int32, [3]> slice_by_index_5_begin_0 = const()[name = string("slice_by_index_5_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_5_end_0 = const()[name = string("slice_by_index_5_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_5_end_mask_0 = const()[name = string("slice_by_index_5_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 16, 22]> slice_by_index_5 = slice_by_index(begin = slice_by_index_5_begin_0, end = slice_by_index_5_end_0, end_mask = slice_by_index_5_end_mask_0, x = mul_44)[name = string("slice_by_index_5")];
            int32 concat_2_axis_0 = const()[name = string("concat_2_axis_0"), val = int32(-1)];
            bool concat_2_interleave_0 = const()[name = string("concat_2_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 16, 44]> concat_2 = concat(axis = concat_2_axis_0, interleave = concat_2_interleave_0, values = (slice_by_index_5, slice_by_index_4))[name = string("concat_2")];
            tensor<fp16, [44]> mul_45_y_0 = const()[name = string("mul_45_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 16, 44]> mul_45 = mul(x = concat_2, y = mul_45_y_0)[name = string("mul_45")];
            tensor<fp16, [8, 16, 44]> mul_46 = mul(x = mul_44, y = mul_11_y_0)[name = string("mul_46")];
            tensor<fp16, [8, 16, 44]> mul_47 = mul(x = mul_45, y = mul_12_y_0)[name = string("mul_47")];
            tensor<fp16, [8, 16, 44]> add_6 = add(x = mul_46, y = mul_47)[name = string("add_6")];
            tensor<fp16, [2, 16, 44]> transpose_5 = transpose(perm = transpose_5_perm_0, x = reshape_11)[name = string("transpose_58")];
            tensor<fp16, [2, 16, 44]> mul_48 = mul(x = transpose_5, y = transpose_5)[name = string("mul_48")];
            tensor<int32, [1]> reduce_mean_10_axes_0 = const()[name = string("reduce_mean_10_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_10_keep_dims_0 = const()[name = string("reduce_mean_10_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 16, 1]> reduce_mean_10 = reduce_mean(axes = reduce_mean_10_axes_0, keep_dims = reduce_mean_10_keep_dims_0, x = mul_48)[name = string("reduce_mean_10")];
            fp32 rsqrt_10_epsilon_0 = const()[name = string("rsqrt_10_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 16, 1]> rsqrt_10 = rsqrt(epsilon = rsqrt_10_epsilon_0, x = reduce_mean_10)[name = string("rsqrt_10")];
            tensor<fp16, [2, 16, 44]> mul_49 = mul(x = transpose_5, y = rsqrt_10)[name = string("mul_49")];
            tensor<fp16, [44]> mul_50_y_0 = const()[name = string("mul_50_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2706176)))];
            tensor<fp16, [2, 16, 44]> mul_50 = mul(x = mul_49, y = mul_50_y_0)[name = string("mul_50")];
            tensor<int32, [3]> slice_by_index_6_begin_0 = const()[name = string("slice_by_index_6_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_6_end_0 = const()[name = string("slice_by_index_6_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_6_end_mask_0 = const()[name = string("slice_by_index_6_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 16, 22]> slice_by_index_6 = slice_by_index(begin = slice_by_index_6_begin_0, end = slice_by_index_6_end_0, end_mask = slice_by_index_6_end_mask_0, x = mul_50)[name = string("slice_by_index_6")];
            tensor<int32, [3]> slice_by_index_7_begin_0 = const()[name = string("slice_by_index_7_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_7_end_0 = const()[name = string("slice_by_index_7_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_7_end_mask_0 = const()[name = string("slice_by_index_7_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 16, 22]> slice_by_index_7 = slice_by_index(begin = slice_by_index_7_begin_0, end = slice_by_index_7_end_0, end_mask = slice_by_index_7_end_mask_0, x = mul_50)[name = string("slice_by_index_7")];
            int32 concat_3_axis_0 = const()[name = string("concat_3_axis_0"), val = int32(-1)];
            bool concat_3_interleave_0 = const()[name = string("concat_3_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 16, 44]> concat_3 = concat(axis = concat_3_axis_0, interleave = concat_3_interleave_0, values = (slice_by_index_7, slice_by_index_6))[name = string("concat_3")];
            tensor<fp16, [44]> mul_51_y_0 = const()[name = string("mul_51_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 16, 44]> mul_51 = mul(x = concat_3, y = mul_51_y_0)[name = string("mul_51")];
            tensor<fp16, [2, 16, 44]> mul_52 = mul(x = mul_50, y = mul_11_y_0)[name = string("mul_52")];
            tensor<fp16, [2, 16, 44]> mul_53 = mul(x = mul_51, y = mul_12_y_0)[name = string("mul_53")];
            tensor<fp16, [2, 16, 44]> add_7 = add(x = mul_52, y = mul_53)[name = string("add_7")];
            tensor<int32, [4]> reshape_13_shape_0 = const()[name = string("reshape_13_shape_0"), val = tensor<int32, [4]>([2, 1, 16, 44])];
            tensor<fp16, [2, 1, 16, 44]> reshape_13 = reshape(shape = reshape_13_shape_0, x = add_7)[name = string("reshape_13")];
            tensor<int32, [4]> tile_2_reps_0 = const()[name = string("tile_2_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 16, 44]> tile_2 = tile(reps = tile_2_reps_0, x = reshape_13)[name = string("tile_2")];
            tensor<int32, [3]> reshape_14_shape_0 = const()[name = string("reshape_14_shape_0"), val = tensor<int32, [3]>([8, 16, 44])];
            tensor<fp16, [8, 16, 44]> reshape_14 = reshape(shape = reshape_14_shape_0, x = tile_2)[name = string("reshape_14")];
            tensor<int32, [4]> reshape_15_shape_0 = const()[name = string("reshape_15_shape_0"), val = tensor<int32, [4]>([2, 1, 16, 44])];
            tensor<fp16, [2, 16, 44]> transpose_6 = transpose(perm = transpose_6_perm_0, x = reshape_12)[name = string("transpose_57")];
            tensor<fp16, [2, 1, 16, 44]> reshape_15 = reshape(shape = reshape_15_shape_0, x = transpose_6)[name = string("reshape_15")];
            tensor<int32, [4]> tile_3_reps_0 = const()[name = string("tile_3_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 16, 44]> tile_3 = tile(reps = tile_3_reps_0, x = reshape_15)[name = string("tile_3")];
            tensor<int32, [3]> reshape_16_shape_0 = const()[name = string("reshape_16_shape_0"), val = tensor<int32, [3]>([8, 16, 44])];
            tensor<fp16, [8, 16, 44]> reshape_16 = reshape(shape = reshape_16_shape_0, x = tile_3)[name = string("reshape_16")];
            fp16 mul_54_y_0 = const()[name = string("mul_54_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 16, 44]> mul_54 = mul(x = add_6, y = mul_54_y_0)[name = string("mul_54")];
            bool matmul_2_transpose_y_0 = const()[name = string("matmul_2_transpose_y_0"), val = bool(true)];
            bool matmul_2_transpose_x_0 = const()[name = string("matmul_2_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 16, 16]> matmul_2 = matmul(transpose_x = matmul_2_transpose_x_0, transpose_y = matmul_2_transpose_y_0, x = mul_54, y = reshape_14)[name = string("matmul_2")];
            tensor<fp16, [8, 16, 16]> add_8 = add(x = matmul_2, y = reshape_1)[name = string("add_8")];
            int32 softmax_1_axis_0 = const()[name = string("softmax_1_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 16, 16]> softmax_1 = softmax(axis = softmax_1_axis_0, x = add_8)[name = string("softmax_1")];
            bool matmul_3_transpose_x_0 = const()[name = string("matmul_3_transpose_x_0"), val = bool(false)];
            bool matmul_3_transpose_y_0 = const()[name = string("matmul_3_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 16, 44]> matmul_3 = matmul(transpose_x = matmul_3_transpose_x_0, transpose_y = matmul_3_transpose_y_0, x = softmax_1, y = reshape_16)[name = string("matmul_3")];
            tensor<int32, [3]> transpose_7_perm_0 = const()[name = string("transpose_7_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_17_shape_0 = const()[name = string("reshape_17_shape_0"), val = tensor<int32, [2]>([16, 352])];
            tensor<fp16, [16, 8, 44]> transpose_7 = transpose(perm = transpose_7_perm_0, x = matmul_3)[name = string("transpose_56")];
            tensor<fp16, [16, 352]> reshape_17 = reshape(shape = reshape_17_shape_0, x = transpose_7)[name = string("reshape_17")];
            tensor<fp16, [16, 352]> mul_55 = mul(x = reshape_17, y = reshape_17)[name = string("mul_55")];
            tensor<int32, [1]> reduce_mean_11_axes_0 = const()[name = string("reduce_mean_11_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_11_keep_dims_0 = const()[name = string("reduce_mean_11_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_11 = reduce_mean(axes = reduce_mean_11_axes_0, keep_dims = reduce_mean_11_keep_dims_0, x = mul_55)[name = string("reduce_mean_11")];
            fp32 rsqrt_11_epsilon_0 = const()[name = string("rsqrt_11_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_11 = rsqrt(epsilon = rsqrt_11_epsilon_0, x = reduce_mean_11)[name = string("rsqrt_11")];
            tensor<fp16, [16, 352]> mul_56 = mul(x = reshape_17, y = rsqrt_11)[name = string("mul_56")];
            tensor<fp16, [352]> mul_57_y_0 = const()[name = string("mul_57_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2706368)))];
            tensor<fp16, [16, 352]> mul_57 = mul(x = mul_56, y = mul_57_y_0)[name = string("mul_57")];
            tensor<fp16, [352, 352]> tern_1_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2707136))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_1_o_weight_0_palettized")];
            tensor<fp16, [16, 352]> tern_1_o = linear(bias = linear_0_bias_0, weight = tern_1_o_weight_0_palettized, x = mul_57)[name = string("tern_1_o")];
            tensor<fp16, [352]> mul_58_y_0 = const()[name = string("mul_58_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2738176)))];
            tensor<fp16, [16, 352]> mul_58 = mul(x = tern_1_o, y = mul_58_y_0)[name = string("mul_58")];
            tensor<fp16, [16, 352]> add_9 = add(x = add_5, y = mul_58)[name = string("add_9")];
            tensor<fp16, [16, 352]> mul_59 = mul(x = add_9, y = add_9)[name = string("mul_59")];
            tensor<int32, [1]> reduce_mean_12_axes_0 = const()[name = string("reduce_mean_12_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_12_keep_dims_0 = const()[name = string("reduce_mean_12_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_12 = reduce_mean(axes = reduce_mean_12_axes_0, keep_dims = reduce_mean_12_keep_dims_0, x = mul_59)[name = string("reduce_mean_12")];
            fp32 rsqrt_12_epsilon_0 = const()[name = string("rsqrt_12_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_12 = rsqrt(epsilon = rsqrt_12_epsilon_0, x = reduce_mean_12)[name = string("rsqrt_12")];
            tensor<fp16, [16, 352]> mul_60 = mul(x = add_9, y = rsqrt_12)[name = string("mul_60")];
            tensor<fp16, [352]> mul_61_y_0 = const()[name = string("mul_61_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2738944)))];
            tensor<fp16, [16, 352]> mul_61 = mul(x = mul_60, y = mul_61_y_0)[name = string("mul_61")];
            tensor<fp16, [16, 352]> mul_62 = mul(x = mul_61, y = mul_61)[name = string("mul_62")];
            tensor<int32, [1]> reduce_mean_13_axes_0 = const()[name = string("reduce_mean_13_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_13_keep_dims_0 = const()[name = string("reduce_mean_13_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_13 = reduce_mean(axes = reduce_mean_13_axes_0, keep_dims = reduce_mean_13_keep_dims_0, x = mul_62)[name = string("reduce_mean_13")];
            fp32 rsqrt_13_epsilon_0 = const()[name = string("rsqrt_13_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_13 = rsqrt(epsilon = rsqrt_13_epsilon_0, x = reduce_mean_13)[name = string("rsqrt_13")];
            tensor<fp16, [16, 352]> mul_63 = mul(x = mul_61, y = rsqrt_13)[name = string("mul_63")];
            tensor<fp16, [352]> mul_64_y_0 = const()[name = string("mul_64_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2739712)))];
            tensor<fp16, [16, 352]> mul_64 = mul(x = mul_63, y = mul_64_y_0)[name = string("mul_64")];
            tensor<fp16, [960, 352]> tern_1_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2740480))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_1_w1_weight_0_palettized")];
            tensor<fp16, [16, 960]> tern_1_w1 = linear(bias = linear_4_bias_0, weight = tern_1_w1_weight_0_palettized, x = mul_64)[name = string("tern_1_w1")];
            tensor<fp16, [960]> mul_65_y_0 = const()[name = string("mul_65_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2825024)))];
            tensor<fp16, [16, 960]> mul_65 = mul(x = tern_1_w1, y = mul_65_y_0)[name = string("mul_65")];
            tensor<fp16, [352]> mul_68_y_0 = const()[name = string("mul_68_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2827008)))];
            tensor<fp16, [16, 352]> mul_68 = mul(x = mul_63, y = mul_68_y_0)[name = string("mul_68")];
            tensor<fp16, [960, 352]> tern_1_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2827776))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_1_w3_weight_0_palettized")];
            tensor<fp16, [16, 960]> tern_1_w3 = linear(bias = linear_4_bias_0, weight = tern_1_w3_weight_0_palettized, x = mul_68)[name = string("tern_1_w3")];
            tensor<fp16, [960]> mul_69_y_0 = const()[name = string("mul_69_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2912320)))];
            tensor<fp16, [16, 960]> mul_69 = mul(x = tern_1_w3, y = mul_69_y_0)[name = string("mul_69")];
            fp16 mul_70_y_0 = const()[name = string("mul_70_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [16, 960]> mul_70 = mul(x = mul_65, y = mul_70_y_0)[name = string("mul_70")];
            tensor<fp16, [16, 960]> tanh_1 = tanh(x = mul_70)[name = string("tanh_1")];
            fp16 mul_71_x_0 = const()[name = string("mul_71_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [16, 960]> mul_71 = mul(x = mul_71_x_0, y = tanh_1)[name = string("mul_71")];
            fp16 add_10_x_0 = const()[name = string("add_10_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [16, 960]> add_10 = add(x = add_10_x_0, y = mul_71)[name = string("add_10")];
            tensor<fp16, [16, 960]> mul_72 = mul(x = mul_65, y = add_10)[name = string("mul_72")];
            tensor<fp16, [16, 960]> mul_73 = mul(x = mul_72, y = mul_69)[name = string("mul_73")];
            tensor<fp16, [16, 960]> mul_74 = mul(x = mul_73, y = mul_73)[name = string("mul_74")];
            tensor<int32, [1]> reduce_mean_15_axes_0 = const()[name = string("reduce_mean_15_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_15_keep_dims_0 = const()[name = string("reduce_mean_15_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_15 = reduce_mean(axes = reduce_mean_15_axes_0, keep_dims = reduce_mean_15_keep_dims_0, x = mul_74)[name = string("reduce_mean_15")];
            fp32 rsqrt_15_epsilon_0 = const()[name = string("rsqrt_15_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_15 = rsqrt(epsilon = rsqrt_15_epsilon_0, x = reduce_mean_15)[name = string("rsqrt_15")];
            tensor<fp16, [16, 960]> mul_75 = mul(x = mul_73, y = rsqrt_15)[name = string("mul_75")];
            tensor<fp16, [960]> mul_76_y_0 = const()[name = string("mul_76_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2914304)))];
            tensor<fp16, [16, 960]> mul_76 = mul(x = mul_75, y = mul_76_y_0)[name = string("mul_76")];
            tensor<fp16, [352, 960]> tern_1_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2916288))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_1_w2_weight_0_palettized")];
            tensor<fp16, [16, 352]> tern_1_w2 = linear(bias = linear_0_bias_0, weight = tern_1_w2_weight_0_palettized, x = mul_76)[name = string("tern_1_w2")];
            tensor<fp16, [352]> mul_77_y_0 = const()[name = string("mul_77_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3000832)))];
            tensor<fp16, [16, 352]> mul_77 = mul(x = tern_1_w2, y = mul_77_y_0)[name = string("mul_77")];
            tensor<fp16, [16, 352]> add_11 = add(x = add_9, y = mul_77)[name = string("add_11")];
            tensor<fp16, [16, 352]> mul_78 = mul(x = add_11, y = add_11)[name = string("mul_78")];
            tensor<int32, [1]> reduce_mean_16_axes_0 = const()[name = string("reduce_mean_16_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_16_keep_dims_0 = const()[name = string("reduce_mean_16_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_16 = reduce_mean(axes = reduce_mean_16_axes_0, keep_dims = reduce_mean_16_keep_dims_0, x = mul_78)[name = string("reduce_mean_16")];
            fp32 rsqrt_16_epsilon_0 = const()[name = string("rsqrt_16_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_16 = rsqrt(epsilon = rsqrt_16_epsilon_0, x = reduce_mean_16)[name = string("rsqrt_16")];
            tensor<fp16, [16, 352]> mul_79 = mul(x = add_11, y = rsqrt_16)[name = string("mul_79")];
            tensor<fp16, [352]> mul_80_y_0 = const()[name = string("mul_80_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3001600)))];
            tensor<fp16, [16, 352]> mul_80 = mul(x = mul_79, y = mul_80_y_0)[name = string("mul_80")];
            tensor<fp16, [16, 352]> mul_81 = mul(x = mul_80, y = mul_80)[name = string("mul_81")];
            tensor<int32, [1]> reduce_mean_17_axes_0 = const()[name = string("reduce_mean_17_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_17_keep_dims_0 = const()[name = string("reduce_mean_17_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_17 = reduce_mean(axes = reduce_mean_17_axes_0, keep_dims = reduce_mean_17_keep_dims_0, x = mul_81)[name = string("reduce_mean_17")];
            fp32 rsqrt_17_epsilon_0 = const()[name = string("rsqrt_17_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_17 = rsqrt(epsilon = rsqrt_17_epsilon_0, x = reduce_mean_17)[name = string("rsqrt_17")];
            tensor<fp16, [16, 352]> mul_82 = mul(x = mul_80, y = rsqrt_17)[name = string("mul_82")];
            tensor<fp16, [352]> mul_83_y_0 = const()[name = string("mul_83_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3002368)))];
            tensor<fp16, [16, 352]> mul_83 = mul(x = mul_82, y = mul_83_y_0)[name = string("mul_83")];
            tensor<fp16, [352, 352]> tern_2_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3003136))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_2_q_weight_0_palettized")];
            tensor<fp16, [16, 352]> tern_2_q = linear(bias = linear_0_bias_0, weight = tern_2_q_weight_0_palettized, x = mul_83)[name = string("tern_2_q")];
            tensor<fp16, [352]> mul_84_y_0 = const()[name = string("mul_84_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3034176)))];
            tensor<fp16, [16, 352]> mul_84 = mul(x = tern_2_q, y = mul_84_y_0)[name = string("mul_84")];
            tensor<int32, [3]> reshape_18_shape_0 = const()[name = string("reshape_18_shape_0"), val = tensor<int32, [3]>([16, 8, 44])];
            tensor<fp16, [16, 8, 44]> reshape_18 = reshape(shape = reshape_18_shape_0, x = mul_84)[name = string("reshape_18")];
            tensor<int32, [3]> transpose_8_perm_0 = const()[name = string("transpose_8_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_87_y_0 = const()[name = string("mul_87_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3034944)))];
            tensor<fp16, [16, 352]> mul_87 = mul(x = mul_82, y = mul_87_y_0)[name = string("mul_87")];
            tensor<fp16, [88, 352]> tern_2_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3035712))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_2_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_2_k_bias_0 = const()[name = string("tern_2_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [16, 88]> tern_2_k = linear(bias = tern_2_k_bias_0, weight = tern_2_k_weight_0_palettized, x = mul_87)[name = string("tern_2_k")];
            tensor<fp16, [88]> mul_88_y_0 = const()[name = string("mul_88_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3043520)))];
            tensor<fp16, [16, 88]> mul_88 = mul(x = tern_2_k, y = mul_88_y_0)[name = string("mul_88")];
            tensor<int32, [3]> reshape_19_shape_0 = const()[name = string("reshape_19_shape_0"), val = tensor<int32, [3]>([16, 2, 44])];
            tensor<fp16, [16, 2, 44]> reshape_19 = reshape(shape = reshape_19_shape_0, x = mul_88)[name = string("reshape_19")];
            tensor<int32, [3]> transpose_9_perm_0 = const()[name = string("transpose_9_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_91_y_0 = const()[name = string("mul_91_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3043776)))];
            tensor<fp16, [16, 352]> mul_91 = mul(x = mul_82, y = mul_91_y_0)[name = string("mul_91")];
            tensor<fp16, [88, 352]> tern_2_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3044544))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_2_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_2_v_bias_0 = const()[name = string("tern_2_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [16, 88]> tern_2_v = linear(bias = tern_2_v_bias_0, weight = tern_2_v_weight_0_palettized, x = mul_91)[name = string("tern_2_v")];
            tensor<fp16, [88]> mul_92_y_0 = const()[name = string("mul_92_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3052352)))];
            tensor<fp16, [16, 88]> mul_92 = mul(x = tern_2_v, y = mul_92_y_0)[name = string("mul_92")];
            tensor<int32, [3]> reshape_20_shape_0 = const()[name = string("reshape_20_shape_0"), val = tensor<int32, [3]>([16, 2, 44])];
            tensor<fp16, [16, 2, 44]> reshape_20 = reshape(shape = reshape_20_shape_0, x = mul_92)[name = string("reshape_20")];
            tensor<int32, [3]> transpose_10_perm_0 = const()[name = string("transpose_10_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 16, 44]> transpose_8 = transpose(perm = transpose_8_perm_0, x = reshape_18)[name = string("transpose_55")];
            tensor<fp16, [8, 16, 44]> mul_93 = mul(x = transpose_8, y = transpose_8)[name = string("mul_93")];
            tensor<int32, [1]> reduce_mean_20_axes_0 = const()[name = string("reduce_mean_20_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_20_keep_dims_0 = const()[name = string("reduce_mean_20_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 16, 1]> reduce_mean_20 = reduce_mean(axes = reduce_mean_20_axes_0, keep_dims = reduce_mean_20_keep_dims_0, x = mul_93)[name = string("reduce_mean_20")];
            fp32 rsqrt_20_epsilon_0 = const()[name = string("rsqrt_20_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 16, 1]> rsqrt_20 = rsqrt(epsilon = rsqrt_20_epsilon_0, x = reduce_mean_20)[name = string("rsqrt_20")];
            tensor<fp16, [8, 16, 44]> mul_94 = mul(x = transpose_8, y = rsqrt_20)[name = string("mul_94")];
            tensor<fp16, [44]> mul_95_y_0 = const()[name = string("mul_95_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3052608)))];
            tensor<fp16, [8, 16, 44]> mul_95 = mul(x = mul_94, y = mul_95_y_0)[name = string("mul_95")];
            tensor<int32, [3]> slice_by_index_8_begin_0 = const()[name = string("slice_by_index_8_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_8_end_0 = const()[name = string("slice_by_index_8_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_8_end_mask_0 = const()[name = string("slice_by_index_8_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 16, 22]> slice_by_index_8 = slice_by_index(begin = slice_by_index_8_begin_0, end = slice_by_index_8_end_0, end_mask = slice_by_index_8_end_mask_0, x = mul_95)[name = string("slice_by_index_8")];
            tensor<int32, [3]> slice_by_index_9_begin_0 = const()[name = string("slice_by_index_9_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_9_end_0 = const()[name = string("slice_by_index_9_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_9_end_mask_0 = const()[name = string("slice_by_index_9_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 16, 22]> slice_by_index_9 = slice_by_index(begin = slice_by_index_9_begin_0, end = slice_by_index_9_end_0, end_mask = slice_by_index_9_end_mask_0, x = mul_95)[name = string("slice_by_index_9")];
            int32 concat_4_axis_0 = const()[name = string("concat_4_axis_0"), val = int32(-1)];
            bool concat_4_interleave_0 = const()[name = string("concat_4_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 16, 44]> concat_4 = concat(axis = concat_4_axis_0, interleave = concat_4_interleave_0, values = (slice_by_index_9, slice_by_index_8))[name = string("concat_4")];
            tensor<fp16, [44]> mul_96_y_0 = const()[name = string("mul_96_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 16, 44]> mul_96 = mul(x = concat_4, y = mul_96_y_0)[name = string("mul_96")];
            tensor<fp16, [8, 16, 44]> mul_97 = mul(x = mul_95, y = mul_11_y_0)[name = string("mul_97")];
            tensor<fp16, [8, 16, 44]> mul_98 = mul(x = mul_96, y = mul_12_y_0)[name = string("mul_98")];
            tensor<fp16, [8, 16, 44]> add_12 = add(x = mul_97, y = mul_98)[name = string("add_12")];
            tensor<fp16, [2, 16, 44]> transpose_9 = transpose(perm = transpose_9_perm_0, x = reshape_19)[name = string("transpose_54")];
            tensor<fp16, [2, 16, 44]> mul_99 = mul(x = transpose_9, y = transpose_9)[name = string("mul_99")];
            tensor<int32, [1]> reduce_mean_21_axes_0 = const()[name = string("reduce_mean_21_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_21_keep_dims_0 = const()[name = string("reduce_mean_21_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 16, 1]> reduce_mean_21 = reduce_mean(axes = reduce_mean_21_axes_0, keep_dims = reduce_mean_21_keep_dims_0, x = mul_99)[name = string("reduce_mean_21")];
            fp32 rsqrt_21_epsilon_0 = const()[name = string("rsqrt_21_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 16, 1]> rsqrt_21 = rsqrt(epsilon = rsqrt_21_epsilon_0, x = reduce_mean_21)[name = string("rsqrt_21")];
            tensor<fp16, [2, 16, 44]> mul_100 = mul(x = transpose_9, y = rsqrt_21)[name = string("mul_100")];
            tensor<fp16, [44]> mul_101_y_0 = const()[name = string("mul_101_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3052800)))];
            tensor<fp16, [2, 16, 44]> mul_101 = mul(x = mul_100, y = mul_101_y_0)[name = string("mul_101")];
            tensor<int32, [3]> slice_by_index_10_begin_0 = const()[name = string("slice_by_index_10_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_10_end_0 = const()[name = string("slice_by_index_10_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_10_end_mask_0 = const()[name = string("slice_by_index_10_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 16, 22]> slice_by_index_10 = slice_by_index(begin = slice_by_index_10_begin_0, end = slice_by_index_10_end_0, end_mask = slice_by_index_10_end_mask_0, x = mul_101)[name = string("slice_by_index_10")];
            tensor<int32, [3]> slice_by_index_11_begin_0 = const()[name = string("slice_by_index_11_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_11_end_0 = const()[name = string("slice_by_index_11_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_11_end_mask_0 = const()[name = string("slice_by_index_11_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 16, 22]> slice_by_index_11 = slice_by_index(begin = slice_by_index_11_begin_0, end = slice_by_index_11_end_0, end_mask = slice_by_index_11_end_mask_0, x = mul_101)[name = string("slice_by_index_11")];
            int32 concat_5_axis_0 = const()[name = string("concat_5_axis_0"), val = int32(-1)];
            bool concat_5_interleave_0 = const()[name = string("concat_5_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 16, 44]> concat_5 = concat(axis = concat_5_axis_0, interleave = concat_5_interleave_0, values = (slice_by_index_11, slice_by_index_10))[name = string("concat_5")];
            tensor<fp16, [44]> mul_102_y_0 = const()[name = string("mul_102_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 16, 44]> mul_102 = mul(x = concat_5, y = mul_102_y_0)[name = string("mul_102")];
            tensor<fp16, [2, 16, 44]> mul_103 = mul(x = mul_101, y = mul_11_y_0)[name = string("mul_103")];
            tensor<fp16, [2, 16, 44]> mul_104 = mul(x = mul_102, y = mul_12_y_0)[name = string("mul_104")];
            tensor<fp16, [2, 16, 44]> add_13 = add(x = mul_103, y = mul_104)[name = string("add_13")];
            tensor<int32, [4]> reshape_21_shape_0 = const()[name = string("reshape_21_shape_0"), val = tensor<int32, [4]>([2, 1, 16, 44])];
            tensor<fp16, [2, 1, 16, 44]> reshape_21 = reshape(shape = reshape_21_shape_0, x = add_13)[name = string("reshape_21")];
            tensor<int32, [4]> tile_4_reps_0 = const()[name = string("tile_4_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 16, 44]> tile_4 = tile(reps = tile_4_reps_0, x = reshape_21)[name = string("tile_4")];
            tensor<int32, [3]> reshape_22_shape_0 = const()[name = string("reshape_22_shape_0"), val = tensor<int32, [3]>([8, 16, 44])];
            tensor<fp16, [8, 16, 44]> reshape_22 = reshape(shape = reshape_22_shape_0, x = tile_4)[name = string("reshape_22")];
            tensor<int32, [4]> reshape_23_shape_0 = const()[name = string("reshape_23_shape_0"), val = tensor<int32, [4]>([2, 1, 16, 44])];
            tensor<fp16, [2, 16, 44]> transpose_10 = transpose(perm = transpose_10_perm_0, x = reshape_20)[name = string("transpose_53")];
            tensor<fp16, [2, 1, 16, 44]> reshape_23 = reshape(shape = reshape_23_shape_0, x = transpose_10)[name = string("reshape_23")];
            tensor<int32, [4]> tile_5_reps_0 = const()[name = string("tile_5_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 16, 44]> tile_5 = tile(reps = tile_5_reps_0, x = reshape_23)[name = string("tile_5")];
            tensor<int32, [3]> reshape_24_shape_0 = const()[name = string("reshape_24_shape_0"), val = tensor<int32, [3]>([8, 16, 44])];
            tensor<fp16, [8, 16, 44]> reshape_24 = reshape(shape = reshape_24_shape_0, x = tile_5)[name = string("reshape_24")];
            fp16 mul_105_y_0 = const()[name = string("mul_105_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 16, 44]> mul_105 = mul(x = add_12, y = mul_105_y_0)[name = string("mul_105")];
            bool matmul_4_transpose_y_0 = const()[name = string("matmul_4_transpose_y_0"), val = bool(true)];
            bool matmul_4_transpose_x_0 = const()[name = string("matmul_4_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 16, 16]> matmul_4 = matmul(transpose_x = matmul_4_transpose_x_0, transpose_y = matmul_4_transpose_y_0, x = mul_105, y = reshape_22)[name = string("matmul_4")];
            tensor<fp16, [8, 16, 16]> add_14 = add(x = matmul_4, y = reshape_1)[name = string("add_14")];
            int32 softmax_2_axis_0 = const()[name = string("softmax_2_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 16, 16]> softmax_2 = softmax(axis = softmax_2_axis_0, x = add_14)[name = string("softmax_2")];
            bool matmul_5_transpose_x_0 = const()[name = string("matmul_5_transpose_x_0"), val = bool(false)];
            bool matmul_5_transpose_y_0 = const()[name = string("matmul_5_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 16, 44]> matmul_5 = matmul(transpose_x = matmul_5_transpose_x_0, transpose_y = matmul_5_transpose_y_0, x = softmax_2, y = reshape_24)[name = string("matmul_5")];
            tensor<int32, [3]> transpose_11_perm_0 = const()[name = string("transpose_11_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_25_shape_0 = const()[name = string("reshape_25_shape_0"), val = tensor<int32, [2]>([16, 352])];
            tensor<fp16, [16, 8, 44]> transpose_11 = transpose(perm = transpose_11_perm_0, x = matmul_5)[name = string("transpose_52")];
            tensor<fp16, [16, 352]> reshape_25 = reshape(shape = reshape_25_shape_0, x = transpose_11)[name = string("reshape_25")];
            tensor<fp16, [16, 352]> mul_106 = mul(x = reshape_25, y = reshape_25)[name = string("mul_106")];
            tensor<int32, [1]> reduce_mean_22_axes_0 = const()[name = string("reduce_mean_22_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_22_keep_dims_0 = const()[name = string("reduce_mean_22_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_22 = reduce_mean(axes = reduce_mean_22_axes_0, keep_dims = reduce_mean_22_keep_dims_0, x = mul_106)[name = string("reduce_mean_22")];
            fp32 rsqrt_22_epsilon_0 = const()[name = string("rsqrt_22_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_22 = rsqrt(epsilon = rsqrt_22_epsilon_0, x = reduce_mean_22)[name = string("rsqrt_22")];
            tensor<fp16, [16, 352]> mul_107 = mul(x = reshape_25, y = rsqrt_22)[name = string("mul_107")];
            tensor<fp16, [352]> mul_108_y_0 = const()[name = string("mul_108_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3052992)))];
            tensor<fp16, [16, 352]> mul_108 = mul(x = mul_107, y = mul_108_y_0)[name = string("mul_108")];
            tensor<fp16, [352, 352]> tern_2_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3053760))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_2_o_weight_0_palettized")];
            tensor<fp16, [16, 352]> tern_2_o = linear(bias = linear_0_bias_0, weight = tern_2_o_weight_0_palettized, x = mul_108)[name = string("tern_2_o")];
            tensor<fp16, [352]> mul_109_y_0 = const()[name = string("mul_109_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3084800)))];
            tensor<fp16, [16, 352]> mul_109 = mul(x = tern_2_o, y = mul_109_y_0)[name = string("mul_109")];
            tensor<fp16, [16, 352]> add_15 = add(x = add_11, y = mul_109)[name = string("add_15")];
            tensor<fp16, [16, 352]> mul_110 = mul(x = add_15, y = add_15)[name = string("mul_110")];
            tensor<int32, [1]> reduce_mean_23_axes_0 = const()[name = string("reduce_mean_23_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_23_keep_dims_0 = const()[name = string("reduce_mean_23_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_23 = reduce_mean(axes = reduce_mean_23_axes_0, keep_dims = reduce_mean_23_keep_dims_0, x = mul_110)[name = string("reduce_mean_23")];
            fp32 rsqrt_23_epsilon_0 = const()[name = string("rsqrt_23_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_23 = rsqrt(epsilon = rsqrt_23_epsilon_0, x = reduce_mean_23)[name = string("rsqrt_23")];
            tensor<fp16, [16, 352]> mul_111 = mul(x = add_15, y = rsqrt_23)[name = string("mul_111")];
            tensor<fp16, [352]> mul_112_y_0 = const()[name = string("mul_112_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3085568)))];
            tensor<fp16, [16, 352]> mul_112 = mul(x = mul_111, y = mul_112_y_0)[name = string("mul_112")];
            tensor<fp16, [16, 352]> mul_113 = mul(x = mul_112, y = mul_112)[name = string("mul_113")];
            tensor<int32, [1]> reduce_mean_24_axes_0 = const()[name = string("reduce_mean_24_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_24_keep_dims_0 = const()[name = string("reduce_mean_24_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_24 = reduce_mean(axes = reduce_mean_24_axes_0, keep_dims = reduce_mean_24_keep_dims_0, x = mul_113)[name = string("reduce_mean_24")];
            fp32 rsqrt_24_epsilon_0 = const()[name = string("rsqrt_24_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_24 = rsqrt(epsilon = rsqrt_24_epsilon_0, x = reduce_mean_24)[name = string("rsqrt_24")];
            tensor<fp16, [16, 352]> mul_114 = mul(x = mul_112, y = rsqrt_24)[name = string("mul_114")];
            tensor<fp16, [352]> mul_115_y_0 = const()[name = string("mul_115_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3086336)))];
            tensor<fp16, [16, 352]> mul_115 = mul(x = mul_114, y = mul_115_y_0)[name = string("mul_115")];
            tensor<fp16, [960, 352]> tern_2_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3087104))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_2_w1_weight_0_palettized")];
            tensor<fp16, [16, 960]> tern_2_w1 = linear(bias = linear_4_bias_0, weight = tern_2_w1_weight_0_palettized, x = mul_115)[name = string("tern_2_w1")];
            tensor<fp16, [960]> mul_116_y_0 = const()[name = string("mul_116_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3171648)))];
            tensor<fp16, [16, 960]> mul_116 = mul(x = tern_2_w1, y = mul_116_y_0)[name = string("mul_116")];
            tensor<fp16, [352]> mul_119_y_0 = const()[name = string("mul_119_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3173632)))];
            tensor<fp16, [16, 352]> mul_119 = mul(x = mul_114, y = mul_119_y_0)[name = string("mul_119")];
            tensor<fp16, [960, 352]> tern_2_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3174400))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_2_w3_weight_0_palettized")];
            tensor<fp16, [16, 960]> tern_2_w3 = linear(bias = linear_4_bias_0, weight = tern_2_w3_weight_0_palettized, x = mul_119)[name = string("tern_2_w3")];
            tensor<fp16, [960]> mul_120_y_0 = const()[name = string("mul_120_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3258944)))];
            tensor<fp16, [16, 960]> mul_120 = mul(x = tern_2_w3, y = mul_120_y_0)[name = string("mul_120")];
            fp16 mul_121_y_0 = const()[name = string("mul_121_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [16, 960]> mul_121 = mul(x = mul_116, y = mul_121_y_0)[name = string("mul_121")];
            tensor<fp16, [16, 960]> tanh_2 = tanh(x = mul_121)[name = string("tanh_2")];
            fp16 mul_122_x_0 = const()[name = string("mul_122_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [16, 960]> mul_122 = mul(x = mul_122_x_0, y = tanh_2)[name = string("mul_122")];
            fp16 add_16_x_0 = const()[name = string("add_16_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [16, 960]> add_16 = add(x = add_16_x_0, y = mul_122)[name = string("add_16")];
            tensor<fp16, [16, 960]> mul_123 = mul(x = mul_116, y = add_16)[name = string("mul_123")];
            tensor<fp16, [16, 960]> mul_124 = mul(x = mul_123, y = mul_120)[name = string("mul_124")];
            tensor<fp16, [16, 960]> mul_125 = mul(x = mul_124, y = mul_124)[name = string("mul_125")];
            tensor<int32, [1]> reduce_mean_26_axes_0 = const()[name = string("reduce_mean_26_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_26_keep_dims_0 = const()[name = string("reduce_mean_26_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_26 = reduce_mean(axes = reduce_mean_26_axes_0, keep_dims = reduce_mean_26_keep_dims_0, x = mul_125)[name = string("reduce_mean_26")];
            fp32 rsqrt_26_epsilon_0 = const()[name = string("rsqrt_26_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_26 = rsqrt(epsilon = rsqrt_26_epsilon_0, x = reduce_mean_26)[name = string("rsqrt_26")];
            tensor<fp16, [16, 960]> mul_126 = mul(x = mul_124, y = rsqrt_26)[name = string("mul_126")];
            tensor<fp16, [960]> mul_127_y_0 = const()[name = string("mul_127_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3260928)))];
            tensor<fp16, [16, 960]> mul_127 = mul(x = mul_126, y = mul_127_y_0)[name = string("mul_127")];
            tensor<fp16, [352, 960]> tern_2_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3262912))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_2_w2_weight_0_palettized")];
            tensor<fp16, [16, 352]> tern_2_w2 = linear(bias = linear_0_bias_0, weight = tern_2_w2_weight_0_palettized, x = mul_127)[name = string("tern_2_w2")];
            tensor<fp16, [352]> mul_128_y_0 = const()[name = string("mul_128_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3347456)))];
            tensor<fp16, [16, 352]> mul_128 = mul(x = tern_2_w2, y = mul_128_y_0)[name = string("mul_128")];
            tensor<fp16, [16, 352]> add_17 = add(x = add_15, y = mul_128)[name = string("add_17")];
            tensor<fp16, [16, 352]> mul_129 = mul(x = add_17, y = add_17)[name = string("mul_129")];
            tensor<int32, [1]> reduce_mean_27_axes_0 = const()[name = string("reduce_mean_27_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_27_keep_dims_0 = const()[name = string("reduce_mean_27_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_27 = reduce_mean(axes = reduce_mean_27_axes_0, keep_dims = reduce_mean_27_keep_dims_0, x = mul_129)[name = string("reduce_mean_27")];
            fp32 rsqrt_27_epsilon_0 = const()[name = string("rsqrt_27_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_27 = rsqrt(epsilon = rsqrt_27_epsilon_0, x = reduce_mean_27)[name = string("rsqrt_27")];
            tensor<fp16, [16, 352]> mul_130 = mul(x = add_17, y = rsqrt_27)[name = string("mul_130")];
            tensor<fp16, [352]> mul_131_y_0 = const()[name = string("mul_131_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3348224)))];
            tensor<fp16, [16, 352]> mul_131 = mul(x = mul_130, y = mul_131_y_0)[name = string("mul_131")];
            tensor<fp16, [16, 352]> mul_132 = mul(x = mul_131, y = mul_131)[name = string("mul_132")];
            tensor<int32, [1]> reduce_mean_28_axes_0 = const()[name = string("reduce_mean_28_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_28_keep_dims_0 = const()[name = string("reduce_mean_28_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_28 = reduce_mean(axes = reduce_mean_28_axes_0, keep_dims = reduce_mean_28_keep_dims_0, x = mul_132)[name = string("reduce_mean_28")];
            fp32 rsqrt_28_epsilon_0 = const()[name = string("rsqrt_28_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_28 = rsqrt(epsilon = rsqrt_28_epsilon_0, x = reduce_mean_28)[name = string("rsqrt_28")];
            tensor<fp16, [16, 352]> mul_133 = mul(x = mul_131, y = rsqrt_28)[name = string("mul_133")];
            tensor<fp16, [352]> mul_134_y_0 = const()[name = string("mul_134_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3348992)))];
            tensor<fp16, [16, 352]> mul_134 = mul(x = mul_133, y = mul_134_y_0)[name = string("mul_134")];
            tensor<fp16, [352, 352]> tern_3_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3349760))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_3_q_weight_0_palettized")];
            tensor<fp16, [16, 352]> tern_3_q = linear(bias = linear_0_bias_0, weight = tern_3_q_weight_0_palettized, x = mul_134)[name = string("tern_3_q")];
            tensor<fp16, [352]> mul_135_y_0 = const()[name = string("mul_135_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3380800)))];
            tensor<fp16, [16, 352]> mul_135 = mul(x = tern_3_q, y = mul_135_y_0)[name = string("mul_135")];
            tensor<int32, [3]> reshape_26_shape_0 = const()[name = string("reshape_26_shape_0"), val = tensor<int32, [3]>([16, 8, 44])];
            tensor<fp16, [16, 8, 44]> reshape_26 = reshape(shape = reshape_26_shape_0, x = mul_135)[name = string("reshape_26")];
            tensor<int32, [3]> transpose_12_perm_0 = const()[name = string("transpose_12_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_138_y_0 = const()[name = string("mul_138_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3381568)))];
            tensor<fp16, [16, 352]> mul_138 = mul(x = mul_133, y = mul_138_y_0)[name = string("mul_138")];
            tensor<fp16, [88, 352]> tern_3_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3382336))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_3_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_3_k_bias_0 = const()[name = string("tern_3_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [16, 88]> tern_3_k = linear(bias = tern_3_k_bias_0, weight = tern_3_k_weight_0_palettized, x = mul_138)[name = string("tern_3_k")];
            tensor<fp16, [88]> mul_139_y_0 = const()[name = string("mul_139_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3390144)))];
            tensor<fp16, [16, 88]> mul_139 = mul(x = tern_3_k, y = mul_139_y_0)[name = string("mul_139")];
            tensor<int32, [3]> reshape_27_shape_0 = const()[name = string("reshape_27_shape_0"), val = tensor<int32, [3]>([16, 2, 44])];
            tensor<fp16, [16, 2, 44]> reshape_27 = reshape(shape = reshape_27_shape_0, x = mul_139)[name = string("reshape_27")];
            tensor<int32, [3]> transpose_13_perm_0 = const()[name = string("transpose_13_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_142_y_0 = const()[name = string("mul_142_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3390400)))];
            tensor<fp16, [16, 352]> mul_142 = mul(x = mul_133, y = mul_142_y_0)[name = string("mul_142")];
            tensor<fp16, [88, 352]> tern_3_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3391168))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_3_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_3_v_bias_0 = const()[name = string("tern_3_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [16, 88]> tern_3_v = linear(bias = tern_3_v_bias_0, weight = tern_3_v_weight_0_palettized, x = mul_142)[name = string("tern_3_v")];
            tensor<fp16, [88]> mul_143_y_0 = const()[name = string("mul_143_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3398976)))];
            tensor<fp16, [16, 88]> mul_143 = mul(x = tern_3_v, y = mul_143_y_0)[name = string("mul_143")];
            tensor<int32, [3]> reshape_28_shape_0 = const()[name = string("reshape_28_shape_0"), val = tensor<int32, [3]>([16, 2, 44])];
            tensor<fp16, [16, 2, 44]> reshape_28 = reshape(shape = reshape_28_shape_0, x = mul_143)[name = string("reshape_28")];
            tensor<int32, [3]> transpose_14_perm_0 = const()[name = string("transpose_14_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 16, 44]> transpose_12 = transpose(perm = transpose_12_perm_0, x = reshape_26)[name = string("transpose_51")];
            tensor<fp16, [8, 16, 44]> mul_144 = mul(x = transpose_12, y = transpose_12)[name = string("mul_144")];
            tensor<int32, [1]> reduce_mean_31_axes_0 = const()[name = string("reduce_mean_31_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_31_keep_dims_0 = const()[name = string("reduce_mean_31_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 16, 1]> reduce_mean_31 = reduce_mean(axes = reduce_mean_31_axes_0, keep_dims = reduce_mean_31_keep_dims_0, x = mul_144)[name = string("reduce_mean_31")];
            fp32 rsqrt_31_epsilon_0 = const()[name = string("rsqrt_31_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 16, 1]> rsqrt_31 = rsqrt(epsilon = rsqrt_31_epsilon_0, x = reduce_mean_31)[name = string("rsqrt_31")];
            tensor<fp16, [8, 16, 44]> mul_145 = mul(x = transpose_12, y = rsqrt_31)[name = string("mul_145")];
            tensor<fp16, [44]> mul_146_y_0 = const()[name = string("mul_146_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3399232)))];
            tensor<fp16, [8, 16, 44]> mul_146 = mul(x = mul_145, y = mul_146_y_0)[name = string("mul_146")];
            tensor<int32, [3]> slice_by_index_12_begin_0 = const()[name = string("slice_by_index_12_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_12_end_0 = const()[name = string("slice_by_index_12_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_12_end_mask_0 = const()[name = string("slice_by_index_12_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 16, 22]> slice_by_index_12 = slice_by_index(begin = slice_by_index_12_begin_0, end = slice_by_index_12_end_0, end_mask = slice_by_index_12_end_mask_0, x = mul_146)[name = string("slice_by_index_12")];
            tensor<int32, [3]> slice_by_index_13_begin_0 = const()[name = string("slice_by_index_13_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_13_end_0 = const()[name = string("slice_by_index_13_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_13_end_mask_0 = const()[name = string("slice_by_index_13_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 16, 22]> slice_by_index_13 = slice_by_index(begin = slice_by_index_13_begin_0, end = slice_by_index_13_end_0, end_mask = slice_by_index_13_end_mask_0, x = mul_146)[name = string("slice_by_index_13")];
            int32 concat_6_axis_0 = const()[name = string("concat_6_axis_0"), val = int32(-1)];
            bool concat_6_interleave_0 = const()[name = string("concat_6_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 16, 44]> concat_6 = concat(axis = concat_6_axis_0, interleave = concat_6_interleave_0, values = (slice_by_index_13, slice_by_index_12))[name = string("concat_6")];
            tensor<fp16, [44]> mul_147_y_0 = const()[name = string("mul_147_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 16, 44]> mul_147 = mul(x = concat_6, y = mul_147_y_0)[name = string("mul_147")];
            tensor<fp16, [8, 16, 44]> mul_148 = mul(x = mul_146, y = mul_11_y_0)[name = string("mul_148")];
            tensor<fp16, [8, 16, 44]> mul_149 = mul(x = mul_147, y = mul_12_y_0)[name = string("mul_149")];
            tensor<fp16, [8, 16, 44]> add_18 = add(x = mul_148, y = mul_149)[name = string("add_18")];
            tensor<fp16, [2, 16, 44]> transpose_13 = transpose(perm = transpose_13_perm_0, x = reshape_27)[name = string("transpose_50")];
            tensor<fp16, [2, 16, 44]> mul_150 = mul(x = transpose_13, y = transpose_13)[name = string("mul_150")];
            tensor<int32, [1]> reduce_mean_32_axes_0 = const()[name = string("reduce_mean_32_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_32_keep_dims_0 = const()[name = string("reduce_mean_32_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 16, 1]> reduce_mean_32 = reduce_mean(axes = reduce_mean_32_axes_0, keep_dims = reduce_mean_32_keep_dims_0, x = mul_150)[name = string("reduce_mean_32")];
            fp32 rsqrt_32_epsilon_0 = const()[name = string("rsqrt_32_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 16, 1]> rsqrt_32 = rsqrt(epsilon = rsqrt_32_epsilon_0, x = reduce_mean_32)[name = string("rsqrt_32")];
            tensor<fp16, [2, 16, 44]> mul_151 = mul(x = transpose_13, y = rsqrt_32)[name = string("mul_151")];
            tensor<fp16, [44]> mul_152_y_0 = const()[name = string("mul_152_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3399424)))];
            tensor<fp16, [2, 16, 44]> mul_152 = mul(x = mul_151, y = mul_152_y_0)[name = string("mul_152")];
            tensor<int32, [3]> slice_by_index_14_begin_0 = const()[name = string("slice_by_index_14_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_14_end_0 = const()[name = string("slice_by_index_14_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_14_end_mask_0 = const()[name = string("slice_by_index_14_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 16, 22]> slice_by_index_14 = slice_by_index(begin = slice_by_index_14_begin_0, end = slice_by_index_14_end_0, end_mask = slice_by_index_14_end_mask_0, x = mul_152)[name = string("slice_by_index_14")];
            tensor<int32, [3]> slice_by_index_15_begin_0 = const()[name = string("slice_by_index_15_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_15_end_0 = const()[name = string("slice_by_index_15_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_15_end_mask_0 = const()[name = string("slice_by_index_15_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 16, 22]> slice_by_index_15 = slice_by_index(begin = slice_by_index_15_begin_0, end = slice_by_index_15_end_0, end_mask = slice_by_index_15_end_mask_0, x = mul_152)[name = string("slice_by_index_15")];
            int32 concat_7_axis_0 = const()[name = string("concat_7_axis_0"), val = int32(-1)];
            bool concat_7_interleave_0 = const()[name = string("concat_7_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 16, 44]> concat_7 = concat(axis = concat_7_axis_0, interleave = concat_7_interleave_0, values = (slice_by_index_15, slice_by_index_14))[name = string("concat_7")];
            tensor<fp16, [44]> mul_153_y_0 = const()[name = string("mul_153_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 16, 44]> mul_153 = mul(x = concat_7, y = mul_153_y_0)[name = string("mul_153")];
            tensor<fp16, [2, 16, 44]> mul_154 = mul(x = mul_152, y = mul_11_y_0)[name = string("mul_154")];
            tensor<fp16, [2, 16, 44]> mul_155 = mul(x = mul_153, y = mul_12_y_0)[name = string("mul_155")];
            tensor<fp16, [2, 16, 44]> add_19 = add(x = mul_154, y = mul_155)[name = string("add_19")];
            tensor<int32, [4]> reshape_29_shape_0 = const()[name = string("reshape_29_shape_0"), val = tensor<int32, [4]>([2, 1, 16, 44])];
            tensor<fp16, [2, 1, 16, 44]> reshape_29 = reshape(shape = reshape_29_shape_0, x = add_19)[name = string("reshape_29")];
            tensor<int32, [4]> tile_6_reps_0 = const()[name = string("tile_6_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 16, 44]> tile_6 = tile(reps = tile_6_reps_0, x = reshape_29)[name = string("tile_6")];
            tensor<int32, [3]> reshape_30_shape_0 = const()[name = string("reshape_30_shape_0"), val = tensor<int32, [3]>([8, 16, 44])];
            tensor<fp16, [8, 16, 44]> reshape_30 = reshape(shape = reshape_30_shape_0, x = tile_6)[name = string("reshape_30")];
            tensor<int32, [4]> reshape_31_shape_0 = const()[name = string("reshape_31_shape_0"), val = tensor<int32, [4]>([2, 1, 16, 44])];
            tensor<fp16, [2, 16, 44]> transpose_14 = transpose(perm = transpose_14_perm_0, x = reshape_28)[name = string("transpose_49")];
            tensor<fp16, [2, 1, 16, 44]> reshape_31 = reshape(shape = reshape_31_shape_0, x = transpose_14)[name = string("reshape_31")];
            tensor<int32, [4]> tile_7_reps_0 = const()[name = string("tile_7_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 16, 44]> tile_7 = tile(reps = tile_7_reps_0, x = reshape_31)[name = string("tile_7")];
            tensor<int32, [3]> reshape_32_shape_0 = const()[name = string("reshape_32_shape_0"), val = tensor<int32, [3]>([8, 16, 44])];
            tensor<fp16, [8, 16, 44]> reshape_32 = reshape(shape = reshape_32_shape_0, x = tile_7)[name = string("reshape_32")];
            fp16 mul_156_y_0 = const()[name = string("mul_156_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 16, 44]> mul_156 = mul(x = add_18, y = mul_156_y_0)[name = string("mul_156")];
            bool matmul_6_transpose_y_0 = const()[name = string("matmul_6_transpose_y_0"), val = bool(true)];
            bool matmul_6_transpose_x_0 = const()[name = string("matmul_6_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 16, 16]> matmul_6 = matmul(transpose_x = matmul_6_transpose_x_0, transpose_y = matmul_6_transpose_y_0, x = mul_156, y = reshape_30)[name = string("matmul_6")];
            tensor<fp16, [8, 16, 16]> add_20 = add(x = matmul_6, y = reshape_1)[name = string("add_20")];
            int32 softmax_3_axis_0 = const()[name = string("softmax_3_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 16, 16]> softmax_3 = softmax(axis = softmax_3_axis_0, x = add_20)[name = string("softmax_3")];
            bool matmul_7_transpose_x_0 = const()[name = string("matmul_7_transpose_x_0"), val = bool(false)];
            bool matmul_7_transpose_y_0 = const()[name = string("matmul_7_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 16, 44]> matmul_7 = matmul(transpose_x = matmul_7_transpose_x_0, transpose_y = matmul_7_transpose_y_0, x = softmax_3, y = reshape_32)[name = string("matmul_7")];
            tensor<int32, [3]> transpose_15_perm_0 = const()[name = string("transpose_15_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_33_shape_0 = const()[name = string("reshape_33_shape_0"), val = tensor<int32, [2]>([16, 352])];
            tensor<fp16, [16, 8, 44]> transpose_15 = transpose(perm = transpose_15_perm_0, x = matmul_7)[name = string("transpose_48")];
            tensor<fp16, [16, 352]> reshape_33 = reshape(shape = reshape_33_shape_0, x = transpose_15)[name = string("reshape_33")];
            tensor<fp16, [16, 352]> mul_157 = mul(x = reshape_33, y = reshape_33)[name = string("mul_157")];
            tensor<int32, [1]> reduce_mean_33_axes_0 = const()[name = string("reduce_mean_33_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_33_keep_dims_0 = const()[name = string("reduce_mean_33_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_33 = reduce_mean(axes = reduce_mean_33_axes_0, keep_dims = reduce_mean_33_keep_dims_0, x = mul_157)[name = string("reduce_mean_33")];
            fp32 rsqrt_33_epsilon_0 = const()[name = string("rsqrt_33_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_33 = rsqrt(epsilon = rsqrt_33_epsilon_0, x = reduce_mean_33)[name = string("rsqrt_33")];
            tensor<fp16, [16, 352]> mul_158 = mul(x = reshape_33, y = rsqrt_33)[name = string("mul_158")];
            tensor<fp16, [352]> mul_159_y_0 = const()[name = string("mul_159_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3399616)))];
            tensor<fp16, [16, 352]> mul_159 = mul(x = mul_158, y = mul_159_y_0)[name = string("mul_159")];
            tensor<fp16, [352, 352]> tern_3_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3400384))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_3_o_weight_0_palettized")];
            tensor<fp16, [16, 352]> tern_3_o = linear(bias = linear_0_bias_0, weight = tern_3_o_weight_0_palettized, x = mul_159)[name = string("tern_3_o")];
            tensor<fp16, [352]> mul_160_y_0 = const()[name = string("mul_160_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3431424)))];
            tensor<fp16, [16, 352]> mul_160 = mul(x = tern_3_o, y = mul_160_y_0)[name = string("mul_160")];
            tensor<fp16, [16, 352]> add_21 = add(x = add_17, y = mul_160)[name = string("add_21")];
            tensor<fp16, [16, 352]> mul_161 = mul(x = add_21, y = add_21)[name = string("mul_161")];
            tensor<int32, [1]> reduce_mean_34_axes_0 = const()[name = string("reduce_mean_34_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_34_keep_dims_0 = const()[name = string("reduce_mean_34_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_34 = reduce_mean(axes = reduce_mean_34_axes_0, keep_dims = reduce_mean_34_keep_dims_0, x = mul_161)[name = string("reduce_mean_34")];
            fp32 rsqrt_34_epsilon_0 = const()[name = string("rsqrt_34_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_34 = rsqrt(epsilon = rsqrt_34_epsilon_0, x = reduce_mean_34)[name = string("rsqrt_34")];
            tensor<fp16, [16, 352]> mul_162 = mul(x = add_21, y = rsqrt_34)[name = string("mul_162")];
            tensor<fp16, [352]> mul_163_y_0 = const()[name = string("mul_163_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3432192)))];
            tensor<fp16, [16, 352]> mul_163 = mul(x = mul_162, y = mul_163_y_0)[name = string("mul_163")];
            tensor<fp16, [16, 352]> mul_164 = mul(x = mul_163, y = mul_163)[name = string("mul_164")];
            tensor<int32, [1]> reduce_mean_35_axes_0 = const()[name = string("reduce_mean_35_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_35_keep_dims_0 = const()[name = string("reduce_mean_35_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_35 = reduce_mean(axes = reduce_mean_35_axes_0, keep_dims = reduce_mean_35_keep_dims_0, x = mul_164)[name = string("reduce_mean_35")];
            fp32 rsqrt_35_epsilon_0 = const()[name = string("rsqrt_35_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_35 = rsqrt(epsilon = rsqrt_35_epsilon_0, x = reduce_mean_35)[name = string("rsqrt_35")];
            tensor<fp16, [16, 352]> mul_165 = mul(x = mul_163, y = rsqrt_35)[name = string("mul_165")];
            tensor<fp16, [352]> mul_166_y_0 = const()[name = string("mul_166_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3432960)))];
            tensor<fp16, [16, 352]> mul_166 = mul(x = mul_165, y = mul_166_y_0)[name = string("mul_166")];
            tensor<fp16, [960, 352]> tern_3_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3433728))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_3_w1_weight_0_palettized")];
            tensor<fp16, [16, 960]> tern_3_w1 = linear(bias = linear_4_bias_0, weight = tern_3_w1_weight_0_palettized, x = mul_166)[name = string("tern_3_w1")];
            tensor<fp16, [960]> mul_167_y_0 = const()[name = string("mul_167_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3518272)))];
            tensor<fp16, [16, 960]> mul_167 = mul(x = tern_3_w1, y = mul_167_y_0)[name = string("mul_167")];
            tensor<fp16, [352]> mul_170_y_0 = const()[name = string("mul_170_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3520256)))];
            tensor<fp16, [16, 352]> mul_170 = mul(x = mul_165, y = mul_170_y_0)[name = string("mul_170")];
            tensor<fp16, [960, 352]> tern_3_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3521024))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_3_w3_weight_0_palettized")];
            tensor<fp16, [16, 960]> tern_3_w3 = linear(bias = linear_4_bias_0, weight = tern_3_w3_weight_0_palettized, x = mul_170)[name = string("tern_3_w3")];
            tensor<fp16, [960]> mul_171_y_0 = const()[name = string("mul_171_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3605568)))];
            tensor<fp16, [16, 960]> mul_171 = mul(x = tern_3_w3, y = mul_171_y_0)[name = string("mul_171")];
            fp16 mul_172_y_0 = const()[name = string("mul_172_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [16, 960]> mul_172 = mul(x = mul_167, y = mul_172_y_0)[name = string("mul_172")];
            tensor<fp16, [16, 960]> tanh_3 = tanh(x = mul_172)[name = string("tanh_3")];
            fp16 mul_173_x_0 = const()[name = string("mul_173_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [16, 960]> mul_173 = mul(x = mul_173_x_0, y = tanh_3)[name = string("mul_173")];
            fp16 add_22_x_0 = const()[name = string("add_22_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [16, 960]> add_22 = add(x = add_22_x_0, y = mul_173)[name = string("add_22")];
            tensor<fp16, [16, 960]> mul_174 = mul(x = mul_167, y = add_22)[name = string("mul_174")];
            tensor<fp16, [16, 960]> mul_175 = mul(x = mul_174, y = mul_171)[name = string("mul_175")];
            tensor<fp16, [16, 960]> mul_176 = mul(x = mul_175, y = mul_175)[name = string("mul_176")];
            tensor<int32, [1]> reduce_mean_37_axes_0 = const()[name = string("reduce_mean_37_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_37_keep_dims_0 = const()[name = string("reduce_mean_37_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_37 = reduce_mean(axes = reduce_mean_37_axes_0, keep_dims = reduce_mean_37_keep_dims_0, x = mul_176)[name = string("reduce_mean_37")];
            fp32 rsqrt_37_epsilon_0 = const()[name = string("rsqrt_37_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_37 = rsqrt(epsilon = rsqrt_37_epsilon_0, x = reduce_mean_37)[name = string("rsqrt_37")];
            tensor<fp16, [16, 960]> mul_177 = mul(x = mul_175, y = rsqrt_37)[name = string("mul_177")];
            tensor<fp16, [960]> mul_178_y_0 = const()[name = string("mul_178_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3607552)))];
            tensor<fp16, [16, 960]> mul_178 = mul(x = mul_177, y = mul_178_y_0)[name = string("mul_178")];
            tensor<fp16, [352, 960]> tern_3_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3609536))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_3_w2_weight_0_palettized")];
            tensor<fp16, [16, 352]> tern_3_w2 = linear(bias = linear_0_bias_0, weight = tern_3_w2_weight_0_palettized, x = mul_178)[name = string("tern_3_w2")];
            tensor<fp16, [352]> mul_179_y_0 = const()[name = string("mul_179_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3694080)))];
            tensor<fp16, [16, 352]> mul_179 = mul(x = tern_3_w2, y = mul_179_y_0)[name = string("mul_179")];
            tensor<fp16, [16, 352]> add_23 = add(x = add_21, y = mul_179)[name = string("add_23")];
            tensor<fp16, [16, 352]> mul_180 = mul(x = add_23, y = add_23)[name = string("mul_180")];
            tensor<int32, [1]> reduce_mean_38_axes_0 = const()[name = string("reduce_mean_38_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_38_keep_dims_0 = const()[name = string("reduce_mean_38_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_38 = reduce_mean(axes = reduce_mean_38_axes_0, keep_dims = reduce_mean_38_keep_dims_0, x = mul_180)[name = string("reduce_mean_38")];
            fp32 rsqrt_38_epsilon_0 = const()[name = string("rsqrt_38_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_38 = rsqrt(epsilon = rsqrt_38_epsilon_0, x = reduce_mean_38)[name = string("rsqrt_38")];
            tensor<fp16, [16, 352]> mul_181 = mul(x = add_23, y = rsqrt_38)[name = string("mul_181")];
            tensor<fp16, [352]> mul_182_y_0 = const()[name = string("mul_182_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3694848)))];
            tensor<fp16, [16, 352]> mul_182 = mul(x = mul_181, y = mul_182_y_0)[name = string("mul_182")];
            tensor<fp16, [16, 352]> mul_183 = mul(x = mul_182, y = mul_182)[name = string("mul_183")];
            tensor<int32, [1]> reduce_mean_39_axes_0 = const()[name = string("reduce_mean_39_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_39_keep_dims_0 = const()[name = string("reduce_mean_39_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_39 = reduce_mean(axes = reduce_mean_39_axes_0, keep_dims = reduce_mean_39_keep_dims_0, x = mul_183)[name = string("reduce_mean_39")];
            fp32 rsqrt_39_epsilon_0 = const()[name = string("rsqrt_39_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_39 = rsqrt(epsilon = rsqrt_39_epsilon_0, x = reduce_mean_39)[name = string("rsqrt_39")];
            tensor<fp16, [16, 352]> mul_184 = mul(x = mul_182, y = rsqrt_39)[name = string("mul_184")];
            tensor<fp16, [352]> mul_185_y_0 = const()[name = string("mul_185_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3695616)))];
            tensor<fp16, [16, 352]> mul_185 = mul(x = mul_184, y = mul_185_y_0)[name = string("mul_185")];
            tensor<fp16, [352, 352]> tern_4_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3696384))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_4_q_weight_0_palettized")];
            tensor<fp16, [16, 352]> tern_4_q = linear(bias = linear_0_bias_0, weight = tern_4_q_weight_0_palettized, x = mul_185)[name = string("tern_4_q")];
            tensor<fp16, [352]> mul_186_y_0 = const()[name = string("mul_186_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3727424)))];
            tensor<fp16, [16, 352]> mul_186 = mul(x = tern_4_q, y = mul_186_y_0)[name = string("mul_186")];
            tensor<int32, [3]> reshape_34_shape_0 = const()[name = string("reshape_34_shape_0"), val = tensor<int32, [3]>([16, 8, 44])];
            tensor<fp16, [16, 8, 44]> reshape_34 = reshape(shape = reshape_34_shape_0, x = mul_186)[name = string("reshape_34")];
            tensor<int32, [3]> transpose_16_perm_0 = const()[name = string("transpose_16_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_189_y_0 = const()[name = string("mul_189_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3728192)))];
            tensor<fp16, [16, 352]> mul_189 = mul(x = mul_184, y = mul_189_y_0)[name = string("mul_189")];
            tensor<fp16, [88, 352]> tern_4_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3728960))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_4_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_4_k_bias_0 = const()[name = string("tern_4_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [16, 88]> tern_4_k = linear(bias = tern_4_k_bias_0, weight = tern_4_k_weight_0_palettized, x = mul_189)[name = string("tern_4_k")];
            tensor<fp16, [88]> mul_190_y_0 = const()[name = string("mul_190_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3736768)))];
            tensor<fp16, [16, 88]> mul_190 = mul(x = tern_4_k, y = mul_190_y_0)[name = string("mul_190")];
            tensor<int32, [3]> reshape_35_shape_0 = const()[name = string("reshape_35_shape_0"), val = tensor<int32, [3]>([16, 2, 44])];
            tensor<fp16, [16, 2, 44]> reshape_35 = reshape(shape = reshape_35_shape_0, x = mul_190)[name = string("reshape_35")];
            tensor<int32, [3]> transpose_17_perm_0 = const()[name = string("transpose_17_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_193_y_0 = const()[name = string("mul_193_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3737024)))];
            tensor<fp16, [16, 352]> mul_193 = mul(x = mul_184, y = mul_193_y_0)[name = string("mul_193")];
            tensor<fp16, [88, 352]> tern_4_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3737792))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_4_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_4_v_bias_0 = const()[name = string("tern_4_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [16, 88]> tern_4_v = linear(bias = tern_4_v_bias_0, weight = tern_4_v_weight_0_palettized, x = mul_193)[name = string("tern_4_v")];
            tensor<fp16, [88]> mul_194_y_0 = const()[name = string("mul_194_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3745600)))];
            tensor<fp16, [16, 88]> mul_194 = mul(x = tern_4_v, y = mul_194_y_0)[name = string("mul_194")];
            tensor<int32, [3]> reshape_36_shape_0 = const()[name = string("reshape_36_shape_0"), val = tensor<int32, [3]>([16, 2, 44])];
            tensor<fp16, [16, 2, 44]> reshape_36 = reshape(shape = reshape_36_shape_0, x = mul_194)[name = string("reshape_36")];
            tensor<int32, [3]> transpose_18_perm_0 = const()[name = string("transpose_18_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 16, 44]> transpose_16 = transpose(perm = transpose_16_perm_0, x = reshape_34)[name = string("transpose_47")];
            tensor<fp16, [8, 16, 44]> mul_195 = mul(x = transpose_16, y = transpose_16)[name = string("mul_195")];
            tensor<int32, [1]> reduce_mean_42_axes_0 = const()[name = string("reduce_mean_42_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_42_keep_dims_0 = const()[name = string("reduce_mean_42_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 16, 1]> reduce_mean_42 = reduce_mean(axes = reduce_mean_42_axes_0, keep_dims = reduce_mean_42_keep_dims_0, x = mul_195)[name = string("reduce_mean_42")];
            fp32 rsqrt_42_epsilon_0 = const()[name = string("rsqrt_42_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 16, 1]> rsqrt_42 = rsqrt(epsilon = rsqrt_42_epsilon_0, x = reduce_mean_42)[name = string("rsqrt_42")];
            tensor<fp16, [8, 16, 44]> mul_196 = mul(x = transpose_16, y = rsqrt_42)[name = string("mul_196")];
            tensor<fp16, [44]> mul_197_y_0 = const()[name = string("mul_197_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3745856)))];
            tensor<fp16, [8, 16, 44]> mul_197 = mul(x = mul_196, y = mul_197_y_0)[name = string("mul_197")];
            tensor<int32, [3]> slice_by_index_16_begin_0 = const()[name = string("slice_by_index_16_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_16_end_0 = const()[name = string("slice_by_index_16_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_16_end_mask_0 = const()[name = string("slice_by_index_16_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 16, 22]> slice_by_index_16 = slice_by_index(begin = slice_by_index_16_begin_0, end = slice_by_index_16_end_0, end_mask = slice_by_index_16_end_mask_0, x = mul_197)[name = string("slice_by_index_16")];
            tensor<int32, [3]> slice_by_index_17_begin_0 = const()[name = string("slice_by_index_17_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_17_end_0 = const()[name = string("slice_by_index_17_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_17_end_mask_0 = const()[name = string("slice_by_index_17_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 16, 22]> slice_by_index_17 = slice_by_index(begin = slice_by_index_17_begin_0, end = slice_by_index_17_end_0, end_mask = slice_by_index_17_end_mask_0, x = mul_197)[name = string("slice_by_index_17")];
            int32 concat_8_axis_0 = const()[name = string("concat_8_axis_0"), val = int32(-1)];
            bool concat_8_interleave_0 = const()[name = string("concat_8_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 16, 44]> concat_8 = concat(axis = concat_8_axis_0, interleave = concat_8_interleave_0, values = (slice_by_index_17, slice_by_index_16))[name = string("concat_8")];
            tensor<fp16, [44]> mul_198_y_0 = const()[name = string("mul_198_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 16, 44]> mul_198 = mul(x = concat_8, y = mul_198_y_0)[name = string("mul_198")];
            tensor<fp16, [8, 16, 44]> mul_199 = mul(x = mul_197, y = mul_11_y_0)[name = string("mul_199")];
            tensor<fp16, [8, 16, 44]> mul_200 = mul(x = mul_198, y = mul_12_y_0)[name = string("mul_200")];
            tensor<fp16, [8, 16, 44]> add_24 = add(x = mul_199, y = mul_200)[name = string("add_24")];
            tensor<fp16, [2, 16, 44]> transpose_17 = transpose(perm = transpose_17_perm_0, x = reshape_35)[name = string("transpose_46")];
            tensor<fp16, [2, 16, 44]> mul_201 = mul(x = transpose_17, y = transpose_17)[name = string("mul_201")];
            tensor<int32, [1]> reduce_mean_43_axes_0 = const()[name = string("reduce_mean_43_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_43_keep_dims_0 = const()[name = string("reduce_mean_43_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 16, 1]> reduce_mean_43 = reduce_mean(axes = reduce_mean_43_axes_0, keep_dims = reduce_mean_43_keep_dims_0, x = mul_201)[name = string("reduce_mean_43")];
            fp32 rsqrt_43_epsilon_0 = const()[name = string("rsqrt_43_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 16, 1]> rsqrt_43 = rsqrt(epsilon = rsqrt_43_epsilon_0, x = reduce_mean_43)[name = string("rsqrt_43")];
            tensor<fp16, [2, 16, 44]> mul_202 = mul(x = transpose_17, y = rsqrt_43)[name = string("mul_202")];
            tensor<fp16, [44]> mul_203_y_0 = const()[name = string("mul_203_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3746048)))];
            tensor<fp16, [2, 16, 44]> mul_203 = mul(x = mul_202, y = mul_203_y_0)[name = string("mul_203")];
            tensor<int32, [3]> slice_by_index_18_begin_0 = const()[name = string("slice_by_index_18_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_18_end_0 = const()[name = string("slice_by_index_18_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_18_end_mask_0 = const()[name = string("slice_by_index_18_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 16, 22]> slice_by_index_18 = slice_by_index(begin = slice_by_index_18_begin_0, end = slice_by_index_18_end_0, end_mask = slice_by_index_18_end_mask_0, x = mul_203)[name = string("slice_by_index_18")];
            tensor<int32, [3]> slice_by_index_19_begin_0 = const()[name = string("slice_by_index_19_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_19_end_0 = const()[name = string("slice_by_index_19_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_19_end_mask_0 = const()[name = string("slice_by_index_19_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 16, 22]> slice_by_index_19 = slice_by_index(begin = slice_by_index_19_begin_0, end = slice_by_index_19_end_0, end_mask = slice_by_index_19_end_mask_0, x = mul_203)[name = string("slice_by_index_19")];
            int32 concat_9_axis_0 = const()[name = string("concat_9_axis_0"), val = int32(-1)];
            bool concat_9_interleave_0 = const()[name = string("concat_9_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 16, 44]> concat_9 = concat(axis = concat_9_axis_0, interleave = concat_9_interleave_0, values = (slice_by_index_19, slice_by_index_18))[name = string("concat_9")];
            tensor<fp16, [44]> mul_204_y_0 = const()[name = string("mul_204_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 16, 44]> mul_204 = mul(x = concat_9, y = mul_204_y_0)[name = string("mul_204")];
            tensor<fp16, [2, 16, 44]> mul_205 = mul(x = mul_203, y = mul_11_y_0)[name = string("mul_205")];
            tensor<fp16, [2, 16, 44]> mul_206 = mul(x = mul_204, y = mul_12_y_0)[name = string("mul_206")];
            tensor<fp16, [2, 16, 44]> add_25 = add(x = mul_205, y = mul_206)[name = string("add_25")];
            tensor<int32, [4]> reshape_37_shape_0 = const()[name = string("reshape_37_shape_0"), val = tensor<int32, [4]>([2, 1, 16, 44])];
            tensor<fp16, [2, 1, 16, 44]> reshape_37 = reshape(shape = reshape_37_shape_0, x = add_25)[name = string("reshape_37")];
            tensor<int32, [4]> tile_8_reps_0 = const()[name = string("tile_8_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 16, 44]> tile_8 = tile(reps = tile_8_reps_0, x = reshape_37)[name = string("tile_8")];
            tensor<int32, [3]> reshape_38_shape_0 = const()[name = string("reshape_38_shape_0"), val = tensor<int32, [3]>([8, 16, 44])];
            tensor<fp16, [8, 16, 44]> reshape_38 = reshape(shape = reshape_38_shape_0, x = tile_8)[name = string("reshape_38")];
            tensor<int32, [4]> reshape_39_shape_0 = const()[name = string("reshape_39_shape_0"), val = tensor<int32, [4]>([2, 1, 16, 44])];
            tensor<fp16, [2, 16, 44]> transpose_18 = transpose(perm = transpose_18_perm_0, x = reshape_36)[name = string("transpose_45")];
            tensor<fp16, [2, 1, 16, 44]> reshape_39 = reshape(shape = reshape_39_shape_0, x = transpose_18)[name = string("reshape_39")];
            tensor<int32, [4]> tile_9_reps_0 = const()[name = string("tile_9_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 16, 44]> tile_9 = tile(reps = tile_9_reps_0, x = reshape_39)[name = string("tile_9")];
            tensor<int32, [3]> reshape_40_shape_0 = const()[name = string("reshape_40_shape_0"), val = tensor<int32, [3]>([8, 16, 44])];
            tensor<fp16, [8, 16, 44]> reshape_40 = reshape(shape = reshape_40_shape_0, x = tile_9)[name = string("reshape_40")];
            fp16 mul_207_y_0 = const()[name = string("mul_207_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 16, 44]> mul_207 = mul(x = add_24, y = mul_207_y_0)[name = string("mul_207")];
            bool matmul_8_transpose_y_0 = const()[name = string("matmul_8_transpose_y_0"), val = bool(true)];
            bool matmul_8_transpose_x_0 = const()[name = string("matmul_8_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 16, 16]> matmul_8 = matmul(transpose_x = matmul_8_transpose_x_0, transpose_y = matmul_8_transpose_y_0, x = mul_207, y = reshape_38)[name = string("matmul_8")];
            tensor<fp16, [8, 16, 16]> add_26 = add(x = matmul_8, y = reshape_1)[name = string("add_26")];
            int32 softmax_4_axis_0 = const()[name = string("softmax_4_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 16, 16]> softmax_4 = softmax(axis = softmax_4_axis_0, x = add_26)[name = string("softmax_4")];
            bool matmul_9_transpose_x_0 = const()[name = string("matmul_9_transpose_x_0"), val = bool(false)];
            bool matmul_9_transpose_y_0 = const()[name = string("matmul_9_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 16, 44]> matmul_9 = matmul(transpose_x = matmul_9_transpose_x_0, transpose_y = matmul_9_transpose_y_0, x = softmax_4, y = reshape_40)[name = string("matmul_9")];
            tensor<int32, [3]> transpose_19_perm_0 = const()[name = string("transpose_19_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_41_shape_0 = const()[name = string("reshape_41_shape_0"), val = tensor<int32, [2]>([16, 352])];
            tensor<fp16, [16, 8, 44]> transpose_19 = transpose(perm = transpose_19_perm_0, x = matmul_9)[name = string("transpose_44")];
            tensor<fp16, [16, 352]> reshape_41 = reshape(shape = reshape_41_shape_0, x = transpose_19)[name = string("reshape_41")];
            tensor<fp16, [16, 352]> mul_208 = mul(x = reshape_41, y = reshape_41)[name = string("mul_208")];
            tensor<int32, [1]> reduce_mean_44_axes_0 = const()[name = string("reduce_mean_44_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_44_keep_dims_0 = const()[name = string("reduce_mean_44_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_44 = reduce_mean(axes = reduce_mean_44_axes_0, keep_dims = reduce_mean_44_keep_dims_0, x = mul_208)[name = string("reduce_mean_44")];
            fp32 rsqrt_44_epsilon_0 = const()[name = string("rsqrt_44_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_44 = rsqrt(epsilon = rsqrt_44_epsilon_0, x = reduce_mean_44)[name = string("rsqrt_44")];
            tensor<fp16, [16, 352]> mul_209 = mul(x = reshape_41, y = rsqrt_44)[name = string("mul_209")];
            tensor<fp16, [352]> mul_210_y_0 = const()[name = string("mul_210_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3746240)))];
            tensor<fp16, [16, 352]> mul_210 = mul(x = mul_209, y = mul_210_y_0)[name = string("mul_210")];
            tensor<fp16, [352, 352]> tern_4_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3747008))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_4_o_weight_0_palettized")];
            tensor<fp16, [16, 352]> tern_4_o = linear(bias = linear_0_bias_0, weight = tern_4_o_weight_0_palettized, x = mul_210)[name = string("tern_4_o")];
            tensor<fp16, [352]> mul_211_y_0 = const()[name = string("mul_211_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3778048)))];
            tensor<fp16, [16, 352]> mul_211 = mul(x = tern_4_o, y = mul_211_y_0)[name = string("mul_211")];
            tensor<fp16, [16, 352]> add_27 = add(x = add_23, y = mul_211)[name = string("add_27")];
            tensor<fp16, [16, 352]> mul_212 = mul(x = add_27, y = add_27)[name = string("mul_212")];
            tensor<int32, [1]> reduce_mean_45_axes_0 = const()[name = string("reduce_mean_45_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_45_keep_dims_0 = const()[name = string("reduce_mean_45_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_45 = reduce_mean(axes = reduce_mean_45_axes_0, keep_dims = reduce_mean_45_keep_dims_0, x = mul_212)[name = string("reduce_mean_45")];
            fp32 rsqrt_45_epsilon_0 = const()[name = string("rsqrt_45_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_45 = rsqrt(epsilon = rsqrt_45_epsilon_0, x = reduce_mean_45)[name = string("rsqrt_45")];
            tensor<fp16, [16, 352]> mul_213 = mul(x = add_27, y = rsqrt_45)[name = string("mul_213")];
            tensor<fp16, [352]> mul_214_y_0 = const()[name = string("mul_214_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3778816)))];
            tensor<fp16, [16, 352]> mul_214 = mul(x = mul_213, y = mul_214_y_0)[name = string("mul_214")];
            tensor<fp16, [16, 352]> mul_215 = mul(x = mul_214, y = mul_214)[name = string("mul_215")];
            tensor<int32, [1]> reduce_mean_46_axes_0 = const()[name = string("reduce_mean_46_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_46_keep_dims_0 = const()[name = string("reduce_mean_46_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_46 = reduce_mean(axes = reduce_mean_46_axes_0, keep_dims = reduce_mean_46_keep_dims_0, x = mul_215)[name = string("reduce_mean_46")];
            fp32 rsqrt_46_epsilon_0 = const()[name = string("rsqrt_46_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_46 = rsqrt(epsilon = rsqrt_46_epsilon_0, x = reduce_mean_46)[name = string("rsqrt_46")];
            tensor<fp16, [16, 352]> mul_216 = mul(x = mul_214, y = rsqrt_46)[name = string("mul_216")];
            tensor<fp16, [352]> mul_217_y_0 = const()[name = string("mul_217_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3779584)))];
            tensor<fp16, [16, 352]> mul_217 = mul(x = mul_216, y = mul_217_y_0)[name = string("mul_217")];
            tensor<fp16, [960, 352]> tern_4_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3780352))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_4_w1_weight_0_palettized")];
            tensor<fp16, [16, 960]> tern_4_w1 = linear(bias = linear_4_bias_0, weight = tern_4_w1_weight_0_palettized, x = mul_217)[name = string("tern_4_w1")];
            tensor<fp16, [960]> mul_218_y_0 = const()[name = string("mul_218_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3864896)))];
            tensor<fp16, [16, 960]> mul_218 = mul(x = tern_4_w1, y = mul_218_y_0)[name = string("mul_218")];
            tensor<fp16, [352]> mul_221_y_0 = const()[name = string("mul_221_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3866880)))];
            tensor<fp16, [16, 352]> mul_221 = mul(x = mul_216, y = mul_221_y_0)[name = string("mul_221")];
            tensor<fp16, [960, 352]> tern_4_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3867648))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_4_w3_weight_0_palettized")];
            tensor<fp16, [16, 960]> tern_4_w3 = linear(bias = linear_4_bias_0, weight = tern_4_w3_weight_0_palettized, x = mul_221)[name = string("tern_4_w3")];
            tensor<fp16, [960]> mul_222_y_0 = const()[name = string("mul_222_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3952192)))];
            tensor<fp16, [16, 960]> mul_222 = mul(x = tern_4_w3, y = mul_222_y_0)[name = string("mul_222")];
            fp16 mul_223_y_0 = const()[name = string("mul_223_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [16, 960]> mul_223 = mul(x = mul_218, y = mul_223_y_0)[name = string("mul_223")];
            tensor<fp16, [16, 960]> tanh_4 = tanh(x = mul_223)[name = string("tanh_4")];
            fp16 mul_224_x_0 = const()[name = string("mul_224_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [16, 960]> mul_224 = mul(x = mul_224_x_0, y = tanh_4)[name = string("mul_224")];
            fp16 add_28_x_0 = const()[name = string("add_28_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [16, 960]> add_28 = add(x = add_28_x_0, y = mul_224)[name = string("add_28")];
            tensor<fp16, [16, 960]> mul_225 = mul(x = mul_218, y = add_28)[name = string("mul_225")];
            tensor<fp16, [16, 960]> mul_226 = mul(x = mul_225, y = mul_222)[name = string("mul_226")];
            tensor<fp16, [16, 960]> mul_227 = mul(x = mul_226, y = mul_226)[name = string("mul_227")];
            tensor<int32, [1]> reduce_mean_48_axes_0 = const()[name = string("reduce_mean_48_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_48_keep_dims_0 = const()[name = string("reduce_mean_48_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_48 = reduce_mean(axes = reduce_mean_48_axes_0, keep_dims = reduce_mean_48_keep_dims_0, x = mul_227)[name = string("reduce_mean_48")];
            fp32 rsqrt_48_epsilon_0 = const()[name = string("rsqrt_48_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_48 = rsqrt(epsilon = rsqrt_48_epsilon_0, x = reduce_mean_48)[name = string("rsqrt_48")];
            tensor<fp16, [16, 960]> mul_228 = mul(x = mul_226, y = rsqrt_48)[name = string("mul_228")];
            tensor<fp16, [960]> mul_229_y_0 = const()[name = string("mul_229_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3954176)))];
            tensor<fp16, [16, 960]> mul_229 = mul(x = mul_228, y = mul_229_y_0)[name = string("mul_229")];
            tensor<fp16, [352, 960]> tern_4_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3956160))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_4_w2_weight_0_palettized")];
            tensor<fp16, [16, 352]> tern_4_w2 = linear(bias = linear_0_bias_0, weight = tern_4_w2_weight_0_palettized, x = mul_229)[name = string("tern_4_w2")];
            tensor<fp16, [352]> mul_230_y_0 = const()[name = string("mul_230_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4040704)))];
            tensor<fp16, [16, 352]> mul_230 = mul(x = tern_4_w2, y = mul_230_y_0)[name = string("mul_230")];
            tensor<fp16, [16, 352]> add_29 = add(x = add_27, y = mul_230)[name = string("add_29")];
            tensor<fp16, [16, 352]> mul_231 = mul(x = add_29, y = add_29)[name = string("mul_231")];
            tensor<int32, [1]> reduce_mean_49_axes_0 = const()[name = string("reduce_mean_49_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_49_keep_dims_0 = const()[name = string("reduce_mean_49_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_49 = reduce_mean(axes = reduce_mean_49_axes_0, keep_dims = reduce_mean_49_keep_dims_0, x = mul_231)[name = string("reduce_mean_49")];
            fp32 rsqrt_49_epsilon_0 = const()[name = string("rsqrt_49_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_49 = rsqrt(epsilon = rsqrt_49_epsilon_0, x = reduce_mean_49)[name = string("rsqrt_49")];
            tensor<fp16, [16, 352]> mul_232 = mul(x = add_29, y = rsqrt_49)[name = string("mul_232")];
            tensor<fp16, [352]> mul_233_y_0 = const()[name = string("mul_233_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4041472)))];
            tensor<fp16, [16, 352]> mul_233 = mul(x = mul_232, y = mul_233_y_0)[name = string("mul_233")];
            tensor<fp16, [16, 352]> mul_234 = mul(x = mul_233, y = mul_233)[name = string("mul_234")];
            tensor<int32, [1]> reduce_mean_50_axes_0 = const()[name = string("reduce_mean_50_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_50_keep_dims_0 = const()[name = string("reduce_mean_50_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_50 = reduce_mean(axes = reduce_mean_50_axes_0, keep_dims = reduce_mean_50_keep_dims_0, x = mul_234)[name = string("reduce_mean_50")];
            fp32 rsqrt_50_epsilon_0 = const()[name = string("rsqrt_50_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_50 = rsqrt(epsilon = rsqrt_50_epsilon_0, x = reduce_mean_50)[name = string("rsqrt_50")];
            tensor<fp16, [16, 352]> mul_235 = mul(x = mul_233, y = rsqrt_50)[name = string("mul_235")];
            tensor<fp16, [352]> mul_236_y_0 = const()[name = string("mul_236_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4042240)))];
            tensor<fp16, [16, 352]> mul_236 = mul(x = mul_235, y = mul_236_y_0)[name = string("mul_236")];
            tensor<fp16, [352, 352]> tern_5_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4043008))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_5_q_weight_0_palettized")];
            tensor<fp16, [16, 352]> tern_5_q = linear(bias = linear_0_bias_0, weight = tern_5_q_weight_0_palettized, x = mul_236)[name = string("tern_5_q")];
            tensor<fp16, [352]> mul_237_y_0 = const()[name = string("mul_237_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4074048)))];
            tensor<fp16, [16, 352]> mul_237 = mul(x = tern_5_q, y = mul_237_y_0)[name = string("mul_237")];
            tensor<int32, [3]> reshape_42_shape_0 = const()[name = string("reshape_42_shape_0"), val = tensor<int32, [3]>([16, 8, 44])];
            tensor<fp16, [16, 8, 44]> reshape_42 = reshape(shape = reshape_42_shape_0, x = mul_237)[name = string("reshape_42")];
            tensor<int32, [3]> transpose_20_perm_0 = const()[name = string("transpose_20_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_240_y_0 = const()[name = string("mul_240_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4074816)))];
            tensor<fp16, [16, 352]> mul_240 = mul(x = mul_235, y = mul_240_y_0)[name = string("mul_240")];
            tensor<fp16, [88, 352]> tern_5_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4075584))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_5_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_5_k_bias_0 = const()[name = string("tern_5_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [16, 88]> tern_5_k = linear(bias = tern_5_k_bias_0, weight = tern_5_k_weight_0_palettized, x = mul_240)[name = string("tern_5_k")];
            tensor<fp16, [88]> mul_241_y_0 = const()[name = string("mul_241_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4083392)))];
            tensor<fp16, [16, 88]> mul_241 = mul(x = tern_5_k, y = mul_241_y_0)[name = string("mul_241")];
            tensor<int32, [3]> reshape_43_shape_0 = const()[name = string("reshape_43_shape_0"), val = tensor<int32, [3]>([16, 2, 44])];
            tensor<fp16, [16, 2, 44]> reshape_43 = reshape(shape = reshape_43_shape_0, x = mul_241)[name = string("reshape_43")];
            tensor<int32, [3]> transpose_21_perm_0 = const()[name = string("transpose_21_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_244_y_0 = const()[name = string("mul_244_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4083648)))];
            tensor<fp16, [16, 352]> mul_244 = mul(x = mul_235, y = mul_244_y_0)[name = string("mul_244")];
            tensor<fp16, [88, 352]> tern_5_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4084416))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_5_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_5_v_bias_0 = const()[name = string("tern_5_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [16, 88]> tern_5_v = linear(bias = tern_5_v_bias_0, weight = tern_5_v_weight_0_palettized, x = mul_244)[name = string("tern_5_v")];
            tensor<fp16, [88]> mul_245_y_0 = const()[name = string("mul_245_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4092224)))];
            tensor<fp16, [16, 88]> mul_245 = mul(x = tern_5_v, y = mul_245_y_0)[name = string("mul_245")];
            tensor<int32, [3]> reshape_44_shape_0 = const()[name = string("reshape_44_shape_0"), val = tensor<int32, [3]>([16, 2, 44])];
            tensor<fp16, [16, 2, 44]> reshape_44 = reshape(shape = reshape_44_shape_0, x = mul_245)[name = string("reshape_44")];
            tensor<int32, [3]> transpose_22_perm_0 = const()[name = string("transpose_22_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 16, 44]> transpose_20 = transpose(perm = transpose_20_perm_0, x = reshape_42)[name = string("transpose_43")];
            tensor<fp16, [8, 16, 44]> mul_246 = mul(x = transpose_20, y = transpose_20)[name = string("mul_246")];
            tensor<int32, [1]> reduce_mean_53_axes_0 = const()[name = string("reduce_mean_53_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_53_keep_dims_0 = const()[name = string("reduce_mean_53_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 16, 1]> reduce_mean_53 = reduce_mean(axes = reduce_mean_53_axes_0, keep_dims = reduce_mean_53_keep_dims_0, x = mul_246)[name = string("reduce_mean_53")];
            fp32 rsqrt_53_epsilon_0 = const()[name = string("rsqrt_53_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 16, 1]> rsqrt_53 = rsqrt(epsilon = rsqrt_53_epsilon_0, x = reduce_mean_53)[name = string("rsqrt_53")];
            tensor<fp16, [8, 16, 44]> mul_247 = mul(x = transpose_20, y = rsqrt_53)[name = string("mul_247")];
            tensor<fp16, [44]> mul_248_y_0 = const()[name = string("mul_248_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4092480)))];
            tensor<fp16, [8, 16, 44]> mul_248 = mul(x = mul_247, y = mul_248_y_0)[name = string("mul_248")];
            tensor<int32, [3]> slice_by_index_20_begin_0 = const()[name = string("slice_by_index_20_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_20_end_0 = const()[name = string("slice_by_index_20_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_20_end_mask_0 = const()[name = string("slice_by_index_20_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 16, 22]> slice_by_index_20 = slice_by_index(begin = slice_by_index_20_begin_0, end = slice_by_index_20_end_0, end_mask = slice_by_index_20_end_mask_0, x = mul_248)[name = string("slice_by_index_20")];
            tensor<int32, [3]> slice_by_index_21_begin_0 = const()[name = string("slice_by_index_21_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_21_end_0 = const()[name = string("slice_by_index_21_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_21_end_mask_0 = const()[name = string("slice_by_index_21_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 16, 22]> slice_by_index_21 = slice_by_index(begin = slice_by_index_21_begin_0, end = slice_by_index_21_end_0, end_mask = slice_by_index_21_end_mask_0, x = mul_248)[name = string("slice_by_index_21")];
            int32 concat_10_axis_0 = const()[name = string("concat_10_axis_0"), val = int32(-1)];
            bool concat_10_interleave_0 = const()[name = string("concat_10_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 16, 44]> concat_10 = concat(axis = concat_10_axis_0, interleave = concat_10_interleave_0, values = (slice_by_index_21, slice_by_index_20))[name = string("concat_10")];
            tensor<fp16, [44]> mul_249_y_0 = const()[name = string("mul_249_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 16, 44]> mul_249 = mul(x = concat_10, y = mul_249_y_0)[name = string("mul_249")];
            tensor<fp16, [8, 16, 44]> mul_250 = mul(x = mul_248, y = mul_11_y_0)[name = string("mul_250")];
            tensor<fp16, [8, 16, 44]> mul_251 = mul(x = mul_249, y = mul_12_y_0)[name = string("mul_251")];
            tensor<fp16, [8, 16, 44]> add_30 = add(x = mul_250, y = mul_251)[name = string("add_30")];
            tensor<fp16, [2, 16, 44]> transpose_21 = transpose(perm = transpose_21_perm_0, x = reshape_43)[name = string("transpose_42")];
            tensor<fp16, [2, 16, 44]> mul_252 = mul(x = transpose_21, y = transpose_21)[name = string("mul_252")];
            tensor<int32, [1]> reduce_mean_54_axes_0 = const()[name = string("reduce_mean_54_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_54_keep_dims_0 = const()[name = string("reduce_mean_54_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 16, 1]> reduce_mean_54 = reduce_mean(axes = reduce_mean_54_axes_0, keep_dims = reduce_mean_54_keep_dims_0, x = mul_252)[name = string("reduce_mean_54")];
            fp32 rsqrt_54_epsilon_0 = const()[name = string("rsqrt_54_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 16, 1]> rsqrt_54 = rsqrt(epsilon = rsqrt_54_epsilon_0, x = reduce_mean_54)[name = string("rsqrt_54")];
            tensor<fp16, [2, 16, 44]> mul_253 = mul(x = transpose_21, y = rsqrt_54)[name = string("mul_253")];
            tensor<fp16, [44]> mul_254_y_0 = const()[name = string("mul_254_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4092672)))];
            tensor<fp16, [2, 16, 44]> mul_254 = mul(x = mul_253, y = mul_254_y_0)[name = string("mul_254")];
            tensor<int32, [3]> slice_by_index_22_begin_0 = const()[name = string("slice_by_index_22_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_22_end_0 = const()[name = string("slice_by_index_22_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_22_end_mask_0 = const()[name = string("slice_by_index_22_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 16, 22]> slice_by_index_22 = slice_by_index(begin = slice_by_index_22_begin_0, end = slice_by_index_22_end_0, end_mask = slice_by_index_22_end_mask_0, x = mul_254)[name = string("slice_by_index_22")];
            tensor<int32, [3]> slice_by_index_23_begin_0 = const()[name = string("slice_by_index_23_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_23_end_0 = const()[name = string("slice_by_index_23_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_23_end_mask_0 = const()[name = string("slice_by_index_23_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 16, 22]> slice_by_index_23 = slice_by_index(begin = slice_by_index_23_begin_0, end = slice_by_index_23_end_0, end_mask = slice_by_index_23_end_mask_0, x = mul_254)[name = string("slice_by_index_23")];
            int32 concat_11_axis_0 = const()[name = string("concat_11_axis_0"), val = int32(-1)];
            bool concat_11_interleave_0 = const()[name = string("concat_11_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 16, 44]> concat_11 = concat(axis = concat_11_axis_0, interleave = concat_11_interleave_0, values = (slice_by_index_23, slice_by_index_22))[name = string("concat_11")];
            tensor<fp16, [44]> mul_255_y_0 = const()[name = string("mul_255_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 16, 44]> mul_255 = mul(x = concat_11, y = mul_255_y_0)[name = string("mul_255")];
            tensor<fp16, [2, 16, 44]> mul_256 = mul(x = mul_254, y = mul_11_y_0)[name = string("mul_256")];
            tensor<fp16, [2, 16, 44]> mul_257 = mul(x = mul_255, y = mul_12_y_0)[name = string("mul_257")];
            tensor<fp16, [2, 16, 44]> add_31 = add(x = mul_256, y = mul_257)[name = string("add_31")];
            tensor<int32, [4]> reshape_45_shape_0 = const()[name = string("reshape_45_shape_0"), val = tensor<int32, [4]>([2, 1, 16, 44])];
            tensor<fp16, [2, 1, 16, 44]> reshape_45 = reshape(shape = reshape_45_shape_0, x = add_31)[name = string("reshape_45")];
            tensor<int32, [4]> tile_10_reps_0 = const()[name = string("tile_10_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 16, 44]> tile_10 = tile(reps = tile_10_reps_0, x = reshape_45)[name = string("tile_10")];
            tensor<int32, [3]> reshape_46_shape_0 = const()[name = string("reshape_46_shape_0"), val = tensor<int32, [3]>([8, 16, 44])];
            tensor<fp16, [8, 16, 44]> reshape_46 = reshape(shape = reshape_46_shape_0, x = tile_10)[name = string("reshape_46")];
            tensor<int32, [4]> reshape_47_shape_0 = const()[name = string("reshape_47_shape_0"), val = tensor<int32, [4]>([2, 1, 16, 44])];
            tensor<fp16, [2, 16, 44]> transpose_22 = transpose(perm = transpose_22_perm_0, x = reshape_44)[name = string("transpose_41")];
            tensor<fp16, [2, 1, 16, 44]> reshape_47 = reshape(shape = reshape_47_shape_0, x = transpose_22)[name = string("reshape_47")];
            tensor<int32, [4]> tile_11_reps_0 = const()[name = string("tile_11_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 16, 44]> tile_11 = tile(reps = tile_11_reps_0, x = reshape_47)[name = string("tile_11")];
            tensor<int32, [3]> reshape_48_shape_0 = const()[name = string("reshape_48_shape_0"), val = tensor<int32, [3]>([8, 16, 44])];
            tensor<fp16, [8, 16, 44]> reshape_48 = reshape(shape = reshape_48_shape_0, x = tile_11)[name = string("reshape_48")];
            fp16 mul_258_y_0 = const()[name = string("mul_258_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 16, 44]> mul_258 = mul(x = add_30, y = mul_258_y_0)[name = string("mul_258")];
            bool matmul_10_transpose_y_0 = const()[name = string("matmul_10_transpose_y_0"), val = bool(true)];
            bool matmul_10_transpose_x_0 = const()[name = string("matmul_10_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 16, 16]> matmul_10 = matmul(transpose_x = matmul_10_transpose_x_0, transpose_y = matmul_10_transpose_y_0, x = mul_258, y = reshape_46)[name = string("matmul_10")];
            tensor<fp16, [8, 16, 16]> add_32 = add(x = matmul_10, y = reshape_1)[name = string("add_32")];
            int32 softmax_5_axis_0 = const()[name = string("softmax_5_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 16, 16]> softmax_5 = softmax(axis = softmax_5_axis_0, x = add_32)[name = string("softmax_5")];
            bool matmul_11_transpose_x_0 = const()[name = string("matmul_11_transpose_x_0"), val = bool(false)];
            bool matmul_11_transpose_y_0 = const()[name = string("matmul_11_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 16, 44]> matmul_11 = matmul(transpose_x = matmul_11_transpose_x_0, transpose_y = matmul_11_transpose_y_0, x = softmax_5, y = reshape_48)[name = string("matmul_11")];
            tensor<int32, [3]> transpose_23_perm_0 = const()[name = string("transpose_23_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_49_shape_0 = const()[name = string("reshape_49_shape_0"), val = tensor<int32, [2]>([16, 352])];
            tensor<fp16, [16, 8, 44]> transpose_23 = transpose(perm = transpose_23_perm_0, x = matmul_11)[name = string("transpose_40")];
            tensor<fp16, [16, 352]> reshape_49 = reshape(shape = reshape_49_shape_0, x = transpose_23)[name = string("reshape_49")];
            tensor<fp16, [16, 352]> mul_259 = mul(x = reshape_49, y = reshape_49)[name = string("mul_259")];
            tensor<int32, [1]> reduce_mean_55_axes_0 = const()[name = string("reduce_mean_55_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_55_keep_dims_0 = const()[name = string("reduce_mean_55_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_55 = reduce_mean(axes = reduce_mean_55_axes_0, keep_dims = reduce_mean_55_keep_dims_0, x = mul_259)[name = string("reduce_mean_55")];
            fp32 rsqrt_55_epsilon_0 = const()[name = string("rsqrt_55_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_55 = rsqrt(epsilon = rsqrt_55_epsilon_0, x = reduce_mean_55)[name = string("rsqrt_55")];
            tensor<fp16, [16, 352]> mul_260 = mul(x = reshape_49, y = rsqrt_55)[name = string("mul_260")];
            tensor<fp16, [352]> mul_261_y_0 = const()[name = string("mul_261_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4092864)))];
            tensor<fp16, [16, 352]> mul_261 = mul(x = mul_260, y = mul_261_y_0)[name = string("mul_261")];
            tensor<fp16, [352, 352]> tern_5_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4093632))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_5_o_weight_0_palettized")];
            tensor<fp16, [16, 352]> tern_5_o = linear(bias = linear_0_bias_0, weight = tern_5_o_weight_0_palettized, x = mul_261)[name = string("tern_5_o")];
            tensor<fp16, [352]> mul_262_y_0 = const()[name = string("mul_262_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4124672)))];
            tensor<fp16, [16, 352]> mul_262 = mul(x = tern_5_o, y = mul_262_y_0)[name = string("mul_262")];
            tensor<fp16, [16, 352]> add_33 = add(x = add_29, y = mul_262)[name = string("add_33")];
            tensor<fp16, [16, 352]> mul_263 = mul(x = add_33, y = add_33)[name = string("mul_263")];
            tensor<int32, [1]> reduce_mean_56_axes_0 = const()[name = string("reduce_mean_56_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_56_keep_dims_0 = const()[name = string("reduce_mean_56_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_56 = reduce_mean(axes = reduce_mean_56_axes_0, keep_dims = reduce_mean_56_keep_dims_0, x = mul_263)[name = string("reduce_mean_56")];
            fp32 rsqrt_56_epsilon_0 = const()[name = string("rsqrt_56_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_56 = rsqrt(epsilon = rsqrt_56_epsilon_0, x = reduce_mean_56)[name = string("rsqrt_56")];
            tensor<fp16, [16, 352]> mul_264 = mul(x = add_33, y = rsqrt_56)[name = string("mul_264")];
            tensor<fp16, [352]> mul_265_y_0 = const()[name = string("mul_265_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4125440)))];
            tensor<fp16, [16, 352]> mul_265 = mul(x = mul_264, y = mul_265_y_0)[name = string("mul_265")];
            tensor<fp16, [16, 352]> mul_266 = mul(x = mul_265, y = mul_265)[name = string("mul_266")];
            tensor<int32, [1]> reduce_mean_57_axes_0 = const()[name = string("reduce_mean_57_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_57_keep_dims_0 = const()[name = string("reduce_mean_57_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_57 = reduce_mean(axes = reduce_mean_57_axes_0, keep_dims = reduce_mean_57_keep_dims_0, x = mul_266)[name = string("reduce_mean_57")];
            fp32 rsqrt_57_epsilon_0 = const()[name = string("rsqrt_57_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_57 = rsqrt(epsilon = rsqrt_57_epsilon_0, x = reduce_mean_57)[name = string("rsqrt_57")];
            tensor<fp16, [16, 352]> mul_267 = mul(x = mul_265, y = rsqrt_57)[name = string("mul_267")];
            tensor<fp16, [352]> mul_268_y_0 = const()[name = string("mul_268_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4126208)))];
            tensor<fp16, [16, 352]> mul_268 = mul(x = mul_267, y = mul_268_y_0)[name = string("mul_268")];
            tensor<fp16, [960, 352]> tern_5_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4126976))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_5_w1_weight_0_palettized")];
            tensor<fp16, [16, 960]> tern_5_w1 = linear(bias = linear_4_bias_0, weight = tern_5_w1_weight_0_palettized, x = mul_268)[name = string("tern_5_w1")];
            tensor<fp16, [960]> mul_269_y_0 = const()[name = string("mul_269_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4211520)))];
            tensor<fp16, [16, 960]> mul_269 = mul(x = tern_5_w1, y = mul_269_y_0)[name = string("mul_269")];
            tensor<fp16, [352]> mul_272_y_0 = const()[name = string("mul_272_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4213504)))];
            tensor<fp16, [16, 352]> mul_272 = mul(x = mul_267, y = mul_272_y_0)[name = string("mul_272")];
            tensor<fp16, [960, 352]> tern_5_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4214272))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_5_w3_weight_0_palettized")];
            tensor<fp16, [16, 960]> tern_5_w3 = linear(bias = linear_4_bias_0, weight = tern_5_w3_weight_0_palettized, x = mul_272)[name = string("tern_5_w3")];
            tensor<fp16, [960]> mul_273_y_0 = const()[name = string("mul_273_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4298816)))];
            tensor<fp16, [16, 960]> mul_273 = mul(x = tern_5_w3, y = mul_273_y_0)[name = string("mul_273")];
            fp16 mul_274_y_0 = const()[name = string("mul_274_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [16, 960]> mul_274 = mul(x = mul_269, y = mul_274_y_0)[name = string("mul_274")];
            tensor<fp16, [16, 960]> tanh_5 = tanh(x = mul_274)[name = string("tanh_5")];
            fp16 mul_275_x_0 = const()[name = string("mul_275_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [16, 960]> mul_275 = mul(x = mul_275_x_0, y = tanh_5)[name = string("mul_275")];
            fp16 add_34_x_0 = const()[name = string("add_34_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [16, 960]> add_34 = add(x = add_34_x_0, y = mul_275)[name = string("add_34")];
            tensor<fp16, [16, 960]> mul_276 = mul(x = mul_269, y = add_34)[name = string("mul_276")];
            tensor<fp16, [16, 960]> mul_277 = mul(x = mul_276, y = mul_273)[name = string("mul_277")];
            tensor<fp16, [16, 960]> mul_278 = mul(x = mul_277, y = mul_277)[name = string("mul_278")];
            tensor<int32, [1]> reduce_mean_59_axes_0 = const()[name = string("reduce_mean_59_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_59_keep_dims_0 = const()[name = string("reduce_mean_59_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_59 = reduce_mean(axes = reduce_mean_59_axes_0, keep_dims = reduce_mean_59_keep_dims_0, x = mul_278)[name = string("reduce_mean_59")];
            fp32 rsqrt_59_epsilon_0 = const()[name = string("rsqrt_59_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_59 = rsqrt(epsilon = rsqrt_59_epsilon_0, x = reduce_mean_59)[name = string("rsqrt_59")];
            tensor<fp16, [16, 960]> mul_279 = mul(x = mul_277, y = rsqrt_59)[name = string("mul_279")];
            tensor<fp16, [960]> mul_280_y_0 = const()[name = string("mul_280_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4300800)))];
            tensor<fp16, [16, 960]> mul_280 = mul(x = mul_279, y = mul_280_y_0)[name = string("mul_280")];
            tensor<fp16, [352, 960]> tern_5_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4302784))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_5_w2_weight_0_palettized")];
            tensor<fp16, [16, 352]> tern_5_w2 = linear(bias = linear_0_bias_0, weight = tern_5_w2_weight_0_palettized, x = mul_280)[name = string("tern_5_w2")];
            tensor<fp16, [352]> mul_281_y_0 = const()[name = string("mul_281_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4387328)))];
            tensor<fp16, [16, 352]> mul_281 = mul(x = tern_5_w2, y = mul_281_y_0)[name = string("mul_281")];
            tensor<fp16, [16, 352]> add_35 = add(x = add_33, y = mul_281)[name = string("add_35")];
            tensor<fp16, [16, 352]> mul_282 = mul(x = add_35, y = add_35)[name = string("mul_282")];
            tensor<int32, [1]> reduce_mean_60_axes_0 = const()[name = string("reduce_mean_60_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_60_keep_dims_0 = const()[name = string("reduce_mean_60_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_60 = reduce_mean(axes = reduce_mean_60_axes_0, keep_dims = reduce_mean_60_keep_dims_0, x = mul_282)[name = string("reduce_mean_60")];
            fp32 rsqrt_60_epsilon_0 = const()[name = string("rsqrt_60_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_60 = rsqrt(epsilon = rsqrt_60_epsilon_0, x = reduce_mean_60)[name = string("rsqrt_60")];
            tensor<fp16, [16, 352]> mul_283 = mul(x = add_35, y = rsqrt_60)[name = string("mul_283")];
            tensor<fp16, [352]> mul_284_y_0 = const()[name = string("mul_284_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4388096)))];
            tensor<fp16, [16, 352]> mul_284 = mul(x = mul_283, y = mul_284_y_0)[name = string("mul_284")];
            tensor<fp16, [16, 352]> mul_285 = mul(x = mul_284, y = mul_284)[name = string("mul_285")];
            tensor<int32, [1]> reduce_mean_61_axes_0 = const()[name = string("reduce_mean_61_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_61_keep_dims_0 = const()[name = string("reduce_mean_61_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_61 = reduce_mean(axes = reduce_mean_61_axes_0, keep_dims = reduce_mean_61_keep_dims_0, x = mul_285)[name = string("reduce_mean_61")];
            fp32 rsqrt_61_epsilon_0 = const()[name = string("rsqrt_61_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_61 = rsqrt(epsilon = rsqrt_61_epsilon_0, x = reduce_mean_61)[name = string("rsqrt_61")];
            tensor<fp16, [16, 352]> mul_286 = mul(x = mul_284, y = rsqrt_61)[name = string("mul_286")];
            tensor<fp16, [352]> mul_287_y_0 = const()[name = string("mul_287_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4388864)))];
            tensor<fp16, [16, 352]> mul_287 = mul(x = mul_286, y = mul_287_y_0)[name = string("mul_287")];
            tensor<fp16, [352, 352]> tern_6_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4389632))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_6_q_weight_0_palettized")];
            tensor<fp16, [16, 352]> tern_6_q = linear(bias = linear_0_bias_0, weight = tern_6_q_weight_0_palettized, x = mul_287)[name = string("tern_6_q")];
            tensor<fp16, [352]> mul_288_y_0 = const()[name = string("mul_288_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4420672)))];
            tensor<fp16, [16, 352]> mul_288 = mul(x = tern_6_q, y = mul_288_y_0)[name = string("mul_288")];
            tensor<int32, [3]> reshape_50_shape_0 = const()[name = string("reshape_50_shape_0"), val = tensor<int32, [3]>([16, 8, 44])];
            tensor<fp16, [16, 8, 44]> reshape_50 = reshape(shape = reshape_50_shape_0, x = mul_288)[name = string("reshape_50")];
            tensor<int32, [3]> transpose_24_perm_0 = const()[name = string("transpose_24_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_291_y_0 = const()[name = string("mul_291_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4421440)))];
            tensor<fp16, [16, 352]> mul_291 = mul(x = mul_286, y = mul_291_y_0)[name = string("mul_291")];
            tensor<fp16, [88, 352]> tern_6_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4422208))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_6_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_6_k_bias_0 = const()[name = string("tern_6_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [16, 88]> tern_6_k = linear(bias = tern_6_k_bias_0, weight = tern_6_k_weight_0_palettized, x = mul_291)[name = string("tern_6_k")];
            tensor<fp16, [88]> mul_292_y_0 = const()[name = string("mul_292_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4430016)))];
            tensor<fp16, [16, 88]> mul_292 = mul(x = tern_6_k, y = mul_292_y_0)[name = string("mul_292")];
            tensor<int32, [3]> reshape_51_shape_0 = const()[name = string("reshape_51_shape_0"), val = tensor<int32, [3]>([16, 2, 44])];
            tensor<fp16, [16, 2, 44]> reshape_51 = reshape(shape = reshape_51_shape_0, x = mul_292)[name = string("reshape_51")];
            tensor<int32, [3]> transpose_25_perm_0 = const()[name = string("transpose_25_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_295_y_0 = const()[name = string("mul_295_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4430272)))];
            tensor<fp16, [16, 352]> mul_295 = mul(x = mul_286, y = mul_295_y_0)[name = string("mul_295")];
            tensor<fp16, [88, 352]> tern_6_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4431040))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_6_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_6_v_bias_0 = const()[name = string("tern_6_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [16, 88]> tern_6_v = linear(bias = tern_6_v_bias_0, weight = tern_6_v_weight_0_palettized, x = mul_295)[name = string("tern_6_v")];
            tensor<fp16, [88]> mul_296_y_0 = const()[name = string("mul_296_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4438848)))];
            tensor<fp16, [16, 88]> mul_296 = mul(x = tern_6_v, y = mul_296_y_0)[name = string("mul_296")];
            tensor<int32, [3]> reshape_52_shape_0 = const()[name = string("reshape_52_shape_0"), val = tensor<int32, [3]>([16, 2, 44])];
            tensor<fp16, [16, 2, 44]> reshape_52 = reshape(shape = reshape_52_shape_0, x = mul_296)[name = string("reshape_52")];
            tensor<int32, [3]> transpose_26_perm_0 = const()[name = string("transpose_26_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 16, 44]> transpose_24 = transpose(perm = transpose_24_perm_0, x = reshape_50)[name = string("transpose_39")];
            tensor<fp16, [8, 16, 44]> mul_297 = mul(x = transpose_24, y = transpose_24)[name = string("mul_297")];
            tensor<int32, [1]> reduce_mean_64_axes_0 = const()[name = string("reduce_mean_64_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_64_keep_dims_0 = const()[name = string("reduce_mean_64_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 16, 1]> reduce_mean_64 = reduce_mean(axes = reduce_mean_64_axes_0, keep_dims = reduce_mean_64_keep_dims_0, x = mul_297)[name = string("reduce_mean_64")];
            fp32 rsqrt_64_epsilon_0 = const()[name = string("rsqrt_64_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 16, 1]> rsqrt_64 = rsqrt(epsilon = rsqrt_64_epsilon_0, x = reduce_mean_64)[name = string("rsqrt_64")];
            tensor<fp16, [8, 16, 44]> mul_298 = mul(x = transpose_24, y = rsqrt_64)[name = string("mul_298")];
            tensor<fp16, [44]> mul_299_y_0 = const()[name = string("mul_299_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4439104)))];
            tensor<fp16, [8, 16, 44]> mul_299 = mul(x = mul_298, y = mul_299_y_0)[name = string("mul_299")];
            tensor<int32, [3]> slice_by_index_24_begin_0 = const()[name = string("slice_by_index_24_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_24_end_0 = const()[name = string("slice_by_index_24_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_24_end_mask_0 = const()[name = string("slice_by_index_24_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 16, 22]> slice_by_index_24 = slice_by_index(begin = slice_by_index_24_begin_0, end = slice_by_index_24_end_0, end_mask = slice_by_index_24_end_mask_0, x = mul_299)[name = string("slice_by_index_24")];
            tensor<int32, [3]> slice_by_index_25_begin_0 = const()[name = string("slice_by_index_25_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_25_end_0 = const()[name = string("slice_by_index_25_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_25_end_mask_0 = const()[name = string("slice_by_index_25_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 16, 22]> slice_by_index_25 = slice_by_index(begin = slice_by_index_25_begin_0, end = slice_by_index_25_end_0, end_mask = slice_by_index_25_end_mask_0, x = mul_299)[name = string("slice_by_index_25")];
            int32 concat_12_axis_0 = const()[name = string("concat_12_axis_0"), val = int32(-1)];
            bool concat_12_interleave_0 = const()[name = string("concat_12_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 16, 44]> concat_12 = concat(axis = concat_12_axis_0, interleave = concat_12_interleave_0, values = (slice_by_index_25, slice_by_index_24))[name = string("concat_12")];
            tensor<fp16, [44]> mul_300_y_0 = const()[name = string("mul_300_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 16, 44]> mul_300 = mul(x = concat_12, y = mul_300_y_0)[name = string("mul_300")];
            tensor<fp16, [8, 16, 44]> mul_301 = mul(x = mul_299, y = mul_11_y_0)[name = string("mul_301")];
            tensor<fp16, [8, 16, 44]> mul_302 = mul(x = mul_300, y = mul_12_y_0)[name = string("mul_302")];
            tensor<fp16, [8, 16, 44]> add_36 = add(x = mul_301, y = mul_302)[name = string("add_36")];
            tensor<fp16, [2, 16, 44]> transpose_25 = transpose(perm = transpose_25_perm_0, x = reshape_51)[name = string("transpose_38")];
            tensor<fp16, [2, 16, 44]> mul_303 = mul(x = transpose_25, y = transpose_25)[name = string("mul_303")];
            tensor<int32, [1]> reduce_mean_65_axes_0 = const()[name = string("reduce_mean_65_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_65_keep_dims_0 = const()[name = string("reduce_mean_65_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 16, 1]> reduce_mean_65 = reduce_mean(axes = reduce_mean_65_axes_0, keep_dims = reduce_mean_65_keep_dims_0, x = mul_303)[name = string("reduce_mean_65")];
            fp32 rsqrt_65_epsilon_0 = const()[name = string("rsqrt_65_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 16, 1]> rsqrt_65 = rsqrt(epsilon = rsqrt_65_epsilon_0, x = reduce_mean_65)[name = string("rsqrt_65")];
            tensor<fp16, [2, 16, 44]> mul_304 = mul(x = transpose_25, y = rsqrt_65)[name = string("mul_304")];
            tensor<fp16, [44]> mul_305_y_0 = const()[name = string("mul_305_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4439296)))];
            tensor<fp16, [2, 16, 44]> mul_305 = mul(x = mul_304, y = mul_305_y_0)[name = string("mul_305")];
            tensor<int32, [3]> slice_by_index_26_begin_0 = const()[name = string("slice_by_index_26_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_26_end_0 = const()[name = string("slice_by_index_26_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_26_end_mask_0 = const()[name = string("slice_by_index_26_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 16, 22]> slice_by_index_26 = slice_by_index(begin = slice_by_index_26_begin_0, end = slice_by_index_26_end_0, end_mask = slice_by_index_26_end_mask_0, x = mul_305)[name = string("slice_by_index_26")];
            tensor<int32, [3]> slice_by_index_27_begin_0 = const()[name = string("slice_by_index_27_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_27_end_0 = const()[name = string("slice_by_index_27_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_27_end_mask_0 = const()[name = string("slice_by_index_27_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 16, 22]> slice_by_index_27 = slice_by_index(begin = slice_by_index_27_begin_0, end = slice_by_index_27_end_0, end_mask = slice_by_index_27_end_mask_0, x = mul_305)[name = string("slice_by_index_27")];
            int32 concat_13_axis_0 = const()[name = string("concat_13_axis_0"), val = int32(-1)];
            bool concat_13_interleave_0 = const()[name = string("concat_13_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 16, 44]> concat_13 = concat(axis = concat_13_axis_0, interleave = concat_13_interleave_0, values = (slice_by_index_27, slice_by_index_26))[name = string("concat_13")];
            tensor<fp16, [44]> mul_306_y_0 = const()[name = string("mul_306_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 16, 44]> mul_306 = mul(x = concat_13, y = mul_306_y_0)[name = string("mul_306")];
            tensor<fp16, [2, 16, 44]> mul_307 = mul(x = mul_305, y = mul_11_y_0)[name = string("mul_307")];
            tensor<fp16, [2, 16, 44]> mul_308 = mul(x = mul_306, y = mul_12_y_0)[name = string("mul_308")];
            tensor<fp16, [2, 16, 44]> add_37 = add(x = mul_307, y = mul_308)[name = string("add_37")];
            tensor<int32, [4]> reshape_53_shape_0 = const()[name = string("reshape_53_shape_0"), val = tensor<int32, [4]>([2, 1, 16, 44])];
            tensor<fp16, [2, 1, 16, 44]> reshape_53 = reshape(shape = reshape_53_shape_0, x = add_37)[name = string("reshape_53")];
            tensor<int32, [4]> tile_12_reps_0 = const()[name = string("tile_12_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 16, 44]> tile_12 = tile(reps = tile_12_reps_0, x = reshape_53)[name = string("tile_12")];
            tensor<int32, [3]> reshape_54_shape_0 = const()[name = string("reshape_54_shape_0"), val = tensor<int32, [3]>([8, 16, 44])];
            tensor<fp16, [8, 16, 44]> reshape_54 = reshape(shape = reshape_54_shape_0, x = tile_12)[name = string("reshape_54")];
            tensor<int32, [4]> reshape_55_shape_0 = const()[name = string("reshape_55_shape_0"), val = tensor<int32, [4]>([2, 1, 16, 44])];
            tensor<fp16, [2, 16, 44]> transpose_26 = transpose(perm = transpose_26_perm_0, x = reshape_52)[name = string("transpose_37")];
            tensor<fp16, [2, 1, 16, 44]> reshape_55 = reshape(shape = reshape_55_shape_0, x = transpose_26)[name = string("reshape_55")];
            tensor<int32, [4]> tile_13_reps_0 = const()[name = string("tile_13_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 16, 44]> tile_13 = tile(reps = tile_13_reps_0, x = reshape_55)[name = string("tile_13")];
            tensor<int32, [3]> reshape_56_shape_0 = const()[name = string("reshape_56_shape_0"), val = tensor<int32, [3]>([8, 16, 44])];
            tensor<fp16, [8, 16, 44]> reshape_56 = reshape(shape = reshape_56_shape_0, x = tile_13)[name = string("reshape_56")];
            fp16 mul_309_y_0 = const()[name = string("mul_309_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 16, 44]> mul_309 = mul(x = add_36, y = mul_309_y_0)[name = string("mul_309")];
            bool matmul_12_transpose_y_0 = const()[name = string("matmul_12_transpose_y_0"), val = bool(true)];
            bool matmul_12_transpose_x_0 = const()[name = string("matmul_12_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 16, 16]> matmul_12 = matmul(transpose_x = matmul_12_transpose_x_0, transpose_y = matmul_12_transpose_y_0, x = mul_309, y = reshape_54)[name = string("matmul_12")];
            tensor<fp16, [8, 16, 16]> add_38 = add(x = matmul_12, y = reshape_1)[name = string("add_38")];
            int32 softmax_6_axis_0 = const()[name = string("softmax_6_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 16, 16]> softmax_6 = softmax(axis = softmax_6_axis_0, x = add_38)[name = string("softmax_6")];
            bool matmul_13_transpose_x_0 = const()[name = string("matmul_13_transpose_x_0"), val = bool(false)];
            bool matmul_13_transpose_y_0 = const()[name = string("matmul_13_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 16, 44]> matmul_13 = matmul(transpose_x = matmul_13_transpose_x_0, transpose_y = matmul_13_transpose_y_0, x = softmax_6, y = reshape_56)[name = string("matmul_13")];
            tensor<int32, [3]> transpose_27_perm_0 = const()[name = string("transpose_27_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_57_shape_0 = const()[name = string("reshape_57_shape_0"), val = tensor<int32, [2]>([16, 352])];
            tensor<fp16, [16, 8, 44]> transpose_27 = transpose(perm = transpose_27_perm_0, x = matmul_13)[name = string("transpose_36")];
            tensor<fp16, [16, 352]> reshape_57 = reshape(shape = reshape_57_shape_0, x = transpose_27)[name = string("reshape_57")];
            tensor<fp16, [16, 352]> mul_310 = mul(x = reshape_57, y = reshape_57)[name = string("mul_310")];
            tensor<int32, [1]> reduce_mean_66_axes_0 = const()[name = string("reduce_mean_66_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_66_keep_dims_0 = const()[name = string("reduce_mean_66_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_66 = reduce_mean(axes = reduce_mean_66_axes_0, keep_dims = reduce_mean_66_keep_dims_0, x = mul_310)[name = string("reduce_mean_66")];
            fp32 rsqrt_66_epsilon_0 = const()[name = string("rsqrt_66_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_66 = rsqrt(epsilon = rsqrt_66_epsilon_0, x = reduce_mean_66)[name = string("rsqrt_66")];
            tensor<fp16, [16, 352]> mul_311 = mul(x = reshape_57, y = rsqrt_66)[name = string("mul_311")];
            tensor<fp16, [352]> mul_312_y_0 = const()[name = string("mul_312_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4439488)))];
            tensor<fp16, [16, 352]> mul_312 = mul(x = mul_311, y = mul_312_y_0)[name = string("mul_312")];
            tensor<fp16, [352, 352]> tern_6_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4440256))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_6_o_weight_0_palettized")];
            tensor<fp16, [16, 352]> tern_6_o = linear(bias = linear_0_bias_0, weight = tern_6_o_weight_0_palettized, x = mul_312)[name = string("tern_6_o")];
            tensor<fp16, [352]> mul_313_y_0 = const()[name = string("mul_313_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4471296)))];
            tensor<fp16, [16, 352]> mul_313 = mul(x = tern_6_o, y = mul_313_y_0)[name = string("mul_313")];
            tensor<fp16, [16, 352]> add_39 = add(x = add_35, y = mul_313)[name = string("add_39")];
            tensor<fp16, [16, 352]> mul_314 = mul(x = add_39, y = add_39)[name = string("mul_314")];
            tensor<int32, [1]> reduce_mean_67_axes_0 = const()[name = string("reduce_mean_67_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_67_keep_dims_0 = const()[name = string("reduce_mean_67_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_67 = reduce_mean(axes = reduce_mean_67_axes_0, keep_dims = reduce_mean_67_keep_dims_0, x = mul_314)[name = string("reduce_mean_67")];
            fp32 rsqrt_67_epsilon_0 = const()[name = string("rsqrt_67_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_67 = rsqrt(epsilon = rsqrt_67_epsilon_0, x = reduce_mean_67)[name = string("rsqrt_67")];
            tensor<fp16, [16, 352]> mul_315 = mul(x = add_39, y = rsqrt_67)[name = string("mul_315")];
            tensor<fp16, [352]> mul_316_y_0 = const()[name = string("mul_316_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4472064)))];
            tensor<fp16, [16, 352]> mul_316 = mul(x = mul_315, y = mul_316_y_0)[name = string("mul_316")];
            tensor<fp16, [16, 352]> mul_317 = mul(x = mul_316, y = mul_316)[name = string("mul_317")];
            tensor<int32, [1]> reduce_mean_68_axes_0 = const()[name = string("reduce_mean_68_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_68_keep_dims_0 = const()[name = string("reduce_mean_68_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_68 = reduce_mean(axes = reduce_mean_68_axes_0, keep_dims = reduce_mean_68_keep_dims_0, x = mul_317)[name = string("reduce_mean_68")];
            fp32 rsqrt_68_epsilon_0 = const()[name = string("rsqrt_68_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_68 = rsqrt(epsilon = rsqrt_68_epsilon_0, x = reduce_mean_68)[name = string("rsqrt_68")];
            tensor<fp16, [16, 352]> mul_318 = mul(x = mul_316, y = rsqrt_68)[name = string("mul_318")];
            tensor<fp16, [352]> mul_319_y_0 = const()[name = string("mul_319_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4472832)))];
            tensor<fp16, [16, 352]> mul_319 = mul(x = mul_318, y = mul_319_y_0)[name = string("mul_319")];
            tensor<fp16, [960, 352]> tern_6_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4473600))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_6_w1_weight_0_palettized")];
            tensor<fp16, [16, 960]> tern_6_w1 = linear(bias = linear_4_bias_0, weight = tern_6_w1_weight_0_palettized, x = mul_319)[name = string("tern_6_w1")];
            tensor<fp16, [960]> mul_320_y_0 = const()[name = string("mul_320_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4558144)))];
            tensor<fp16, [16, 960]> mul_320 = mul(x = tern_6_w1, y = mul_320_y_0)[name = string("mul_320")];
            tensor<fp16, [352]> mul_323_y_0 = const()[name = string("mul_323_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4560128)))];
            tensor<fp16, [16, 352]> mul_323 = mul(x = mul_318, y = mul_323_y_0)[name = string("mul_323")];
            tensor<fp16, [960, 352]> tern_6_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4560896))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_6_w3_weight_0_palettized")];
            tensor<fp16, [16, 960]> tern_6_w3 = linear(bias = linear_4_bias_0, weight = tern_6_w3_weight_0_palettized, x = mul_323)[name = string("tern_6_w3")];
            tensor<fp16, [960]> mul_324_y_0 = const()[name = string("mul_324_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4645440)))];
            tensor<fp16, [16, 960]> mul_324 = mul(x = tern_6_w3, y = mul_324_y_0)[name = string("mul_324")];
            fp16 mul_325_y_0 = const()[name = string("mul_325_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [16, 960]> mul_325 = mul(x = mul_320, y = mul_325_y_0)[name = string("mul_325")];
            tensor<fp16, [16, 960]> tanh_6 = tanh(x = mul_325)[name = string("tanh_6")];
            fp16 mul_326_x_0 = const()[name = string("mul_326_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [16, 960]> mul_326 = mul(x = mul_326_x_0, y = tanh_6)[name = string("mul_326")];
            fp16 add_40_x_0 = const()[name = string("add_40_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [16, 960]> add_40 = add(x = add_40_x_0, y = mul_326)[name = string("add_40")];
            tensor<fp16, [16, 960]> mul_327 = mul(x = mul_320, y = add_40)[name = string("mul_327")];
            tensor<fp16, [16, 960]> mul_328 = mul(x = mul_327, y = mul_324)[name = string("mul_328")];
            tensor<fp16, [16, 960]> mul_329 = mul(x = mul_328, y = mul_328)[name = string("mul_329")];
            tensor<int32, [1]> reduce_mean_70_axes_0 = const()[name = string("reduce_mean_70_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_70_keep_dims_0 = const()[name = string("reduce_mean_70_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_70 = reduce_mean(axes = reduce_mean_70_axes_0, keep_dims = reduce_mean_70_keep_dims_0, x = mul_329)[name = string("reduce_mean_70")];
            fp32 rsqrt_70_epsilon_0 = const()[name = string("rsqrt_70_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_70 = rsqrt(epsilon = rsqrt_70_epsilon_0, x = reduce_mean_70)[name = string("rsqrt_70")];
            tensor<fp16, [16, 960]> mul_330 = mul(x = mul_328, y = rsqrt_70)[name = string("mul_330")];
            tensor<fp16, [960]> mul_331_y_0 = const()[name = string("mul_331_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4647424)))];
            tensor<fp16, [16, 960]> mul_331 = mul(x = mul_330, y = mul_331_y_0)[name = string("mul_331")];
            tensor<fp16, [352, 960]> tern_6_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4649408))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_6_w2_weight_0_palettized")];
            tensor<fp16, [16, 352]> tern_6_w2 = linear(bias = linear_0_bias_0, weight = tern_6_w2_weight_0_palettized, x = mul_331)[name = string("tern_6_w2")];
            tensor<fp16, [352]> mul_332_y_0 = const()[name = string("mul_332_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4733952)))];
            tensor<fp16, [16, 352]> mul_332 = mul(x = tern_6_w2, y = mul_332_y_0)[name = string("mul_332")];
            tensor<fp16, [16, 352]> add_41 = add(x = add_39, y = mul_332)[name = string("add_41")];
            tensor<fp16, [16, 352]> mul_333 = mul(x = add_41, y = add_41)[name = string("mul_333")];
            tensor<int32, [1]> reduce_mean_71_axes_0 = const()[name = string("reduce_mean_71_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_71_keep_dims_0 = const()[name = string("reduce_mean_71_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_71 = reduce_mean(axes = reduce_mean_71_axes_0, keep_dims = reduce_mean_71_keep_dims_0, x = mul_333)[name = string("reduce_mean_71")];
            fp32 rsqrt_71_epsilon_0 = const()[name = string("rsqrt_71_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_71 = rsqrt(epsilon = rsqrt_71_epsilon_0, x = reduce_mean_71)[name = string("rsqrt_71")];
            tensor<fp16, [16, 352]> mul_334 = mul(x = add_41, y = rsqrt_71)[name = string("mul_334")];
            tensor<fp16, [352]> mul_335_y_0 = const()[name = string("mul_335_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4734720)))];
            tensor<fp16, [16, 352]> mul_335 = mul(x = mul_334, y = mul_335_y_0)[name = string("mul_335")];
            tensor<fp16, [16, 352]> mul_336 = mul(x = mul_335, y = mul_335)[name = string("mul_336")];
            tensor<int32, [1]> reduce_mean_72_axes_0 = const()[name = string("reduce_mean_72_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_72_keep_dims_0 = const()[name = string("reduce_mean_72_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_72 = reduce_mean(axes = reduce_mean_72_axes_0, keep_dims = reduce_mean_72_keep_dims_0, x = mul_336)[name = string("reduce_mean_72")];
            fp32 rsqrt_72_epsilon_0 = const()[name = string("rsqrt_72_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_72 = rsqrt(epsilon = rsqrt_72_epsilon_0, x = reduce_mean_72)[name = string("rsqrt_72")];
            tensor<fp16, [16, 352]> mul_337 = mul(x = mul_335, y = rsqrt_72)[name = string("mul_337")];
            tensor<fp16, [352]> mul_338_y_0 = const()[name = string("mul_338_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4735488)))];
            tensor<fp16, [16, 352]> mul_338 = mul(x = mul_337, y = mul_338_y_0)[name = string("mul_338")];
            tensor<fp16, [352, 352]> tern_7_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4736256))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_7_q_weight_0_palettized")];
            tensor<fp16, [16, 352]> tern_7_q = linear(bias = linear_0_bias_0, weight = tern_7_q_weight_0_palettized, x = mul_338)[name = string("tern_7_q")];
            tensor<fp16, [352]> mul_339_y_0 = const()[name = string("mul_339_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4767296)))];
            tensor<fp16, [16, 352]> mul_339 = mul(x = tern_7_q, y = mul_339_y_0)[name = string("mul_339")];
            tensor<int32, [3]> reshape_58_shape_0 = const()[name = string("reshape_58_shape_0"), val = tensor<int32, [3]>([16, 8, 44])];
            tensor<fp16, [16, 8, 44]> reshape_58 = reshape(shape = reshape_58_shape_0, x = mul_339)[name = string("reshape_58")];
            tensor<int32, [3]> transpose_28_perm_0 = const()[name = string("transpose_28_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_342_y_0 = const()[name = string("mul_342_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4768064)))];
            tensor<fp16, [16, 352]> mul_342 = mul(x = mul_337, y = mul_342_y_0)[name = string("mul_342")];
            tensor<fp16, [88, 352]> tern_7_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4768832))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_7_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_7_k_bias_0 = const()[name = string("tern_7_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [16, 88]> tern_7_k = linear(bias = tern_7_k_bias_0, weight = tern_7_k_weight_0_palettized, x = mul_342)[name = string("tern_7_k")];
            tensor<fp16, [88]> mul_343_y_0 = const()[name = string("mul_343_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4776640)))];
            tensor<fp16, [16, 88]> mul_343 = mul(x = tern_7_k, y = mul_343_y_0)[name = string("mul_343")];
            tensor<int32, [3]> reshape_59_shape_0 = const()[name = string("reshape_59_shape_0"), val = tensor<int32, [3]>([16, 2, 44])];
            tensor<fp16, [16, 2, 44]> reshape_59 = reshape(shape = reshape_59_shape_0, x = mul_343)[name = string("reshape_59")];
            tensor<int32, [3]> transpose_29_perm_0 = const()[name = string("transpose_29_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_346_y_0 = const()[name = string("mul_346_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4776896)))];
            tensor<fp16, [16, 352]> mul_346 = mul(x = mul_337, y = mul_346_y_0)[name = string("mul_346")];
            tensor<fp16, [88, 352]> tern_7_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4777664))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_7_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_7_v_bias_0 = const()[name = string("tern_7_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [16, 88]> tern_7_v = linear(bias = tern_7_v_bias_0, weight = tern_7_v_weight_0_palettized, x = mul_346)[name = string("tern_7_v")];
            tensor<fp16, [88]> mul_347_y_0 = const()[name = string("mul_347_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4785472)))];
            tensor<fp16, [16, 88]> mul_347 = mul(x = tern_7_v, y = mul_347_y_0)[name = string("mul_347")];
            tensor<int32, [3]> reshape_60_shape_0 = const()[name = string("reshape_60_shape_0"), val = tensor<int32, [3]>([16, 2, 44])];
            tensor<fp16, [16, 2, 44]> reshape_60 = reshape(shape = reshape_60_shape_0, x = mul_347)[name = string("reshape_60")];
            tensor<int32, [3]> transpose_30_perm_0 = const()[name = string("transpose_30_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 16, 44]> transpose_28 = transpose(perm = transpose_28_perm_0, x = reshape_58)[name = string("transpose_35")];
            tensor<fp16, [8, 16, 44]> mul_348 = mul(x = transpose_28, y = transpose_28)[name = string("mul_348")];
            tensor<int32, [1]> reduce_mean_75_axes_0 = const()[name = string("reduce_mean_75_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_75_keep_dims_0 = const()[name = string("reduce_mean_75_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 16, 1]> reduce_mean_75 = reduce_mean(axes = reduce_mean_75_axes_0, keep_dims = reduce_mean_75_keep_dims_0, x = mul_348)[name = string("reduce_mean_75")];
            fp32 rsqrt_75_epsilon_0 = const()[name = string("rsqrt_75_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 16, 1]> rsqrt_75 = rsqrt(epsilon = rsqrt_75_epsilon_0, x = reduce_mean_75)[name = string("rsqrt_75")];
            tensor<fp16, [8, 16, 44]> mul_349 = mul(x = transpose_28, y = rsqrt_75)[name = string("mul_349")];
            tensor<fp16, [44]> mul_350_y_0 = const()[name = string("mul_350_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4785728)))];
            tensor<fp16, [8, 16, 44]> mul_350 = mul(x = mul_349, y = mul_350_y_0)[name = string("mul_350")];
            tensor<int32, [3]> slice_by_index_28_begin_0 = const()[name = string("slice_by_index_28_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_28_end_0 = const()[name = string("slice_by_index_28_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_28_end_mask_0 = const()[name = string("slice_by_index_28_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 16, 22]> slice_by_index_28 = slice_by_index(begin = slice_by_index_28_begin_0, end = slice_by_index_28_end_0, end_mask = slice_by_index_28_end_mask_0, x = mul_350)[name = string("slice_by_index_28")];
            tensor<int32, [3]> slice_by_index_29_begin_0 = const()[name = string("slice_by_index_29_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_29_end_0 = const()[name = string("slice_by_index_29_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_29_end_mask_0 = const()[name = string("slice_by_index_29_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 16, 22]> slice_by_index_29 = slice_by_index(begin = slice_by_index_29_begin_0, end = slice_by_index_29_end_0, end_mask = slice_by_index_29_end_mask_0, x = mul_350)[name = string("slice_by_index_29")];
            int32 concat_14_axis_0 = const()[name = string("concat_14_axis_0"), val = int32(-1)];
            bool concat_14_interleave_0 = const()[name = string("concat_14_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 16, 44]> concat_14 = concat(axis = concat_14_axis_0, interleave = concat_14_interleave_0, values = (slice_by_index_29, slice_by_index_28))[name = string("concat_14")];
            tensor<fp16, [44]> mul_351_y_0 = const()[name = string("mul_351_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 16, 44]> mul_351 = mul(x = concat_14, y = mul_351_y_0)[name = string("mul_351")];
            tensor<fp16, [8, 16, 44]> mul_352 = mul(x = mul_350, y = mul_11_y_0)[name = string("mul_352")];
            tensor<fp16, [8, 16, 44]> mul_353 = mul(x = mul_351, y = mul_12_y_0)[name = string("mul_353")];
            tensor<fp16, [8, 16, 44]> add_42 = add(x = mul_352, y = mul_353)[name = string("add_42")];
            tensor<fp16, [2, 16, 44]> transpose_29 = transpose(perm = transpose_29_perm_0, x = reshape_59)[name = string("transpose_34")];
            tensor<fp16, [2, 16, 44]> mul_354 = mul(x = transpose_29, y = transpose_29)[name = string("mul_354")];
            tensor<int32, [1]> reduce_mean_76_axes_0 = const()[name = string("reduce_mean_76_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_76_keep_dims_0 = const()[name = string("reduce_mean_76_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 16, 1]> reduce_mean_76 = reduce_mean(axes = reduce_mean_76_axes_0, keep_dims = reduce_mean_76_keep_dims_0, x = mul_354)[name = string("reduce_mean_76")];
            fp32 rsqrt_76_epsilon_0 = const()[name = string("rsqrt_76_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 16, 1]> rsqrt_76 = rsqrt(epsilon = rsqrt_76_epsilon_0, x = reduce_mean_76)[name = string("rsqrt_76")];
            tensor<fp16, [2, 16, 44]> mul_355 = mul(x = transpose_29, y = rsqrt_76)[name = string("mul_355")];
            tensor<fp16, [44]> mul_356_y_0 = const()[name = string("mul_356_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4785920)))];
            tensor<fp16, [2, 16, 44]> mul_356 = mul(x = mul_355, y = mul_356_y_0)[name = string("mul_356")];
            tensor<int32, [3]> slice_by_index_30_begin_0 = const()[name = string("slice_by_index_30_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_30_end_0 = const()[name = string("slice_by_index_30_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_30_end_mask_0 = const()[name = string("slice_by_index_30_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 16, 22]> slice_by_index_30 = slice_by_index(begin = slice_by_index_30_begin_0, end = slice_by_index_30_end_0, end_mask = slice_by_index_30_end_mask_0, x = mul_356)[name = string("slice_by_index_30")];
            tensor<int32, [3]> slice_by_index_31_begin_0 = const()[name = string("slice_by_index_31_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_31_end_0 = const()[name = string("slice_by_index_31_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_31_end_mask_0 = const()[name = string("slice_by_index_31_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 16, 22]> slice_by_index_31 = slice_by_index(begin = slice_by_index_31_begin_0, end = slice_by_index_31_end_0, end_mask = slice_by_index_31_end_mask_0, x = mul_356)[name = string("slice_by_index_31")];
            int32 concat_15_axis_0 = const()[name = string("concat_15_axis_0"), val = int32(-1)];
            bool concat_15_interleave_0 = const()[name = string("concat_15_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 16, 44]> concat_15 = concat(axis = concat_15_axis_0, interleave = concat_15_interleave_0, values = (slice_by_index_31, slice_by_index_30))[name = string("concat_15")];
            tensor<fp16, [44]> mul_357_y_0 = const()[name = string("mul_357_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 16, 44]> mul_357 = mul(x = concat_15, y = mul_357_y_0)[name = string("mul_357")];
            tensor<fp16, [2, 16, 44]> mul_358 = mul(x = mul_356, y = mul_11_y_0)[name = string("mul_358")];
            tensor<fp16, [2, 16, 44]> mul_359 = mul(x = mul_357, y = mul_12_y_0)[name = string("mul_359")];
            tensor<fp16, [2, 16, 44]> add_43 = add(x = mul_358, y = mul_359)[name = string("add_43")];
            tensor<int32, [4]> reshape_61_shape_0 = const()[name = string("reshape_61_shape_0"), val = tensor<int32, [4]>([2, 1, 16, 44])];
            tensor<fp16, [2, 1, 16, 44]> reshape_61 = reshape(shape = reshape_61_shape_0, x = add_43)[name = string("reshape_61")];
            tensor<int32, [4]> tile_14_reps_0 = const()[name = string("tile_14_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 16, 44]> tile_14 = tile(reps = tile_14_reps_0, x = reshape_61)[name = string("tile_14")];
            tensor<int32, [3]> reshape_62_shape_0 = const()[name = string("reshape_62_shape_0"), val = tensor<int32, [3]>([8, 16, 44])];
            tensor<fp16, [8, 16, 44]> reshape_62 = reshape(shape = reshape_62_shape_0, x = tile_14)[name = string("reshape_62")];
            tensor<int32, [4]> reshape_63_shape_0 = const()[name = string("reshape_63_shape_0"), val = tensor<int32, [4]>([2, 1, 16, 44])];
            tensor<fp16, [2, 16, 44]> transpose_30 = transpose(perm = transpose_30_perm_0, x = reshape_60)[name = string("transpose_33")];
            tensor<fp16, [2, 1, 16, 44]> reshape_63 = reshape(shape = reshape_63_shape_0, x = transpose_30)[name = string("reshape_63")];
            tensor<int32, [4]> tile_15_reps_0 = const()[name = string("tile_15_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 16, 44]> tile_15 = tile(reps = tile_15_reps_0, x = reshape_63)[name = string("tile_15")];
            tensor<int32, [3]> reshape_64_shape_0 = const()[name = string("reshape_64_shape_0"), val = tensor<int32, [3]>([8, 16, 44])];
            tensor<fp16, [8, 16, 44]> reshape_64 = reshape(shape = reshape_64_shape_0, x = tile_15)[name = string("reshape_64")];
            fp16 mul_360_y_0 = const()[name = string("mul_360_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 16, 44]> mul_360 = mul(x = add_42, y = mul_360_y_0)[name = string("mul_360")];
            bool matmul_14_transpose_y_0 = const()[name = string("matmul_14_transpose_y_0"), val = bool(true)];
            bool matmul_14_transpose_x_0 = const()[name = string("matmul_14_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 16, 16]> matmul_14 = matmul(transpose_x = matmul_14_transpose_x_0, transpose_y = matmul_14_transpose_y_0, x = mul_360, y = reshape_62)[name = string("matmul_14")];
            tensor<fp16, [8, 16, 16]> add_44 = add(x = matmul_14, y = reshape_1)[name = string("add_44")];
            int32 softmax_7_axis_0 = const()[name = string("softmax_7_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 16, 16]> softmax_7 = softmax(axis = softmax_7_axis_0, x = add_44)[name = string("softmax_7")];
            bool matmul_15_transpose_x_0 = const()[name = string("matmul_15_transpose_x_0"), val = bool(false)];
            bool matmul_15_transpose_y_0 = const()[name = string("matmul_15_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 16, 44]> matmul_15 = matmul(transpose_x = matmul_15_transpose_x_0, transpose_y = matmul_15_transpose_y_0, x = softmax_7, y = reshape_64)[name = string("matmul_15")];
            tensor<int32, [3]> transpose_31_perm_0 = const()[name = string("transpose_31_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_65_shape_0 = const()[name = string("reshape_65_shape_0"), val = tensor<int32, [2]>([16, 352])];
            tensor<fp16, [16, 8, 44]> transpose_31 = transpose(perm = transpose_31_perm_0, x = matmul_15)[name = string("transpose_32")];
            tensor<fp16, [16, 352]> reshape_65 = reshape(shape = reshape_65_shape_0, x = transpose_31)[name = string("reshape_65")];
            tensor<fp16, [16, 352]> mul_361 = mul(x = reshape_65, y = reshape_65)[name = string("mul_361")];
            tensor<int32, [1]> reduce_mean_77_axes_0 = const()[name = string("reduce_mean_77_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_77_keep_dims_0 = const()[name = string("reduce_mean_77_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_77 = reduce_mean(axes = reduce_mean_77_axes_0, keep_dims = reduce_mean_77_keep_dims_0, x = mul_361)[name = string("reduce_mean_77")];
            fp32 rsqrt_77_epsilon_0 = const()[name = string("rsqrt_77_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_77 = rsqrt(epsilon = rsqrt_77_epsilon_0, x = reduce_mean_77)[name = string("rsqrt_77")];
            tensor<fp16, [16, 352]> mul_362 = mul(x = reshape_65, y = rsqrt_77)[name = string("mul_362")];
            tensor<fp16, [352]> mul_363_y_0 = const()[name = string("mul_363_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4786112)))];
            tensor<fp16, [16, 352]> mul_363 = mul(x = mul_362, y = mul_363_y_0)[name = string("mul_363")];
            tensor<fp16, [352, 352]> tern_7_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4786880))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_7_o_weight_0_palettized")];
            tensor<fp16, [16, 352]> tern_7_o = linear(bias = linear_0_bias_0, weight = tern_7_o_weight_0_palettized, x = mul_363)[name = string("tern_7_o")];
            tensor<fp16, [352]> mul_364_y_0 = const()[name = string("mul_364_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4817920)))];
            tensor<fp16, [16, 352]> mul_364 = mul(x = tern_7_o, y = mul_364_y_0)[name = string("mul_364")];
            tensor<fp16, [16, 352]> add_45 = add(x = add_41, y = mul_364)[name = string("add_45")];
            tensor<fp16, [16, 352]> mul_365 = mul(x = add_45, y = add_45)[name = string("mul_365")];
            tensor<int32, [1]> reduce_mean_78_axes_0 = const()[name = string("reduce_mean_78_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_78_keep_dims_0 = const()[name = string("reduce_mean_78_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_78 = reduce_mean(axes = reduce_mean_78_axes_0, keep_dims = reduce_mean_78_keep_dims_0, x = mul_365)[name = string("reduce_mean_78")];
            fp32 rsqrt_78_epsilon_0 = const()[name = string("rsqrt_78_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_78 = rsqrt(epsilon = rsqrt_78_epsilon_0, x = reduce_mean_78)[name = string("rsqrt_78")];
            tensor<fp16, [16, 352]> mul_366 = mul(x = add_45, y = rsqrt_78)[name = string("mul_366")];
            tensor<fp16, [352]> mul_367_y_0 = const()[name = string("mul_367_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4818688)))];
            tensor<fp16, [16, 352]> mul_367 = mul(x = mul_366, y = mul_367_y_0)[name = string("mul_367")];
            tensor<fp16, [16, 352]> mul_368 = mul(x = mul_367, y = mul_367)[name = string("mul_368")];
            tensor<int32, [1]> reduce_mean_79_axes_0 = const()[name = string("reduce_mean_79_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_79_keep_dims_0 = const()[name = string("reduce_mean_79_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_79 = reduce_mean(axes = reduce_mean_79_axes_0, keep_dims = reduce_mean_79_keep_dims_0, x = mul_368)[name = string("reduce_mean_79")];
            fp32 rsqrt_79_epsilon_0 = const()[name = string("rsqrt_79_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_79 = rsqrt(epsilon = rsqrt_79_epsilon_0, x = reduce_mean_79)[name = string("rsqrt_79")];
            tensor<fp16, [16, 352]> mul_369 = mul(x = mul_367, y = rsqrt_79)[name = string("mul_369")];
            tensor<fp16, [352]> mul_370_y_0 = const()[name = string("mul_370_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4819456)))];
            tensor<fp16, [16, 352]> mul_370 = mul(x = mul_369, y = mul_370_y_0)[name = string("mul_370")];
            tensor<fp16, [960, 352]> tern_7_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4820224))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_7_w1_weight_0_palettized")];
            tensor<fp16, [16, 960]> tern_7_w1 = linear(bias = linear_4_bias_0, weight = tern_7_w1_weight_0_palettized, x = mul_370)[name = string("tern_7_w1")];
            tensor<fp16, [960]> mul_371_y_0 = const()[name = string("mul_371_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4904768)))];
            tensor<fp16, [16, 960]> mul_371 = mul(x = tern_7_w1, y = mul_371_y_0)[name = string("mul_371")];
            tensor<fp16, [352]> mul_374_y_0 = const()[name = string("mul_374_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4906752)))];
            tensor<fp16, [16, 352]> mul_374 = mul(x = mul_369, y = mul_374_y_0)[name = string("mul_374")];
            tensor<fp16, [960, 352]> tern_7_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4907520))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_7_w3_weight_0_palettized")];
            tensor<fp16, [16, 960]> tern_7_w3 = linear(bias = linear_4_bias_0, weight = tern_7_w3_weight_0_palettized, x = mul_374)[name = string("tern_7_w3")];
            tensor<fp16, [960]> mul_375_y_0 = const()[name = string("mul_375_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4992064)))];
            tensor<fp16, [16, 960]> mul_375 = mul(x = tern_7_w3, y = mul_375_y_0)[name = string("mul_375")];
            fp16 mul_376_y_0 = const()[name = string("mul_376_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [16, 960]> mul_376 = mul(x = mul_371, y = mul_376_y_0)[name = string("mul_376")];
            tensor<fp16, [16, 960]> tanh_7 = tanh(x = mul_376)[name = string("tanh_7")];
            fp16 mul_377_x_0 = const()[name = string("mul_377_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [16, 960]> mul_377 = mul(x = mul_377_x_0, y = tanh_7)[name = string("mul_377")];
            fp16 add_46_x_0 = const()[name = string("add_46_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [16, 960]> add_46 = add(x = add_46_x_0, y = mul_377)[name = string("add_46")];
            tensor<fp16, [16, 960]> mul_378 = mul(x = mul_371, y = add_46)[name = string("mul_378")];
            tensor<fp16, [16, 960]> mul_379 = mul(x = mul_378, y = mul_375)[name = string("mul_379")];
            tensor<fp16, [16, 960]> mul_380 = mul(x = mul_379, y = mul_379)[name = string("mul_380")];
            tensor<int32, [1]> reduce_mean_81_axes_0 = const()[name = string("reduce_mean_81_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_81_keep_dims_0 = const()[name = string("reduce_mean_81_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_81 = reduce_mean(axes = reduce_mean_81_axes_0, keep_dims = reduce_mean_81_keep_dims_0, x = mul_380)[name = string("reduce_mean_81")];
            fp32 rsqrt_81_epsilon_0 = const()[name = string("rsqrt_81_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_81 = rsqrt(epsilon = rsqrt_81_epsilon_0, x = reduce_mean_81)[name = string("rsqrt_81")];
            tensor<fp16, [16, 960]> mul_381 = mul(x = mul_379, y = rsqrt_81)[name = string("mul_381")];
            tensor<fp16, [960]> mul_382_y_0 = const()[name = string("mul_382_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4994048)))];
            tensor<fp16, [16, 960]> mul_382 = mul(x = mul_381, y = mul_382_y_0)[name = string("mul_382")];
            tensor<fp16, [352, 960]> tern_7_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4996032))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_7_w2_weight_0_palettized")];
            tensor<fp16, [16, 352]> tern_7_w2 = linear(bias = linear_0_bias_0, weight = tern_7_w2_weight_0_palettized, x = mul_382)[name = string("tern_7_w2")];
            tensor<fp16, [352]> mul_383_y_0 = const()[name = string("mul_383_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5080576)))];
            tensor<fp16, [16, 352]> mul_383 = mul(x = tern_7_w2, y = mul_383_y_0)[name = string("mul_383")];
            tensor<fp16, [16, 352]> add_47 = add(x = add_45, y = mul_383)[name = string("add_47")];
            tensor<fp16, [16, 352]> mul_384 = mul(x = add_47, y = add_47)[name = string("mul_384")];
            tensor<int32, [1]> reduce_mean_82_axes_0 = const()[name = string("reduce_mean_82_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_82_keep_dims_0 = const()[name = string("reduce_mean_82_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_82 = reduce_mean(axes = reduce_mean_82_axes_0, keep_dims = reduce_mean_82_keep_dims_0, x = mul_384)[name = string("reduce_mean_82")];
            fp32 rsqrt_82_epsilon_0 = const()[name = string("rsqrt_82_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_82 = rsqrt(epsilon = rsqrt_82_epsilon_0, x = reduce_mean_82)[name = string("rsqrt_82")];
            tensor<fp16, [16, 352]> mul_385 = mul(x = add_47, y = rsqrt_82)[name = string("mul_385")];
            tensor<fp16, [352]> mul_386_y_0 = const()[name = string("mul_386_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5081344)))];
            tensor<fp16, [16, 352]> mul_386 = mul(x = mul_385, y = mul_386_y_0)[name = string("mul_386")];
            tensor<fp16, [16, 352]> mul_387 = mul(x = mul_386, y = mul_386)[name = string("mul_387")];
            tensor<int32, [1]> reduce_mean_83_axes_0 = const()[name = string("reduce_mean_83_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_83_keep_dims_0 = const()[name = string("reduce_mean_83_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_83 = reduce_mean(axes = reduce_mean_83_axes_0, keep_dims = reduce_mean_83_keep_dims_0, x = mul_387)[name = string("reduce_mean_83")];
            fp32 rsqrt_83_epsilon_0 = const()[name = string("rsqrt_83_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_83 = rsqrt(epsilon = rsqrt_83_epsilon_0, x = reduce_mean_83)[name = string("rsqrt_83")];
            tensor<fp16, [16, 352]> mul_388 = mul(x = mul_386, y = rsqrt_83)[name = string("mul_388")];
            tensor<fp16, [352]> mul_389_y_0 = const()[name = string("mul_389_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5082112)))];
            tensor<fp16, [16, 352]> mul_389 = mul(x = mul_388, y = mul_389_y_0)[name = string("mul_389")];
            tensor<fp16, [352, 352]> tern_8_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5082880))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_8_q_weight_0_palettized")];
            tensor<fp16, [16, 352]> tern_8_q = linear(bias = linear_0_bias_0, weight = tern_8_q_weight_0_palettized, x = mul_389)[name = string("tern_8_q")];
            tensor<fp16, [352]> mul_390_y_0 = const()[name = string("mul_390_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5113920)))];
            tensor<fp16, [16, 352]> mul_390 = mul(x = tern_8_q, y = mul_390_y_0)[name = string("mul_390")];
            tensor<int32, [3]> reshape_66_shape_0 = const()[name = string("reshape_66_shape_0"), val = tensor<int32, [3]>([16, 8, 44])];
            tensor<fp16, [16, 8, 44]> reshape_66 = reshape(shape = reshape_66_shape_0, x = mul_390)[name = string("reshape_66")];
            tensor<int32, [3]> transpose_32_perm_0 = const()[name = string("transpose_32_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_393_y_0 = const()[name = string("mul_393_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5114688)))];
            tensor<fp16, [16, 352]> mul_393 = mul(x = mul_388, y = mul_393_y_0)[name = string("mul_393")];
            tensor<fp16, [88, 352]> tern_8_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5115456))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_8_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_8_k_bias_0 = const()[name = string("tern_8_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [16, 88]> tern_8_k = linear(bias = tern_8_k_bias_0, weight = tern_8_k_weight_0_palettized, x = mul_393)[name = string("tern_8_k")];
            tensor<fp16, [88]> mul_394_y_0 = const()[name = string("mul_394_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5123264)))];
            tensor<fp16, [16, 88]> mul_394 = mul(x = tern_8_k, y = mul_394_y_0)[name = string("mul_394")];
            tensor<int32, [3]> reshape_67_shape_0 = const()[name = string("reshape_67_shape_0"), val = tensor<int32, [3]>([16, 2, 44])];
            tensor<fp16, [16, 2, 44]> reshape_67 = reshape(shape = reshape_67_shape_0, x = mul_394)[name = string("reshape_67")];
            tensor<int32, [3]> transpose_33_perm_0 = const()[name = string("transpose_33_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_397_y_0 = const()[name = string("mul_397_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5123520)))];
            tensor<fp16, [16, 352]> mul_397 = mul(x = mul_388, y = mul_397_y_0)[name = string("mul_397")];
            tensor<fp16, [88, 352]> tern_8_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5124288))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_8_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_8_v_bias_0 = const()[name = string("tern_8_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [16, 88]> tern_8_v = linear(bias = tern_8_v_bias_0, weight = tern_8_v_weight_0_palettized, x = mul_397)[name = string("tern_8_v")];
            tensor<fp16, [88]> mul_398_y_0 = const()[name = string("mul_398_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5132096)))];
            tensor<fp16, [16, 88]> mul_398 = mul(x = tern_8_v, y = mul_398_y_0)[name = string("mul_398")];
            tensor<int32, [3]> reshape_68_shape_0 = const()[name = string("reshape_68_shape_0"), val = tensor<int32, [3]>([16, 2, 44])];
            tensor<fp16, [16, 2, 44]> reshape_68 = reshape(shape = reshape_68_shape_0, x = mul_398)[name = string("reshape_68")];
            tensor<int32, [3]> transpose_34_perm_0 = const()[name = string("transpose_34_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 16, 44]> transpose_32 = transpose(perm = transpose_32_perm_0, x = reshape_66)[name = string("transpose_31")];
            tensor<fp16, [8, 16, 44]> mul_399 = mul(x = transpose_32, y = transpose_32)[name = string("mul_399")];
            tensor<int32, [1]> reduce_mean_86_axes_0 = const()[name = string("reduce_mean_86_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_86_keep_dims_0 = const()[name = string("reduce_mean_86_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 16, 1]> reduce_mean_86 = reduce_mean(axes = reduce_mean_86_axes_0, keep_dims = reduce_mean_86_keep_dims_0, x = mul_399)[name = string("reduce_mean_86")];
            fp32 rsqrt_86_epsilon_0 = const()[name = string("rsqrt_86_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 16, 1]> rsqrt_86 = rsqrt(epsilon = rsqrt_86_epsilon_0, x = reduce_mean_86)[name = string("rsqrt_86")];
            tensor<fp16, [8, 16, 44]> mul_400 = mul(x = transpose_32, y = rsqrt_86)[name = string("mul_400")];
            tensor<fp16, [44]> mul_401_y_0 = const()[name = string("mul_401_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5132352)))];
            tensor<fp16, [8, 16, 44]> mul_401 = mul(x = mul_400, y = mul_401_y_0)[name = string("mul_401")];
            tensor<int32, [3]> slice_by_index_32_begin_0 = const()[name = string("slice_by_index_32_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_32_end_0 = const()[name = string("slice_by_index_32_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_32_end_mask_0 = const()[name = string("slice_by_index_32_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 16, 22]> slice_by_index_32 = slice_by_index(begin = slice_by_index_32_begin_0, end = slice_by_index_32_end_0, end_mask = slice_by_index_32_end_mask_0, x = mul_401)[name = string("slice_by_index_32")];
            tensor<int32, [3]> slice_by_index_33_begin_0 = const()[name = string("slice_by_index_33_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_33_end_0 = const()[name = string("slice_by_index_33_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_33_end_mask_0 = const()[name = string("slice_by_index_33_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 16, 22]> slice_by_index_33 = slice_by_index(begin = slice_by_index_33_begin_0, end = slice_by_index_33_end_0, end_mask = slice_by_index_33_end_mask_0, x = mul_401)[name = string("slice_by_index_33")];
            int32 concat_16_axis_0 = const()[name = string("concat_16_axis_0"), val = int32(-1)];
            bool concat_16_interleave_0 = const()[name = string("concat_16_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 16, 44]> concat_16 = concat(axis = concat_16_axis_0, interleave = concat_16_interleave_0, values = (slice_by_index_33, slice_by_index_32))[name = string("concat_16")];
            tensor<fp16, [44]> mul_402_y_0 = const()[name = string("mul_402_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 16, 44]> mul_402 = mul(x = concat_16, y = mul_402_y_0)[name = string("mul_402")];
            tensor<fp16, [8, 16, 44]> mul_403 = mul(x = mul_401, y = mul_11_y_0)[name = string("mul_403")];
            tensor<fp16, [8, 16, 44]> mul_404 = mul(x = mul_402, y = mul_12_y_0)[name = string("mul_404")];
            tensor<fp16, [8, 16, 44]> add_48 = add(x = mul_403, y = mul_404)[name = string("add_48")];
            tensor<fp16, [2, 16, 44]> transpose_33 = transpose(perm = transpose_33_perm_0, x = reshape_67)[name = string("transpose_30")];
            tensor<fp16, [2, 16, 44]> mul_405 = mul(x = transpose_33, y = transpose_33)[name = string("mul_405")];
            tensor<int32, [1]> reduce_mean_87_axes_0 = const()[name = string("reduce_mean_87_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_87_keep_dims_0 = const()[name = string("reduce_mean_87_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 16, 1]> reduce_mean_87 = reduce_mean(axes = reduce_mean_87_axes_0, keep_dims = reduce_mean_87_keep_dims_0, x = mul_405)[name = string("reduce_mean_87")];
            fp32 rsqrt_87_epsilon_0 = const()[name = string("rsqrt_87_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 16, 1]> rsqrt_87 = rsqrt(epsilon = rsqrt_87_epsilon_0, x = reduce_mean_87)[name = string("rsqrt_87")];
            tensor<fp16, [2, 16, 44]> mul_406 = mul(x = transpose_33, y = rsqrt_87)[name = string("mul_406")];
            tensor<fp16, [44]> mul_407_y_0 = const()[name = string("mul_407_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5132544)))];
            tensor<fp16, [2, 16, 44]> mul_407 = mul(x = mul_406, y = mul_407_y_0)[name = string("mul_407")];
            tensor<int32, [3]> slice_by_index_34_begin_0 = const()[name = string("slice_by_index_34_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_34_end_0 = const()[name = string("slice_by_index_34_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_34_end_mask_0 = const()[name = string("slice_by_index_34_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 16, 22]> slice_by_index_34 = slice_by_index(begin = slice_by_index_34_begin_0, end = slice_by_index_34_end_0, end_mask = slice_by_index_34_end_mask_0, x = mul_407)[name = string("slice_by_index_34")];
            tensor<int32, [3]> slice_by_index_35_begin_0 = const()[name = string("slice_by_index_35_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_35_end_0 = const()[name = string("slice_by_index_35_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_35_end_mask_0 = const()[name = string("slice_by_index_35_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 16, 22]> slice_by_index_35 = slice_by_index(begin = slice_by_index_35_begin_0, end = slice_by_index_35_end_0, end_mask = slice_by_index_35_end_mask_0, x = mul_407)[name = string("slice_by_index_35")];
            int32 concat_17_axis_0 = const()[name = string("concat_17_axis_0"), val = int32(-1)];
            bool concat_17_interleave_0 = const()[name = string("concat_17_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 16, 44]> concat_17 = concat(axis = concat_17_axis_0, interleave = concat_17_interleave_0, values = (slice_by_index_35, slice_by_index_34))[name = string("concat_17")];
            tensor<fp16, [44]> mul_408_y_0 = const()[name = string("mul_408_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 16, 44]> mul_408 = mul(x = concat_17, y = mul_408_y_0)[name = string("mul_408")];
            tensor<fp16, [2, 16, 44]> mul_409 = mul(x = mul_407, y = mul_11_y_0)[name = string("mul_409")];
            tensor<fp16, [2, 16, 44]> mul_410 = mul(x = mul_408, y = mul_12_y_0)[name = string("mul_410")];
            tensor<fp16, [2, 16, 44]> add_49 = add(x = mul_409, y = mul_410)[name = string("add_49")];
            tensor<int32, [4]> reshape_69_shape_0 = const()[name = string("reshape_69_shape_0"), val = tensor<int32, [4]>([2, 1, 16, 44])];
            tensor<fp16, [2, 1, 16, 44]> reshape_69 = reshape(shape = reshape_69_shape_0, x = add_49)[name = string("reshape_69")];
            tensor<int32, [4]> tile_16_reps_0 = const()[name = string("tile_16_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 16, 44]> tile_16 = tile(reps = tile_16_reps_0, x = reshape_69)[name = string("tile_16")];
            tensor<int32, [3]> reshape_70_shape_0 = const()[name = string("reshape_70_shape_0"), val = tensor<int32, [3]>([8, 16, 44])];
            tensor<fp16, [8, 16, 44]> reshape_70 = reshape(shape = reshape_70_shape_0, x = tile_16)[name = string("reshape_70")];
            tensor<int32, [4]> reshape_71_shape_0 = const()[name = string("reshape_71_shape_0"), val = tensor<int32, [4]>([2, 1, 16, 44])];
            tensor<fp16, [2, 16, 44]> transpose_34 = transpose(perm = transpose_34_perm_0, x = reshape_68)[name = string("transpose_29")];
            tensor<fp16, [2, 1, 16, 44]> reshape_71 = reshape(shape = reshape_71_shape_0, x = transpose_34)[name = string("reshape_71")];
            tensor<int32, [4]> tile_17_reps_0 = const()[name = string("tile_17_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 16, 44]> tile_17 = tile(reps = tile_17_reps_0, x = reshape_71)[name = string("tile_17")];
            tensor<int32, [3]> reshape_72_shape_0 = const()[name = string("reshape_72_shape_0"), val = tensor<int32, [3]>([8, 16, 44])];
            tensor<fp16, [8, 16, 44]> reshape_72 = reshape(shape = reshape_72_shape_0, x = tile_17)[name = string("reshape_72")];
            fp16 mul_411_y_0 = const()[name = string("mul_411_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 16, 44]> mul_411 = mul(x = add_48, y = mul_411_y_0)[name = string("mul_411")];
            bool matmul_16_transpose_y_0 = const()[name = string("matmul_16_transpose_y_0"), val = bool(true)];
            bool matmul_16_transpose_x_0 = const()[name = string("matmul_16_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 16, 16]> matmul_16 = matmul(transpose_x = matmul_16_transpose_x_0, transpose_y = matmul_16_transpose_y_0, x = mul_411, y = reshape_70)[name = string("matmul_16")];
            tensor<fp16, [8, 16, 16]> add_50 = add(x = matmul_16, y = reshape_1)[name = string("add_50")];
            int32 softmax_8_axis_0 = const()[name = string("softmax_8_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 16, 16]> softmax_8 = softmax(axis = softmax_8_axis_0, x = add_50)[name = string("softmax_8")];
            bool matmul_17_transpose_x_0 = const()[name = string("matmul_17_transpose_x_0"), val = bool(false)];
            bool matmul_17_transpose_y_0 = const()[name = string("matmul_17_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 16, 44]> matmul_17 = matmul(transpose_x = matmul_17_transpose_x_0, transpose_y = matmul_17_transpose_y_0, x = softmax_8, y = reshape_72)[name = string("matmul_17")];
            tensor<int32, [3]> transpose_35_perm_0 = const()[name = string("transpose_35_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_73_shape_0 = const()[name = string("reshape_73_shape_0"), val = tensor<int32, [2]>([16, 352])];
            tensor<fp16, [16, 8, 44]> transpose_35 = transpose(perm = transpose_35_perm_0, x = matmul_17)[name = string("transpose_28")];
            tensor<fp16, [16, 352]> reshape_73 = reshape(shape = reshape_73_shape_0, x = transpose_35)[name = string("reshape_73")];
            tensor<fp16, [16, 352]> mul_412 = mul(x = reshape_73, y = reshape_73)[name = string("mul_412")];
            tensor<int32, [1]> reduce_mean_88_axes_0 = const()[name = string("reduce_mean_88_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_88_keep_dims_0 = const()[name = string("reduce_mean_88_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_88 = reduce_mean(axes = reduce_mean_88_axes_0, keep_dims = reduce_mean_88_keep_dims_0, x = mul_412)[name = string("reduce_mean_88")];
            fp32 rsqrt_88_epsilon_0 = const()[name = string("rsqrt_88_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_88 = rsqrt(epsilon = rsqrt_88_epsilon_0, x = reduce_mean_88)[name = string("rsqrt_88")];
            tensor<fp16, [16, 352]> mul_413 = mul(x = reshape_73, y = rsqrt_88)[name = string("mul_413")];
            tensor<fp16, [352]> mul_414_y_0 = const()[name = string("mul_414_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5132736)))];
            tensor<fp16, [16, 352]> mul_414 = mul(x = mul_413, y = mul_414_y_0)[name = string("mul_414")];
            tensor<fp16, [352, 352]> tern_8_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5133504))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_8_o_weight_0_palettized")];
            tensor<fp16, [16, 352]> tern_8_o = linear(bias = linear_0_bias_0, weight = tern_8_o_weight_0_palettized, x = mul_414)[name = string("tern_8_o")];
            tensor<fp16, [352]> mul_415_y_0 = const()[name = string("mul_415_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5164544)))];
            tensor<fp16, [16, 352]> mul_415 = mul(x = tern_8_o, y = mul_415_y_0)[name = string("mul_415")];
            tensor<fp16, [16, 352]> add_51 = add(x = add_47, y = mul_415)[name = string("add_51")];
            tensor<fp16, [16, 352]> mul_416 = mul(x = add_51, y = add_51)[name = string("mul_416")];
            tensor<int32, [1]> reduce_mean_89_axes_0 = const()[name = string("reduce_mean_89_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_89_keep_dims_0 = const()[name = string("reduce_mean_89_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_89 = reduce_mean(axes = reduce_mean_89_axes_0, keep_dims = reduce_mean_89_keep_dims_0, x = mul_416)[name = string("reduce_mean_89")];
            fp32 rsqrt_89_epsilon_0 = const()[name = string("rsqrt_89_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_89 = rsqrt(epsilon = rsqrt_89_epsilon_0, x = reduce_mean_89)[name = string("rsqrt_89")];
            tensor<fp16, [16, 352]> mul_417 = mul(x = add_51, y = rsqrt_89)[name = string("mul_417")];
            tensor<fp16, [352]> mul_418_y_0 = const()[name = string("mul_418_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5165312)))];
            tensor<fp16, [16, 352]> mul_418 = mul(x = mul_417, y = mul_418_y_0)[name = string("mul_418")];
            tensor<fp16, [16, 352]> mul_419 = mul(x = mul_418, y = mul_418)[name = string("mul_419")];
            tensor<int32, [1]> reduce_mean_90_axes_0 = const()[name = string("reduce_mean_90_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_90_keep_dims_0 = const()[name = string("reduce_mean_90_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_90 = reduce_mean(axes = reduce_mean_90_axes_0, keep_dims = reduce_mean_90_keep_dims_0, x = mul_419)[name = string("reduce_mean_90")];
            fp32 rsqrt_90_epsilon_0 = const()[name = string("rsqrt_90_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_90 = rsqrt(epsilon = rsqrt_90_epsilon_0, x = reduce_mean_90)[name = string("rsqrt_90")];
            tensor<fp16, [16, 352]> mul_420 = mul(x = mul_418, y = rsqrt_90)[name = string("mul_420")];
            tensor<fp16, [352]> mul_421_y_0 = const()[name = string("mul_421_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5166080)))];
            tensor<fp16, [16, 352]> mul_421 = mul(x = mul_420, y = mul_421_y_0)[name = string("mul_421")];
            tensor<fp16, [960, 352]> tern_8_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5166848))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_8_w1_weight_0_palettized")];
            tensor<fp16, [16, 960]> tern_8_w1 = linear(bias = linear_4_bias_0, weight = tern_8_w1_weight_0_palettized, x = mul_421)[name = string("tern_8_w1")];
            tensor<fp16, [960]> mul_422_y_0 = const()[name = string("mul_422_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5251392)))];
            tensor<fp16, [16, 960]> mul_422 = mul(x = tern_8_w1, y = mul_422_y_0)[name = string("mul_422")];
            tensor<fp16, [352]> mul_425_y_0 = const()[name = string("mul_425_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5253376)))];
            tensor<fp16, [16, 352]> mul_425 = mul(x = mul_420, y = mul_425_y_0)[name = string("mul_425")];
            tensor<fp16, [960, 352]> tern_8_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5254144))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_8_w3_weight_0_palettized")];
            tensor<fp16, [16, 960]> tern_8_w3 = linear(bias = linear_4_bias_0, weight = tern_8_w3_weight_0_palettized, x = mul_425)[name = string("tern_8_w3")];
            tensor<fp16, [960]> mul_426_y_0 = const()[name = string("mul_426_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5338688)))];
            tensor<fp16, [16, 960]> mul_426 = mul(x = tern_8_w3, y = mul_426_y_0)[name = string("mul_426")];
            fp16 mul_427_y_0 = const()[name = string("mul_427_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [16, 960]> mul_427 = mul(x = mul_422, y = mul_427_y_0)[name = string("mul_427")];
            tensor<fp16, [16, 960]> tanh_8 = tanh(x = mul_427)[name = string("tanh_8")];
            fp16 mul_428_x_0 = const()[name = string("mul_428_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [16, 960]> mul_428 = mul(x = mul_428_x_0, y = tanh_8)[name = string("mul_428")];
            fp16 add_52_x_0 = const()[name = string("add_52_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [16, 960]> add_52 = add(x = add_52_x_0, y = mul_428)[name = string("add_52")];
            tensor<fp16, [16, 960]> mul_429 = mul(x = mul_422, y = add_52)[name = string("mul_429")];
            tensor<fp16, [16, 960]> mul_430 = mul(x = mul_429, y = mul_426)[name = string("mul_430")];
            tensor<fp16, [16, 960]> mul_431 = mul(x = mul_430, y = mul_430)[name = string("mul_431")];
            tensor<int32, [1]> reduce_mean_92_axes_0 = const()[name = string("reduce_mean_92_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_92_keep_dims_0 = const()[name = string("reduce_mean_92_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_92 = reduce_mean(axes = reduce_mean_92_axes_0, keep_dims = reduce_mean_92_keep_dims_0, x = mul_431)[name = string("reduce_mean_92")];
            fp32 rsqrt_92_epsilon_0 = const()[name = string("rsqrt_92_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_92 = rsqrt(epsilon = rsqrt_92_epsilon_0, x = reduce_mean_92)[name = string("rsqrt_92")];
            tensor<fp16, [16, 960]> mul_432 = mul(x = mul_430, y = rsqrt_92)[name = string("mul_432")];
            tensor<fp16, [960]> mul_433_y_0 = const()[name = string("mul_433_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5340672)))];
            tensor<fp16, [16, 960]> mul_433 = mul(x = mul_432, y = mul_433_y_0)[name = string("mul_433")];
            tensor<fp16, [352, 960]> tern_8_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5342656))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_8_w2_weight_0_palettized")];
            tensor<fp16, [16, 352]> tern_8_w2 = linear(bias = linear_0_bias_0, weight = tern_8_w2_weight_0_palettized, x = mul_433)[name = string("tern_8_w2")];
            tensor<fp16, [352]> mul_434_y_0 = const()[name = string("mul_434_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5427200)))];
            tensor<fp16, [16, 352]> mul_434 = mul(x = tern_8_w2, y = mul_434_y_0)[name = string("mul_434")];
            tensor<fp16, [16, 352]> add_53 = add(x = add_51, y = mul_434)[name = string("add_53")];
            tensor<fp16, [16, 352]> mul_435 = mul(x = add_53, y = add_53)[name = string("mul_435")];
            tensor<int32, [1]> reduce_mean_93_axes_0 = const()[name = string("reduce_mean_93_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_93_keep_dims_0 = const()[name = string("reduce_mean_93_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_93 = reduce_mean(axes = reduce_mean_93_axes_0, keep_dims = reduce_mean_93_keep_dims_0, x = mul_435)[name = string("reduce_mean_93")];
            fp32 rsqrt_93_epsilon_0 = const()[name = string("rsqrt_93_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_93 = rsqrt(epsilon = rsqrt_93_epsilon_0, x = reduce_mean_93)[name = string("rsqrt_93")];
            tensor<fp16, [16, 352]> mul_436 = mul(x = add_53, y = rsqrt_93)[name = string("mul_436")];
            tensor<fp16, [352]> mul_437_y_0 = const()[name = string("mul_437_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5427968)))];
            tensor<fp16, [16, 352]> mul_437 = mul(x = mul_436, y = mul_437_y_0)[name = string("mul_437")];
            tensor<fp16, [16, 352]> mul_438 = mul(x = mul_437, y = mul_437)[name = string("mul_438")];
            tensor<int32, [1]> reduce_mean_94_axes_0 = const()[name = string("reduce_mean_94_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_94_keep_dims_0 = const()[name = string("reduce_mean_94_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_94 = reduce_mean(axes = reduce_mean_94_axes_0, keep_dims = reduce_mean_94_keep_dims_0, x = mul_438)[name = string("reduce_mean_94")];
            fp32 rsqrt_94_epsilon_0 = const()[name = string("rsqrt_94_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_94 = rsqrt(epsilon = rsqrt_94_epsilon_0, x = reduce_mean_94)[name = string("rsqrt_94")];
            tensor<fp16, [16, 352]> mul_439 = mul(x = mul_437, y = rsqrt_94)[name = string("mul_439")];
            tensor<fp16, [352]> mul_440_y_0 = const()[name = string("mul_440_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5428736)))];
            tensor<fp16, [16, 352]> mul_440 = mul(x = mul_439, y = mul_440_y_0)[name = string("mul_440")];
            tensor<fp16, [352, 352]> tern_9_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5429504))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_9_q_weight_0_palettized")];
            tensor<fp16, [16, 352]> tern_9_q = linear(bias = linear_0_bias_0, weight = tern_9_q_weight_0_palettized, x = mul_440)[name = string("tern_9_q")];
            tensor<fp16, [352]> mul_441_y_0 = const()[name = string("mul_441_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5460544)))];
            tensor<fp16, [16, 352]> mul_441 = mul(x = tern_9_q, y = mul_441_y_0)[name = string("mul_441")];
            tensor<int32, [3]> reshape_74_shape_0 = const()[name = string("reshape_74_shape_0"), val = tensor<int32, [3]>([16, 8, 44])];
            tensor<fp16, [16, 8, 44]> reshape_74 = reshape(shape = reshape_74_shape_0, x = mul_441)[name = string("reshape_74")];
            tensor<int32, [3]> transpose_36_perm_0 = const()[name = string("transpose_36_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_444_y_0 = const()[name = string("mul_444_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5461312)))];
            tensor<fp16, [16, 352]> mul_444 = mul(x = mul_439, y = mul_444_y_0)[name = string("mul_444")];
            tensor<fp16, [88, 352]> tern_9_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5462080))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_9_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_9_k_bias_0 = const()[name = string("tern_9_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [16, 88]> tern_9_k = linear(bias = tern_9_k_bias_0, weight = tern_9_k_weight_0_palettized, x = mul_444)[name = string("tern_9_k")];
            tensor<fp16, [88]> mul_445_y_0 = const()[name = string("mul_445_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5469888)))];
            tensor<fp16, [16, 88]> mul_445 = mul(x = tern_9_k, y = mul_445_y_0)[name = string("mul_445")];
            tensor<int32, [3]> reshape_75_shape_0 = const()[name = string("reshape_75_shape_0"), val = tensor<int32, [3]>([16, 2, 44])];
            tensor<fp16, [16, 2, 44]> reshape_75 = reshape(shape = reshape_75_shape_0, x = mul_445)[name = string("reshape_75")];
            tensor<int32, [3]> transpose_37_perm_0 = const()[name = string("transpose_37_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_448_y_0 = const()[name = string("mul_448_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5470144)))];
            tensor<fp16, [16, 352]> mul_448 = mul(x = mul_439, y = mul_448_y_0)[name = string("mul_448")];
            tensor<fp16, [88, 352]> tern_9_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5470912))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_9_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_9_v_bias_0 = const()[name = string("tern_9_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [16, 88]> tern_9_v = linear(bias = tern_9_v_bias_0, weight = tern_9_v_weight_0_palettized, x = mul_448)[name = string("tern_9_v")];
            tensor<fp16, [88]> mul_449_y_0 = const()[name = string("mul_449_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5478720)))];
            tensor<fp16, [16, 88]> mul_449 = mul(x = tern_9_v, y = mul_449_y_0)[name = string("mul_449")];
            tensor<int32, [3]> reshape_76_shape_0 = const()[name = string("reshape_76_shape_0"), val = tensor<int32, [3]>([16, 2, 44])];
            tensor<fp16, [16, 2, 44]> reshape_76 = reshape(shape = reshape_76_shape_0, x = mul_449)[name = string("reshape_76")];
            tensor<int32, [3]> transpose_38_perm_0 = const()[name = string("transpose_38_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 16, 44]> transpose_36 = transpose(perm = transpose_36_perm_0, x = reshape_74)[name = string("transpose_27")];
            tensor<fp16, [8, 16, 44]> mul_450 = mul(x = transpose_36, y = transpose_36)[name = string("mul_450")];
            tensor<int32, [1]> reduce_mean_97_axes_0 = const()[name = string("reduce_mean_97_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_97_keep_dims_0 = const()[name = string("reduce_mean_97_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 16, 1]> reduce_mean_97 = reduce_mean(axes = reduce_mean_97_axes_0, keep_dims = reduce_mean_97_keep_dims_0, x = mul_450)[name = string("reduce_mean_97")];
            fp32 rsqrt_97_epsilon_0 = const()[name = string("rsqrt_97_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 16, 1]> rsqrt_97 = rsqrt(epsilon = rsqrt_97_epsilon_0, x = reduce_mean_97)[name = string("rsqrt_97")];
            tensor<fp16, [8, 16, 44]> mul_451 = mul(x = transpose_36, y = rsqrt_97)[name = string("mul_451")];
            tensor<fp16, [44]> mul_452_y_0 = const()[name = string("mul_452_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5478976)))];
            tensor<fp16, [8, 16, 44]> mul_452 = mul(x = mul_451, y = mul_452_y_0)[name = string("mul_452")];
            tensor<int32, [3]> slice_by_index_36_begin_0 = const()[name = string("slice_by_index_36_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_36_end_0 = const()[name = string("slice_by_index_36_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_36_end_mask_0 = const()[name = string("slice_by_index_36_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 16, 22]> slice_by_index_36 = slice_by_index(begin = slice_by_index_36_begin_0, end = slice_by_index_36_end_0, end_mask = slice_by_index_36_end_mask_0, x = mul_452)[name = string("slice_by_index_36")];
            tensor<int32, [3]> slice_by_index_37_begin_0 = const()[name = string("slice_by_index_37_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_37_end_0 = const()[name = string("slice_by_index_37_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_37_end_mask_0 = const()[name = string("slice_by_index_37_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 16, 22]> slice_by_index_37 = slice_by_index(begin = slice_by_index_37_begin_0, end = slice_by_index_37_end_0, end_mask = slice_by_index_37_end_mask_0, x = mul_452)[name = string("slice_by_index_37")];
            int32 concat_18_axis_0 = const()[name = string("concat_18_axis_0"), val = int32(-1)];
            bool concat_18_interleave_0 = const()[name = string("concat_18_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 16, 44]> concat_18 = concat(axis = concat_18_axis_0, interleave = concat_18_interleave_0, values = (slice_by_index_37, slice_by_index_36))[name = string("concat_18")];
            tensor<fp16, [44]> mul_453_y_0 = const()[name = string("mul_453_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 16, 44]> mul_453 = mul(x = concat_18, y = mul_453_y_0)[name = string("mul_453")];
            tensor<fp16, [8, 16, 44]> mul_454 = mul(x = mul_452, y = mul_11_y_0)[name = string("mul_454")];
            tensor<fp16, [8, 16, 44]> mul_455 = mul(x = mul_453, y = mul_12_y_0)[name = string("mul_455")];
            tensor<fp16, [8, 16, 44]> add_54 = add(x = mul_454, y = mul_455)[name = string("add_54")];
            tensor<fp16, [2, 16, 44]> transpose_37 = transpose(perm = transpose_37_perm_0, x = reshape_75)[name = string("transpose_26")];
            tensor<fp16, [2, 16, 44]> mul_456 = mul(x = transpose_37, y = transpose_37)[name = string("mul_456")];
            tensor<int32, [1]> reduce_mean_98_axes_0 = const()[name = string("reduce_mean_98_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_98_keep_dims_0 = const()[name = string("reduce_mean_98_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 16, 1]> reduce_mean_98 = reduce_mean(axes = reduce_mean_98_axes_0, keep_dims = reduce_mean_98_keep_dims_0, x = mul_456)[name = string("reduce_mean_98")];
            fp32 rsqrt_98_epsilon_0 = const()[name = string("rsqrt_98_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 16, 1]> rsqrt_98 = rsqrt(epsilon = rsqrt_98_epsilon_0, x = reduce_mean_98)[name = string("rsqrt_98")];
            tensor<fp16, [2, 16, 44]> mul_457 = mul(x = transpose_37, y = rsqrt_98)[name = string("mul_457")];
            tensor<fp16, [44]> mul_458_y_0 = const()[name = string("mul_458_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5479168)))];
            tensor<fp16, [2, 16, 44]> mul_458 = mul(x = mul_457, y = mul_458_y_0)[name = string("mul_458")];
            tensor<int32, [3]> slice_by_index_38_begin_0 = const()[name = string("slice_by_index_38_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_38_end_0 = const()[name = string("slice_by_index_38_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_38_end_mask_0 = const()[name = string("slice_by_index_38_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 16, 22]> slice_by_index_38 = slice_by_index(begin = slice_by_index_38_begin_0, end = slice_by_index_38_end_0, end_mask = slice_by_index_38_end_mask_0, x = mul_458)[name = string("slice_by_index_38")];
            tensor<int32, [3]> slice_by_index_39_begin_0 = const()[name = string("slice_by_index_39_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_39_end_0 = const()[name = string("slice_by_index_39_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_39_end_mask_0 = const()[name = string("slice_by_index_39_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 16, 22]> slice_by_index_39 = slice_by_index(begin = slice_by_index_39_begin_0, end = slice_by_index_39_end_0, end_mask = slice_by_index_39_end_mask_0, x = mul_458)[name = string("slice_by_index_39")];
            int32 concat_19_axis_0 = const()[name = string("concat_19_axis_0"), val = int32(-1)];
            bool concat_19_interleave_0 = const()[name = string("concat_19_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 16, 44]> concat_19 = concat(axis = concat_19_axis_0, interleave = concat_19_interleave_0, values = (slice_by_index_39, slice_by_index_38))[name = string("concat_19")];
            tensor<fp16, [44]> mul_459_y_0 = const()[name = string("mul_459_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 16, 44]> mul_459 = mul(x = concat_19, y = mul_459_y_0)[name = string("mul_459")];
            tensor<fp16, [2, 16, 44]> mul_460 = mul(x = mul_458, y = mul_11_y_0)[name = string("mul_460")];
            tensor<fp16, [2, 16, 44]> mul_461 = mul(x = mul_459, y = mul_12_y_0)[name = string("mul_461")];
            tensor<fp16, [2, 16, 44]> add_55 = add(x = mul_460, y = mul_461)[name = string("add_55")];
            tensor<int32, [4]> reshape_77_shape_0 = const()[name = string("reshape_77_shape_0"), val = tensor<int32, [4]>([2, 1, 16, 44])];
            tensor<fp16, [2, 1, 16, 44]> reshape_77 = reshape(shape = reshape_77_shape_0, x = add_55)[name = string("reshape_77")];
            tensor<int32, [4]> tile_18_reps_0 = const()[name = string("tile_18_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 16, 44]> tile_18 = tile(reps = tile_18_reps_0, x = reshape_77)[name = string("tile_18")];
            tensor<int32, [3]> reshape_78_shape_0 = const()[name = string("reshape_78_shape_0"), val = tensor<int32, [3]>([8, 16, 44])];
            tensor<fp16, [8, 16, 44]> reshape_78 = reshape(shape = reshape_78_shape_0, x = tile_18)[name = string("reshape_78")];
            tensor<int32, [4]> reshape_79_shape_0 = const()[name = string("reshape_79_shape_0"), val = tensor<int32, [4]>([2, 1, 16, 44])];
            tensor<fp16, [2, 16, 44]> transpose_38 = transpose(perm = transpose_38_perm_0, x = reshape_76)[name = string("transpose_25")];
            tensor<fp16, [2, 1, 16, 44]> reshape_79 = reshape(shape = reshape_79_shape_0, x = transpose_38)[name = string("reshape_79")];
            tensor<int32, [4]> tile_19_reps_0 = const()[name = string("tile_19_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 16, 44]> tile_19 = tile(reps = tile_19_reps_0, x = reshape_79)[name = string("tile_19")];
            tensor<int32, [3]> reshape_80_shape_0 = const()[name = string("reshape_80_shape_0"), val = tensor<int32, [3]>([8, 16, 44])];
            tensor<fp16, [8, 16, 44]> reshape_80 = reshape(shape = reshape_80_shape_0, x = tile_19)[name = string("reshape_80")];
            fp16 mul_462_y_0 = const()[name = string("mul_462_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 16, 44]> mul_462 = mul(x = add_54, y = mul_462_y_0)[name = string("mul_462")];
            bool matmul_18_transpose_y_0 = const()[name = string("matmul_18_transpose_y_0"), val = bool(true)];
            bool matmul_18_transpose_x_0 = const()[name = string("matmul_18_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 16, 16]> matmul_18 = matmul(transpose_x = matmul_18_transpose_x_0, transpose_y = matmul_18_transpose_y_0, x = mul_462, y = reshape_78)[name = string("matmul_18")];
            tensor<fp16, [8, 16, 16]> add_56 = add(x = matmul_18, y = reshape_1)[name = string("add_56")];
            int32 softmax_9_axis_0 = const()[name = string("softmax_9_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 16, 16]> softmax_9 = softmax(axis = softmax_9_axis_0, x = add_56)[name = string("softmax_9")];
            bool matmul_19_transpose_x_0 = const()[name = string("matmul_19_transpose_x_0"), val = bool(false)];
            bool matmul_19_transpose_y_0 = const()[name = string("matmul_19_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 16, 44]> matmul_19 = matmul(transpose_x = matmul_19_transpose_x_0, transpose_y = matmul_19_transpose_y_0, x = softmax_9, y = reshape_80)[name = string("matmul_19")];
            tensor<int32, [3]> transpose_39_perm_0 = const()[name = string("transpose_39_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_81_shape_0 = const()[name = string("reshape_81_shape_0"), val = tensor<int32, [2]>([16, 352])];
            tensor<fp16, [16, 8, 44]> transpose_39 = transpose(perm = transpose_39_perm_0, x = matmul_19)[name = string("transpose_24")];
            tensor<fp16, [16, 352]> reshape_81 = reshape(shape = reshape_81_shape_0, x = transpose_39)[name = string("reshape_81")];
            tensor<fp16, [16, 352]> mul_463 = mul(x = reshape_81, y = reshape_81)[name = string("mul_463")];
            tensor<int32, [1]> reduce_mean_99_axes_0 = const()[name = string("reduce_mean_99_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_99_keep_dims_0 = const()[name = string("reduce_mean_99_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_99 = reduce_mean(axes = reduce_mean_99_axes_0, keep_dims = reduce_mean_99_keep_dims_0, x = mul_463)[name = string("reduce_mean_99")];
            fp32 rsqrt_99_epsilon_0 = const()[name = string("rsqrt_99_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_99 = rsqrt(epsilon = rsqrt_99_epsilon_0, x = reduce_mean_99)[name = string("rsqrt_99")];
            tensor<fp16, [16, 352]> mul_464 = mul(x = reshape_81, y = rsqrt_99)[name = string("mul_464")];
            tensor<fp16, [352]> mul_465_y_0 = const()[name = string("mul_465_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5479360)))];
            tensor<fp16, [16, 352]> mul_465 = mul(x = mul_464, y = mul_465_y_0)[name = string("mul_465")];
            tensor<fp16, [352, 352]> tern_9_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5480128))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_9_o_weight_0_palettized")];
            tensor<fp16, [16, 352]> tern_9_o = linear(bias = linear_0_bias_0, weight = tern_9_o_weight_0_palettized, x = mul_465)[name = string("tern_9_o")];
            tensor<fp16, [352]> mul_466_y_0 = const()[name = string("mul_466_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5511168)))];
            tensor<fp16, [16, 352]> mul_466 = mul(x = tern_9_o, y = mul_466_y_0)[name = string("mul_466")];
            tensor<fp16, [16, 352]> add_57 = add(x = add_53, y = mul_466)[name = string("add_57")];
            tensor<fp16, [16, 352]> mul_467 = mul(x = add_57, y = add_57)[name = string("mul_467")];
            tensor<int32, [1]> reduce_mean_100_axes_0 = const()[name = string("reduce_mean_100_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_100_keep_dims_0 = const()[name = string("reduce_mean_100_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_100 = reduce_mean(axes = reduce_mean_100_axes_0, keep_dims = reduce_mean_100_keep_dims_0, x = mul_467)[name = string("reduce_mean_100")];
            fp32 rsqrt_100_epsilon_0 = const()[name = string("rsqrt_100_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_100 = rsqrt(epsilon = rsqrt_100_epsilon_0, x = reduce_mean_100)[name = string("rsqrt_100")];
            tensor<fp16, [16, 352]> mul_468 = mul(x = add_57, y = rsqrt_100)[name = string("mul_468")];
            tensor<fp16, [352]> mul_469_y_0 = const()[name = string("mul_469_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5511936)))];
            tensor<fp16, [16, 352]> mul_469 = mul(x = mul_468, y = mul_469_y_0)[name = string("mul_469")];
            tensor<fp16, [16, 352]> mul_470 = mul(x = mul_469, y = mul_469)[name = string("mul_470")];
            tensor<int32, [1]> reduce_mean_101_axes_0 = const()[name = string("reduce_mean_101_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_101_keep_dims_0 = const()[name = string("reduce_mean_101_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_101 = reduce_mean(axes = reduce_mean_101_axes_0, keep_dims = reduce_mean_101_keep_dims_0, x = mul_470)[name = string("reduce_mean_101")];
            fp32 rsqrt_101_epsilon_0 = const()[name = string("rsqrt_101_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_101 = rsqrt(epsilon = rsqrt_101_epsilon_0, x = reduce_mean_101)[name = string("rsqrt_101")];
            tensor<fp16, [16, 352]> mul_471 = mul(x = mul_469, y = rsqrt_101)[name = string("mul_471")];
            tensor<fp16, [352]> mul_472_y_0 = const()[name = string("mul_472_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5512704)))];
            tensor<fp16, [16, 352]> mul_472 = mul(x = mul_471, y = mul_472_y_0)[name = string("mul_472")];
            tensor<fp16, [960, 352]> tern_9_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5513472))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_9_w1_weight_0_palettized")];
            tensor<fp16, [16, 960]> tern_9_w1 = linear(bias = linear_4_bias_0, weight = tern_9_w1_weight_0_palettized, x = mul_472)[name = string("tern_9_w1")];
            tensor<fp16, [960]> mul_473_y_0 = const()[name = string("mul_473_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5598016)))];
            tensor<fp16, [16, 960]> mul_473 = mul(x = tern_9_w1, y = mul_473_y_0)[name = string("mul_473")];
            tensor<fp16, [352]> mul_476_y_0 = const()[name = string("mul_476_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5600000)))];
            tensor<fp16, [16, 352]> mul_476 = mul(x = mul_471, y = mul_476_y_0)[name = string("mul_476")];
            tensor<fp16, [960, 352]> tern_9_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5600768))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_9_w3_weight_0_palettized")];
            tensor<fp16, [16, 960]> tern_9_w3 = linear(bias = linear_4_bias_0, weight = tern_9_w3_weight_0_palettized, x = mul_476)[name = string("tern_9_w3")];
            tensor<fp16, [960]> mul_477_y_0 = const()[name = string("mul_477_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5685312)))];
            tensor<fp16, [16, 960]> mul_477 = mul(x = tern_9_w3, y = mul_477_y_0)[name = string("mul_477")];
            fp16 mul_478_y_0 = const()[name = string("mul_478_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [16, 960]> mul_478 = mul(x = mul_473, y = mul_478_y_0)[name = string("mul_478")];
            tensor<fp16, [16, 960]> tanh_9 = tanh(x = mul_478)[name = string("tanh_9")];
            fp16 mul_479_x_0 = const()[name = string("mul_479_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [16, 960]> mul_479 = mul(x = mul_479_x_0, y = tanh_9)[name = string("mul_479")];
            fp16 add_58_x_0 = const()[name = string("add_58_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [16, 960]> add_58 = add(x = add_58_x_0, y = mul_479)[name = string("add_58")];
            tensor<fp16, [16, 960]> mul_480 = mul(x = mul_473, y = add_58)[name = string("mul_480")];
            tensor<fp16, [16, 960]> mul_481 = mul(x = mul_480, y = mul_477)[name = string("mul_481")];
            tensor<fp16, [16, 960]> mul_482 = mul(x = mul_481, y = mul_481)[name = string("mul_482")];
            tensor<int32, [1]> reduce_mean_103_axes_0 = const()[name = string("reduce_mean_103_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_103_keep_dims_0 = const()[name = string("reduce_mean_103_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_103 = reduce_mean(axes = reduce_mean_103_axes_0, keep_dims = reduce_mean_103_keep_dims_0, x = mul_482)[name = string("reduce_mean_103")];
            fp32 rsqrt_103_epsilon_0 = const()[name = string("rsqrt_103_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_103 = rsqrt(epsilon = rsqrt_103_epsilon_0, x = reduce_mean_103)[name = string("rsqrt_103")];
            tensor<fp16, [16, 960]> mul_483 = mul(x = mul_481, y = rsqrt_103)[name = string("mul_483")];
            tensor<fp16, [960]> mul_484_y_0 = const()[name = string("mul_484_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5687296)))];
            tensor<fp16, [16, 960]> mul_484 = mul(x = mul_483, y = mul_484_y_0)[name = string("mul_484")];
            tensor<fp16, [352, 960]> tern_9_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5689280))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_9_w2_weight_0_palettized")];
            tensor<fp16, [16, 352]> tern_9_w2 = linear(bias = linear_0_bias_0, weight = tern_9_w2_weight_0_palettized, x = mul_484)[name = string("tern_9_w2")];
            tensor<fp16, [352]> mul_485_y_0 = const()[name = string("mul_485_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5773824)))];
            tensor<fp16, [16, 352]> mul_485 = mul(x = tern_9_w2, y = mul_485_y_0)[name = string("mul_485")];
            tensor<fp16, [16, 352]> add_59 = add(x = add_57, y = mul_485)[name = string("add_59")];
            tensor<fp16, [16, 352]> mul_486 = mul(x = add_59, y = add_59)[name = string("mul_486")];
            tensor<int32, [1]> reduce_mean_104_axes_0 = const()[name = string("reduce_mean_104_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_104_keep_dims_0 = const()[name = string("reduce_mean_104_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_104 = reduce_mean(axes = reduce_mean_104_axes_0, keep_dims = reduce_mean_104_keep_dims_0, x = mul_486)[name = string("reduce_mean_104")];
            fp32 rsqrt_104_epsilon_0 = const()[name = string("rsqrt_104_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_104 = rsqrt(epsilon = rsqrt_104_epsilon_0, x = reduce_mean_104)[name = string("rsqrt_104")];
            tensor<fp16, [16, 352]> mul_487 = mul(x = add_59, y = rsqrt_104)[name = string("mul_487")];
            tensor<fp16, [352]> mul_488_y_0 = const()[name = string("mul_488_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5774592)))];
            tensor<fp16, [16, 352]> mul_488 = mul(x = mul_487, y = mul_488_y_0)[name = string("mul_488")];
            tensor<fp16, [16, 352]> mul_489 = mul(x = mul_488, y = mul_488)[name = string("mul_489")];
            tensor<int32, [1]> reduce_mean_105_axes_0 = const()[name = string("reduce_mean_105_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_105_keep_dims_0 = const()[name = string("reduce_mean_105_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_105 = reduce_mean(axes = reduce_mean_105_axes_0, keep_dims = reduce_mean_105_keep_dims_0, x = mul_489)[name = string("reduce_mean_105")];
            fp32 rsqrt_105_epsilon_0 = const()[name = string("rsqrt_105_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_105 = rsqrt(epsilon = rsqrt_105_epsilon_0, x = reduce_mean_105)[name = string("rsqrt_105")];
            tensor<fp16, [16, 352]> mul_490 = mul(x = mul_488, y = rsqrt_105)[name = string("mul_490")];
            tensor<fp16, [352]> mul_491_y_0 = const()[name = string("mul_491_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5775360)))];
            tensor<fp16, [16, 352]> mul_491 = mul(x = mul_490, y = mul_491_y_0)[name = string("mul_491")];
            tensor<fp16, [352, 352]> tern_10_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5776128))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_10_q_weight_0_palettized")];
            tensor<fp16, [16, 352]> tern_10_q = linear(bias = linear_0_bias_0, weight = tern_10_q_weight_0_palettized, x = mul_491)[name = string("tern_10_q")];
            tensor<fp16, [352]> mul_492_y_0 = const()[name = string("mul_492_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5807168)))];
            tensor<fp16, [16, 352]> mul_492 = mul(x = tern_10_q, y = mul_492_y_0)[name = string("mul_492")];
            tensor<int32, [3]> reshape_82_shape_0 = const()[name = string("reshape_82_shape_0"), val = tensor<int32, [3]>([16, 8, 44])];
            tensor<fp16, [16, 8, 44]> reshape_82 = reshape(shape = reshape_82_shape_0, x = mul_492)[name = string("reshape_82")];
            tensor<int32, [3]> transpose_40_perm_0 = const()[name = string("transpose_40_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_495_y_0 = const()[name = string("mul_495_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5807936)))];
            tensor<fp16, [16, 352]> mul_495 = mul(x = mul_490, y = mul_495_y_0)[name = string("mul_495")];
            tensor<fp16, [88, 352]> tern_10_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5808704))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_10_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_10_k_bias_0 = const()[name = string("tern_10_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [16, 88]> tern_10_k = linear(bias = tern_10_k_bias_0, weight = tern_10_k_weight_0_palettized, x = mul_495)[name = string("tern_10_k")];
            tensor<fp16, [88]> mul_496_y_0 = const()[name = string("mul_496_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5816512)))];
            tensor<fp16, [16, 88]> mul_496 = mul(x = tern_10_k, y = mul_496_y_0)[name = string("mul_496")];
            tensor<int32, [3]> reshape_83_shape_0 = const()[name = string("reshape_83_shape_0"), val = tensor<int32, [3]>([16, 2, 44])];
            tensor<fp16, [16, 2, 44]> reshape_83 = reshape(shape = reshape_83_shape_0, x = mul_496)[name = string("reshape_83")];
            tensor<int32, [3]> transpose_41_perm_0 = const()[name = string("transpose_41_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_499_y_0 = const()[name = string("mul_499_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5816768)))];
            tensor<fp16, [16, 352]> mul_499 = mul(x = mul_490, y = mul_499_y_0)[name = string("mul_499")];
            tensor<fp16, [88, 352]> tern_10_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5817536))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_10_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_10_v_bias_0 = const()[name = string("tern_10_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [16, 88]> tern_10_v = linear(bias = tern_10_v_bias_0, weight = tern_10_v_weight_0_palettized, x = mul_499)[name = string("tern_10_v")];
            tensor<fp16, [88]> mul_500_y_0 = const()[name = string("mul_500_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5825344)))];
            tensor<fp16, [16, 88]> mul_500 = mul(x = tern_10_v, y = mul_500_y_0)[name = string("mul_500")];
            tensor<int32, [3]> reshape_84_shape_0 = const()[name = string("reshape_84_shape_0"), val = tensor<int32, [3]>([16, 2, 44])];
            tensor<fp16, [16, 2, 44]> reshape_84 = reshape(shape = reshape_84_shape_0, x = mul_500)[name = string("reshape_84")];
            tensor<int32, [3]> transpose_42_perm_0 = const()[name = string("transpose_42_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 16, 44]> transpose_40 = transpose(perm = transpose_40_perm_0, x = reshape_82)[name = string("transpose_23")];
            tensor<fp16, [8, 16, 44]> mul_501 = mul(x = transpose_40, y = transpose_40)[name = string("mul_501")];
            tensor<int32, [1]> reduce_mean_108_axes_0 = const()[name = string("reduce_mean_108_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_108_keep_dims_0 = const()[name = string("reduce_mean_108_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 16, 1]> reduce_mean_108 = reduce_mean(axes = reduce_mean_108_axes_0, keep_dims = reduce_mean_108_keep_dims_0, x = mul_501)[name = string("reduce_mean_108")];
            fp32 rsqrt_108_epsilon_0 = const()[name = string("rsqrt_108_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 16, 1]> rsqrt_108 = rsqrt(epsilon = rsqrt_108_epsilon_0, x = reduce_mean_108)[name = string("rsqrt_108")];
            tensor<fp16, [8, 16, 44]> mul_502 = mul(x = transpose_40, y = rsqrt_108)[name = string("mul_502")];
            tensor<fp16, [44]> mul_503_y_0 = const()[name = string("mul_503_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5825600)))];
            tensor<fp16, [8, 16, 44]> mul_503 = mul(x = mul_502, y = mul_503_y_0)[name = string("mul_503")];
            tensor<int32, [3]> slice_by_index_40_begin_0 = const()[name = string("slice_by_index_40_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_40_end_0 = const()[name = string("slice_by_index_40_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_40_end_mask_0 = const()[name = string("slice_by_index_40_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 16, 22]> slice_by_index_40 = slice_by_index(begin = slice_by_index_40_begin_0, end = slice_by_index_40_end_0, end_mask = slice_by_index_40_end_mask_0, x = mul_503)[name = string("slice_by_index_40")];
            tensor<int32, [3]> slice_by_index_41_begin_0 = const()[name = string("slice_by_index_41_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_41_end_0 = const()[name = string("slice_by_index_41_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_41_end_mask_0 = const()[name = string("slice_by_index_41_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 16, 22]> slice_by_index_41 = slice_by_index(begin = slice_by_index_41_begin_0, end = slice_by_index_41_end_0, end_mask = slice_by_index_41_end_mask_0, x = mul_503)[name = string("slice_by_index_41")];
            int32 concat_20_axis_0 = const()[name = string("concat_20_axis_0"), val = int32(-1)];
            bool concat_20_interleave_0 = const()[name = string("concat_20_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 16, 44]> concat_20 = concat(axis = concat_20_axis_0, interleave = concat_20_interleave_0, values = (slice_by_index_41, slice_by_index_40))[name = string("concat_20")];
            tensor<fp16, [44]> mul_504_y_0 = const()[name = string("mul_504_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 16, 44]> mul_504 = mul(x = concat_20, y = mul_504_y_0)[name = string("mul_504")];
            tensor<fp16, [8, 16, 44]> mul_505 = mul(x = mul_503, y = mul_11_y_0)[name = string("mul_505")];
            tensor<fp16, [8, 16, 44]> mul_506 = mul(x = mul_504, y = mul_12_y_0)[name = string("mul_506")];
            tensor<fp16, [8, 16, 44]> add_60 = add(x = mul_505, y = mul_506)[name = string("add_60")];
            tensor<fp16, [2, 16, 44]> transpose_41 = transpose(perm = transpose_41_perm_0, x = reshape_83)[name = string("transpose_22")];
            tensor<fp16, [2, 16, 44]> mul_507 = mul(x = transpose_41, y = transpose_41)[name = string("mul_507")];
            tensor<int32, [1]> reduce_mean_109_axes_0 = const()[name = string("reduce_mean_109_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_109_keep_dims_0 = const()[name = string("reduce_mean_109_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 16, 1]> reduce_mean_109 = reduce_mean(axes = reduce_mean_109_axes_0, keep_dims = reduce_mean_109_keep_dims_0, x = mul_507)[name = string("reduce_mean_109")];
            fp32 rsqrt_109_epsilon_0 = const()[name = string("rsqrt_109_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 16, 1]> rsqrt_109 = rsqrt(epsilon = rsqrt_109_epsilon_0, x = reduce_mean_109)[name = string("rsqrt_109")];
            tensor<fp16, [2, 16, 44]> mul_508 = mul(x = transpose_41, y = rsqrt_109)[name = string("mul_508")];
            tensor<fp16, [44]> mul_509_y_0 = const()[name = string("mul_509_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5825792)))];
            tensor<fp16, [2, 16, 44]> mul_509 = mul(x = mul_508, y = mul_509_y_0)[name = string("mul_509")];
            tensor<int32, [3]> slice_by_index_42_begin_0 = const()[name = string("slice_by_index_42_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_42_end_0 = const()[name = string("slice_by_index_42_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_42_end_mask_0 = const()[name = string("slice_by_index_42_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 16, 22]> slice_by_index_42 = slice_by_index(begin = slice_by_index_42_begin_0, end = slice_by_index_42_end_0, end_mask = slice_by_index_42_end_mask_0, x = mul_509)[name = string("slice_by_index_42")];
            tensor<int32, [3]> slice_by_index_43_begin_0 = const()[name = string("slice_by_index_43_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_43_end_0 = const()[name = string("slice_by_index_43_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_43_end_mask_0 = const()[name = string("slice_by_index_43_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 16, 22]> slice_by_index_43 = slice_by_index(begin = slice_by_index_43_begin_0, end = slice_by_index_43_end_0, end_mask = slice_by_index_43_end_mask_0, x = mul_509)[name = string("slice_by_index_43")];
            int32 concat_21_axis_0 = const()[name = string("concat_21_axis_0"), val = int32(-1)];
            bool concat_21_interleave_0 = const()[name = string("concat_21_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 16, 44]> concat_21 = concat(axis = concat_21_axis_0, interleave = concat_21_interleave_0, values = (slice_by_index_43, slice_by_index_42))[name = string("concat_21")];
            tensor<fp16, [44]> mul_510_y_0 = const()[name = string("mul_510_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 16, 44]> mul_510 = mul(x = concat_21, y = mul_510_y_0)[name = string("mul_510")];
            tensor<fp16, [2, 16, 44]> mul_511 = mul(x = mul_509, y = mul_11_y_0)[name = string("mul_511")];
            tensor<fp16, [2, 16, 44]> mul_512 = mul(x = mul_510, y = mul_12_y_0)[name = string("mul_512")];
            tensor<fp16, [2, 16, 44]> add_61 = add(x = mul_511, y = mul_512)[name = string("add_61")];
            tensor<int32, [4]> reshape_85_shape_0 = const()[name = string("reshape_85_shape_0"), val = tensor<int32, [4]>([2, 1, 16, 44])];
            tensor<fp16, [2, 1, 16, 44]> reshape_85 = reshape(shape = reshape_85_shape_0, x = add_61)[name = string("reshape_85")];
            tensor<int32, [4]> tile_20_reps_0 = const()[name = string("tile_20_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 16, 44]> tile_20 = tile(reps = tile_20_reps_0, x = reshape_85)[name = string("tile_20")];
            tensor<int32, [3]> reshape_86_shape_0 = const()[name = string("reshape_86_shape_0"), val = tensor<int32, [3]>([8, 16, 44])];
            tensor<fp16, [8, 16, 44]> reshape_86 = reshape(shape = reshape_86_shape_0, x = tile_20)[name = string("reshape_86")];
            tensor<int32, [4]> reshape_87_shape_0 = const()[name = string("reshape_87_shape_0"), val = tensor<int32, [4]>([2, 1, 16, 44])];
            tensor<fp16, [2, 16, 44]> transpose_42 = transpose(perm = transpose_42_perm_0, x = reshape_84)[name = string("transpose_21")];
            tensor<fp16, [2, 1, 16, 44]> reshape_87 = reshape(shape = reshape_87_shape_0, x = transpose_42)[name = string("reshape_87")];
            tensor<int32, [4]> tile_21_reps_0 = const()[name = string("tile_21_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 16, 44]> tile_21 = tile(reps = tile_21_reps_0, x = reshape_87)[name = string("tile_21")];
            tensor<int32, [3]> reshape_88_shape_0 = const()[name = string("reshape_88_shape_0"), val = tensor<int32, [3]>([8, 16, 44])];
            tensor<fp16, [8, 16, 44]> reshape_88 = reshape(shape = reshape_88_shape_0, x = tile_21)[name = string("reshape_88")];
            fp16 mul_513_y_0 = const()[name = string("mul_513_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 16, 44]> mul_513 = mul(x = add_60, y = mul_513_y_0)[name = string("mul_513")];
            bool matmul_20_transpose_y_0 = const()[name = string("matmul_20_transpose_y_0"), val = bool(true)];
            bool matmul_20_transpose_x_0 = const()[name = string("matmul_20_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 16, 16]> matmul_20 = matmul(transpose_x = matmul_20_transpose_x_0, transpose_y = matmul_20_transpose_y_0, x = mul_513, y = reshape_86)[name = string("matmul_20")];
            tensor<fp16, [8, 16, 16]> add_62 = add(x = matmul_20, y = reshape_1)[name = string("add_62")];
            int32 softmax_10_axis_0 = const()[name = string("softmax_10_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 16, 16]> softmax_10 = softmax(axis = softmax_10_axis_0, x = add_62)[name = string("softmax_10")];
            bool matmul_21_transpose_x_0 = const()[name = string("matmul_21_transpose_x_0"), val = bool(false)];
            bool matmul_21_transpose_y_0 = const()[name = string("matmul_21_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 16, 44]> matmul_21 = matmul(transpose_x = matmul_21_transpose_x_0, transpose_y = matmul_21_transpose_y_0, x = softmax_10, y = reshape_88)[name = string("matmul_21")];
            tensor<int32, [3]> transpose_43_perm_0 = const()[name = string("transpose_43_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_89_shape_0 = const()[name = string("reshape_89_shape_0"), val = tensor<int32, [2]>([16, 352])];
            tensor<fp16, [16, 8, 44]> transpose_43 = transpose(perm = transpose_43_perm_0, x = matmul_21)[name = string("transpose_20")];
            tensor<fp16, [16, 352]> reshape_89 = reshape(shape = reshape_89_shape_0, x = transpose_43)[name = string("reshape_89")];
            tensor<fp16, [16, 352]> mul_514 = mul(x = reshape_89, y = reshape_89)[name = string("mul_514")];
            tensor<int32, [1]> reduce_mean_110_axes_0 = const()[name = string("reduce_mean_110_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_110_keep_dims_0 = const()[name = string("reduce_mean_110_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_110 = reduce_mean(axes = reduce_mean_110_axes_0, keep_dims = reduce_mean_110_keep_dims_0, x = mul_514)[name = string("reduce_mean_110")];
            fp32 rsqrt_110_epsilon_0 = const()[name = string("rsqrt_110_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_110 = rsqrt(epsilon = rsqrt_110_epsilon_0, x = reduce_mean_110)[name = string("rsqrt_110")];
            tensor<fp16, [16, 352]> mul_515 = mul(x = reshape_89, y = rsqrt_110)[name = string("mul_515")];
            tensor<fp16, [352]> mul_516_y_0 = const()[name = string("mul_516_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5825984)))];
            tensor<fp16, [16, 352]> mul_516 = mul(x = mul_515, y = mul_516_y_0)[name = string("mul_516")];
            tensor<fp16, [352, 352]> tern_10_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5826752))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_10_o_weight_0_palettized")];
            tensor<fp16, [16, 352]> tern_10_o = linear(bias = linear_0_bias_0, weight = tern_10_o_weight_0_palettized, x = mul_516)[name = string("tern_10_o")];
            tensor<fp16, [352]> mul_517_y_0 = const()[name = string("mul_517_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5857792)))];
            tensor<fp16, [16, 352]> mul_517 = mul(x = tern_10_o, y = mul_517_y_0)[name = string("mul_517")];
            tensor<fp16, [16, 352]> add_63 = add(x = add_59, y = mul_517)[name = string("add_63")];
            tensor<fp16, [16, 352]> mul_518 = mul(x = add_63, y = add_63)[name = string("mul_518")];
            tensor<int32, [1]> reduce_mean_111_axes_0 = const()[name = string("reduce_mean_111_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_111_keep_dims_0 = const()[name = string("reduce_mean_111_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_111 = reduce_mean(axes = reduce_mean_111_axes_0, keep_dims = reduce_mean_111_keep_dims_0, x = mul_518)[name = string("reduce_mean_111")];
            fp32 rsqrt_111_epsilon_0 = const()[name = string("rsqrt_111_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_111 = rsqrt(epsilon = rsqrt_111_epsilon_0, x = reduce_mean_111)[name = string("rsqrt_111")];
            tensor<fp16, [16, 352]> mul_519 = mul(x = add_63, y = rsqrt_111)[name = string("mul_519")];
            tensor<fp16, [352]> mul_520_y_0 = const()[name = string("mul_520_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5858560)))];
            tensor<fp16, [16, 352]> mul_520 = mul(x = mul_519, y = mul_520_y_0)[name = string("mul_520")];
            tensor<fp16, [16, 352]> mul_521 = mul(x = mul_520, y = mul_520)[name = string("mul_521")];
            tensor<int32, [1]> reduce_mean_112_axes_0 = const()[name = string("reduce_mean_112_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_112_keep_dims_0 = const()[name = string("reduce_mean_112_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_112 = reduce_mean(axes = reduce_mean_112_axes_0, keep_dims = reduce_mean_112_keep_dims_0, x = mul_521)[name = string("reduce_mean_112")];
            fp32 rsqrt_112_epsilon_0 = const()[name = string("rsqrt_112_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_112 = rsqrt(epsilon = rsqrt_112_epsilon_0, x = reduce_mean_112)[name = string("rsqrt_112")];
            tensor<fp16, [16, 352]> mul_522 = mul(x = mul_520, y = rsqrt_112)[name = string("mul_522")];
            tensor<fp16, [352]> mul_523_y_0 = const()[name = string("mul_523_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5859328)))];
            tensor<fp16, [16, 352]> mul_523 = mul(x = mul_522, y = mul_523_y_0)[name = string("mul_523")];
            tensor<fp16, [960, 352]> tern_10_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5860096))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_10_w1_weight_0_palettized")];
            tensor<fp16, [16, 960]> tern_10_w1 = linear(bias = linear_4_bias_0, weight = tern_10_w1_weight_0_palettized, x = mul_523)[name = string("tern_10_w1")];
            tensor<fp16, [960]> mul_524_y_0 = const()[name = string("mul_524_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5944640)))];
            tensor<fp16, [16, 960]> mul_524 = mul(x = tern_10_w1, y = mul_524_y_0)[name = string("mul_524")];
            tensor<fp16, [352]> mul_527_y_0 = const()[name = string("mul_527_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5946624)))];
            tensor<fp16, [16, 352]> mul_527 = mul(x = mul_522, y = mul_527_y_0)[name = string("mul_527")];
            tensor<fp16, [960, 352]> tern_10_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5947392))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_10_w3_weight_0_palettized")];
            tensor<fp16, [16, 960]> tern_10_w3 = linear(bias = linear_4_bias_0, weight = tern_10_w3_weight_0_palettized, x = mul_527)[name = string("tern_10_w3")];
            tensor<fp16, [960]> mul_528_y_0 = const()[name = string("mul_528_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6031936)))];
            tensor<fp16, [16, 960]> mul_528 = mul(x = tern_10_w3, y = mul_528_y_0)[name = string("mul_528")];
            fp16 mul_529_y_0 = const()[name = string("mul_529_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [16, 960]> mul_529 = mul(x = mul_524, y = mul_529_y_0)[name = string("mul_529")];
            tensor<fp16, [16, 960]> tanh_10 = tanh(x = mul_529)[name = string("tanh_10")];
            fp16 mul_530_x_0 = const()[name = string("mul_530_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [16, 960]> mul_530 = mul(x = mul_530_x_0, y = tanh_10)[name = string("mul_530")];
            fp16 add_64_x_0 = const()[name = string("add_64_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [16, 960]> add_64 = add(x = add_64_x_0, y = mul_530)[name = string("add_64")];
            tensor<fp16, [16, 960]> mul_531 = mul(x = mul_524, y = add_64)[name = string("mul_531")];
            tensor<fp16, [16, 960]> mul_532 = mul(x = mul_531, y = mul_528)[name = string("mul_532")];
            tensor<fp16, [16, 960]> mul_533 = mul(x = mul_532, y = mul_532)[name = string("mul_533")];
            tensor<int32, [1]> reduce_mean_114_axes_0 = const()[name = string("reduce_mean_114_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_114_keep_dims_0 = const()[name = string("reduce_mean_114_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_114 = reduce_mean(axes = reduce_mean_114_axes_0, keep_dims = reduce_mean_114_keep_dims_0, x = mul_533)[name = string("reduce_mean_114")];
            fp32 rsqrt_114_epsilon_0 = const()[name = string("rsqrt_114_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_114 = rsqrt(epsilon = rsqrt_114_epsilon_0, x = reduce_mean_114)[name = string("rsqrt_114")];
            tensor<fp16, [16, 960]> mul_534 = mul(x = mul_532, y = rsqrt_114)[name = string("mul_534")];
            tensor<fp16, [960]> mul_535_y_0 = const()[name = string("mul_535_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6033920)))];
            tensor<fp16, [16, 960]> mul_535 = mul(x = mul_534, y = mul_535_y_0)[name = string("mul_535")];
            tensor<fp16, [352, 960]> tern_10_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6035904))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_10_w2_weight_0_palettized")];
            tensor<fp16, [16, 352]> tern_10_w2 = linear(bias = linear_0_bias_0, weight = tern_10_w2_weight_0_palettized, x = mul_535)[name = string("tern_10_w2")];
            tensor<fp16, [352]> mul_536_y_0 = const()[name = string("mul_536_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6120448)))];
            tensor<fp16, [16, 352]> mul_536 = mul(x = tern_10_w2, y = mul_536_y_0)[name = string("mul_536")];
            tensor<fp16, [16, 352]> add_65 = add(x = add_63, y = mul_536)[name = string("add_65")];
            tensor<fp16, [16, 352]> mul_537 = mul(x = add_65, y = add_65)[name = string("mul_537")];
            tensor<int32, [1]> reduce_mean_115_axes_0 = const()[name = string("reduce_mean_115_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_115_keep_dims_0 = const()[name = string("reduce_mean_115_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_115 = reduce_mean(axes = reduce_mean_115_axes_0, keep_dims = reduce_mean_115_keep_dims_0, x = mul_537)[name = string("reduce_mean_115")];
            fp32 rsqrt_115_epsilon_0 = const()[name = string("rsqrt_115_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_115 = rsqrt(epsilon = rsqrt_115_epsilon_0, x = reduce_mean_115)[name = string("rsqrt_115")];
            tensor<fp16, [16, 352]> mul_538 = mul(x = add_65, y = rsqrt_115)[name = string("mul_538")];
            tensor<fp16, [352]> mul_539_y_0 = const()[name = string("mul_539_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6121216)))];
            tensor<fp16, [16, 352]> mul_539 = mul(x = mul_538, y = mul_539_y_0)[name = string("mul_539")];
            tensor<fp16, [16, 352]> mul_540 = mul(x = mul_539, y = mul_539)[name = string("mul_540")];
            tensor<int32, [1]> reduce_mean_116_axes_0 = const()[name = string("reduce_mean_116_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_116_keep_dims_0 = const()[name = string("reduce_mean_116_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_116 = reduce_mean(axes = reduce_mean_116_axes_0, keep_dims = reduce_mean_116_keep_dims_0, x = mul_540)[name = string("reduce_mean_116")];
            fp32 rsqrt_116_epsilon_0 = const()[name = string("rsqrt_116_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_116 = rsqrt(epsilon = rsqrt_116_epsilon_0, x = reduce_mean_116)[name = string("rsqrt_116")];
            tensor<fp16, [16, 352]> mul_541 = mul(x = mul_539, y = rsqrt_116)[name = string("mul_541")];
            tensor<fp16, [352]> mul_542_y_0 = const()[name = string("mul_542_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6121984)))];
            tensor<fp16, [16, 352]> mul_542 = mul(x = mul_541, y = mul_542_y_0)[name = string("mul_542")];
            tensor<fp16, [352, 352]> tern_11_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6122752))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_11_q_weight_0_palettized")];
            tensor<fp16, [16, 352]> tern_11_q = linear(bias = linear_0_bias_0, weight = tern_11_q_weight_0_palettized, x = mul_542)[name = string("tern_11_q")];
            tensor<fp16, [352]> mul_543_y_0 = const()[name = string("mul_543_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6153792)))];
            tensor<fp16, [16, 352]> mul_543 = mul(x = tern_11_q, y = mul_543_y_0)[name = string("mul_543")];
            tensor<int32, [3]> reshape_90_shape_0 = const()[name = string("reshape_90_shape_0"), val = tensor<int32, [3]>([16, 8, 44])];
            tensor<fp16, [16, 8, 44]> reshape_90 = reshape(shape = reshape_90_shape_0, x = mul_543)[name = string("reshape_90")];
            tensor<int32, [3]> transpose_44_perm_0 = const()[name = string("transpose_44_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_546_y_0 = const()[name = string("mul_546_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6154560)))];
            tensor<fp16, [16, 352]> mul_546 = mul(x = mul_541, y = mul_546_y_0)[name = string("mul_546")];
            tensor<fp16, [88, 352]> tern_11_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6155328))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_11_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_11_k_bias_0 = const()[name = string("tern_11_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [16, 88]> tern_11_k = linear(bias = tern_11_k_bias_0, weight = tern_11_k_weight_0_palettized, x = mul_546)[name = string("tern_11_k")];
            tensor<fp16, [88]> mul_547_y_0 = const()[name = string("mul_547_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6163136)))];
            tensor<fp16, [16, 88]> mul_547 = mul(x = tern_11_k, y = mul_547_y_0)[name = string("mul_547")];
            tensor<int32, [3]> reshape_91_shape_0 = const()[name = string("reshape_91_shape_0"), val = tensor<int32, [3]>([16, 2, 44])];
            tensor<fp16, [16, 2, 44]> reshape_91 = reshape(shape = reshape_91_shape_0, x = mul_547)[name = string("reshape_91")];
            tensor<int32, [3]> transpose_45_perm_0 = const()[name = string("transpose_45_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_550_y_0 = const()[name = string("mul_550_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6163392)))];
            tensor<fp16, [16, 352]> mul_550 = mul(x = mul_541, y = mul_550_y_0)[name = string("mul_550")];
            tensor<fp16, [88, 352]> tern_11_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6164160))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_11_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_11_v_bias_0 = const()[name = string("tern_11_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [16, 88]> tern_11_v = linear(bias = tern_11_v_bias_0, weight = tern_11_v_weight_0_palettized, x = mul_550)[name = string("tern_11_v")];
            tensor<fp16, [88]> mul_551_y_0 = const()[name = string("mul_551_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6171968)))];
            tensor<fp16, [16, 88]> mul_551 = mul(x = tern_11_v, y = mul_551_y_0)[name = string("mul_551")];
            tensor<int32, [3]> reshape_92_shape_0 = const()[name = string("reshape_92_shape_0"), val = tensor<int32, [3]>([16, 2, 44])];
            tensor<fp16, [16, 2, 44]> reshape_92 = reshape(shape = reshape_92_shape_0, x = mul_551)[name = string("reshape_92")];
            tensor<int32, [3]> transpose_46_perm_0 = const()[name = string("transpose_46_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 16, 44]> transpose_44 = transpose(perm = transpose_44_perm_0, x = reshape_90)[name = string("transpose_19")];
            tensor<fp16, [8, 16, 44]> mul_552 = mul(x = transpose_44, y = transpose_44)[name = string("mul_552")];
            tensor<int32, [1]> reduce_mean_119_axes_0 = const()[name = string("reduce_mean_119_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_119_keep_dims_0 = const()[name = string("reduce_mean_119_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 16, 1]> reduce_mean_119 = reduce_mean(axes = reduce_mean_119_axes_0, keep_dims = reduce_mean_119_keep_dims_0, x = mul_552)[name = string("reduce_mean_119")];
            fp32 rsqrt_119_epsilon_0 = const()[name = string("rsqrt_119_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 16, 1]> rsqrt_119 = rsqrt(epsilon = rsqrt_119_epsilon_0, x = reduce_mean_119)[name = string("rsqrt_119")];
            tensor<fp16, [8, 16, 44]> mul_553 = mul(x = transpose_44, y = rsqrt_119)[name = string("mul_553")];
            tensor<fp16, [44]> mul_554_y_0 = const()[name = string("mul_554_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6172224)))];
            tensor<fp16, [8, 16, 44]> mul_554 = mul(x = mul_553, y = mul_554_y_0)[name = string("mul_554")];
            tensor<int32, [3]> slice_by_index_44_begin_0 = const()[name = string("slice_by_index_44_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_44_end_0 = const()[name = string("slice_by_index_44_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_44_end_mask_0 = const()[name = string("slice_by_index_44_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 16, 22]> slice_by_index_44 = slice_by_index(begin = slice_by_index_44_begin_0, end = slice_by_index_44_end_0, end_mask = slice_by_index_44_end_mask_0, x = mul_554)[name = string("slice_by_index_44")];
            tensor<int32, [3]> slice_by_index_45_begin_0 = const()[name = string("slice_by_index_45_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_45_end_0 = const()[name = string("slice_by_index_45_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_45_end_mask_0 = const()[name = string("slice_by_index_45_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 16, 22]> slice_by_index_45 = slice_by_index(begin = slice_by_index_45_begin_0, end = slice_by_index_45_end_0, end_mask = slice_by_index_45_end_mask_0, x = mul_554)[name = string("slice_by_index_45")];
            int32 concat_22_axis_0 = const()[name = string("concat_22_axis_0"), val = int32(-1)];
            bool concat_22_interleave_0 = const()[name = string("concat_22_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 16, 44]> concat_22 = concat(axis = concat_22_axis_0, interleave = concat_22_interleave_0, values = (slice_by_index_45, slice_by_index_44))[name = string("concat_22")];
            tensor<fp16, [44]> mul_555_y_0 = const()[name = string("mul_555_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 16, 44]> mul_555 = mul(x = concat_22, y = mul_555_y_0)[name = string("mul_555")];
            tensor<fp16, [8, 16, 44]> mul_556 = mul(x = mul_554, y = mul_11_y_0)[name = string("mul_556")];
            tensor<fp16, [8, 16, 44]> mul_557 = mul(x = mul_555, y = mul_12_y_0)[name = string("mul_557")];
            tensor<fp16, [8, 16, 44]> add_66 = add(x = mul_556, y = mul_557)[name = string("add_66")];
            tensor<fp16, [2, 16, 44]> transpose_45 = transpose(perm = transpose_45_perm_0, x = reshape_91)[name = string("transpose_18")];
            tensor<fp16, [2, 16, 44]> mul_558 = mul(x = transpose_45, y = transpose_45)[name = string("mul_558")];
            tensor<int32, [1]> reduce_mean_120_axes_0 = const()[name = string("reduce_mean_120_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_120_keep_dims_0 = const()[name = string("reduce_mean_120_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 16, 1]> reduce_mean_120 = reduce_mean(axes = reduce_mean_120_axes_0, keep_dims = reduce_mean_120_keep_dims_0, x = mul_558)[name = string("reduce_mean_120")];
            fp32 rsqrt_120_epsilon_0 = const()[name = string("rsqrt_120_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 16, 1]> rsqrt_120 = rsqrt(epsilon = rsqrt_120_epsilon_0, x = reduce_mean_120)[name = string("rsqrt_120")];
            tensor<fp16, [2, 16, 44]> mul_559 = mul(x = transpose_45, y = rsqrt_120)[name = string("mul_559")];
            tensor<fp16, [44]> mul_560_y_0 = const()[name = string("mul_560_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6172416)))];
            tensor<fp16, [2, 16, 44]> mul_560 = mul(x = mul_559, y = mul_560_y_0)[name = string("mul_560")];
            tensor<int32, [3]> slice_by_index_46_begin_0 = const()[name = string("slice_by_index_46_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_46_end_0 = const()[name = string("slice_by_index_46_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_46_end_mask_0 = const()[name = string("slice_by_index_46_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 16, 22]> slice_by_index_46 = slice_by_index(begin = slice_by_index_46_begin_0, end = slice_by_index_46_end_0, end_mask = slice_by_index_46_end_mask_0, x = mul_560)[name = string("slice_by_index_46")];
            tensor<int32, [3]> slice_by_index_47_begin_0 = const()[name = string("slice_by_index_47_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_47_end_0 = const()[name = string("slice_by_index_47_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_47_end_mask_0 = const()[name = string("slice_by_index_47_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 16, 22]> slice_by_index_47 = slice_by_index(begin = slice_by_index_47_begin_0, end = slice_by_index_47_end_0, end_mask = slice_by_index_47_end_mask_0, x = mul_560)[name = string("slice_by_index_47")];
            int32 concat_23_axis_0 = const()[name = string("concat_23_axis_0"), val = int32(-1)];
            bool concat_23_interleave_0 = const()[name = string("concat_23_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 16, 44]> concat_23 = concat(axis = concat_23_axis_0, interleave = concat_23_interleave_0, values = (slice_by_index_47, slice_by_index_46))[name = string("concat_23")];
            tensor<fp16, [44]> mul_561_y_0 = const()[name = string("mul_561_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 16, 44]> mul_561 = mul(x = concat_23, y = mul_561_y_0)[name = string("mul_561")];
            tensor<fp16, [2, 16, 44]> mul_562 = mul(x = mul_560, y = mul_11_y_0)[name = string("mul_562")];
            tensor<fp16, [2, 16, 44]> mul_563 = mul(x = mul_561, y = mul_12_y_0)[name = string("mul_563")];
            tensor<fp16, [2, 16, 44]> add_67 = add(x = mul_562, y = mul_563)[name = string("add_67")];
            tensor<int32, [4]> reshape_93_shape_0 = const()[name = string("reshape_93_shape_0"), val = tensor<int32, [4]>([2, 1, 16, 44])];
            tensor<fp16, [2, 1, 16, 44]> reshape_93 = reshape(shape = reshape_93_shape_0, x = add_67)[name = string("reshape_93")];
            tensor<int32, [4]> tile_22_reps_0 = const()[name = string("tile_22_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 16, 44]> tile_22 = tile(reps = tile_22_reps_0, x = reshape_93)[name = string("tile_22")];
            tensor<int32, [3]> reshape_94_shape_0 = const()[name = string("reshape_94_shape_0"), val = tensor<int32, [3]>([8, 16, 44])];
            tensor<fp16, [8, 16, 44]> reshape_94 = reshape(shape = reshape_94_shape_0, x = tile_22)[name = string("reshape_94")];
            tensor<int32, [4]> reshape_95_shape_0 = const()[name = string("reshape_95_shape_0"), val = tensor<int32, [4]>([2, 1, 16, 44])];
            tensor<fp16, [2, 16, 44]> transpose_46 = transpose(perm = transpose_46_perm_0, x = reshape_92)[name = string("transpose_17")];
            tensor<fp16, [2, 1, 16, 44]> reshape_95 = reshape(shape = reshape_95_shape_0, x = transpose_46)[name = string("reshape_95")];
            tensor<int32, [4]> tile_23_reps_0 = const()[name = string("tile_23_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 16, 44]> tile_23 = tile(reps = tile_23_reps_0, x = reshape_95)[name = string("tile_23")];
            tensor<int32, [3]> reshape_96_shape_0 = const()[name = string("reshape_96_shape_0"), val = tensor<int32, [3]>([8, 16, 44])];
            tensor<fp16, [8, 16, 44]> reshape_96 = reshape(shape = reshape_96_shape_0, x = tile_23)[name = string("reshape_96")];
            fp16 mul_564_y_0 = const()[name = string("mul_564_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 16, 44]> mul_564 = mul(x = add_66, y = mul_564_y_0)[name = string("mul_564")];
            bool matmul_22_transpose_y_0 = const()[name = string("matmul_22_transpose_y_0"), val = bool(true)];
            bool matmul_22_transpose_x_0 = const()[name = string("matmul_22_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 16, 16]> matmul_22 = matmul(transpose_x = matmul_22_transpose_x_0, transpose_y = matmul_22_transpose_y_0, x = mul_564, y = reshape_94)[name = string("matmul_22")];
            tensor<fp16, [8, 16, 16]> add_68 = add(x = matmul_22, y = reshape_1)[name = string("add_68")];
            int32 softmax_11_axis_0 = const()[name = string("softmax_11_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 16, 16]> softmax_11 = softmax(axis = softmax_11_axis_0, x = add_68)[name = string("softmax_11")];
            bool matmul_23_transpose_x_0 = const()[name = string("matmul_23_transpose_x_0"), val = bool(false)];
            bool matmul_23_transpose_y_0 = const()[name = string("matmul_23_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 16, 44]> matmul_23 = matmul(transpose_x = matmul_23_transpose_x_0, transpose_y = matmul_23_transpose_y_0, x = softmax_11, y = reshape_96)[name = string("matmul_23")];
            tensor<int32, [3]> transpose_47_perm_0 = const()[name = string("transpose_47_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_97_shape_0 = const()[name = string("reshape_97_shape_0"), val = tensor<int32, [2]>([16, 352])];
            tensor<fp16, [16, 8, 44]> transpose_47 = transpose(perm = transpose_47_perm_0, x = matmul_23)[name = string("transpose_16")];
            tensor<fp16, [16, 352]> reshape_97 = reshape(shape = reshape_97_shape_0, x = transpose_47)[name = string("reshape_97")];
            tensor<fp16, [16, 352]> mul_565 = mul(x = reshape_97, y = reshape_97)[name = string("mul_565")];
            tensor<int32, [1]> reduce_mean_121_axes_0 = const()[name = string("reduce_mean_121_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_121_keep_dims_0 = const()[name = string("reduce_mean_121_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_121 = reduce_mean(axes = reduce_mean_121_axes_0, keep_dims = reduce_mean_121_keep_dims_0, x = mul_565)[name = string("reduce_mean_121")];
            fp32 rsqrt_121_epsilon_0 = const()[name = string("rsqrt_121_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_121 = rsqrt(epsilon = rsqrt_121_epsilon_0, x = reduce_mean_121)[name = string("rsqrt_121")];
            tensor<fp16, [16, 352]> mul_566 = mul(x = reshape_97, y = rsqrt_121)[name = string("mul_566")];
            tensor<fp16, [352]> mul_567_y_0 = const()[name = string("mul_567_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6172608)))];
            tensor<fp16, [16, 352]> mul_567 = mul(x = mul_566, y = mul_567_y_0)[name = string("mul_567")];
            tensor<fp16, [352, 352]> tern_11_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6173376))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_11_o_weight_0_palettized")];
            tensor<fp16, [16, 352]> tern_11_o = linear(bias = linear_0_bias_0, weight = tern_11_o_weight_0_palettized, x = mul_567)[name = string("tern_11_o")];
            tensor<fp16, [352]> mul_568_y_0 = const()[name = string("mul_568_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6204416)))];
            tensor<fp16, [16, 352]> mul_568 = mul(x = tern_11_o, y = mul_568_y_0)[name = string("mul_568")];
            tensor<fp16, [16, 352]> add_69 = add(x = add_65, y = mul_568)[name = string("add_69")];
            tensor<fp16, [16, 352]> mul_569 = mul(x = add_69, y = add_69)[name = string("mul_569")];
            tensor<int32, [1]> reduce_mean_122_axes_0 = const()[name = string("reduce_mean_122_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_122_keep_dims_0 = const()[name = string("reduce_mean_122_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_122 = reduce_mean(axes = reduce_mean_122_axes_0, keep_dims = reduce_mean_122_keep_dims_0, x = mul_569)[name = string("reduce_mean_122")];
            fp32 rsqrt_122_epsilon_0 = const()[name = string("rsqrt_122_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_122 = rsqrt(epsilon = rsqrt_122_epsilon_0, x = reduce_mean_122)[name = string("rsqrt_122")];
            tensor<fp16, [16, 352]> mul_570 = mul(x = add_69, y = rsqrt_122)[name = string("mul_570")];
            tensor<fp16, [352]> mul_571_y_0 = const()[name = string("mul_571_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6205184)))];
            tensor<fp16, [16, 352]> mul_571 = mul(x = mul_570, y = mul_571_y_0)[name = string("mul_571")];
            tensor<fp16, [16, 352]> mul_572 = mul(x = mul_571, y = mul_571)[name = string("mul_572")];
            tensor<int32, [1]> reduce_mean_123_axes_0 = const()[name = string("reduce_mean_123_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_123_keep_dims_0 = const()[name = string("reduce_mean_123_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_123 = reduce_mean(axes = reduce_mean_123_axes_0, keep_dims = reduce_mean_123_keep_dims_0, x = mul_572)[name = string("reduce_mean_123")];
            fp32 rsqrt_123_epsilon_0 = const()[name = string("rsqrt_123_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_123 = rsqrt(epsilon = rsqrt_123_epsilon_0, x = reduce_mean_123)[name = string("rsqrt_123")];
            tensor<fp16, [16, 352]> mul_573 = mul(x = mul_571, y = rsqrt_123)[name = string("mul_573")];
            tensor<fp16, [352]> mul_574_y_0 = const()[name = string("mul_574_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6205952)))];
            tensor<fp16, [16, 352]> mul_574 = mul(x = mul_573, y = mul_574_y_0)[name = string("mul_574")];
            tensor<fp16, [960, 352]> tern_11_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6206720))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_11_w1_weight_0_palettized")];
            tensor<fp16, [16, 960]> tern_11_w1 = linear(bias = linear_4_bias_0, weight = tern_11_w1_weight_0_palettized, x = mul_574)[name = string("tern_11_w1")];
            tensor<fp16, [960]> mul_575_y_0 = const()[name = string("mul_575_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6291264)))];
            tensor<fp16, [16, 960]> mul_575 = mul(x = tern_11_w1, y = mul_575_y_0)[name = string("mul_575")];
            tensor<fp16, [352]> mul_578_y_0 = const()[name = string("mul_578_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6293248)))];
            tensor<fp16, [16, 352]> mul_578 = mul(x = mul_573, y = mul_578_y_0)[name = string("mul_578")];
            tensor<fp16, [960, 352]> tern_11_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6294016))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_11_w3_weight_0_palettized")];
            tensor<fp16, [16, 960]> tern_11_w3 = linear(bias = linear_4_bias_0, weight = tern_11_w3_weight_0_palettized, x = mul_578)[name = string("tern_11_w3")];
            tensor<fp16, [960]> mul_579_y_0 = const()[name = string("mul_579_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6378560)))];
            tensor<fp16, [16, 960]> mul_579 = mul(x = tern_11_w3, y = mul_579_y_0)[name = string("mul_579")];
            fp16 mul_580_y_0 = const()[name = string("mul_580_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [16, 960]> mul_580 = mul(x = mul_575, y = mul_580_y_0)[name = string("mul_580")];
            tensor<fp16, [16, 960]> tanh_11 = tanh(x = mul_580)[name = string("tanh_11")];
            fp16 mul_581_x_0 = const()[name = string("mul_581_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [16, 960]> mul_581 = mul(x = mul_581_x_0, y = tanh_11)[name = string("mul_581")];
            fp16 add_70_x_0 = const()[name = string("add_70_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [16, 960]> add_70 = add(x = add_70_x_0, y = mul_581)[name = string("add_70")];
            tensor<fp16, [16, 960]> mul_582 = mul(x = mul_575, y = add_70)[name = string("mul_582")];
            tensor<fp16, [16, 960]> mul_583 = mul(x = mul_582, y = mul_579)[name = string("mul_583")];
            tensor<fp16, [16, 960]> mul_584 = mul(x = mul_583, y = mul_583)[name = string("mul_584")];
            tensor<int32, [1]> reduce_mean_125_axes_0 = const()[name = string("reduce_mean_125_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_125_keep_dims_0 = const()[name = string("reduce_mean_125_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_125 = reduce_mean(axes = reduce_mean_125_axes_0, keep_dims = reduce_mean_125_keep_dims_0, x = mul_584)[name = string("reduce_mean_125")];
            fp32 rsqrt_125_epsilon_0 = const()[name = string("rsqrt_125_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_125 = rsqrt(epsilon = rsqrt_125_epsilon_0, x = reduce_mean_125)[name = string("rsqrt_125")];
            tensor<fp16, [16, 960]> mul_585 = mul(x = mul_583, y = rsqrt_125)[name = string("mul_585")];
            tensor<fp16, [960]> mul_586_y_0 = const()[name = string("mul_586_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6380544)))];
            tensor<fp16, [16, 960]> mul_586 = mul(x = mul_585, y = mul_586_y_0)[name = string("mul_586")];
            tensor<fp16, [352, 960]> tern_11_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6382528))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_11_w2_weight_0_palettized")];
            tensor<fp16, [16, 352]> tern_11_w2 = linear(bias = linear_0_bias_0, weight = tern_11_w2_weight_0_palettized, x = mul_586)[name = string("tern_11_w2")];
            tensor<fp16, [352]> mul_587_y_0 = const()[name = string("mul_587_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6467072)))];
            tensor<fp16, [16, 352]> mul_587 = mul(x = tern_11_w2, y = mul_587_y_0)[name = string("mul_587")];
            tensor<fp16, [16, 352]> add_71 = add(x = add_69, y = mul_587)[name = string("add_71")];
            tensor<fp16, [16, 352]> mul_588 = mul(x = add_71, y = add_71)[name = string("mul_588")];
            tensor<int32, [1]> reduce_mean_126_axes_0 = const()[name = string("reduce_mean_126_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_126_keep_dims_0 = const()[name = string("reduce_mean_126_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_126 = reduce_mean(axes = reduce_mean_126_axes_0, keep_dims = reduce_mean_126_keep_dims_0, x = mul_588)[name = string("reduce_mean_126")];
            fp32 rsqrt_126_epsilon_0 = const()[name = string("rsqrt_126_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_126 = rsqrt(epsilon = rsqrt_126_epsilon_0, x = reduce_mean_126)[name = string("rsqrt_126")];
            tensor<fp16, [16, 352]> mul_589 = mul(x = add_71, y = rsqrt_126)[name = string("mul_589")];
            tensor<fp16, [352]> mul_590_y_0 = const()[name = string("mul_590_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6467840)))];
            tensor<fp16, [16, 352]> mul_590 = mul(x = mul_589, y = mul_590_y_0)[name = string("mul_590")];
            tensor<fp16, [16, 352]> mul_591 = mul(x = mul_590, y = mul_590)[name = string("mul_591")];
            tensor<int32, [1]> reduce_mean_127_axes_0 = const()[name = string("reduce_mean_127_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_127_keep_dims_0 = const()[name = string("reduce_mean_127_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_127 = reduce_mean(axes = reduce_mean_127_axes_0, keep_dims = reduce_mean_127_keep_dims_0, x = mul_591)[name = string("reduce_mean_127")];
            fp32 rsqrt_127_epsilon_0 = const()[name = string("rsqrt_127_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_127 = rsqrt(epsilon = rsqrt_127_epsilon_0, x = reduce_mean_127)[name = string("rsqrt_127")];
            tensor<fp16, [16, 352]> mul_592 = mul(x = mul_590, y = rsqrt_127)[name = string("mul_592")];
            tensor<fp16, [352]> mul_593_y_0 = const()[name = string("mul_593_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6468608)))];
            tensor<fp16, [16, 352]> mul_593 = mul(x = mul_592, y = mul_593_y_0)[name = string("mul_593")];
            tensor<fp16, [352, 352]> tern_12_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6469376))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_12_q_weight_0_palettized")];
            tensor<fp16, [16, 352]> tern_12_q = linear(bias = linear_0_bias_0, weight = tern_12_q_weight_0_palettized, x = mul_593)[name = string("tern_12_q")];
            tensor<fp16, [352]> mul_594_y_0 = const()[name = string("mul_594_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6500416)))];
            tensor<fp16, [16, 352]> mul_594 = mul(x = tern_12_q, y = mul_594_y_0)[name = string("mul_594")];
            tensor<int32, [3]> reshape_98_shape_0 = const()[name = string("reshape_98_shape_0"), val = tensor<int32, [3]>([16, 8, 44])];
            tensor<fp16, [16, 8, 44]> reshape_98 = reshape(shape = reshape_98_shape_0, x = mul_594)[name = string("reshape_98")];
            tensor<int32, [3]> transpose_48_perm_0 = const()[name = string("transpose_48_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_597_y_0 = const()[name = string("mul_597_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6501184)))];
            tensor<fp16, [16, 352]> mul_597 = mul(x = mul_592, y = mul_597_y_0)[name = string("mul_597")];
            tensor<fp16, [88, 352]> tern_12_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6501952))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_12_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_12_k_bias_0 = const()[name = string("tern_12_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [16, 88]> tern_12_k = linear(bias = tern_12_k_bias_0, weight = tern_12_k_weight_0_palettized, x = mul_597)[name = string("tern_12_k")];
            tensor<fp16, [88]> mul_598_y_0 = const()[name = string("mul_598_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6509760)))];
            tensor<fp16, [16, 88]> mul_598 = mul(x = tern_12_k, y = mul_598_y_0)[name = string("mul_598")];
            tensor<int32, [3]> reshape_99_shape_0 = const()[name = string("reshape_99_shape_0"), val = tensor<int32, [3]>([16, 2, 44])];
            tensor<fp16, [16, 2, 44]> reshape_99 = reshape(shape = reshape_99_shape_0, x = mul_598)[name = string("reshape_99")];
            tensor<int32, [3]> transpose_49_perm_0 = const()[name = string("transpose_49_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_601_y_0 = const()[name = string("mul_601_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6510016)))];
            tensor<fp16, [16, 352]> mul_601 = mul(x = mul_592, y = mul_601_y_0)[name = string("mul_601")];
            tensor<fp16, [88, 352]> tern_12_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6510784))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_12_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_12_v_bias_0 = const()[name = string("tern_12_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [16, 88]> tern_12_v = linear(bias = tern_12_v_bias_0, weight = tern_12_v_weight_0_palettized, x = mul_601)[name = string("tern_12_v")];
            tensor<fp16, [88]> mul_602_y_0 = const()[name = string("mul_602_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6518592)))];
            tensor<fp16, [16, 88]> mul_602 = mul(x = tern_12_v, y = mul_602_y_0)[name = string("mul_602")];
            tensor<int32, [3]> reshape_100_shape_0 = const()[name = string("reshape_100_shape_0"), val = tensor<int32, [3]>([16, 2, 44])];
            tensor<fp16, [16, 2, 44]> reshape_100 = reshape(shape = reshape_100_shape_0, x = mul_602)[name = string("reshape_100")];
            tensor<int32, [3]> transpose_50_perm_0 = const()[name = string("transpose_50_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 16, 44]> transpose_48 = transpose(perm = transpose_48_perm_0, x = reshape_98)[name = string("transpose_15")];
            tensor<fp16, [8, 16, 44]> mul_603 = mul(x = transpose_48, y = transpose_48)[name = string("mul_603")];
            tensor<int32, [1]> reduce_mean_130_axes_0 = const()[name = string("reduce_mean_130_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_130_keep_dims_0 = const()[name = string("reduce_mean_130_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 16, 1]> reduce_mean_130 = reduce_mean(axes = reduce_mean_130_axes_0, keep_dims = reduce_mean_130_keep_dims_0, x = mul_603)[name = string("reduce_mean_130")];
            fp32 rsqrt_130_epsilon_0 = const()[name = string("rsqrt_130_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 16, 1]> rsqrt_130 = rsqrt(epsilon = rsqrt_130_epsilon_0, x = reduce_mean_130)[name = string("rsqrt_130")];
            tensor<fp16, [8, 16, 44]> mul_604 = mul(x = transpose_48, y = rsqrt_130)[name = string("mul_604")];
            tensor<fp16, [44]> mul_605_y_0 = const()[name = string("mul_605_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6518848)))];
            tensor<fp16, [8, 16, 44]> mul_605 = mul(x = mul_604, y = mul_605_y_0)[name = string("mul_605")];
            tensor<int32, [3]> slice_by_index_48_begin_0 = const()[name = string("slice_by_index_48_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_48_end_0 = const()[name = string("slice_by_index_48_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_48_end_mask_0 = const()[name = string("slice_by_index_48_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 16, 22]> slice_by_index_48 = slice_by_index(begin = slice_by_index_48_begin_0, end = slice_by_index_48_end_0, end_mask = slice_by_index_48_end_mask_0, x = mul_605)[name = string("slice_by_index_48")];
            tensor<int32, [3]> slice_by_index_49_begin_0 = const()[name = string("slice_by_index_49_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_49_end_0 = const()[name = string("slice_by_index_49_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_49_end_mask_0 = const()[name = string("slice_by_index_49_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 16, 22]> slice_by_index_49 = slice_by_index(begin = slice_by_index_49_begin_0, end = slice_by_index_49_end_0, end_mask = slice_by_index_49_end_mask_0, x = mul_605)[name = string("slice_by_index_49")];
            int32 concat_24_axis_0 = const()[name = string("concat_24_axis_0"), val = int32(-1)];
            bool concat_24_interleave_0 = const()[name = string("concat_24_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 16, 44]> concat_24 = concat(axis = concat_24_axis_0, interleave = concat_24_interleave_0, values = (slice_by_index_49, slice_by_index_48))[name = string("concat_24")];
            tensor<fp16, [44]> mul_606_y_0 = const()[name = string("mul_606_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 16, 44]> mul_606 = mul(x = concat_24, y = mul_606_y_0)[name = string("mul_606")];
            tensor<fp16, [8, 16, 44]> mul_607 = mul(x = mul_605, y = mul_11_y_0)[name = string("mul_607")];
            tensor<fp16, [8, 16, 44]> mul_608 = mul(x = mul_606, y = mul_12_y_0)[name = string("mul_608")];
            tensor<fp16, [8, 16, 44]> add_72 = add(x = mul_607, y = mul_608)[name = string("add_72")];
            tensor<fp16, [2, 16, 44]> transpose_49 = transpose(perm = transpose_49_perm_0, x = reshape_99)[name = string("transpose_14")];
            tensor<fp16, [2, 16, 44]> mul_609 = mul(x = transpose_49, y = transpose_49)[name = string("mul_609")];
            tensor<int32, [1]> reduce_mean_131_axes_0 = const()[name = string("reduce_mean_131_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_131_keep_dims_0 = const()[name = string("reduce_mean_131_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 16, 1]> reduce_mean_131 = reduce_mean(axes = reduce_mean_131_axes_0, keep_dims = reduce_mean_131_keep_dims_0, x = mul_609)[name = string("reduce_mean_131")];
            fp32 rsqrt_131_epsilon_0 = const()[name = string("rsqrt_131_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 16, 1]> rsqrt_131 = rsqrt(epsilon = rsqrt_131_epsilon_0, x = reduce_mean_131)[name = string("rsqrt_131")];
            tensor<fp16, [2, 16, 44]> mul_610 = mul(x = transpose_49, y = rsqrt_131)[name = string("mul_610")];
            tensor<fp16, [44]> mul_611_y_0 = const()[name = string("mul_611_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6519040)))];
            tensor<fp16, [2, 16, 44]> mul_611 = mul(x = mul_610, y = mul_611_y_0)[name = string("mul_611")];
            tensor<int32, [3]> slice_by_index_50_begin_0 = const()[name = string("slice_by_index_50_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_50_end_0 = const()[name = string("slice_by_index_50_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_50_end_mask_0 = const()[name = string("slice_by_index_50_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 16, 22]> slice_by_index_50 = slice_by_index(begin = slice_by_index_50_begin_0, end = slice_by_index_50_end_0, end_mask = slice_by_index_50_end_mask_0, x = mul_611)[name = string("slice_by_index_50")];
            tensor<int32, [3]> slice_by_index_51_begin_0 = const()[name = string("slice_by_index_51_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_51_end_0 = const()[name = string("slice_by_index_51_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_51_end_mask_0 = const()[name = string("slice_by_index_51_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 16, 22]> slice_by_index_51 = slice_by_index(begin = slice_by_index_51_begin_0, end = slice_by_index_51_end_0, end_mask = slice_by_index_51_end_mask_0, x = mul_611)[name = string("slice_by_index_51")];
            int32 concat_25_axis_0 = const()[name = string("concat_25_axis_0"), val = int32(-1)];
            bool concat_25_interleave_0 = const()[name = string("concat_25_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 16, 44]> concat_25 = concat(axis = concat_25_axis_0, interleave = concat_25_interleave_0, values = (slice_by_index_51, slice_by_index_50))[name = string("concat_25")];
            tensor<fp16, [44]> mul_612_y_0 = const()[name = string("mul_612_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 16, 44]> mul_612 = mul(x = concat_25, y = mul_612_y_0)[name = string("mul_612")];
            tensor<fp16, [2, 16, 44]> mul_613 = mul(x = mul_611, y = mul_11_y_0)[name = string("mul_613")];
            tensor<fp16, [2, 16, 44]> mul_614 = mul(x = mul_612, y = mul_12_y_0)[name = string("mul_614")];
            tensor<fp16, [2, 16, 44]> add_73 = add(x = mul_613, y = mul_614)[name = string("add_73")];
            tensor<int32, [4]> reshape_101_shape_0 = const()[name = string("reshape_101_shape_0"), val = tensor<int32, [4]>([2, 1, 16, 44])];
            tensor<fp16, [2, 1, 16, 44]> reshape_101 = reshape(shape = reshape_101_shape_0, x = add_73)[name = string("reshape_101")];
            tensor<int32, [4]> tile_24_reps_0 = const()[name = string("tile_24_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 16, 44]> tile_24 = tile(reps = tile_24_reps_0, x = reshape_101)[name = string("tile_24")];
            tensor<int32, [3]> reshape_102_shape_0 = const()[name = string("reshape_102_shape_0"), val = tensor<int32, [3]>([8, 16, 44])];
            tensor<fp16, [8, 16, 44]> reshape_102 = reshape(shape = reshape_102_shape_0, x = tile_24)[name = string("reshape_102")];
            tensor<int32, [4]> reshape_103_shape_0 = const()[name = string("reshape_103_shape_0"), val = tensor<int32, [4]>([2, 1, 16, 44])];
            tensor<fp16, [2, 16, 44]> transpose_50 = transpose(perm = transpose_50_perm_0, x = reshape_100)[name = string("transpose_13")];
            tensor<fp16, [2, 1, 16, 44]> reshape_103 = reshape(shape = reshape_103_shape_0, x = transpose_50)[name = string("reshape_103")];
            tensor<int32, [4]> tile_25_reps_0 = const()[name = string("tile_25_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 16, 44]> tile_25 = tile(reps = tile_25_reps_0, x = reshape_103)[name = string("tile_25")];
            tensor<int32, [3]> reshape_104_shape_0 = const()[name = string("reshape_104_shape_0"), val = tensor<int32, [3]>([8, 16, 44])];
            tensor<fp16, [8, 16, 44]> reshape_104 = reshape(shape = reshape_104_shape_0, x = tile_25)[name = string("reshape_104")];
            fp16 mul_615_y_0 = const()[name = string("mul_615_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 16, 44]> mul_615 = mul(x = add_72, y = mul_615_y_0)[name = string("mul_615")];
            bool matmul_24_transpose_y_0 = const()[name = string("matmul_24_transpose_y_0"), val = bool(true)];
            bool matmul_24_transpose_x_0 = const()[name = string("matmul_24_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 16, 16]> matmul_24 = matmul(transpose_x = matmul_24_transpose_x_0, transpose_y = matmul_24_transpose_y_0, x = mul_615, y = reshape_102)[name = string("matmul_24")];
            tensor<fp16, [8, 16, 16]> add_74 = add(x = matmul_24, y = reshape_1)[name = string("add_74")];
            int32 softmax_12_axis_0 = const()[name = string("softmax_12_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 16, 16]> softmax_12 = softmax(axis = softmax_12_axis_0, x = add_74)[name = string("softmax_12")];
            bool matmul_25_transpose_x_0 = const()[name = string("matmul_25_transpose_x_0"), val = bool(false)];
            bool matmul_25_transpose_y_0 = const()[name = string("matmul_25_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 16, 44]> matmul_25 = matmul(transpose_x = matmul_25_transpose_x_0, transpose_y = matmul_25_transpose_y_0, x = softmax_12, y = reshape_104)[name = string("matmul_25")];
            tensor<int32, [3]> transpose_51_perm_0 = const()[name = string("transpose_51_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_105_shape_0 = const()[name = string("reshape_105_shape_0"), val = tensor<int32, [2]>([16, 352])];
            tensor<fp16, [16, 8, 44]> transpose_51 = transpose(perm = transpose_51_perm_0, x = matmul_25)[name = string("transpose_12")];
            tensor<fp16, [16, 352]> reshape_105 = reshape(shape = reshape_105_shape_0, x = transpose_51)[name = string("reshape_105")];
            tensor<fp16, [16, 352]> mul_616 = mul(x = reshape_105, y = reshape_105)[name = string("mul_616")];
            tensor<int32, [1]> reduce_mean_132_axes_0 = const()[name = string("reduce_mean_132_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_132_keep_dims_0 = const()[name = string("reduce_mean_132_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_132 = reduce_mean(axes = reduce_mean_132_axes_0, keep_dims = reduce_mean_132_keep_dims_0, x = mul_616)[name = string("reduce_mean_132")];
            fp32 rsqrt_132_epsilon_0 = const()[name = string("rsqrt_132_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_132 = rsqrt(epsilon = rsqrt_132_epsilon_0, x = reduce_mean_132)[name = string("rsqrt_132")];
            tensor<fp16, [16, 352]> mul_617 = mul(x = reshape_105, y = rsqrt_132)[name = string("mul_617")];
            tensor<fp16, [352]> mul_618_y_0 = const()[name = string("mul_618_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6519232)))];
            tensor<fp16, [16, 352]> mul_618 = mul(x = mul_617, y = mul_618_y_0)[name = string("mul_618")];
            tensor<fp16, [352, 352]> tern_12_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6520000))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_12_o_weight_0_palettized")];
            tensor<fp16, [16, 352]> tern_12_o = linear(bias = linear_0_bias_0, weight = tern_12_o_weight_0_palettized, x = mul_618)[name = string("tern_12_o")];
            tensor<fp16, [352]> mul_619_y_0 = const()[name = string("mul_619_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6551040)))];
            tensor<fp16, [16, 352]> mul_619 = mul(x = tern_12_o, y = mul_619_y_0)[name = string("mul_619")];
            tensor<fp16, [16, 352]> add_75 = add(x = add_71, y = mul_619)[name = string("add_75")];
            tensor<fp16, [16, 352]> mul_620 = mul(x = add_75, y = add_75)[name = string("mul_620")];
            tensor<int32, [1]> reduce_mean_133_axes_0 = const()[name = string("reduce_mean_133_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_133_keep_dims_0 = const()[name = string("reduce_mean_133_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_133 = reduce_mean(axes = reduce_mean_133_axes_0, keep_dims = reduce_mean_133_keep_dims_0, x = mul_620)[name = string("reduce_mean_133")];
            fp32 rsqrt_133_epsilon_0 = const()[name = string("rsqrt_133_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_133 = rsqrt(epsilon = rsqrt_133_epsilon_0, x = reduce_mean_133)[name = string("rsqrt_133")];
            tensor<fp16, [16, 352]> mul_621 = mul(x = add_75, y = rsqrt_133)[name = string("mul_621")];
            tensor<fp16, [352]> mul_622_y_0 = const()[name = string("mul_622_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6551808)))];
            tensor<fp16, [16, 352]> mul_622 = mul(x = mul_621, y = mul_622_y_0)[name = string("mul_622")];
            tensor<fp16, [16, 352]> mul_623 = mul(x = mul_622, y = mul_622)[name = string("mul_623")];
            tensor<int32, [1]> reduce_mean_134_axes_0 = const()[name = string("reduce_mean_134_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_134_keep_dims_0 = const()[name = string("reduce_mean_134_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_134 = reduce_mean(axes = reduce_mean_134_axes_0, keep_dims = reduce_mean_134_keep_dims_0, x = mul_623)[name = string("reduce_mean_134")];
            fp32 rsqrt_134_epsilon_0 = const()[name = string("rsqrt_134_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_134 = rsqrt(epsilon = rsqrt_134_epsilon_0, x = reduce_mean_134)[name = string("rsqrt_134")];
            tensor<fp16, [16, 352]> mul_624 = mul(x = mul_622, y = rsqrt_134)[name = string("mul_624")];
            tensor<fp16, [352]> mul_625_y_0 = const()[name = string("mul_625_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6552576)))];
            tensor<fp16, [16, 352]> mul_625 = mul(x = mul_624, y = mul_625_y_0)[name = string("mul_625")];
            tensor<fp16, [960, 352]> tern_12_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6553344))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_12_w1_weight_0_palettized")];
            tensor<fp16, [16, 960]> tern_12_w1 = linear(bias = linear_4_bias_0, weight = tern_12_w1_weight_0_palettized, x = mul_625)[name = string("tern_12_w1")];
            tensor<fp16, [960]> mul_626_y_0 = const()[name = string("mul_626_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6637888)))];
            tensor<fp16, [16, 960]> mul_626 = mul(x = tern_12_w1, y = mul_626_y_0)[name = string("mul_626")];
            tensor<fp16, [352]> mul_629_y_0 = const()[name = string("mul_629_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6639872)))];
            tensor<fp16, [16, 352]> mul_629 = mul(x = mul_624, y = mul_629_y_0)[name = string("mul_629")];
            tensor<fp16, [960, 352]> tern_12_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6640640))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_12_w3_weight_0_palettized")];
            tensor<fp16, [16, 960]> tern_12_w3 = linear(bias = linear_4_bias_0, weight = tern_12_w3_weight_0_palettized, x = mul_629)[name = string("tern_12_w3")];
            tensor<fp16, [960]> mul_630_y_0 = const()[name = string("mul_630_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6725184)))];
            tensor<fp16, [16, 960]> mul_630 = mul(x = tern_12_w3, y = mul_630_y_0)[name = string("mul_630")];
            fp16 mul_631_y_0 = const()[name = string("mul_631_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [16, 960]> mul_631 = mul(x = mul_626, y = mul_631_y_0)[name = string("mul_631")];
            tensor<fp16, [16, 960]> tanh_12 = tanh(x = mul_631)[name = string("tanh_12")];
            fp16 mul_632_x_0 = const()[name = string("mul_632_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [16, 960]> mul_632 = mul(x = mul_632_x_0, y = tanh_12)[name = string("mul_632")];
            fp16 add_76_x_0 = const()[name = string("add_76_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [16, 960]> add_76 = add(x = add_76_x_0, y = mul_632)[name = string("add_76")];
            tensor<fp16, [16, 960]> mul_633 = mul(x = mul_626, y = add_76)[name = string("mul_633")];
            tensor<fp16, [16, 960]> mul_634 = mul(x = mul_633, y = mul_630)[name = string("mul_634")];
            tensor<fp16, [16, 960]> mul_635 = mul(x = mul_634, y = mul_634)[name = string("mul_635")];
            tensor<int32, [1]> reduce_mean_136_axes_0 = const()[name = string("reduce_mean_136_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_136_keep_dims_0 = const()[name = string("reduce_mean_136_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_136 = reduce_mean(axes = reduce_mean_136_axes_0, keep_dims = reduce_mean_136_keep_dims_0, x = mul_635)[name = string("reduce_mean_136")];
            fp32 rsqrt_136_epsilon_0 = const()[name = string("rsqrt_136_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_136 = rsqrt(epsilon = rsqrt_136_epsilon_0, x = reduce_mean_136)[name = string("rsqrt_136")];
            tensor<fp16, [16, 960]> mul_636 = mul(x = mul_634, y = rsqrt_136)[name = string("mul_636")];
            tensor<fp16, [960]> mul_637_y_0 = const()[name = string("mul_637_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6727168)))];
            tensor<fp16, [16, 960]> mul_637 = mul(x = mul_636, y = mul_637_y_0)[name = string("mul_637")];
            tensor<fp16, [352, 960]> tern_12_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6729152))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_12_w2_weight_0_palettized")];
            tensor<fp16, [16, 352]> tern_12_w2 = linear(bias = linear_0_bias_0, weight = tern_12_w2_weight_0_palettized, x = mul_637)[name = string("tern_12_w2")];
            tensor<fp16, [352]> mul_638_y_0 = const()[name = string("mul_638_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6813696)))];
            tensor<fp16, [16, 352]> mul_638 = mul(x = tern_12_w2, y = mul_638_y_0)[name = string("mul_638")];
            tensor<fp16, [16, 352]> add_77 = add(x = add_75, y = mul_638)[name = string("add_77")];
            tensor<fp16, [16, 352]> mul_639 = mul(x = add_77, y = add_77)[name = string("mul_639")];
            tensor<int32, [1]> reduce_mean_137_axes_0 = const()[name = string("reduce_mean_137_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_137_keep_dims_0 = const()[name = string("reduce_mean_137_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_137 = reduce_mean(axes = reduce_mean_137_axes_0, keep_dims = reduce_mean_137_keep_dims_0, x = mul_639)[name = string("reduce_mean_137")];
            fp32 rsqrt_137_epsilon_0 = const()[name = string("rsqrt_137_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_137 = rsqrt(epsilon = rsqrt_137_epsilon_0, x = reduce_mean_137)[name = string("rsqrt_137")];
            tensor<fp16, [16, 352]> mul_640 = mul(x = add_77, y = rsqrt_137)[name = string("mul_640")];
            tensor<fp16, [352]> mul_641_y_0 = const()[name = string("mul_641_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6814464)))];
            tensor<fp16, [16, 352]> mul_641 = mul(x = mul_640, y = mul_641_y_0)[name = string("mul_641")];
            tensor<fp16, [16, 352]> mul_642 = mul(x = mul_641, y = mul_641)[name = string("mul_642")];
            tensor<int32, [1]> reduce_mean_138_axes_0 = const()[name = string("reduce_mean_138_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_138_keep_dims_0 = const()[name = string("reduce_mean_138_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_138 = reduce_mean(axes = reduce_mean_138_axes_0, keep_dims = reduce_mean_138_keep_dims_0, x = mul_642)[name = string("reduce_mean_138")];
            fp32 rsqrt_138_epsilon_0 = const()[name = string("rsqrt_138_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_138 = rsqrt(epsilon = rsqrt_138_epsilon_0, x = reduce_mean_138)[name = string("rsqrt_138")];
            tensor<fp16, [16, 352]> mul_643 = mul(x = mul_641, y = rsqrt_138)[name = string("mul_643")];
            tensor<fp16, [352]> mul_644_y_0 = const()[name = string("mul_644_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6815232)))];
            tensor<fp16, [16, 352]> mul_644 = mul(x = mul_643, y = mul_644_y_0)[name = string("mul_644")];
            tensor<fp16, [352, 352]> tern_13_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6816000))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_13_q_weight_0_palettized")];
            tensor<fp16, [16, 352]> tern_13_q = linear(bias = linear_0_bias_0, weight = tern_13_q_weight_0_palettized, x = mul_644)[name = string("tern_13_q")];
            tensor<fp16, [352]> mul_645_y_0 = const()[name = string("mul_645_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6847040)))];
            tensor<fp16, [16, 352]> mul_645 = mul(x = tern_13_q, y = mul_645_y_0)[name = string("mul_645")];
            tensor<int32, [3]> reshape_106_shape_0 = const()[name = string("reshape_106_shape_0"), val = tensor<int32, [3]>([16, 8, 44])];
            tensor<fp16, [16, 8, 44]> reshape_106 = reshape(shape = reshape_106_shape_0, x = mul_645)[name = string("reshape_106")];
            tensor<int32, [3]> transpose_52_perm_0 = const()[name = string("transpose_52_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_648_y_0 = const()[name = string("mul_648_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6847808)))];
            tensor<fp16, [16, 352]> mul_648 = mul(x = mul_643, y = mul_648_y_0)[name = string("mul_648")];
            tensor<fp16, [88, 352]> tern_13_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6848576))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_13_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_13_k_bias_0 = const()[name = string("tern_13_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [16, 88]> tern_13_k = linear(bias = tern_13_k_bias_0, weight = tern_13_k_weight_0_palettized, x = mul_648)[name = string("tern_13_k")];
            tensor<fp16, [88]> mul_649_y_0 = const()[name = string("mul_649_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6856384)))];
            tensor<fp16, [16, 88]> mul_649 = mul(x = tern_13_k, y = mul_649_y_0)[name = string("mul_649")];
            tensor<int32, [3]> reshape_107_shape_0 = const()[name = string("reshape_107_shape_0"), val = tensor<int32, [3]>([16, 2, 44])];
            tensor<fp16, [16, 2, 44]> reshape_107 = reshape(shape = reshape_107_shape_0, x = mul_649)[name = string("reshape_107")];
            tensor<int32, [3]> transpose_53_perm_0 = const()[name = string("transpose_53_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_652_y_0 = const()[name = string("mul_652_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6856640)))];
            tensor<fp16, [16, 352]> mul_652 = mul(x = mul_643, y = mul_652_y_0)[name = string("mul_652")];
            tensor<fp16, [88, 352]> tern_13_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6857408))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_13_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_13_v_bias_0 = const()[name = string("tern_13_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [16, 88]> tern_13_v = linear(bias = tern_13_v_bias_0, weight = tern_13_v_weight_0_palettized, x = mul_652)[name = string("tern_13_v")];
            tensor<fp16, [88]> mul_653_y_0 = const()[name = string("mul_653_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6865216)))];
            tensor<fp16, [16, 88]> mul_653 = mul(x = tern_13_v, y = mul_653_y_0)[name = string("mul_653")];
            tensor<int32, [3]> reshape_108_shape_0 = const()[name = string("reshape_108_shape_0"), val = tensor<int32, [3]>([16, 2, 44])];
            tensor<fp16, [16, 2, 44]> reshape_108 = reshape(shape = reshape_108_shape_0, x = mul_653)[name = string("reshape_108")];
            tensor<int32, [3]> transpose_54_perm_0 = const()[name = string("transpose_54_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 16, 44]> transpose_52 = transpose(perm = transpose_52_perm_0, x = reshape_106)[name = string("transpose_11")];
            tensor<fp16, [8, 16, 44]> mul_654 = mul(x = transpose_52, y = transpose_52)[name = string("mul_654")];
            tensor<int32, [1]> reduce_mean_141_axes_0 = const()[name = string("reduce_mean_141_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_141_keep_dims_0 = const()[name = string("reduce_mean_141_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 16, 1]> reduce_mean_141 = reduce_mean(axes = reduce_mean_141_axes_0, keep_dims = reduce_mean_141_keep_dims_0, x = mul_654)[name = string("reduce_mean_141")];
            fp32 rsqrt_141_epsilon_0 = const()[name = string("rsqrt_141_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 16, 1]> rsqrt_141 = rsqrt(epsilon = rsqrt_141_epsilon_0, x = reduce_mean_141)[name = string("rsqrt_141")];
            tensor<fp16, [8, 16, 44]> mul_655 = mul(x = transpose_52, y = rsqrt_141)[name = string("mul_655")];
            tensor<fp16, [44]> mul_656_y_0 = const()[name = string("mul_656_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6865472)))];
            tensor<fp16, [8, 16, 44]> mul_656 = mul(x = mul_655, y = mul_656_y_0)[name = string("mul_656")];
            tensor<int32, [3]> slice_by_index_52_begin_0 = const()[name = string("slice_by_index_52_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_52_end_0 = const()[name = string("slice_by_index_52_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_52_end_mask_0 = const()[name = string("slice_by_index_52_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 16, 22]> slice_by_index_52 = slice_by_index(begin = slice_by_index_52_begin_0, end = slice_by_index_52_end_0, end_mask = slice_by_index_52_end_mask_0, x = mul_656)[name = string("slice_by_index_52")];
            tensor<int32, [3]> slice_by_index_53_begin_0 = const()[name = string("slice_by_index_53_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_53_end_0 = const()[name = string("slice_by_index_53_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_53_end_mask_0 = const()[name = string("slice_by_index_53_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 16, 22]> slice_by_index_53 = slice_by_index(begin = slice_by_index_53_begin_0, end = slice_by_index_53_end_0, end_mask = slice_by_index_53_end_mask_0, x = mul_656)[name = string("slice_by_index_53")];
            int32 concat_26_axis_0 = const()[name = string("concat_26_axis_0"), val = int32(-1)];
            bool concat_26_interleave_0 = const()[name = string("concat_26_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 16, 44]> concat_26 = concat(axis = concat_26_axis_0, interleave = concat_26_interleave_0, values = (slice_by_index_53, slice_by_index_52))[name = string("concat_26")];
            tensor<fp16, [44]> mul_657_y_0 = const()[name = string("mul_657_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 16, 44]> mul_657 = mul(x = concat_26, y = mul_657_y_0)[name = string("mul_657")];
            tensor<fp16, [8, 16, 44]> mul_658 = mul(x = mul_656, y = mul_11_y_0)[name = string("mul_658")];
            tensor<fp16, [8, 16, 44]> mul_659 = mul(x = mul_657, y = mul_12_y_0)[name = string("mul_659")];
            tensor<fp16, [8, 16, 44]> add_78 = add(x = mul_658, y = mul_659)[name = string("add_78")];
            tensor<fp16, [2, 16, 44]> transpose_53 = transpose(perm = transpose_53_perm_0, x = reshape_107)[name = string("transpose_10")];
            tensor<fp16, [2, 16, 44]> mul_660 = mul(x = transpose_53, y = transpose_53)[name = string("mul_660")];
            tensor<int32, [1]> reduce_mean_142_axes_0 = const()[name = string("reduce_mean_142_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_142_keep_dims_0 = const()[name = string("reduce_mean_142_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 16, 1]> reduce_mean_142 = reduce_mean(axes = reduce_mean_142_axes_0, keep_dims = reduce_mean_142_keep_dims_0, x = mul_660)[name = string("reduce_mean_142")];
            fp32 rsqrt_142_epsilon_0 = const()[name = string("rsqrt_142_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 16, 1]> rsqrt_142 = rsqrt(epsilon = rsqrt_142_epsilon_0, x = reduce_mean_142)[name = string("rsqrt_142")];
            tensor<fp16, [2, 16, 44]> mul_661 = mul(x = transpose_53, y = rsqrt_142)[name = string("mul_661")];
            tensor<fp16, [44]> mul_662_y_0 = const()[name = string("mul_662_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6865664)))];
            tensor<fp16, [2, 16, 44]> mul_662 = mul(x = mul_661, y = mul_662_y_0)[name = string("mul_662")];
            tensor<int32, [3]> slice_by_index_54_begin_0 = const()[name = string("slice_by_index_54_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_54_end_0 = const()[name = string("slice_by_index_54_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_54_end_mask_0 = const()[name = string("slice_by_index_54_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 16, 22]> slice_by_index_54 = slice_by_index(begin = slice_by_index_54_begin_0, end = slice_by_index_54_end_0, end_mask = slice_by_index_54_end_mask_0, x = mul_662)[name = string("slice_by_index_54")];
            tensor<int32, [3]> slice_by_index_55_begin_0 = const()[name = string("slice_by_index_55_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_55_end_0 = const()[name = string("slice_by_index_55_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_55_end_mask_0 = const()[name = string("slice_by_index_55_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 16, 22]> slice_by_index_55 = slice_by_index(begin = slice_by_index_55_begin_0, end = slice_by_index_55_end_0, end_mask = slice_by_index_55_end_mask_0, x = mul_662)[name = string("slice_by_index_55")];
            int32 concat_27_axis_0 = const()[name = string("concat_27_axis_0"), val = int32(-1)];
            bool concat_27_interleave_0 = const()[name = string("concat_27_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 16, 44]> concat_27 = concat(axis = concat_27_axis_0, interleave = concat_27_interleave_0, values = (slice_by_index_55, slice_by_index_54))[name = string("concat_27")];
            tensor<fp16, [44]> mul_663_y_0 = const()[name = string("mul_663_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 16, 44]> mul_663 = mul(x = concat_27, y = mul_663_y_0)[name = string("mul_663")];
            tensor<fp16, [2, 16, 44]> mul_664 = mul(x = mul_662, y = mul_11_y_0)[name = string("mul_664")];
            tensor<fp16, [2, 16, 44]> mul_665 = mul(x = mul_663, y = mul_12_y_0)[name = string("mul_665")];
            tensor<fp16, [2, 16, 44]> add_79 = add(x = mul_664, y = mul_665)[name = string("add_79")];
            tensor<int32, [4]> reshape_109_shape_0 = const()[name = string("reshape_109_shape_0"), val = tensor<int32, [4]>([2, 1, 16, 44])];
            tensor<fp16, [2, 1, 16, 44]> reshape_109 = reshape(shape = reshape_109_shape_0, x = add_79)[name = string("reshape_109")];
            tensor<int32, [4]> tile_26_reps_0 = const()[name = string("tile_26_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 16, 44]> tile_26 = tile(reps = tile_26_reps_0, x = reshape_109)[name = string("tile_26")];
            tensor<int32, [3]> reshape_110_shape_0 = const()[name = string("reshape_110_shape_0"), val = tensor<int32, [3]>([8, 16, 44])];
            tensor<fp16, [8, 16, 44]> reshape_110 = reshape(shape = reshape_110_shape_0, x = tile_26)[name = string("reshape_110")];
            tensor<int32, [4]> reshape_111_shape_0 = const()[name = string("reshape_111_shape_0"), val = tensor<int32, [4]>([2, 1, 16, 44])];
            tensor<fp16, [2, 16, 44]> transpose_54 = transpose(perm = transpose_54_perm_0, x = reshape_108)[name = string("transpose_9")];
            tensor<fp16, [2, 1, 16, 44]> reshape_111 = reshape(shape = reshape_111_shape_0, x = transpose_54)[name = string("reshape_111")];
            tensor<int32, [4]> tile_27_reps_0 = const()[name = string("tile_27_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 16, 44]> tile_27 = tile(reps = tile_27_reps_0, x = reshape_111)[name = string("tile_27")];
            tensor<int32, [3]> reshape_112_shape_0 = const()[name = string("reshape_112_shape_0"), val = tensor<int32, [3]>([8, 16, 44])];
            tensor<fp16, [8, 16, 44]> reshape_112 = reshape(shape = reshape_112_shape_0, x = tile_27)[name = string("reshape_112")];
            fp16 mul_666_y_0 = const()[name = string("mul_666_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 16, 44]> mul_666 = mul(x = add_78, y = mul_666_y_0)[name = string("mul_666")];
            bool matmul_26_transpose_y_0 = const()[name = string("matmul_26_transpose_y_0"), val = bool(true)];
            bool matmul_26_transpose_x_0 = const()[name = string("matmul_26_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 16, 16]> matmul_26 = matmul(transpose_x = matmul_26_transpose_x_0, transpose_y = matmul_26_transpose_y_0, x = mul_666, y = reshape_110)[name = string("matmul_26")];
            tensor<fp16, [8, 16, 16]> add_80 = add(x = matmul_26, y = reshape_1)[name = string("add_80")];
            int32 softmax_13_axis_0 = const()[name = string("softmax_13_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 16, 16]> softmax_13 = softmax(axis = softmax_13_axis_0, x = add_80)[name = string("softmax_13")];
            bool matmul_27_transpose_x_0 = const()[name = string("matmul_27_transpose_x_0"), val = bool(false)];
            bool matmul_27_transpose_y_0 = const()[name = string("matmul_27_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 16, 44]> matmul_27 = matmul(transpose_x = matmul_27_transpose_x_0, transpose_y = matmul_27_transpose_y_0, x = softmax_13, y = reshape_112)[name = string("matmul_27")];
            tensor<int32, [3]> transpose_55_perm_0 = const()[name = string("transpose_55_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_113_shape_0 = const()[name = string("reshape_113_shape_0"), val = tensor<int32, [2]>([16, 352])];
            tensor<fp16, [16, 8, 44]> transpose_55 = transpose(perm = transpose_55_perm_0, x = matmul_27)[name = string("transpose_8")];
            tensor<fp16, [16, 352]> reshape_113 = reshape(shape = reshape_113_shape_0, x = transpose_55)[name = string("reshape_113")];
            tensor<fp16, [16, 352]> mul_667 = mul(x = reshape_113, y = reshape_113)[name = string("mul_667")];
            tensor<int32, [1]> reduce_mean_143_axes_0 = const()[name = string("reduce_mean_143_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_143_keep_dims_0 = const()[name = string("reduce_mean_143_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_143 = reduce_mean(axes = reduce_mean_143_axes_0, keep_dims = reduce_mean_143_keep_dims_0, x = mul_667)[name = string("reduce_mean_143")];
            fp32 rsqrt_143_epsilon_0 = const()[name = string("rsqrt_143_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_143 = rsqrt(epsilon = rsqrt_143_epsilon_0, x = reduce_mean_143)[name = string("rsqrt_143")];
            tensor<fp16, [16, 352]> mul_668 = mul(x = reshape_113, y = rsqrt_143)[name = string("mul_668")];
            tensor<fp16, [352]> mul_669_y_0 = const()[name = string("mul_669_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6865856)))];
            tensor<fp16, [16, 352]> mul_669 = mul(x = mul_668, y = mul_669_y_0)[name = string("mul_669")];
            tensor<fp16, [352, 352]> tern_13_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6866624))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_13_o_weight_0_palettized")];
            tensor<fp16, [16, 352]> tern_13_o = linear(bias = linear_0_bias_0, weight = tern_13_o_weight_0_palettized, x = mul_669)[name = string("tern_13_o")];
            tensor<fp16, [352]> mul_670_y_0 = const()[name = string("mul_670_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6897664)))];
            tensor<fp16, [16, 352]> mul_670 = mul(x = tern_13_o, y = mul_670_y_0)[name = string("mul_670")];
            tensor<fp16, [16, 352]> add_81 = add(x = add_77, y = mul_670)[name = string("add_81")];
            tensor<fp16, [16, 352]> mul_671 = mul(x = add_81, y = add_81)[name = string("mul_671")];
            tensor<int32, [1]> reduce_mean_144_axes_0 = const()[name = string("reduce_mean_144_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_144_keep_dims_0 = const()[name = string("reduce_mean_144_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_144 = reduce_mean(axes = reduce_mean_144_axes_0, keep_dims = reduce_mean_144_keep_dims_0, x = mul_671)[name = string("reduce_mean_144")];
            fp32 rsqrt_144_epsilon_0 = const()[name = string("rsqrt_144_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_144 = rsqrt(epsilon = rsqrt_144_epsilon_0, x = reduce_mean_144)[name = string("rsqrt_144")];
            tensor<fp16, [16, 352]> mul_672 = mul(x = add_81, y = rsqrt_144)[name = string("mul_672")];
            tensor<fp16, [352]> mul_673_y_0 = const()[name = string("mul_673_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6898432)))];
            tensor<fp16, [16, 352]> mul_673 = mul(x = mul_672, y = mul_673_y_0)[name = string("mul_673")];
            tensor<fp16, [16, 352]> mul_674 = mul(x = mul_673, y = mul_673)[name = string("mul_674")];
            tensor<int32, [1]> reduce_mean_145_axes_0 = const()[name = string("reduce_mean_145_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_145_keep_dims_0 = const()[name = string("reduce_mean_145_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_145 = reduce_mean(axes = reduce_mean_145_axes_0, keep_dims = reduce_mean_145_keep_dims_0, x = mul_674)[name = string("reduce_mean_145")];
            fp32 rsqrt_145_epsilon_0 = const()[name = string("rsqrt_145_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_145 = rsqrt(epsilon = rsqrt_145_epsilon_0, x = reduce_mean_145)[name = string("rsqrt_145")];
            tensor<fp16, [16, 352]> mul_675 = mul(x = mul_673, y = rsqrt_145)[name = string("mul_675")];
            tensor<fp16, [352]> mul_676_y_0 = const()[name = string("mul_676_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6899200)))];
            tensor<fp16, [16, 352]> mul_676 = mul(x = mul_675, y = mul_676_y_0)[name = string("mul_676")];
            tensor<fp16, [960, 352]> tern_13_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6899968))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_13_w1_weight_0_palettized")];
            tensor<fp16, [16, 960]> tern_13_w1 = linear(bias = linear_4_bias_0, weight = tern_13_w1_weight_0_palettized, x = mul_676)[name = string("tern_13_w1")];
            tensor<fp16, [960]> mul_677_y_0 = const()[name = string("mul_677_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6984512)))];
            tensor<fp16, [16, 960]> mul_677 = mul(x = tern_13_w1, y = mul_677_y_0)[name = string("mul_677")];
            tensor<fp16, [352]> mul_680_y_0 = const()[name = string("mul_680_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6986496)))];
            tensor<fp16, [16, 352]> mul_680 = mul(x = mul_675, y = mul_680_y_0)[name = string("mul_680")];
            tensor<fp16, [960, 352]> tern_13_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6987264))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_13_w3_weight_0_palettized")];
            tensor<fp16, [16, 960]> tern_13_w3 = linear(bias = linear_4_bias_0, weight = tern_13_w3_weight_0_palettized, x = mul_680)[name = string("tern_13_w3")];
            tensor<fp16, [960]> mul_681_y_0 = const()[name = string("mul_681_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7071808)))];
            tensor<fp16, [16, 960]> mul_681 = mul(x = tern_13_w3, y = mul_681_y_0)[name = string("mul_681")];
            fp16 mul_682_y_0 = const()[name = string("mul_682_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [16, 960]> mul_682 = mul(x = mul_677, y = mul_682_y_0)[name = string("mul_682")];
            tensor<fp16, [16, 960]> tanh_13 = tanh(x = mul_682)[name = string("tanh_13")];
            fp16 mul_683_x_0 = const()[name = string("mul_683_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [16, 960]> mul_683 = mul(x = mul_683_x_0, y = tanh_13)[name = string("mul_683")];
            fp16 add_82_x_0 = const()[name = string("add_82_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [16, 960]> add_82 = add(x = add_82_x_0, y = mul_683)[name = string("add_82")];
            tensor<fp16, [16, 960]> mul_684 = mul(x = mul_677, y = add_82)[name = string("mul_684")];
            tensor<fp16, [16, 960]> mul_685 = mul(x = mul_684, y = mul_681)[name = string("mul_685")];
            tensor<fp16, [16, 960]> mul_686 = mul(x = mul_685, y = mul_685)[name = string("mul_686")];
            tensor<int32, [1]> reduce_mean_147_axes_0 = const()[name = string("reduce_mean_147_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_147_keep_dims_0 = const()[name = string("reduce_mean_147_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_147 = reduce_mean(axes = reduce_mean_147_axes_0, keep_dims = reduce_mean_147_keep_dims_0, x = mul_686)[name = string("reduce_mean_147")];
            fp32 rsqrt_147_epsilon_0 = const()[name = string("rsqrt_147_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_147 = rsqrt(epsilon = rsqrt_147_epsilon_0, x = reduce_mean_147)[name = string("rsqrt_147")];
            tensor<fp16, [16, 960]> mul_687 = mul(x = mul_685, y = rsqrt_147)[name = string("mul_687")];
            tensor<fp16, [960]> mul_688_y_0 = const()[name = string("mul_688_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7073792)))];
            tensor<fp16, [16, 960]> mul_688 = mul(x = mul_687, y = mul_688_y_0)[name = string("mul_688")];
            tensor<fp16, [352, 960]> tern_13_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7075776))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_13_w2_weight_0_palettized")];
            tensor<fp16, [16, 352]> tern_13_w2 = linear(bias = linear_0_bias_0, weight = tern_13_w2_weight_0_palettized, x = mul_688)[name = string("tern_13_w2")];
            tensor<fp16, [352]> mul_689_y_0 = const()[name = string("mul_689_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7160320)))];
            tensor<fp16, [16, 352]> mul_689 = mul(x = tern_13_w2, y = mul_689_y_0)[name = string("mul_689")];
            tensor<fp16, [16, 352]> add_83 = add(x = add_81, y = mul_689)[name = string("add_83")];
            tensor<fp16, [16, 352]> mul_690 = mul(x = add_83, y = add_83)[name = string("mul_690")];
            tensor<int32, [1]> reduce_mean_148_axes_0 = const()[name = string("reduce_mean_148_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_148_keep_dims_0 = const()[name = string("reduce_mean_148_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_148 = reduce_mean(axes = reduce_mean_148_axes_0, keep_dims = reduce_mean_148_keep_dims_0, x = mul_690)[name = string("reduce_mean_148")];
            fp32 rsqrt_148_epsilon_0 = const()[name = string("rsqrt_148_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_148 = rsqrt(epsilon = rsqrt_148_epsilon_0, x = reduce_mean_148)[name = string("rsqrt_148")];
            tensor<fp16, [16, 352]> mul_691 = mul(x = add_83, y = rsqrt_148)[name = string("mul_691")];
            tensor<fp16, [352]> mul_692_y_0 = const()[name = string("mul_692_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7161088)))];
            tensor<fp16, [16, 352]> mul_692 = mul(x = mul_691, y = mul_692_y_0)[name = string("mul_692")];
            tensor<fp16, [16, 352]> mul_693 = mul(x = mul_692, y = mul_692)[name = string("mul_693")];
            tensor<int32, [1]> reduce_mean_149_axes_0 = const()[name = string("reduce_mean_149_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_149_keep_dims_0 = const()[name = string("reduce_mean_149_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_149 = reduce_mean(axes = reduce_mean_149_axes_0, keep_dims = reduce_mean_149_keep_dims_0, x = mul_693)[name = string("reduce_mean_149")];
            fp32 rsqrt_149_epsilon_0 = const()[name = string("rsqrt_149_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_149 = rsqrt(epsilon = rsqrt_149_epsilon_0, x = reduce_mean_149)[name = string("rsqrt_149")];
            tensor<fp16, [16, 352]> mul_694 = mul(x = mul_692, y = rsqrt_149)[name = string("mul_694")];
            tensor<fp16, [352]> mul_695_y_0 = const()[name = string("mul_695_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7161856)))];
            tensor<fp16, [16, 352]> mul_695 = mul(x = mul_694, y = mul_695_y_0)[name = string("mul_695")];
            tensor<fp16, [352, 352]> tern_14_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7162624))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_14_q_weight_0_palettized")];
            tensor<fp16, [16, 352]> tern_14_q = linear(bias = linear_0_bias_0, weight = tern_14_q_weight_0_palettized, x = mul_695)[name = string("tern_14_q")];
            tensor<fp16, [352]> mul_696_y_0 = const()[name = string("mul_696_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7193664)))];
            tensor<fp16, [16, 352]> mul_696 = mul(x = tern_14_q, y = mul_696_y_0)[name = string("mul_696")];
            tensor<int32, [3]> reshape_114_shape_0 = const()[name = string("reshape_114_shape_0"), val = tensor<int32, [3]>([16, 8, 44])];
            tensor<fp16, [16, 8, 44]> reshape_114 = reshape(shape = reshape_114_shape_0, x = mul_696)[name = string("reshape_114")];
            tensor<int32, [3]> transpose_56_perm_0 = const()[name = string("transpose_56_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_699_y_0 = const()[name = string("mul_699_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7194432)))];
            tensor<fp16, [16, 352]> mul_699 = mul(x = mul_694, y = mul_699_y_0)[name = string("mul_699")];
            tensor<fp16, [88, 352]> tern_14_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7195200))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_14_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_14_k_bias_0 = const()[name = string("tern_14_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [16, 88]> tern_14_k = linear(bias = tern_14_k_bias_0, weight = tern_14_k_weight_0_palettized, x = mul_699)[name = string("tern_14_k")];
            tensor<fp16, [88]> mul_700_y_0 = const()[name = string("mul_700_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7203008)))];
            tensor<fp16, [16, 88]> mul_700 = mul(x = tern_14_k, y = mul_700_y_0)[name = string("mul_700")];
            tensor<int32, [3]> reshape_115_shape_0 = const()[name = string("reshape_115_shape_0"), val = tensor<int32, [3]>([16, 2, 44])];
            tensor<fp16, [16, 2, 44]> reshape_115 = reshape(shape = reshape_115_shape_0, x = mul_700)[name = string("reshape_115")];
            tensor<int32, [3]> transpose_57_perm_0 = const()[name = string("transpose_57_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_703_y_0 = const()[name = string("mul_703_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7203264)))];
            tensor<fp16, [16, 352]> mul_703 = mul(x = mul_694, y = mul_703_y_0)[name = string("mul_703")];
            tensor<fp16, [88, 352]> tern_14_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7204032))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_14_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_14_v_bias_0 = const()[name = string("tern_14_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [16, 88]> tern_14_v = linear(bias = tern_14_v_bias_0, weight = tern_14_v_weight_0_palettized, x = mul_703)[name = string("tern_14_v")];
            tensor<fp16, [88]> mul_704_y_0 = const()[name = string("mul_704_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7211840)))];
            tensor<fp16, [16, 88]> mul_704 = mul(x = tern_14_v, y = mul_704_y_0)[name = string("mul_704")];
            tensor<int32, [3]> reshape_116_shape_0 = const()[name = string("reshape_116_shape_0"), val = tensor<int32, [3]>([16, 2, 44])];
            tensor<fp16, [16, 2, 44]> reshape_116 = reshape(shape = reshape_116_shape_0, x = mul_704)[name = string("reshape_116")];
            tensor<int32, [3]> transpose_58_perm_0 = const()[name = string("transpose_58_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 16, 44]> transpose_56 = transpose(perm = transpose_56_perm_0, x = reshape_114)[name = string("transpose_7")];
            tensor<fp16, [8, 16, 44]> mul_705 = mul(x = transpose_56, y = transpose_56)[name = string("mul_705")];
            tensor<int32, [1]> reduce_mean_152_axes_0 = const()[name = string("reduce_mean_152_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_152_keep_dims_0 = const()[name = string("reduce_mean_152_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 16, 1]> reduce_mean_152 = reduce_mean(axes = reduce_mean_152_axes_0, keep_dims = reduce_mean_152_keep_dims_0, x = mul_705)[name = string("reduce_mean_152")];
            fp32 rsqrt_152_epsilon_0 = const()[name = string("rsqrt_152_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 16, 1]> rsqrt_152 = rsqrt(epsilon = rsqrt_152_epsilon_0, x = reduce_mean_152)[name = string("rsqrt_152")];
            tensor<fp16, [8, 16, 44]> mul_706 = mul(x = transpose_56, y = rsqrt_152)[name = string("mul_706")];
            tensor<fp16, [44]> mul_707_y_0 = const()[name = string("mul_707_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7212096)))];
            tensor<fp16, [8, 16, 44]> mul_707 = mul(x = mul_706, y = mul_707_y_0)[name = string("mul_707")];
            tensor<int32, [3]> slice_by_index_56_begin_0 = const()[name = string("slice_by_index_56_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_56_end_0 = const()[name = string("slice_by_index_56_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_56_end_mask_0 = const()[name = string("slice_by_index_56_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 16, 22]> slice_by_index_56 = slice_by_index(begin = slice_by_index_56_begin_0, end = slice_by_index_56_end_0, end_mask = slice_by_index_56_end_mask_0, x = mul_707)[name = string("slice_by_index_56")];
            tensor<int32, [3]> slice_by_index_57_begin_0 = const()[name = string("slice_by_index_57_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_57_end_0 = const()[name = string("slice_by_index_57_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_57_end_mask_0 = const()[name = string("slice_by_index_57_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 16, 22]> slice_by_index_57 = slice_by_index(begin = slice_by_index_57_begin_0, end = slice_by_index_57_end_0, end_mask = slice_by_index_57_end_mask_0, x = mul_707)[name = string("slice_by_index_57")];
            int32 concat_28_axis_0 = const()[name = string("concat_28_axis_0"), val = int32(-1)];
            bool concat_28_interleave_0 = const()[name = string("concat_28_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 16, 44]> concat_28 = concat(axis = concat_28_axis_0, interleave = concat_28_interleave_0, values = (slice_by_index_57, slice_by_index_56))[name = string("concat_28")];
            tensor<fp16, [44]> mul_708_y_0 = const()[name = string("mul_708_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 16, 44]> mul_708 = mul(x = concat_28, y = mul_708_y_0)[name = string("mul_708")];
            tensor<fp16, [8, 16, 44]> mul_709 = mul(x = mul_707, y = mul_11_y_0)[name = string("mul_709")];
            tensor<fp16, [8, 16, 44]> mul_710 = mul(x = mul_708, y = mul_12_y_0)[name = string("mul_710")];
            tensor<fp16, [8, 16, 44]> add_84 = add(x = mul_709, y = mul_710)[name = string("add_84")];
            tensor<fp16, [2, 16, 44]> transpose_57 = transpose(perm = transpose_57_perm_0, x = reshape_115)[name = string("transpose_6")];
            tensor<fp16, [2, 16, 44]> mul_711 = mul(x = transpose_57, y = transpose_57)[name = string("mul_711")];
            tensor<int32, [1]> reduce_mean_153_axes_0 = const()[name = string("reduce_mean_153_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_153_keep_dims_0 = const()[name = string("reduce_mean_153_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 16, 1]> reduce_mean_153 = reduce_mean(axes = reduce_mean_153_axes_0, keep_dims = reduce_mean_153_keep_dims_0, x = mul_711)[name = string("reduce_mean_153")];
            fp32 rsqrt_153_epsilon_0 = const()[name = string("rsqrt_153_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 16, 1]> rsqrt_153 = rsqrt(epsilon = rsqrt_153_epsilon_0, x = reduce_mean_153)[name = string("rsqrt_153")];
            tensor<fp16, [2, 16, 44]> mul_712 = mul(x = transpose_57, y = rsqrt_153)[name = string("mul_712")];
            tensor<fp16, [44]> mul_713_y_0 = const()[name = string("mul_713_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7212288)))];
            tensor<fp16, [2, 16, 44]> mul_713 = mul(x = mul_712, y = mul_713_y_0)[name = string("mul_713")];
            tensor<int32, [3]> slice_by_index_58_begin_0 = const()[name = string("slice_by_index_58_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_58_end_0 = const()[name = string("slice_by_index_58_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_58_end_mask_0 = const()[name = string("slice_by_index_58_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 16, 22]> slice_by_index_58 = slice_by_index(begin = slice_by_index_58_begin_0, end = slice_by_index_58_end_0, end_mask = slice_by_index_58_end_mask_0, x = mul_713)[name = string("slice_by_index_58")];
            tensor<int32, [3]> slice_by_index_59_begin_0 = const()[name = string("slice_by_index_59_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_59_end_0 = const()[name = string("slice_by_index_59_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_59_end_mask_0 = const()[name = string("slice_by_index_59_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 16, 22]> slice_by_index_59 = slice_by_index(begin = slice_by_index_59_begin_0, end = slice_by_index_59_end_0, end_mask = slice_by_index_59_end_mask_0, x = mul_713)[name = string("slice_by_index_59")];
            int32 concat_29_axis_0 = const()[name = string("concat_29_axis_0"), val = int32(-1)];
            bool concat_29_interleave_0 = const()[name = string("concat_29_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 16, 44]> concat_29 = concat(axis = concat_29_axis_0, interleave = concat_29_interleave_0, values = (slice_by_index_59, slice_by_index_58))[name = string("concat_29")];
            tensor<fp16, [44]> mul_714_y_0 = const()[name = string("mul_714_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 16, 44]> mul_714 = mul(x = concat_29, y = mul_714_y_0)[name = string("mul_714")];
            tensor<fp16, [2, 16, 44]> mul_715 = mul(x = mul_713, y = mul_11_y_0)[name = string("mul_715")];
            tensor<fp16, [2, 16, 44]> mul_716 = mul(x = mul_714, y = mul_12_y_0)[name = string("mul_716")];
            tensor<fp16, [2, 16, 44]> add_85 = add(x = mul_715, y = mul_716)[name = string("add_85")];
            tensor<int32, [4]> reshape_117_shape_0 = const()[name = string("reshape_117_shape_0"), val = tensor<int32, [4]>([2, 1, 16, 44])];
            tensor<fp16, [2, 1, 16, 44]> reshape_117 = reshape(shape = reshape_117_shape_0, x = add_85)[name = string("reshape_117")];
            tensor<int32, [4]> tile_28_reps_0 = const()[name = string("tile_28_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 16, 44]> tile_28 = tile(reps = tile_28_reps_0, x = reshape_117)[name = string("tile_28")];
            tensor<int32, [3]> reshape_118_shape_0 = const()[name = string("reshape_118_shape_0"), val = tensor<int32, [3]>([8, 16, 44])];
            tensor<fp16, [8, 16, 44]> reshape_118 = reshape(shape = reshape_118_shape_0, x = tile_28)[name = string("reshape_118")];
            tensor<int32, [4]> reshape_119_shape_0 = const()[name = string("reshape_119_shape_0"), val = tensor<int32, [4]>([2, 1, 16, 44])];
            tensor<fp16, [2, 16, 44]> transpose_58 = transpose(perm = transpose_58_perm_0, x = reshape_116)[name = string("transpose_5")];
            tensor<fp16, [2, 1, 16, 44]> reshape_119 = reshape(shape = reshape_119_shape_0, x = transpose_58)[name = string("reshape_119")];
            tensor<int32, [4]> tile_29_reps_0 = const()[name = string("tile_29_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 16, 44]> tile_29 = tile(reps = tile_29_reps_0, x = reshape_119)[name = string("tile_29")];
            tensor<int32, [3]> reshape_120_shape_0 = const()[name = string("reshape_120_shape_0"), val = tensor<int32, [3]>([8, 16, 44])];
            tensor<fp16, [8, 16, 44]> reshape_120 = reshape(shape = reshape_120_shape_0, x = tile_29)[name = string("reshape_120")];
            fp16 mul_717_y_0 = const()[name = string("mul_717_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 16, 44]> mul_717 = mul(x = add_84, y = mul_717_y_0)[name = string("mul_717")];
            bool matmul_28_transpose_y_0 = const()[name = string("matmul_28_transpose_y_0"), val = bool(true)];
            bool matmul_28_transpose_x_0 = const()[name = string("matmul_28_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 16, 16]> matmul_28 = matmul(transpose_x = matmul_28_transpose_x_0, transpose_y = matmul_28_transpose_y_0, x = mul_717, y = reshape_118)[name = string("matmul_28")];
            tensor<fp16, [8, 16, 16]> add_86 = add(x = matmul_28, y = reshape_1)[name = string("add_86")];
            int32 softmax_14_axis_0 = const()[name = string("softmax_14_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 16, 16]> softmax_14 = softmax(axis = softmax_14_axis_0, x = add_86)[name = string("softmax_14")];
            bool matmul_29_transpose_x_0 = const()[name = string("matmul_29_transpose_x_0"), val = bool(false)];
            bool matmul_29_transpose_y_0 = const()[name = string("matmul_29_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 16, 44]> matmul_29 = matmul(transpose_x = matmul_29_transpose_x_0, transpose_y = matmul_29_transpose_y_0, x = softmax_14, y = reshape_120)[name = string("matmul_29")];
            tensor<int32, [3]> transpose_59_perm_0 = const()[name = string("transpose_59_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_121_shape_0 = const()[name = string("reshape_121_shape_0"), val = tensor<int32, [2]>([16, 352])];
            tensor<fp16, [16, 8, 44]> transpose_59 = transpose(perm = transpose_59_perm_0, x = matmul_29)[name = string("transpose_4")];
            tensor<fp16, [16, 352]> reshape_121 = reshape(shape = reshape_121_shape_0, x = transpose_59)[name = string("reshape_121")];
            tensor<fp16, [16, 352]> mul_718 = mul(x = reshape_121, y = reshape_121)[name = string("mul_718")];
            tensor<int32, [1]> reduce_mean_154_axes_0 = const()[name = string("reduce_mean_154_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_154_keep_dims_0 = const()[name = string("reduce_mean_154_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_154 = reduce_mean(axes = reduce_mean_154_axes_0, keep_dims = reduce_mean_154_keep_dims_0, x = mul_718)[name = string("reduce_mean_154")];
            fp32 rsqrt_154_epsilon_0 = const()[name = string("rsqrt_154_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_154 = rsqrt(epsilon = rsqrt_154_epsilon_0, x = reduce_mean_154)[name = string("rsqrt_154")];
            tensor<fp16, [16, 352]> mul_719 = mul(x = reshape_121, y = rsqrt_154)[name = string("mul_719")];
            tensor<fp16, [352]> mul_720_y_0 = const()[name = string("mul_720_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7212480)))];
            tensor<fp16, [16, 352]> mul_720 = mul(x = mul_719, y = mul_720_y_0)[name = string("mul_720")];
            tensor<fp16, [352, 352]> tern_14_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7213248))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_14_o_weight_0_palettized")];
            tensor<fp16, [16, 352]> tern_14_o = linear(bias = linear_0_bias_0, weight = tern_14_o_weight_0_palettized, x = mul_720)[name = string("tern_14_o")];
            tensor<fp16, [352]> mul_721_y_0 = const()[name = string("mul_721_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7244288)))];
            tensor<fp16, [16, 352]> mul_721 = mul(x = tern_14_o, y = mul_721_y_0)[name = string("mul_721")];
            tensor<fp16, [16, 352]> add_87 = add(x = add_83, y = mul_721)[name = string("add_87")];
            tensor<fp16, [16, 352]> mul_722 = mul(x = add_87, y = add_87)[name = string("mul_722")];
            tensor<int32, [1]> reduce_mean_155_axes_0 = const()[name = string("reduce_mean_155_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_155_keep_dims_0 = const()[name = string("reduce_mean_155_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_155 = reduce_mean(axes = reduce_mean_155_axes_0, keep_dims = reduce_mean_155_keep_dims_0, x = mul_722)[name = string("reduce_mean_155")];
            fp32 rsqrt_155_epsilon_0 = const()[name = string("rsqrt_155_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_155 = rsqrt(epsilon = rsqrt_155_epsilon_0, x = reduce_mean_155)[name = string("rsqrt_155")];
            tensor<fp16, [16, 352]> mul_723 = mul(x = add_87, y = rsqrt_155)[name = string("mul_723")];
            tensor<fp16, [352]> mul_724_y_0 = const()[name = string("mul_724_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7245056)))];
            tensor<fp16, [16, 352]> mul_724 = mul(x = mul_723, y = mul_724_y_0)[name = string("mul_724")];
            tensor<fp16, [16, 352]> mul_725 = mul(x = mul_724, y = mul_724)[name = string("mul_725")];
            tensor<int32, [1]> reduce_mean_156_axes_0 = const()[name = string("reduce_mean_156_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_156_keep_dims_0 = const()[name = string("reduce_mean_156_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_156 = reduce_mean(axes = reduce_mean_156_axes_0, keep_dims = reduce_mean_156_keep_dims_0, x = mul_725)[name = string("reduce_mean_156")];
            fp32 rsqrt_156_epsilon_0 = const()[name = string("rsqrt_156_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_156 = rsqrt(epsilon = rsqrt_156_epsilon_0, x = reduce_mean_156)[name = string("rsqrt_156")];
            tensor<fp16, [16, 352]> mul_726 = mul(x = mul_724, y = rsqrt_156)[name = string("mul_726")];
            tensor<fp16, [352]> mul_727_y_0 = const()[name = string("mul_727_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7245824)))];
            tensor<fp16, [16, 352]> mul_727 = mul(x = mul_726, y = mul_727_y_0)[name = string("mul_727")];
            tensor<fp16, [960, 352]> tern_14_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7246592))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_14_w1_weight_0_palettized")];
            tensor<fp16, [16, 960]> tern_14_w1 = linear(bias = linear_4_bias_0, weight = tern_14_w1_weight_0_palettized, x = mul_727)[name = string("tern_14_w1")];
            tensor<fp16, [960]> mul_728_y_0 = const()[name = string("mul_728_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7331136)))];
            tensor<fp16, [16, 960]> mul_728 = mul(x = tern_14_w1, y = mul_728_y_0)[name = string("mul_728")];
            tensor<fp16, [352]> mul_731_y_0 = const()[name = string("mul_731_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7333120)))];
            tensor<fp16, [16, 352]> mul_731 = mul(x = mul_726, y = mul_731_y_0)[name = string("mul_731")];
            tensor<fp16, [960, 352]> tern_14_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7333888))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_14_w3_weight_0_palettized")];
            tensor<fp16, [16, 960]> tern_14_w3 = linear(bias = linear_4_bias_0, weight = tern_14_w3_weight_0_palettized, x = mul_731)[name = string("tern_14_w3")];
            tensor<fp16, [960]> mul_732_y_0 = const()[name = string("mul_732_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7418432)))];
            tensor<fp16, [16, 960]> mul_732 = mul(x = tern_14_w3, y = mul_732_y_0)[name = string("mul_732")];
            fp16 mul_733_y_0 = const()[name = string("mul_733_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [16, 960]> mul_733 = mul(x = mul_728, y = mul_733_y_0)[name = string("mul_733")];
            tensor<fp16, [16, 960]> tanh_14 = tanh(x = mul_733)[name = string("tanh_14")];
            fp16 mul_734_x_0 = const()[name = string("mul_734_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [16, 960]> mul_734 = mul(x = mul_734_x_0, y = tanh_14)[name = string("mul_734")];
            fp16 add_88_x_0 = const()[name = string("add_88_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [16, 960]> add_88 = add(x = add_88_x_0, y = mul_734)[name = string("add_88")];
            tensor<fp16, [16, 960]> mul_735 = mul(x = mul_728, y = add_88)[name = string("mul_735")];
            tensor<fp16, [16, 960]> mul_736 = mul(x = mul_735, y = mul_732)[name = string("mul_736")];
            tensor<fp16, [16, 960]> mul_737 = mul(x = mul_736, y = mul_736)[name = string("mul_737")];
            tensor<int32, [1]> reduce_mean_158_axes_0 = const()[name = string("reduce_mean_158_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_158_keep_dims_0 = const()[name = string("reduce_mean_158_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_158 = reduce_mean(axes = reduce_mean_158_axes_0, keep_dims = reduce_mean_158_keep_dims_0, x = mul_737)[name = string("reduce_mean_158")];
            fp32 rsqrt_158_epsilon_0 = const()[name = string("rsqrt_158_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_158 = rsqrt(epsilon = rsqrt_158_epsilon_0, x = reduce_mean_158)[name = string("rsqrt_158")];
            tensor<fp16, [16, 960]> mul_738 = mul(x = mul_736, y = rsqrt_158)[name = string("mul_738")];
            tensor<fp16, [960]> mul_739_y_0 = const()[name = string("mul_739_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7420416)))];
            tensor<fp16, [16, 960]> mul_739 = mul(x = mul_738, y = mul_739_y_0)[name = string("mul_739")];
            tensor<fp16, [352, 960]> tern_14_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7422400))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_14_w2_weight_0_palettized")];
            tensor<fp16, [16, 352]> tern_14_w2 = linear(bias = linear_0_bias_0, weight = tern_14_w2_weight_0_palettized, x = mul_739)[name = string("tern_14_w2")];
            tensor<fp16, [352]> mul_740_y_0 = const()[name = string("mul_740_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7506944)))];
            tensor<fp16, [16, 352]> mul_740 = mul(x = tern_14_w2, y = mul_740_y_0)[name = string("mul_740")];
            tensor<fp16, [16, 352]> add_89 = add(x = add_87, y = mul_740)[name = string("add_89")];
            tensor<fp16, [16, 352]> mul_741 = mul(x = add_89, y = add_89)[name = string("mul_741")];
            tensor<int32, [1]> reduce_mean_159_axes_0 = const()[name = string("reduce_mean_159_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_159_keep_dims_0 = const()[name = string("reduce_mean_159_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_159 = reduce_mean(axes = reduce_mean_159_axes_0, keep_dims = reduce_mean_159_keep_dims_0, x = mul_741)[name = string("reduce_mean_159")];
            fp32 rsqrt_159_epsilon_0 = const()[name = string("rsqrt_159_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_159 = rsqrt(epsilon = rsqrt_159_epsilon_0, x = reduce_mean_159)[name = string("rsqrt_159")];
            tensor<fp16, [16, 352]> mul_742 = mul(x = add_89, y = rsqrt_159)[name = string("mul_742")];
            tensor<fp16, [352]> mul_743_y_0 = const()[name = string("mul_743_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7507712)))];
            tensor<fp16, [16, 352]> mul_743 = mul(x = mul_742, y = mul_743_y_0)[name = string("mul_743")];
            tensor<fp16, [352, 352]> linear_7_weight_0 = const()[name = string("linear_7_weight_0"), val = tensor<fp16, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7508480)))];
            tensor<fp16, [16, 352]> linear_7 = linear(bias = linear_0_bias_0, weight = linear_7_weight_0, x = mul_743)[name = string("linear_7")];
            tensor<int32, [3]> reshape_122_shape_0 = const()[name = string("reshape_122_shape_0"), val = tensor<int32, [3]>([16, 8, 44])];
            tensor<fp16, [16, 8, 44]> reshape_122 = reshape(shape = reshape_122_shape_0, x = linear_7)[name = string("reshape_122")];
            tensor<int32, [3]> transpose_60_perm_0 = const()[name = string("transpose_60_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [88, 352]> linear_8_weight_0 = const()[name = string("linear_8_weight_0"), val = tensor<fp16, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7756352)))];
            tensor<fp16, [88]> linear_8_bias_0 = const()[name = string("linear_8_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [16, 88]> linear_8 = linear(bias = linear_8_bias_0, weight = linear_8_weight_0, x = mul_743)[name = string("linear_8")];
            tensor<int32, [3]> reshape_123_shape_0 = const()[name = string("reshape_123_shape_0"), val = tensor<int32, [3]>([16, 2, 44])];
            tensor<fp16, [16, 2, 44]> reshape_123 = reshape(shape = reshape_123_shape_0, x = linear_8)[name = string("reshape_123")];
            tensor<int32, [3]> transpose_61_perm_0 = const()[name = string("transpose_61_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [88, 352]> linear_9_weight_0 = const()[name = string("linear_9_weight_0"), val = tensor<fp16, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7818368)))];
            tensor<fp16, [88]> linear_9_bias_0 = const()[name = string("linear_9_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [16, 88]> linear_9 = linear(bias = linear_9_bias_0, weight = linear_9_weight_0, x = mul_743)[name = string("linear_9")];
            tensor<int32, [3]> reshape_124_shape_0 = const()[name = string("reshape_124_shape_0"), val = tensor<int32, [3]>([16, 2, 44])];
            tensor<fp16, [16, 2, 44]> reshape_124 = reshape(shape = reshape_124_shape_0, x = linear_9)[name = string("reshape_124")];
            tensor<int32, [3]> transpose_62_perm_0 = const()[name = string("transpose_62_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 16, 44]> transpose_60 = transpose(perm = transpose_60_perm_0, x = reshape_122)[name = string("transpose_3")];
            tensor<fp16, [8, 16, 44]> mul_744 = mul(x = transpose_60, y = transpose_60)[name = string("mul_744")];
            tensor<int32, [1]> reduce_mean_160_axes_0 = const()[name = string("reduce_mean_160_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_160_keep_dims_0 = const()[name = string("reduce_mean_160_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 16, 1]> reduce_mean_160 = reduce_mean(axes = reduce_mean_160_axes_0, keep_dims = reduce_mean_160_keep_dims_0, x = mul_744)[name = string("reduce_mean_160")];
            fp32 rsqrt_160_epsilon_0 = const()[name = string("rsqrt_160_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 16, 1]> rsqrt_160 = rsqrt(epsilon = rsqrt_160_epsilon_0, x = reduce_mean_160)[name = string("rsqrt_160")];
            tensor<fp16, [8, 16, 44]> mul_745 = mul(x = transpose_60, y = rsqrt_160)[name = string("mul_745")];
            tensor<fp16, [44]> mul_746_y_0 = const()[name = string("mul_746_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7880384)))];
            tensor<fp16, [8, 16, 44]> mul_746 = mul(x = mul_745, y = mul_746_y_0)[name = string("mul_746")];
            tensor<int32, [3]> slice_by_index_60_begin_0 = const()[name = string("slice_by_index_60_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_60_end_0 = const()[name = string("slice_by_index_60_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_60_end_mask_0 = const()[name = string("slice_by_index_60_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 16, 22]> slice_by_index_60 = slice_by_index(begin = slice_by_index_60_begin_0, end = slice_by_index_60_end_0, end_mask = slice_by_index_60_end_mask_0, x = mul_746)[name = string("slice_by_index_60")];
            tensor<int32, [3]> slice_by_index_61_begin_0 = const()[name = string("slice_by_index_61_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_61_end_0 = const()[name = string("slice_by_index_61_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_61_end_mask_0 = const()[name = string("slice_by_index_61_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 16, 22]> slice_by_index_61 = slice_by_index(begin = slice_by_index_61_begin_0, end = slice_by_index_61_end_0, end_mask = slice_by_index_61_end_mask_0, x = mul_746)[name = string("slice_by_index_61")];
            int32 concat_30_axis_0 = const()[name = string("concat_30_axis_0"), val = int32(-1)];
            bool concat_30_interleave_0 = const()[name = string("concat_30_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 16, 44]> concat_30 = concat(axis = concat_30_axis_0, interleave = concat_30_interleave_0, values = (slice_by_index_61, slice_by_index_60))[name = string("concat_30")];
            tensor<fp16, [44]> mul_747_y_0 = const()[name = string("mul_747_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 16, 44]> mul_747 = mul(x = concat_30, y = mul_747_y_0)[name = string("mul_747")];
            tensor<fp16, [8, 16, 44]> mul_748 = mul(x = mul_746, y = mul_11_y_0)[name = string("mul_748")];
            tensor<fp16, [8, 16, 44]> mul_749 = mul(x = mul_747, y = mul_12_y_0)[name = string("mul_749")];
            tensor<fp16, [8, 16, 44]> add_90 = add(x = mul_748, y = mul_749)[name = string("add_90")];
            tensor<fp16, [2, 16, 44]> transpose_61 = transpose(perm = transpose_61_perm_0, x = reshape_123)[name = string("transpose_2")];
            tensor<fp16, [2, 16, 44]> mul_750 = mul(x = transpose_61, y = transpose_61)[name = string("mul_750")];
            tensor<int32, [1]> reduce_mean_161_axes_0 = const()[name = string("reduce_mean_161_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_161_keep_dims_0 = const()[name = string("reduce_mean_161_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 16, 1]> reduce_mean_161 = reduce_mean(axes = reduce_mean_161_axes_0, keep_dims = reduce_mean_161_keep_dims_0, x = mul_750)[name = string("reduce_mean_161")];
            fp32 rsqrt_161_epsilon_0 = const()[name = string("rsqrt_161_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 16, 1]> rsqrt_161 = rsqrt(epsilon = rsqrt_161_epsilon_0, x = reduce_mean_161)[name = string("rsqrt_161")];
            tensor<fp16, [2, 16, 44]> mul_751 = mul(x = transpose_61, y = rsqrt_161)[name = string("mul_751")];
            tensor<fp16, [44]> mul_752_y_0 = const()[name = string("mul_752_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7880576)))];
            tensor<fp16, [2, 16, 44]> mul_752 = mul(x = mul_751, y = mul_752_y_0)[name = string("mul_752")];
            tensor<int32, [3]> slice_by_index_62_begin_0 = const()[name = string("slice_by_index_62_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_62_end_0 = const()[name = string("slice_by_index_62_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_62_end_mask_0 = const()[name = string("slice_by_index_62_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 16, 22]> slice_by_index_62 = slice_by_index(begin = slice_by_index_62_begin_0, end = slice_by_index_62_end_0, end_mask = slice_by_index_62_end_mask_0, x = mul_752)[name = string("slice_by_index_62")];
            tensor<int32, [3]> slice_by_index_63_begin_0 = const()[name = string("slice_by_index_63_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_63_end_0 = const()[name = string("slice_by_index_63_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_63_end_mask_0 = const()[name = string("slice_by_index_63_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 16, 22]> slice_by_index_63 = slice_by_index(begin = slice_by_index_63_begin_0, end = slice_by_index_63_end_0, end_mask = slice_by_index_63_end_mask_0, x = mul_752)[name = string("slice_by_index_63")];
            int32 concat_31_axis_0 = const()[name = string("concat_31_axis_0"), val = int32(-1)];
            bool concat_31_interleave_0 = const()[name = string("concat_31_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 16, 44]> concat_31 = concat(axis = concat_31_axis_0, interleave = concat_31_interleave_0, values = (slice_by_index_63, slice_by_index_62))[name = string("concat_31")];
            tensor<fp16, [44]> mul_753_y_0 = const()[name = string("mul_753_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 16, 44]> mul_753 = mul(x = concat_31, y = mul_753_y_0)[name = string("mul_753")];
            tensor<fp16, [2, 16, 44]> mul_754 = mul(x = mul_752, y = mul_11_y_0)[name = string("mul_754")];
            tensor<fp16, [2, 16, 44]> mul_755 = mul(x = mul_753, y = mul_12_y_0)[name = string("mul_755")];
            tensor<fp16, [2, 16, 44]> add_91 = add(x = mul_754, y = mul_755)[name = string("add_91")];
            tensor<int32, [4]> reshape_125_shape_0 = const()[name = string("reshape_125_shape_0"), val = tensor<int32, [4]>([2, 1, 16, 44])];
            tensor<fp16, [2, 1, 16, 44]> reshape_125 = reshape(shape = reshape_125_shape_0, x = add_91)[name = string("reshape_125")];
            tensor<int32, [4]> tile_30_reps_0 = const()[name = string("tile_30_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 16, 44]> tile_30 = tile(reps = tile_30_reps_0, x = reshape_125)[name = string("tile_30")];
            tensor<int32, [3]> reshape_126_shape_0 = const()[name = string("reshape_126_shape_0"), val = tensor<int32, [3]>([8, 16, 44])];
            tensor<fp16, [8, 16, 44]> reshape_126 = reshape(shape = reshape_126_shape_0, x = tile_30)[name = string("reshape_126")];
            tensor<int32, [4]> reshape_127_shape_0 = const()[name = string("reshape_127_shape_0"), val = tensor<int32, [4]>([2, 1, 16, 44])];
            tensor<fp16, [2, 16, 44]> transpose_62 = transpose(perm = transpose_62_perm_0, x = reshape_124)[name = string("transpose_1")];
            tensor<fp16, [2, 1, 16, 44]> reshape_127 = reshape(shape = reshape_127_shape_0, x = transpose_62)[name = string("reshape_127")];
            tensor<int32, [4]> tile_31_reps_0 = const()[name = string("tile_31_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 16, 44]> tile_31 = tile(reps = tile_31_reps_0, x = reshape_127)[name = string("tile_31")];
            tensor<int32, [3]> reshape_128_shape_0 = const()[name = string("reshape_128_shape_0"), val = tensor<int32, [3]>([8, 16, 44])];
            tensor<fp16, [8, 16, 44]> reshape_128 = reshape(shape = reshape_128_shape_0, x = tile_31)[name = string("reshape_128")];
            fp16 mul_756_y_0 = const()[name = string("mul_756_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 16, 44]> mul_756 = mul(x = add_90, y = mul_756_y_0)[name = string("mul_756")];
            bool matmul_30_transpose_y_0 = const()[name = string("matmul_30_transpose_y_0"), val = bool(true)];
            bool matmul_30_transpose_x_0 = const()[name = string("matmul_30_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 16, 16]> matmul_30 = matmul(transpose_x = matmul_30_transpose_x_0, transpose_y = matmul_30_transpose_y_0, x = mul_756, y = reshape_126)[name = string("matmul_30")];
            tensor<fp16, [8, 16, 16]> add_92 = add(x = matmul_30, y = reshape_1)[name = string("add_92")];
            int32 softmax_15_axis_0 = const()[name = string("softmax_15_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 16, 16]> softmax_15 = softmax(axis = softmax_15_axis_0, x = add_92)[name = string("softmax_15")];
            bool matmul_31_transpose_x_0 = const()[name = string("matmul_31_transpose_x_0"), val = bool(false)];
            bool matmul_31_transpose_y_0 = const()[name = string("matmul_31_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 16, 44]> matmul_31 = matmul(transpose_x = matmul_31_transpose_x_0, transpose_y = matmul_31_transpose_y_0, x = softmax_15, y = reshape_128)[name = string("matmul_31")];
            tensor<int32, [3]> transpose_63_perm_0 = const()[name = string("transpose_63_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_129_shape_0 = const()[name = string("reshape_129_shape_0"), val = tensor<int32, [2]>([16, 352])];
            tensor<fp16, [16, 8, 44]> transpose_63 = transpose(perm = transpose_63_perm_0, x = matmul_31)[name = string("transpose_0")];
            tensor<fp16, [16, 352]> reshape_129 = reshape(shape = reshape_129_shape_0, x = transpose_63)[name = string("reshape_129")];
            tensor<fp16, [352, 352]> linear_10_weight_0 = const()[name = string("linear_10_weight_0"), val = tensor<fp16, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7880768)))];
            tensor<fp16, [16, 352]> linear_10 = linear(bias = linear_0_bias_0, weight = linear_10_weight_0, x = reshape_129)[name = string("linear_10")];
            tensor<fp16, [16, 352]> add_93 = add(x = add_89, y = linear_10)[name = string("add_93")];
            tensor<fp16, [16, 352]> mul_757 = mul(x = add_93, y = add_93)[name = string("mul_757")];
            tensor<int32, [1]> reduce_mean_162_axes_0 = const()[name = string("reduce_mean_162_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_162_keep_dims_0 = const()[name = string("reduce_mean_162_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_162 = reduce_mean(axes = reduce_mean_162_axes_0, keep_dims = reduce_mean_162_keep_dims_0, x = mul_757)[name = string("reduce_mean_162")];
            fp32 rsqrt_162_epsilon_0 = const()[name = string("rsqrt_162_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_162 = rsqrt(epsilon = rsqrt_162_epsilon_0, x = reduce_mean_162)[name = string("rsqrt_162")];
            tensor<fp16, [16, 352]> mul_758 = mul(x = add_93, y = rsqrt_162)[name = string("mul_758")];
            tensor<fp16, [352]> mul_759_y_0 = const()[name = string("mul_759_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8128640)))];
            tensor<fp16, [16, 352]> mul_759 = mul(x = mul_758, y = mul_759_y_0)[name = string("mul_759")];
            tensor<fp16, [960, 352]> linear_11_weight_0 = const()[name = string("linear_11_weight_0"), val = tensor<fp16, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8129408)))];
            tensor<fp16, [16, 960]> linear_11 = linear(bias = linear_4_bias_0, weight = linear_11_weight_0, x = mul_759)[name = string("linear_11")];
            tensor<fp16, [960, 352]> linear_12_weight_0 = const()[name = string("linear_12_weight_0"), val = tensor<fp16, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8805312)))];
            tensor<fp16, [16, 960]> linear_12 = linear(bias = linear_4_bias_0, weight = linear_12_weight_0, x = mul_759)[name = string("linear_12")];
            fp16 mul_760_y_0 = const()[name = string("mul_760_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [16, 960]> mul_760 = mul(x = linear_11, y = mul_760_y_0)[name = string("mul_760")];
            tensor<fp16, [16, 960]> tanh_15 = tanh(x = mul_760)[name = string("tanh_15")];
            fp16 mul_761_x_0 = const()[name = string("mul_761_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [16, 960]> mul_761 = mul(x = mul_761_x_0, y = tanh_15)[name = string("mul_761")];
            fp16 add_94_x_0 = const()[name = string("add_94_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [16, 960]> add_94 = add(x = add_94_x_0, y = mul_761)[name = string("add_94")];
            tensor<fp16, [16, 960]> mul_762 = mul(x = linear_11, y = add_94)[name = string("mul_762")];
            tensor<fp16, [16, 960]> mul_763 = mul(x = mul_762, y = linear_12)[name = string("mul_763")];
            tensor<fp16, [352, 960]> linear_13_weight_0 = const()[name = string("linear_13_weight_0"), val = tensor<fp16, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9481216)))];
            tensor<fp16, [16, 352]> linear_13 = linear(bias = linear_0_bias_0, weight = linear_13_weight_0, x = mul_763)[name = string("linear_13")];
            tensor<fp16, [16, 352]> add_95 = add(x = add_93, y = linear_13)[name = string("add_95")];
            tensor<fp16, [16, 352]> mul_764 = mul(x = add_95, y = add_95)[name = string("mul_764")];
            tensor<int32, [1]> reduce_mean_163_axes_0 = const()[name = string("reduce_mean_163_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_163_keep_dims_0 = const()[name = string("reduce_mean_163_keep_dims_0"), val = bool(true)];
            tensor<fp16, [16, 1]> reduce_mean_163 = reduce_mean(axes = reduce_mean_163_axes_0, keep_dims = reduce_mean_163_keep_dims_0, x = mul_764)[name = string("reduce_mean_163")];
            fp32 rsqrt_163_epsilon_0 = const()[name = string("rsqrt_163_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [16, 1]> rsqrt_163 = rsqrt(epsilon = rsqrt_163_epsilon_0, x = reduce_mean_163)[name = string("rsqrt_163")];
            tensor<fp16, [16, 352]> mul_765 = mul(x = add_95, y = rsqrt_163)[name = string("mul_765")];
            tensor<fp16, [352]> mul_766_y_0 = const()[name = string("mul_766_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10157120)))];
            tensor<fp16, [16, 352]> mul_766 = mul(x = mul_765, y = mul_766_y_0)[name = string("mul_766")];
            tensor<fp16, [8342, 352]> linear_14_weight_0 = const()[name = string("linear_14_weight_0"), val = tensor<fp16, [8342, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10157888)))];
            tensor<fp16, [8342]> linear_14_bias_0 = const()[name = string("linear_14_bias_0"), val = tensor<fp16, [8342]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16030720)))];
            tensor<fp16, [16, 8342]> linear_14 = linear(bias = linear_14_bias_0, weight = linear_14_weight_0, x = mul_766)[name = string("linear_14")];
            tensor<int32, [3]> logits_shape_0 = const()[name = string("logits_shape_0"), val = tensor<int32, [3]>([1, 16, 8342])];
            tensor<fp16, [1, 16, 8342]> logits = reshape(shape = logits_shape_0, x = linear_14)[name = string("logits")];
        } -> (logits);
    func L256<ios18>(tensor<fp16, [1, 256, 352]> ids, tensor<fp16, [1, 256]> mask) {
            tensor<int32, [2]> reshape_0_shape_0 = const()[name = string("reshape_0_shape_0"), val = tensor<int32, [2]>([256, 352])];
            tensor<fp16, [256, 352]> reshape_0 = reshape(shape = reshape_0_shape_0, x = ids)[name = string("reshape_0")];
            tensor<fp16, [256, 352]> mul_0 = mul(x = reshape_0, y = reshape_0)[name = string("mul_0")];
            tensor<int32, [1]> reduce_mean_0_axes_0 = const()[name = string("reduce_mean_0_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_0_keep_dims_0 = const()[name = string("reduce_mean_0_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_0 = reduce_mean(axes = reduce_mean_0_axes_0, keep_dims = reduce_mean_0_keep_dims_0, x = mul_0)[name = string("reduce_mean_0")];
            fp32 rsqrt_0_epsilon_0 = const()[name = string("rsqrt_0_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_0 = rsqrt(epsilon = rsqrt_0_epsilon_0, x = reduce_mean_0)[name = string("rsqrt_0")];
            tensor<fp16, [256, 352]> mul_1 = mul(x = reshape_0, y = rsqrt_0)[name = string("mul_1")];
            tensor<fp16, [352]> mul_2_y_0 = const()[name = string("mul_2_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(64)))];
            tensor<fp16, [256, 352]> mul_2 = mul(x = mul_1, y = mul_2_y_0)[name = string("mul_2")];
            fp16 sub_0_y_0 = const()[name = string("sub_0_y_0"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 256]> sub_0 = sub(x = mask, y = sub_0_y_0)[name = string("sub_0")];
            fp16 mul_3_y_0 = const()[name = string("mul_3_y_0"), val = fp16(0x1.388p+13)];
            tensor<fp16, [1, 256]> mul_3 = mul(x = sub_0, y = mul_3_y_0)[name = string("mul_3")];
            tensor<int32, [3]> reshape_1_shape_0 = const()[name = string("reshape_1_shape_0"), val = tensor<int32, [3]>([1, 1, 256])];
            tensor<fp16, [1, 1, 256]> reshape_1 = reshape(shape = reshape_1_shape_0, x = mul_3)[name = string("reshape_1")];
            tensor<fp16, [256, 352]> mul_4 = mul(x = mul_2, y = mul_2)[name = string("mul_4")];
            tensor<int32, [1]> reduce_mean_1_axes_0 = const()[name = string("reduce_mean_1_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_1_keep_dims_0 = const()[name = string("reduce_mean_1_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_1 = reduce_mean(axes = reduce_mean_1_axes_0, keep_dims = reduce_mean_1_keep_dims_0, x = mul_4)[name = string("reduce_mean_1")];
            fp32 rsqrt_1_epsilon_0 = const()[name = string("rsqrt_1_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_1 = rsqrt(epsilon = rsqrt_1_epsilon_0, x = reduce_mean_1)[name = string("rsqrt_1")];
            tensor<fp16, [256, 352]> mul_5 = mul(x = mul_2, y = rsqrt_1)[name = string("mul_5")];
            tensor<fp16, [352]> mul_6_y_0 = const()[name = string("mul_6_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(832)))];
            tensor<fp16, [256, 352]> mul_6 = mul(x = mul_5, y = mul_6_y_0)[name = string("mul_6")];
            tensor<fp16, [352, 352]> linear_0_weight_0 = const()[name = string("linear_0_weight_0"), val = tensor<fp16, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1600)))];
            tensor<fp16, [352]> linear_0_bias_0 = const()[name = string("linear_0_bias_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(249472)))];
            tensor<fp16, [256, 352]> linear_0 = linear(bias = linear_0_bias_0, weight = linear_0_weight_0, x = mul_6)[name = string("linear_0")];
            tensor<int32, [3]> reshape_2_shape_0 = const()[name = string("reshape_2_shape_0"), val = tensor<int32, [3]>([256, 8, 44])];
            tensor<fp16, [256, 8, 44]> reshape_2 = reshape(shape = reshape_2_shape_0, x = linear_0)[name = string("reshape_2")];
            tensor<int32, [3]> transpose_0_perm_0 = const()[name = string("transpose_0_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [88, 352]> linear_1_weight_0 = const()[name = string("linear_1_weight_0"), val = tensor<fp16, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(250240)))];
            tensor<fp16, [88]> linear_1_bias_0 = const()[name = string("linear_1_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [256, 88]> linear_1 = linear(bias = linear_1_bias_0, weight = linear_1_weight_0, x = mul_6)[name = string("linear_1")];
            tensor<int32, [3]> reshape_3_shape_0 = const()[name = string("reshape_3_shape_0"), val = tensor<int32, [3]>([256, 2, 44])];
            tensor<fp16, [256, 2, 44]> reshape_3 = reshape(shape = reshape_3_shape_0, x = linear_1)[name = string("reshape_3")];
            tensor<int32, [3]> transpose_1_perm_0 = const()[name = string("transpose_1_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [88, 352]> linear_2_weight_0 = const()[name = string("linear_2_weight_0"), val = tensor<fp16, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312512)))];
            tensor<fp16, [88]> linear_2_bias_0 = const()[name = string("linear_2_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [256, 88]> linear_2 = linear(bias = linear_2_bias_0, weight = linear_2_weight_0, x = mul_6)[name = string("linear_2")];
            tensor<int32, [3]> reshape_4_shape_0 = const()[name = string("reshape_4_shape_0"), val = tensor<int32, [3]>([256, 2, 44])];
            tensor<fp16, [256, 2, 44]> reshape_4 = reshape(shape = reshape_4_shape_0, x = linear_2)[name = string("reshape_4")];
            tensor<int32, [3]> transpose_2_perm_0 = const()[name = string("transpose_2_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 256, 44]> transpose_0 = transpose(perm = transpose_0_perm_0, x = reshape_2)[name = string("transpose_63")];
            tensor<fp16, [8, 256, 44]> mul_7 = mul(x = transpose_0, y = transpose_0)[name = string("mul_7")];
            tensor<int32, [1]> reduce_mean_2_axes_0 = const()[name = string("reduce_mean_2_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_2_keep_dims_0 = const()[name = string("reduce_mean_2_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 256, 1]> reduce_mean_2 = reduce_mean(axes = reduce_mean_2_axes_0, keep_dims = reduce_mean_2_keep_dims_0, x = mul_7)[name = string("reduce_mean_2")];
            fp32 rsqrt_2_epsilon_0 = const()[name = string("rsqrt_2_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 256, 1]> rsqrt_2 = rsqrt(epsilon = rsqrt_2_epsilon_0, x = reduce_mean_2)[name = string("rsqrt_2")];
            tensor<fp16, [8, 256, 44]> mul_8 = mul(x = transpose_0, y = rsqrt_2)[name = string("mul_8")];
            tensor<fp16, [44]> mul_9_y_0 = const()[name = string("mul_9_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374528)))];
            tensor<fp16, [8, 256, 44]> mul_9 = mul(x = mul_8, y = mul_9_y_0)[name = string("mul_9")];
            tensor<int32, [3]> slice_by_index_0_begin_0 = const()[name = string("slice_by_index_0_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_0_end_0 = const()[name = string("slice_by_index_0_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_0_end_mask_0 = const()[name = string("slice_by_index_0_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 256, 22]> slice_by_index_0 = slice_by_index(begin = slice_by_index_0_begin_0, end = slice_by_index_0_end_0, end_mask = slice_by_index_0_end_mask_0, x = mul_9)[name = string("slice_by_index_0")];
            tensor<int32, [3]> slice_by_index_1_begin_0 = const()[name = string("slice_by_index_1_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_1_end_0 = const()[name = string("slice_by_index_1_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_1_end_mask_0 = const()[name = string("slice_by_index_1_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 256, 22]> slice_by_index_1 = slice_by_index(begin = slice_by_index_1_begin_0, end = slice_by_index_1_end_0, end_mask = slice_by_index_1_end_mask_0, x = mul_9)[name = string("slice_by_index_1")];
            int32 concat_0_axis_0 = const()[name = string("concat_0_axis_0"), val = int32(-1)];
            bool concat_0_interleave_0 = const()[name = string("concat_0_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 256, 44]> concat_0 = concat(axis = concat_0_axis_0, interleave = concat_0_interleave_0, values = (slice_by_index_1, slice_by_index_0))[name = string("concat_0")];
            tensor<fp16, [44]> mul_10_y_0 = const()[name = string("mul_10_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 256, 44]> mul_10 = mul(x = concat_0, y = mul_10_y_0)[name = string("mul_10")];
            tensor<fp16, [1, 256, 44]> mul_11_y_0 = const()[name = string("mul_11_y_0"), val = tensor<fp16, [1, 256, 44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16067584)))];
            tensor<fp16, [8, 256, 44]> mul_11 = mul(x = mul_9, y = mul_11_y_0)[name = string("mul_11")];
            tensor<fp16, [1, 256, 44]> mul_12_y_0 = const()[name = string("mul_12_y_0"), val = tensor<fp16, [1, 256, 44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16090176)))];
            tensor<fp16, [8, 256, 44]> mul_12 = mul(x = mul_10, y = mul_12_y_0)[name = string("mul_12")];
            tensor<fp16, [8, 256, 44]> add_0 = add(x = mul_11, y = mul_12)[name = string("add_0")];
            tensor<fp16, [2, 256, 44]> transpose_1 = transpose(perm = transpose_1_perm_0, x = reshape_3)[name = string("transpose_62")];
            tensor<fp16, [2, 256, 44]> mul_13 = mul(x = transpose_1, y = transpose_1)[name = string("mul_13")];
            tensor<int32, [1]> reduce_mean_3_axes_0 = const()[name = string("reduce_mean_3_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_3_keep_dims_0 = const()[name = string("reduce_mean_3_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 256, 1]> reduce_mean_3 = reduce_mean(axes = reduce_mean_3_axes_0, keep_dims = reduce_mean_3_keep_dims_0, x = mul_13)[name = string("reduce_mean_3")];
            fp32 rsqrt_3_epsilon_0 = const()[name = string("rsqrt_3_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 256, 1]> rsqrt_3 = rsqrt(epsilon = rsqrt_3_epsilon_0, x = reduce_mean_3)[name = string("rsqrt_3")];
            tensor<fp16, [2, 256, 44]> mul_14 = mul(x = transpose_1, y = rsqrt_3)[name = string("mul_14")];
            tensor<fp16, [44]> mul_15_y_0 = const()[name = string("mul_15_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(376448)))];
            tensor<fp16, [2, 256, 44]> mul_15 = mul(x = mul_14, y = mul_15_y_0)[name = string("mul_15")];
            tensor<int32, [3]> slice_by_index_2_begin_0 = const()[name = string("slice_by_index_2_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_2_end_0 = const()[name = string("slice_by_index_2_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_2_end_mask_0 = const()[name = string("slice_by_index_2_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 256, 22]> slice_by_index_2 = slice_by_index(begin = slice_by_index_2_begin_0, end = slice_by_index_2_end_0, end_mask = slice_by_index_2_end_mask_0, x = mul_15)[name = string("slice_by_index_2")];
            tensor<int32, [3]> slice_by_index_3_begin_0 = const()[name = string("slice_by_index_3_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_3_end_0 = const()[name = string("slice_by_index_3_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_3_end_mask_0 = const()[name = string("slice_by_index_3_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 256, 22]> slice_by_index_3 = slice_by_index(begin = slice_by_index_3_begin_0, end = slice_by_index_3_end_0, end_mask = slice_by_index_3_end_mask_0, x = mul_15)[name = string("slice_by_index_3")];
            int32 concat_1_axis_0 = const()[name = string("concat_1_axis_0"), val = int32(-1)];
            bool concat_1_interleave_0 = const()[name = string("concat_1_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 256, 44]> concat_1 = concat(axis = concat_1_axis_0, interleave = concat_1_interleave_0, values = (slice_by_index_3, slice_by_index_2))[name = string("concat_1")];
            tensor<fp16, [44]> mul_16_y_0 = const()[name = string("mul_16_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 256, 44]> mul_16 = mul(x = concat_1, y = mul_16_y_0)[name = string("mul_16")];
            tensor<fp16, [2, 256, 44]> mul_17 = mul(x = mul_15, y = mul_11_y_0)[name = string("mul_17")];
            tensor<fp16, [2, 256, 44]> mul_18 = mul(x = mul_16, y = mul_12_y_0)[name = string("mul_18")];
            tensor<fp16, [2, 256, 44]> add_1 = add(x = mul_17, y = mul_18)[name = string("add_1")];
            tensor<int32, [4]> reshape_5_shape_0 = const()[name = string("reshape_5_shape_0"), val = tensor<int32, [4]>([2, 1, 256, 44])];
            tensor<fp16, [2, 1, 256, 44]> reshape_5 = reshape(shape = reshape_5_shape_0, x = add_1)[name = string("reshape_5")];
            tensor<int32, [4]> tile_0_reps_0 = const()[name = string("tile_0_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 256, 44]> tile_0 = tile(reps = tile_0_reps_0, x = reshape_5)[name = string("tile_0")];
            tensor<int32, [3]> reshape_6_shape_0 = const()[name = string("reshape_6_shape_0"), val = tensor<int32, [3]>([8, 256, 44])];
            tensor<fp16, [8, 256, 44]> reshape_6 = reshape(shape = reshape_6_shape_0, x = tile_0)[name = string("reshape_6")];
            tensor<int32, [4]> reshape_7_shape_0 = const()[name = string("reshape_7_shape_0"), val = tensor<int32, [4]>([2, 1, 256, 44])];
            tensor<fp16, [2, 256, 44]> transpose_2 = transpose(perm = transpose_2_perm_0, x = reshape_4)[name = string("transpose_61")];
            tensor<fp16, [2, 1, 256, 44]> reshape_7 = reshape(shape = reshape_7_shape_0, x = transpose_2)[name = string("reshape_7")];
            tensor<int32, [4]> tile_1_reps_0 = const()[name = string("tile_1_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 256, 44]> tile_1 = tile(reps = tile_1_reps_0, x = reshape_7)[name = string("tile_1")];
            tensor<int32, [3]> reshape_8_shape_0 = const()[name = string("reshape_8_shape_0"), val = tensor<int32, [3]>([8, 256, 44])];
            tensor<fp16, [8, 256, 44]> reshape_8 = reshape(shape = reshape_8_shape_0, x = tile_1)[name = string("reshape_8")];
            fp16 mul_19_y_0 = const()[name = string("mul_19_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 256, 44]> mul_19 = mul(x = add_0, y = mul_19_y_0)[name = string("mul_19")];
            bool matmul_0_transpose_y_0 = const()[name = string("matmul_0_transpose_y_0"), val = bool(true)];
            bool matmul_0_transpose_x_0 = const()[name = string("matmul_0_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 256, 256]> matmul_0 = matmul(transpose_x = matmul_0_transpose_x_0, transpose_y = matmul_0_transpose_y_0, x = mul_19, y = reshape_6)[name = string("matmul_0")];
            tensor<fp16, [8, 256, 256]> add_2 = add(x = matmul_0, y = reshape_1)[name = string("add_2")];
            int32 softmax_0_axis_0 = const()[name = string("softmax_0_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 256, 256]> softmax_0 = softmax(axis = softmax_0_axis_0, x = add_2)[name = string("softmax_0")];
            bool matmul_1_transpose_x_0 = const()[name = string("matmul_1_transpose_x_0"), val = bool(false)];
            bool matmul_1_transpose_y_0 = const()[name = string("matmul_1_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 256, 44]> matmul_1 = matmul(transpose_x = matmul_1_transpose_x_0, transpose_y = matmul_1_transpose_y_0, x = softmax_0, y = reshape_8)[name = string("matmul_1")];
            tensor<int32, [3]> transpose_3_perm_0 = const()[name = string("transpose_3_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_9_shape_0 = const()[name = string("reshape_9_shape_0"), val = tensor<int32, [2]>([256, 352])];
            tensor<fp16, [256, 8, 44]> transpose_3 = transpose(perm = transpose_3_perm_0, x = matmul_1)[name = string("transpose_60")];
            tensor<fp16, [256, 352]> reshape_9 = reshape(shape = reshape_9_shape_0, x = transpose_3)[name = string("reshape_9")];
            tensor<fp16, [352, 352]> linear_3_weight_0 = const()[name = string("linear_3_weight_0"), val = tensor<fp16, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(376640)))];
            tensor<fp16, [256, 352]> linear_3 = linear(bias = linear_0_bias_0, weight = linear_3_weight_0, x = reshape_9)[name = string("linear_3")];
            tensor<fp16, [256, 352]> add_3 = add(x = mul_2, y = linear_3)[name = string("add_3")];
            tensor<fp16, [256, 352]> mul_20 = mul(x = add_3, y = add_3)[name = string("mul_20")];
            tensor<int32, [1]> reduce_mean_4_axes_0 = const()[name = string("reduce_mean_4_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_4_keep_dims_0 = const()[name = string("reduce_mean_4_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_4 = reduce_mean(axes = reduce_mean_4_axes_0, keep_dims = reduce_mean_4_keep_dims_0, x = mul_20)[name = string("reduce_mean_4")];
            fp32 rsqrt_4_epsilon_0 = const()[name = string("rsqrt_4_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_4 = rsqrt(epsilon = rsqrt_4_epsilon_0, x = reduce_mean_4)[name = string("rsqrt_4")];
            tensor<fp16, [256, 352]> mul_21 = mul(x = add_3, y = rsqrt_4)[name = string("mul_21")];
            tensor<fp16, [352]> mul_22_y_0 = const()[name = string("mul_22_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(624512)))];
            tensor<fp16, [256, 352]> mul_22 = mul(x = mul_21, y = mul_22_y_0)[name = string("mul_22")];
            tensor<fp16, [960, 352]> linear_4_weight_0 = const()[name = string("linear_4_weight_0"), val = tensor<fp16, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(625280)))];
            tensor<fp16, [960]> linear_4_bias_0 = const()[name = string("linear_4_bias_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1301184)))];
            tensor<fp16, [256, 960]> linear_4 = linear(bias = linear_4_bias_0, weight = linear_4_weight_0, x = mul_22)[name = string("linear_4")];
            tensor<fp16, [960, 352]> linear_5_weight_0 = const()[name = string("linear_5_weight_0"), val = tensor<fp16, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1303168)))];
            tensor<fp16, [256, 960]> linear_5 = linear(bias = linear_4_bias_0, weight = linear_5_weight_0, x = mul_22)[name = string("linear_5")];
            fp16 mul_23_y_0 = const()[name = string("mul_23_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [256, 960]> mul_23 = mul(x = linear_4, y = mul_23_y_0)[name = string("mul_23")];
            tensor<fp16, [256, 960]> tanh_0 = tanh(x = mul_23)[name = string("tanh_0")];
            fp16 mul_24_x_0 = const()[name = string("mul_24_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [256, 960]> mul_24 = mul(x = mul_24_x_0, y = tanh_0)[name = string("mul_24")];
            fp16 add_4_x_0 = const()[name = string("add_4_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [256, 960]> add_4 = add(x = add_4_x_0, y = mul_24)[name = string("add_4")];
            tensor<fp16, [256, 960]> mul_25 = mul(x = linear_4, y = add_4)[name = string("mul_25")];
            tensor<fp16, [256, 960]> mul_26 = mul(x = mul_25, y = linear_5)[name = string("mul_26")];
            tensor<fp16, [352, 960]> linear_6_weight_0 = const()[name = string("linear_6_weight_0"), val = tensor<fp16, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1979072)))];
            tensor<fp16, [256, 352]> linear_6 = linear(bias = linear_0_bias_0, weight = linear_6_weight_0, x = mul_26)[name = string("linear_6")];
            tensor<fp16, [256, 352]> add_5 = add(x = add_3, y = linear_6)[name = string("add_5")];
            tensor<fp16, [256, 352]> mul_27 = mul(x = add_5, y = add_5)[name = string("mul_27")];
            tensor<int32, [1]> reduce_mean_5_axes_0 = const()[name = string("reduce_mean_5_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_5_keep_dims_0 = const()[name = string("reduce_mean_5_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_5 = reduce_mean(axes = reduce_mean_5_axes_0, keep_dims = reduce_mean_5_keep_dims_0, x = mul_27)[name = string("reduce_mean_5")];
            fp32 rsqrt_5_epsilon_0 = const()[name = string("rsqrt_5_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_5 = rsqrt(epsilon = rsqrt_5_epsilon_0, x = reduce_mean_5)[name = string("rsqrt_5")];
            tensor<fp16, [256, 352]> mul_28 = mul(x = add_5, y = rsqrt_5)[name = string("mul_28")];
            tensor<fp16, [352]> mul_29_y_0 = const()[name = string("mul_29_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2654976)))];
            tensor<fp16, [256, 352]> mul_29 = mul(x = mul_28, y = mul_29_y_0)[name = string("mul_29")];
            tensor<fp16, [256, 352]> mul_30 = mul(x = mul_29, y = mul_29)[name = string("mul_30")];
            tensor<int32, [1]> reduce_mean_6_axes_0 = const()[name = string("reduce_mean_6_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_6_keep_dims_0 = const()[name = string("reduce_mean_6_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_6 = reduce_mean(axes = reduce_mean_6_axes_0, keep_dims = reduce_mean_6_keep_dims_0, x = mul_30)[name = string("reduce_mean_6")];
            fp32 rsqrt_6_epsilon_0 = const()[name = string("rsqrt_6_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_6 = rsqrt(epsilon = rsqrt_6_epsilon_0, x = reduce_mean_6)[name = string("rsqrt_6")];
            tensor<fp16, [256, 352]> mul_31 = mul(x = mul_29, y = rsqrt_6)[name = string("mul_31")];
            tensor<fp16, [352]> mul_32_y_0 = const()[name = string("mul_32_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2655744)))];
            tensor<fp16, [256, 352]> mul_32 = mul(x = mul_31, y = mul_32_y_0)[name = string("mul_32")];
            tensor<fp16, [352, 352]> tern_1_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2656512))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_1_q_weight_0_palettized")];
            tensor<fp16, [256, 352]> tern_1_q = linear(bias = linear_0_bias_0, weight = tern_1_q_weight_0_palettized, x = mul_32)[name = string("tern_1_q")];
            tensor<fp16, [352]> mul_33_y_0 = const()[name = string("mul_33_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2687552)))];
            tensor<fp16, [256, 352]> mul_33 = mul(x = tern_1_q, y = mul_33_y_0)[name = string("mul_33")];
            tensor<int32, [3]> reshape_10_shape_0 = const()[name = string("reshape_10_shape_0"), val = tensor<int32, [3]>([256, 8, 44])];
            tensor<fp16, [256, 8, 44]> reshape_10 = reshape(shape = reshape_10_shape_0, x = mul_33)[name = string("reshape_10")];
            tensor<int32, [3]> transpose_4_perm_0 = const()[name = string("transpose_4_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_36_y_0 = const()[name = string("mul_36_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2688320)))];
            tensor<fp16, [256, 352]> mul_36 = mul(x = mul_31, y = mul_36_y_0)[name = string("mul_36")];
            tensor<fp16, [88, 352]> tern_1_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2689088))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_1_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_1_k_bias_0 = const()[name = string("tern_1_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [256, 88]> tern_1_k = linear(bias = tern_1_k_bias_0, weight = tern_1_k_weight_0_palettized, x = mul_36)[name = string("tern_1_k")];
            tensor<fp16, [88]> mul_37_y_0 = const()[name = string("mul_37_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2696896)))];
            tensor<fp16, [256, 88]> mul_37 = mul(x = tern_1_k, y = mul_37_y_0)[name = string("mul_37")];
            tensor<int32, [3]> reshape_11_shape_0 = const()[name = string("reshape_11_shape_0"), val = tensor<int32, [3]>([256, 2, 44])];
            tensor<fp16, [256, 2, 44]> reshape_11 = reshape(shape = reshape_11_shape_0, x = mul_37)[name = string("reshape_11")];
            tensor<int32, [3]> transpose_5_perm_0 = const()[name = string("transpose_5_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_40_y_0 = const()[name = string("mul_40_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2697152)))];
            tensor<fp16, [256, 352]> mul_40 = mul(x = mul_31, y = mul_40_y_0)[name = string("mul_40")];
            tensor<fp16, [88, 352]> tern_1_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2697920))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_1_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_1_v_bias_0 = const()[name = string("tern_1_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [256, 88]> tern_1_v = linear(bias = tern_1_v_bias_0, weight = tern_1_v_weight_0_palettized, x = mul_40)[name = string("tern_1_v")];
            tensor<fp16, [88]> mul_41_y_0 = const()[name = string("mul_41_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2705728)))];
            tensor<fp16, [256, 88]> mul_41 = mul(x = tern_1_v, y = mul_41_y_0)[name = string("mul_41")];
            tensor<int32, [3]> reshape_12_shape_0 = const()[name = string("reshape_12_shape_0"), val = tensor<int32, [3]>([256, 2, 44])];
            tensor<fp16, [256, 2, 44]> reshape_12 = reshape(shape = reshape_12_shape_0, x = mul_41)[name = string("reshape_12")];
            tensor<int32, [3]> transpose_6_perm_0 = const()[name = string("transpose_6_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 256, 44]> transpose_4 = transpose(perm = transpose_4_perm_0, x = reshape_10)[name = string("transpose_59")];
            tensor<fp16, [8, 256, 44]> mul_42 = mul(x = transpose_4, y = transpose_4)[name = string("mul_42")];
            tensor<int32, [1]> reduce_mean_9_axes_0 = const()[name = string("reduce_mean_9_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_9_keep_dims_0 = const()[name = string("reduce_mean_9_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 256, 1]> reduce_mean_9 = reduce_mean(axes = reduce_mean_9_axes_0, keep_dims = reduce_mean_9_keep_dims_0, x = mul_42)[name = string("reduce_mean_9")];
            fp32 rsqrt_9_epsilon_0 = const()[name = string("rsqrt_9_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 256, 1]> rsqrt_9 = rsqrt(epsilon = rsqrt_9_epsilon_0, x = reduce_mean_9)[name = string("rsqrt_9")];
            tensor<fp16, [8, 256, 44]> mul_43 = mul(x = transpose_4, y = rsqrt_9)[name = string("mul_43")];
            tensor<fp16, [44]> mul_44_y_0 = const()[name = string("mul_44_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2705984)))];
            tensor<fp16, [8, 256, 44]> mul_44 = mul(x = mul_43, y = mul_44_y_0)[name = string("mul_44")];
            tensor<int32, [3]> slice_by_index_4_begin_0 = const()[name = string("slice_by_index_4_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_4_end_0 = const()[name = string("slice_by_index_4_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_4_end_mask_0 = const()[name = string("slice_by_index_4_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 256, 22]> slice_by_index_4 = slice_by_index(begin = slice_by_index_4_begin_0, end = slice_by_index_4_end_0, end_mask = slice_by_index_4_end_mask_0, x = mul_44)[name = string("slice_by_index_4")];
            tensor<int32, [3]> slice_by_index_5_begin_0 = const()[name = string("slice_by_index_5_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_5_end_0 = const()[name = string("slice_by_index_5_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_5_end_mask_0 = const()[name = string("slice_by_index_5_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 256, 22]> slice_by_index_5 = slice_by_index(begin = slice_by_index_5_begin_0, end = slice_by_index_5_end_0, end_mask = slice_by_index_5_end_mask_0, x = mul_44)[name = string("slice_by_index_5")];
            int32 concat_2_axis_0 = const()[name = string("concat_2_axis_0"), val = int32(-1)];
            bool concat_2_interleave_0 = const()[name = string("concat_2_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 256, 44]> concat_2 = concat(axis = concat_2_axis_0, interleave = concat_2_interleave_0, values = (slice_by_index_5, slice_by_index_4))[name = string("concat_2")];
            tensor<fp16, [44]> mul_45_y_0 = const()[name = string("mul_45_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 256, 44]> mul_45 = mul(x = concat_2, y = mul_45_y_0)[name = string("mul_45")];
            tensor<fp16, [8, 256, 44]> mul_46 = mul(x = mul_44, y = mul_11_y_0)[name = string("mul_46")];
            tensor<fp16, [8, 256, 44]> mul_47 = mul(x = mul_45, y = mul_12_y_0)[name = string("mul_47")];
            tensor<fp16, [8, 256, 44]> add_6 = add(x = mul_46, y = mul_47)[name = string("add_6")];
            tensor<fp16, [2, 256, 44]> transpose_5 = transpose(perm = transpose_5_perm_0, x = reshape_11)[name = string("transpose_58")];
            tensor<fp16, [2, 256, 44]> mul_48 = mul(x = transpose_5, y = transpose_5)[name = string("mul_48")];
            tensor<int32, [1]> reduce_mean_10_axes_0 = const()[name = string("reduce_mean_10_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_10_keep_dims_0 = const()[name = string("reduce_mean_10_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 256, 1]> reduce_mean_10 = reduce_mean(axes = reduce_mean_10_axes_0, keep_dims = reduce_mean_10_keep_dims_0, x = mul_48)[name = string("reduce_mean_10")];
            fp32 rsqrt_10_epsilon_0 = const()[name = string("rsqrt_10_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 256, 1]> rsqrt_10 = rsqrt(epsilon = rsqrt_10_epsilon_0, x = reduce_mean_10)[name = string("rsqrt_10")];
            tensor<fp16, [2, 256, 44]> mul_49 = mul(x = transpose_5, y = rsqrt_10)[name = string("mul_49")];
            tensor<fp16, [44]> mul_50_y_0 = const()[name = string("mul_50_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2706176)))];
            tensor<fp16, [2, 256, 44]> mul_50 = mul(x = mul_49, y = mul_50_y_0)[name = string("mul_50")];
            tensor<int32, [3]> slice_by_index_6_begin_0 = const()[name = string("slice_by_index_6_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_6_end_0 = const()[name = string("slice_by_index_6_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_6_end_mask_0 = const()[name = string("slice_by_index_6_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 256, 22]> slice_by_index_6 = slice_by_index(begin = slice_by_index_6_begin_0, end = slice_by_index_6_end_0, end_mask = slice_by_index_6_end_mask_0, x = mul_50)[name = string("slice_by_index_6")];
            tensor<int32, [3]> slice_by_index_7_begin_0 = const()[name = string("slice_by_index_7_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_7_end_0 = const()[name = string("slice_by_index_7_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_7_end_mask_0 = const()[name = string("slice_by_index_7_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 256, 22]> slice_by_index_7 = slice_by_index(begin = slice_by_index_7_begin_0, end = slice_by_index_7_end_0, end_mask = slice_by_index_7_end_mask_0, x = mul_50)[name = string("slice_by_index_7")];
            int32 concat_3_axis_0 = const()[name = string("concat_3_axis_0"), val = int32(-1)];
            bool concat_3_interleave_0 = const()[name = string("concat_3_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 256, 44]> concat_3 = concat(axis = concat_3_axis_0, interleave = concat_3_interleave_0, values = (slice_by_index_7, slice_by_index_6))[name = string("concat_3")];
            tensor<fp16, [44]> mul_51_y_0 = const()[name = string("mul_51_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 256, 44]> mul_51 = mul(x = concat_3, y = mul_51_y_0)[name = string("mul_51")];
            tensor<fp16, [2, 256, 44]> mul_52 = mul(x = mul_50, y = mul_11_y_0)[name = string("mul_52")];
            tensor<fp16, [2, 256, 44]> mul_53 = mul(x = mul_51, y = mul_12_y_0)[name = string("mul_53")];
            tensor<fp16, [2, 256, 44]> add_7 = add(x = mul_52, y = mul_53)[name = string("add_7")];
            tensor<int32, [4]> reshape_13_shape_0 = const()[name = string("reshape_13_shape_0"), val = tensor<int32, [4]>([2, 1, 256, 44])];
            tensor<fp16, [2, 1, 256, 44]> reshape_13 = reshape(shape = reshape_13_shape_0, x = add_7)[name = string("reshape_13")];
            tensor<int32, [4]> tile_2_reps_0 = const()[name = string("tile_2_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 256, 44]> tile_2 = tile(reps = tile_2_reps_0, x = reshape_13)[name = string("tile_2")];
            tensor<int32, [3]> reshape_14_shape_0 = const()[name = string("reshape_14_shape_0"), val = tensor<int32, [3]>([8, 256, 44])];
            tensor<fp16, [8, 256, 44]> reshape_14 = reshape(shape = reshape_14_shape_0, x = tile_2)[name = string("reshape_14")];
            tensor<int32, [4]> reshape_15_shape_0 = const()[name = string("reshape_15_shape_0"), val = tensor<int32, [4]>([2, 1, 256, 44])];
            tensor<fp16, [2, 256, 44]> transpose_6 = transpose(perm = transpose_6_perm_0, x = reshape_12)[name = string("transpose_57")];
            tensor<fp16, [2, 1, 256, 44]> reshape_15 = reshape(shape = reshape_15_shape_0, x = transpose_6)[name = string("reshape_15")];
            tensor<int32, [4]> tile_3_reps_0 = const()[name = string("tile_3_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 256, 44]> tile_3 = tile(reps = tile_3_reps_0, x = reshape_15)[name = string("tile_3")];
            tensor<int32, [3]> reshape_16_shape_0 = const()[name = string("reshape_16_shape_0"), val = tensor<int32, [3]>([8, 256, 44])];
            tensor<fp16, [8, 256, 44]> reshape_16 = reshape(shape = reshape_16_shape_0, x = tile_3)[name = string("reshape_16")];
            fp16 mul_54_y_0 = const()[name = string("mul_54_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 256, 44]> mul_54 = mul(x = add_6, y = mul_54_y_0)[name = string("mul_54")];
            bool matmul_2_transpose_y_0 = const()[name = string("matmul_2_transpose_y_0"), val = bool(true)];
            bool matmul_2_transpose_x_0 = const()[name = string("matmul_2_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 256, 256]> matmul_2 = matmul(transpose_x = matmul_2_transpose_x_0, transpose_y = matmul_2_transpose_y_0, x = mul_54, y = reshape_14)[name = string("matmul_2")];
            tensor<fp16, [8, 256, 256]> add_8 = add(x = matmul_2, y = reshape_1)[name = string("add_8")];
            int32 softmax_1_axis_0 = const()[name = string("softmax_1_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 256, 256]> softmax_1 = softmax(axis = softmax_1_axis_0, x = add_8)[name = string("softmax_1")];
            bool matmul_3_transpose_x_0 = const()[name = string("matmul_3_transpose_x_0"), val = bool(false)];
            bool matmul_3_transpose_y_0 = const()[name = string("matmul_3_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 256, 44]> matmul_3 = matmul(transpose_x = matmul_3_transpose_x_0, transpose_y = matmul_3_transpose_y_0, x = softmax_1, y = reshape_16)[name = string("matmul_3")];
            tensor<int32, [3]> transpose_7_perm_0 = const()[name = string("transpose_7_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_17_shape_0 = const()[name = string("reshape_17_shape_0"), val = tensor<int32, [2]>([256, 352])];
            tensor<fp16, [256, 8, 44]> transpose_7 = transpose(perm = transpose_7_perm_0, x = matmul_3)[name = string("transpose_56")];
            tensor<fp16, [256, 352]> reshape_17 = reshape(shape = reshape_17_shape_0, x = transpose_7)[name = string("reshape_17")];
            tensor<fp16, [256, 352]> mul_55 = mul(x = reshape_17, y = reshape_17)[name = string("mul_55")];
            tensor<int32, [1]> reduce_mean_11_axes_0 = const()[name = string("reduce_mean_11_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_11_keep_dims_0 = const()[name = string("reduce_mean_11_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_11 = reduce_mean(axes = reduce_mean_11_axes_0, keep_dims = reduce_mean_11_keep_dims_0, x = mul_55)[name = string("reduce_mean_11")];
            fp32 rsqrt_11_epsilon_0 = const()[name = string("rsqrt_11_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_11 = rsqrt(epsilon = rsqrt_11_epsilon_0, x = reduce_mean_11)[name = string("rsqrt_11")];
            tensor<fp16, [256, 352]> mul_56 = mul(x = reshape_17, y = rsqrt_11)[name = string("mul_56")];
            tensor<fp16, [352]> mul_57_y_0 = const()[name = string("mul_57_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2706368)))];
            tensor<fp16, [256, 352]> mul_57 = mul(x = mul_56, y = mul_57_y_0)[name = string("mul_57")];
            tensor<fp16, [352, 352]> tern_1_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2707136))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_1_o_weight_0_palettized")];
            tensor<fp16, [256, 352]> tern_1_o = linear(bias = linear_0_bias_0, weight = tern_1_o_weight_0_palettized, x = mul_57)[name = string("tern_1_o")];
            tensor<fp16, [352]> mul_58_y_0 = const()[name = string("mul_58_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2738176)))];
            tensor<fp16, [256, 352]> mul_58 = mul(x = tern_1_o, y = mul_58_y_0)[name = string("mul_58")];
            tensor<fp16, [256, 352]> add_9 = add(x = add_5, y = mul_58)[name = string("add_9")];
            tensor<fp16, [256, 352]> mul_59 = mul(x = add_9, y = add_9)[name = string("mul_59")];
            tensor<int32, [1]> reduce_mean_12_axes_0 = const()[name = string("reduce_mean_12_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_12_keep_dims_0 = const()[name = string("reduce_mean_12_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_12 = reduce_mean(axes = reduce_mean_12_axes_0, keep_dims = reduce_mean_12_keep_dims_0, x = mul_59)[name = string("reduce_mean_12")];
            fp32 rsqrt_12_epsilon_0 = const()[name = string("rsqrt_12_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_12 = rsqrt(epsilon = rsqrt_12_epsilon_0, x = reduce_mean_12)[name = string("rsqrt_12")];
            tensor<fp16, [256, 352]> mul_60 = mul(x = add_9, y = rsqrt_12)[name = string("mul_60")];
            tensor<fp16, [352]> mul_61_y_0 = const()[name = string("mul_61_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2738944)))];
            tensor<fp16, [256, 352]> mul_61 = mul(x = mul_60, y = mul_61_y_0)[name = string("mul_61")];
            tensor<fp16, [256, 352]> mul_62 = mul(x = mul_61, y = mul_61)[name = string("mul_62")];
            tensor<int32, [1]> reduce_mean_13_axes_0 = const()[name = string("reduce_mean_13_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_13_keep_dims_0 = const()[name = string("reduce_mean_13_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_13 = reduce_mean(axes = reduce_mean_13_axes_0, keep_dims = reduce_mean_13_keep_dims_0, x = mul_62)[name = string("reduce_mean_13")];
            fp32 rsqrt_13_epsilon_0 = const()[name = string("rsqrt_13_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_13 = rsqrt(epsilon = rsqrt_13_epsilon_0, x = reduce_mean_13)[name = string("rsqrt_13")];
            tensor<fp16, [256, 352]> mul_63 = mul(x = mul_61, y = rsqrt_13)[name = string("mul_63")];
            tensor<fp16, [352]> mul_64_y_0 = const()[name = string("mul_64_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2739712)))];
            tensor<fp16, [256, 352]> mul_64 = mul(x = mul_63, y = mul_64_y_0)[name = string("mul_64")];
            tensor<fp16, [960, 352]> tern_1_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2740480))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_1_w1_weight_0_palettized")];
            tensor<fp16, [256, 960]> tern_1_w1 = linear(bias = linear_4_bias_0, weight = tern_1_w1_weight_0_palettized, x = mul_64)[name = string("tern_1_w1")];
            tensor<fp16, [960]> mul_65_y_0 = const()[name = string("mul_65_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2825024)))];
            tensor<fp16, [256, 960]> mul_65 = mul(x = tern_1_w1, y = mul_65_y_0)[name = string("mul_65")];
            tensor<fp16, [352]> mul_68_y_0 = const()[name = string("mul_68_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2827008)))];
            tensor<fp16, [256, 352]> mul_68 = mul(x = mul_63, y = mul_68_y_0)[name = string("mul_68")];
            tensor<fp16, [960, 352]> tern_1_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2827776))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_1_w3_weight_0_palettized")];
            tensor<fp16, [256, 960]> tern_1_w3 = linear(bias = linear_4_bias_0, weight = tern_1_w3_weight_0_palettized, x = mul_68)[name = string("tern_1_w3")];
            tensor<fp16, [960]> mul_69_y_0 = const()[name = string("mul_69_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2912320)))];
            tensor<fp16, [256, 960]> mul_69 = mul(x = tern_1_w3, y = mul_69_y_0)[name = string("mul_69")];
            fp16 mul_70_y_0 = const()[name = string("mul_70_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [256, 960]> mul_70 = mul(x = mul_65, y = mul_70_y_0)[name = string("mul_70")];
            tensor<fp16, [256, 960]> tanh_1 = tanh(x = mul_70)[name = string("tanh_1")];
            fp16 mul_71_x_0 = const()[name = string("mul_71_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [256, 960]> mul_71 = mul(x = mul_71_x_0, y = tanh_1)[name = string("mul_71")];
            fp16 add_10_x_0 = const()[name = string("add_10_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [256, 960]> add_10 = add(x = add_10_x_0, y = mul_71)[name = string("add_10")];
            tensor<fp16, [256, 960]> mul_72 = mul(x = mul_65, y = add_10)[name = string("mul_72")];
            tensor<fp16, [256, 960]> mul_73 = mul(x = mul_72, y = mul_69)[name = string("mul_73")];
            tensor<fp16, [256, 960]> mul_74 = mul(x = mul_73, y = mul_73)[name = string("mul_74")];
            tensor<int32, [1]> reduce_mean_15_axes_0 = const()[name = string("reduce_mean_15_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_15_keep_dims_0 = const()[name = string("reduce_mean_15_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_15 = reduce_mean(axes = reduce_mean_15_axes_0, keep_dims = reduce_mean_15_keep_dims_0, x = mul_74)[name = string("reduce_mean_15")];
            fp32 rsqrt_15_epsilon_0 = const()[name = string("rsqrt_15_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_15 = rsqrt(epsilon = rsqrt_15_epsilon_0, x = reduce_mean_15)[name = string("rsqrt_15")];
            tensor<fp16, [256, 960]> mul_75 = mul(x = mul_73, y = rsqrt_15)[name = string("mul_75")];
            tensor<fp16, [960]> mul_76_y_0 = const()[name = string("mul_76_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2914304)))];
            tensor<fp16, [256, 960]> mul_76 = mul(x = mul_75, y = mul_76_y_0)[name = string("mul_76")];
            tensor<fp16, [352, 960]> tern_1_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2916288))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_1_w2_weight_0_palettized")];
            tensor<fp16, [256, 352]> tern_1_w2 = linear(bias = linear_0_bias_0, weight = tern_1_w2_weight_0_palettized, x = mul_76)[name = string("tern_1_w2")];
            tensor<fp16, [352]> mul_77_y_0 = const()[name = string("mul_77_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3000832)))];
            tensor<fp16, [256, 352]> mul_77 = mul(x = tern_1_w2, y = mul_77_y_0)[name = string("mul_77")];
            tensor<fp16, [256, 352]> add_11 = add(x = add_9, y = mul_77)[name = string("add_11")];
            tensor<fp16, [256, 352]> mul_78 = mul(x = add_11, y = add_11)[name = string("mul_78")];
            tensor<int32, [1]> reduce_mean_16_axes_0 = const()[name = string("reduce_mean_16_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_16_keep_dims_0 = const()[name = string("reduce_mean_16_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_16 = reduce_mean(axes = reduce_mean_16_axes_0, keep_dims = reduce_mean_16_keep_dims_0, x = mul_78)[name = string("reduce_mean_16")];
            fp32 rsqrt_16_epsilon_0 = const()[name = string("rsqrt_16_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_16 = rsqrt(epsilon = rsqrt_16_epsilon_0, x = reduce_mean_16)[name = string("rsqrt_16")];
            tensor<fp16, [256, 352]> mul_79 = mul(x = add_11, y = rsqrt_16)[name = string("mul_79")];
            tensor<fp16, [352]> mul_80_y_0 = const()[name = string("mul_80_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3001600)))];
            tensor<fp16, [256, 352]> mul_80 = mul(x = mul_79, y = mul_80_y_0)[name = string("mul_80")];
            tensor<fp16, [256, 352]> mul_81 = mul(x = mul_80, y = mul_80)[name = string("mul_81")];
            tensor<int32, [1]> reduce_mean_17_axes_0 = const()[name = string("reduce_mean_17_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_17_keep_dims_0 = const()[name = string("reduce_mean_17_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_17 = reduce_mean(axes = reduce_mean_17_axes_0, keep_dims = reduce_mean_17_keep_dims_0, x = mul_81)[name = string("reduce_mean_17")];
            fp32 rsqrt_17_epsilon_0 = const()[name = string("rsqrt_17_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_17 = rsqrt(epsilon = rsqrt_17_epsilon_0, x = reduce_mean_17)[name = string("rsqrt_17")];
            tensor<fp16, [256, 352]> mul_82 = mul(x = mul_80, y = rsqrt_17)[name = string("mul_82")];
            tensor<fp16, [352]> mul_83_y_0 = const()[name = string("mul_83_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3002368)))];
            tensor<fp16, [256, 352]> mul_83 = mul(x = mul_82, y = mul_83_y_0)[name = string("mul_83")];
            tensor<fp16, [352, 352]> tern_2_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3003136))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_2_q_weight_0_palettized")];
            tensor<fp16, [256, 352]> tern_2_q = linear(bias = linear_0_bias_0, weight = tern_2_q_weight_0_palettized, x = mul_83)[name = string("tern_2_q")];
            tensor<fp16, [352]> mul_84_y_0 = const()[name = string("mul_84_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3034176)))];
            tensor<fp16, [256, 352]> mul_84 = mul(x = tern_2_q, y = mul_84_y_0)[name = string("mul_84")];
            tensor<int32, [3]> reshape_18_shape_0 = const()[name = string("reshape_18_shape_0"), val = tensor<int32, [3]>([256, 8, 44])];
            tensor<fp16, [256, 8, 44]> reshape_18 = reshape(shape = reshape_18_shape_0, x = mul_84)[name = string("reshape_18")];
            tensor<int32, [3]> transpose_8_perm_0 = const()[name = string("transpose_8_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_87_y_0 = const()[name = string("mul_87_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3034944)))];
            tensor<fp16, [256, 352]> mul_87 = mul(x = mul_82, y = mul_87_y_0)[name = string("mul_87")];
            tensor<fp16, [88, 352]> tern_2_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3035712))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_2_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_2_k_bias_0 = const()[name = string("tern_2_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [256, 88]> tern_2_k = linear(bias = tern_2_k_bias_0, weight = tern_2_k_weight_0_palettized, x = mul_87)[name = string("tern_2_k")];
            tensor<fp16, [88]> mul_88_y_0 = const()[name = string("mul_88_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3043520)))];
            tensor<fp16, [256, 88]> mul_88 = mul(x = tern_2_k, y = mul_88_y_0)[name = string("mul_88")];
            tensor<int32, [3]> reshape_19_shape_0 = const()[name = string("reshape_19_shape_0"), val = tensor<int32, [3]>([256, 2, 44])];
            tensor<fp16, [256, 2, 44]> reshape_19 = reshape(shape = reshape_19_shape_0, x = mul_88)[name = string("reshape_19")];
            tensor<int32, [3]> transpose_9_perm_0 = const()[name = string("transpose_9_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_91_y_0 = const()[name = string("mul_91_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3043776)))];
            tensor<fp16, [256, 352]> mul_91 = mul(x = mul_82, y = mul_91_y_0)[name = string("mul_91")];
            tensor<fp16, [88, 352]> tern_2_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3044544))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_2_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_2_v_bias_0 = const()[name = string("tern_2_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [256, 88]> tern_2_v = linear(bias = tern_2_v_bias_0, weight = tern_2_v_weight_0_palettized, x = mul_91)[name = string("tern_2_v")];
            tensor<fp16, [88]> mul_92_y_0 = const()[name = string("mul_92_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3052352)))];
            tensor<fp16, [256, 88]> mul_92 = mul(x = tern_2_v, y = mul_92_y_0)[name = string("mul_92")];
            tensor<int32, [3]> reshape_20_shape_0 = const()[name = string("reshape_20_shape_0"), val = tensor<int32, [3]>([256, 2, 44])];
            tensor<fp16, [256, 2, 44]> reshape_20 = reshape(shape = reshape_20_shape_0, x = mul_92)[name = string("reshape_20")];
            tensor<int32, [3]> transpose_10_perm_0 = const()[name = string("transpose_10_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 256, 44]> transpose_8 = transpose(perm = transpose_8_perm_0, x = reshape_18)[name = string("transpose_55")];
            tensor<fp16, [8, 256, 44]> mul_93 = mul(x = transpose_8, y = transpose_8)[name = string("mul_93")];
            tensor<int32, [1]> reduce_mean_20_axes_0 = const()[name = string("reduce_mean_20_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_20_keep_dims_0 = const()[name = string("reduce_mean_20_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 256, 1]> reduce_mean_20 = reduce_mean(axes = reduce_mean_20_axes_0, keep_dims = reduce_mean_20_keep_dims_0, x = mul_93)[name = string("reduce_mean_20")];
            fp32 rsqrt_20_epsilon_0 = const()[name = string("rsqrt_20_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 256, 1]> rsqrt_20 = rsqrt(epsilon = rsqrt_20_epsilon_0, x = reduce_mean_20)[name = string("rsqrt_20")];
            tensor<fp16, [8, 256, 44]> mul_94 = mul(x = transpose_8, y = rsqrt_20)[name = string("mul_94")];
            tensor<fp16, [44]> mul_95_y_0 = const()[name = string("mul_95_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3052608)))];
            tensor<fp16, [8, 256, 44]> mul_95 = mul(x = mul_94, y = mul_95_y_0)[name = string("mul_95")];
            tensor<int32, [3]> slice_by_index_8_begin_0 = const()[name = string("slice_by_index_8_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_8_end_0 = const()[name = string("slice_by_index_8_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_8_end_mask_0 = const()[name = string("slice_by_index_8_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 256, 22]> slice_by_index_8 = slice_by_index(begin = slice_by_index_8_begin_0, end = slice_by_index_8_end_0, end_mask = slice_by_index_8_end_mask_0, x = mul_95)[name = string("slice_by_index_8")];
            tensor<int32, [3]> slice_by_index_9_begin_0 = const()[name = string("slice_by_index_9_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_9_end_0 = const()[name = string("slice_by_index_9_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_9_end_mask_0 = const()[name = string("slice_by_index_9_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 256, 22]> slice_by_index_9 = slice_by_index(begin = slice_by_index_9_begin_0, end = slice_by_index_9_end_0, end_mask = slice_by_index_9_end_mask_0, x = mul_95)[name = string("slice_by_index_9")];
            int32 concat_4_axis_0 = const()[name = string("concat_4_axis_0"), val = int32(-1)];
            bool concat_4_interleave_0 = const()[name = string("concat_4_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 256, 44]> concat_4 = concat(axis = concat_4_axis_0, interleave = concat_4_interleave_0, values = (slice_by_index_9, slice_by_index_8))[name = string("concat_4")];
            tensor<fp16, [44]> mul_96_y_0 = const()[name = string("mul_96_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 256, 44]> mul_96 = mul(x = concat_4, y = mul_96_y_0)[name = string("mul_96")];
            tensor<fp16, [8, 256, 44]> mul_97 = mul(x = mul_95, y = mul_11_y_0)[name = string("mul_97")];
            tensor<fp16, [8, 256, 44]> mul_98 = mul(x = mul_96, y = mul_12_y_0)[name = string("mul_98")];
            tensor<fp16, [8, 256, 44]> add_12 = add(x = mul_97, y = mul_98)[name = string("add_12")];
            tensor<fp16, [2, 256, 44]> transpose_9 = transpose(perm = transpose_9_perm_0, x = reshape_19)[name = string("transpose_54")];
            tensor<fp16, [2, 256, 44]> mul_99 = mul(x = transpose_9, y = transpose_9)[name = string("mul_99")];
            tensor<int32, [1]> reduce_mean_21_axes_0 = const()[name = string("reduce_mean_21_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_21_keep_dims_0 = const()[name = string("reduce_mean_21_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 256, 1]> reduce_mean_21 = reduce_mean(axes = reduce_mean_21_axes_0, keep_dims = reduce_mean_21_keep_dims_0, x = mul_99)[name = string("reduce_mean_21")];
            fp32 rsqrt_21_epsilon_0 = const()[name = string("rsqrt_21_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 256, 1]> rsqrt_21 = rsqrt(epsilon = rsqrt_21_epsilon_0, x = reduce_mean_21)[name = string("rsqrt_21")];
            tensor<fp16, [2, 256, 44]> mul_100 = mul(x = transpose_9, y = rsqrt_21)[name = string("mul_100")];
            tensor<fp16, [44]> mul_101_y_0 = const()[name = string("mul_101_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3052800)))];
            tensor<fp16, [2, 256, 44]> mul_101 = mul(x = mul_100, y = mul_101_y_0)[name = string("mul_101")];
            tensor<int32, [3]> slice_by_index_10_begin_0 = const()[name = string("slice_by_index_10_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_10_end_0 = const()[name = string("slice_by_index_10_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_10_end_mask_0 = const()[name = string("slice_by_index_10_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 256, 22]> slice_by_index_10 = slice_by_index(begin = slice_by_index_10_begin_0, end = slice_by_index_10_end_0, end_mask = slice_by_index_10_end_mask_0, x = mul_101)[name = string("slice_by_index_10")];
            tensor<int32, [3]> slice_by_index_11_begin_0 = const()[name = string("slice_by_index_11_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_11_end_0 = const()[name = string("slice_by_index_11_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_11_end_mask_0 = const()[name = string("slice_by_index_11_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 256, 22]> slice_by_index_11 = slice_by_index(begin = slice_by_index_11_begin_0, end = slice_by_index_11_end_0, end_mask = slice_by_index_11_end_mask_0, x = mul_101)[name = string("slice_by_index_11")];
            int32 concat_5_axis_0 = const()[name = string("concat_5_axis_0"), val = int32(-1)];
            bool concat_5_interleave_0 = const()[name = string("concat_5_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 256, 44]> concat_5 = concat(axis = concat_5_axis_0, interleave = concat_5_interleave_0, values = (slice_by_index_11, slice_by_index_10))[name = string("concat_5")];
            tensor<fp16, [44]> mul_102_y_0 = const()[name = string("mul_102_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 256, 44]> mul_102 = mul(x = concat_5, y = mul_102_y_0)[name = string("mul_102")];
            tensor<fp16, [2, 256, 44]> mul_103 = mul(x = mul_101, y = mul_11_y_0)[name = string("mul_103")];
            tensor<fp16, [2, 256, 44]> mul_104 = mul(x = mul_102, y = mul_12_y_0)[name = string("mul_104")];
            tensor<fp16, [2, 256, 44]> add_13 = add(x = mul_103, y = mul_104)[name = string("add_13")];
            tensor<int32, [4]> reshape_21_shape_0 = const()[name = string("reshape_21_shape_0"), val = tensor<int32, [4]>([2, 1, 256, 44])];
            tensor<fp16, [2, 1, 256, 44]> reshape_21 = reshape(shape = reshape_21_shape_0, x = add_13)[name = string("reshape_21")];
            tensor<int32, [4]> tile_4_reps_0 = const()[name = string("tile_4_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 256, 44]> tile_4 = tile(reps = tile_4_reps_0, x = reshape_21)[name = string("tile_4")];
            tensor<int32, [3]> reshape_22_shape_0 = const()[name = string("reshape_22_shape_0"), val = tensor<int32, [3]>([8, 256, 44])];
            tensor<fp16, [8, 256, 44]> reshape_22 = reshape(shape = reshape_22_shape_0, x = tile_4)[name = string("reshape_22")];
            tensor<int32, [4]> reshape_23_shape_0 = const()[name = string("reshape_23_shape_0"), val = tensor<int32, [4]>([2, 1, 256, 44])];
            tensor<fp16, [2, 256, 44]> transpose_10 = transpose(perm = transpose_10_perm_0, x = reshape_20)[name = string("transpose_53")];
            tensor<fp16, [2, 1, 256, 44]> reshape_23 = reshape(shape = reshape_23_shape_0, x = transpose_10)[name = string("reshape_23")];
            tensor<int32, [4]> tile_5_reps_0 = const()[name = string("tile_5_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 256, 44]> tile_5 = tile(reps = tile_5_reps_0, x = reshape_23)[name = string("tile_5")];
            tensor<int32, [3]> reshape_24_shape_0 = const()[name = string("reshape_24_shape_0"), val = tensor<int32, [3]>([8, 256, 44])];
            tensor<fp16, [8, 256, 44]> reshape_24 = reshape(shape = reshape_24_shape_0, x = tile_5)[name = string("reshape_24")];
            fp16 mul_105_y_0 = const()[name = string("mul_105_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 256, 44]> mul_105 = mul(x = add_12, y = mul_105_y_0)[name = string("mul_105")];
            bool matmul_4_transpose_y_0 = const()[name = string("matmul_4_transpose_y_0"), val = bool(true)];
            bool matmul_4_transpose_x_0 = const()[name = string("matmul_4_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 256, 256]> matmul_4 = matmul(transpose_x = matmul_4_transpose_x_0, transpose_y = matmul_4_transpose_y_0, x = mul_105, y = reshape_22)[name = string("matmul_4")];
            tensor<fp16, [8, 256, 256]> add_14 = add(x = matmul_4, y = reshape_1)[name = string("add_14")];
            int32 softmax_2_axis_0 = const()[name = string("softmax_2_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 256, 256]> softmax_2 = softmax(axis = softmax_2_axis_0, x = add_14)[name = string("softmax_2")];
            bool matmul_5_transpose_x_0 = const()[name = string("matmul_5_transpose_x_0"), val = bool(false)];
            bool matmul_5_transpose_y_0 = const()[name = string("matmul_5_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 256, 44]> matmul_5 = matmul(transpose_x = matmul_5_transpose_x_0, transpose_y = matmul_5_transpose_y_0, x = softmax_2, y = reshape_24)[name = string("matmul_5")];
            tensor<int32, [3]> transpose_11_perm_0 = const()[name = string("transpose_11_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_25_shape_0 = const()[name = string("reshape_25_shape_0"), val = tensor<int32, [2]>([256, 352])];
            tensor<fp16, [256, 8, 44]> transpose_11 = transpose(perm = transpose_11_perm_0, x = matmul_5)[name = string("transpose_52")];
            tensor<fp16, [256, 352]> reshape_25 = reshape(shape = reshape_25_shape_0, x = transpose_11)[name = string("reshape_25")];
            tensor<fp16, [256, 352]> mul_106 = mul(x = reshape_25, y = reshape_25)[name = string("mul_106")];
            tensor<int32, [1]> reduce_mean_22_axes_0 = const()[name = string("reduce_mean_22_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_22_keep_dims_0 = const()[name = string("reduce_mean_22_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_22 = reduce_mean(axes = reduce_mean_22_axes_0, keep_dims = reduce_mean_22_keep_dims_0, x = mul_106)[name = string("reduce_mean_22")];
            fp32 rsqrt_22_epsilon_0 = const()[name = string("rsqrt_22_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_22 = rsqrt(epsilon = rsqrt_22_epsilon_0, x = reduce_mean_22)[name = string("rsqrt_22")];
            tensor<fp16, [256, 352]> mul_107 = mul(x = reshape_25, y = rsqrt_22)[name = string("mul_107")];
            tensor<fp16, [352]> mul_108_y_0 = const()[name = string("mul_108_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3052992)))];
            tensor<fp16, [256, 352]> mul_108 = mul(x = mul_107, y = mul_108_y_0)[name = string("mul_108")];
            tensor<fp16, [352, 352]> tern_2_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3053760))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_2_o_weight_0_palettized")];
            tensor<fp16, [256, 352]> tern_2_o = linear(bias = linear_0_bias_0, weight = tern_2_o_weight_0_palettized, x = mul_108)[name = string("tern_2_o")];
            tensor<fp16, [352]> mul_109_y_0 = const()[name = string("mul_109_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3084800)))];
            tensor<fp16, [256, 352]> mul_109 = mul(x = tern_2_o, y = mul_109_y_0)[name = string("mul_109")];
            tensor<fp16, [256, 352]> add_15 = add(x = add_11, y = mul_109)[name = string("add_15")];
            tensor<fp16, [256, 352]> mul_110 = mul(x = add_15, y = add_15)[name = string("mul_110")];
            tensor<int32, [1]> reduce_mean_23_axes_0 = const()[name = string("reduce_mean_23_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_23_keep_dims_0 = const()[name = string("reduce_mean_23_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_23 = reduce_mean(axes = reduce_mean_23_axes_0, keep_dims = reduce_mean_23_keep_dims_0, x = mul_110)[name = string("reduce_mean_23")];
            fp32 rsqrt_23_epsilon_0 = const()[name = string("rsqrt_23_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_23 = rsqrt(epsilon = rsqrt_23_epsilon_0, x = reduce_mean_23)[name = string("rsqrt_23")];
            tensor<fp16, [256, 352]> mul_111 = mul(x = add_15, y = rsqrt_23)[name = string("mul_111")];
            tensor<fp16, [352]> mul_112_y_0 = const()[name = string("mul_112_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3085568)))];
            tensor<fp16, [256, 352]> mul_112 = mul(x = mul_111, y = mul_112_y_0)[name = string("mul_112")];
            tensor<fp16, [256, 352]> mul_113 = mul(x = mul_112, y = mul_112)[name = string("mul_113")];
            tensor<int32, [1]> reduce_mean_24_axes_0 = const()[name = string("reduce_mean_24_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_24_keep_dims_0 = const()[name = string("reduce_mean_24_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_24 = reduce_mean(axes = reduce_mean_24_axes_0, keep_dims = reduce_mean_24_keep_dims_0, x = mul_113)[name = string("reduce_mean_24")];
            fp32 rsqrt_24_epsilon_0 = const()[name = string("rsqrt_24_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_24 = rsqrt(epsilon = rsqrt_24_epsilon_0, x = reduce_mean_24)[name = string("rsqrt_24")];
            tensor<fp16, [256, 352]> mul_114 = mul(x = mul_112, y = rsqrt_24)[name = string("mul_114")];
            tensor<fp16, [352]> mul_115_y_0 = const()[name = string("mul_115_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3086336)))];
            tensor<fp16, [256, 352]> mul_115 = mul(x = mul_114, y = mul_115_y_0)[name = string("mul_115")];
            tensor<fp16, [960, 352]> tern_2_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3087104))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_2_w1_weight_0_palettized")];
            tensor<fp16, [256, 960]> tern_2_w1 = linear(bias = linear_4_bias_0, weight = tern_2_w1_weight_0_palettized, x = mul_115)[name = string("tern_2_w1")];
            tensor<fp16, [960]> mul_116_y_0 = const()[name = string("mul_116_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3171648)))];
            tensor<fp16, [256, 960]> mul_116 = mul(x = tern_2_w1, y = mul_116_y_0)[name = string("mul_116")];
            tensor<fp16, [352]> mul_119_y_0 = const()[name = string("mul_119_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3173632)))];
            tensor<fp16, [256, 352]> mul_119 = mul(x = mul_114, y = mul_119_y_0)[name = string("mul_119")];
            tensor<fp16, [960, 352]> tern_2_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3174400))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_2_w3_weight_0_palettized")];
            tensor<fp16, [256, 960]> tern_2_w3 = linear(bias = linear_4_bias_0, weight = tern_2_w3_weight_0_palettized, x = mul_119)[name = string("tern_2_w3")];
            tensor<fp16, [960]> mul_120_y_0 = const()[name = string("mul_120_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3258944)))];
            tensor<fp16, [256, 960]> mul_120 = mul(x = tern_2_w3, y = mul_120_y_0)[name = string("mul_120")];
            fp16 mul_121_y_0 = const()[name = string("mul_121_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [256, 960]> mul_121 = mul(x = mul_116, y = mul_121_y_0)[name = string("mul_121")];
            tensor<fp16, [256, 960]> tanh_2 = tanh(x = mul_121)[name = string("tanh_2")];
            fp16 mul_122_x_0 = const()[name = string("mul_122_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [256, 960]> mul_122 = mul(x = mul_122_x_0, y = tanh_2)[name = string("mul_122")];
            fp16 add_16_x_0 = const()[name = string("add_16_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [256, 960]> add_16 = add(x = add_16_x_0, y = mul_122)[name = string("add_16")];
            tensor<fp16, [256, 960]> mul_123 = mul(x = mul_116, y = add_16)[name = string("mul_123")];
            tensor<fp16, [256, 960]> mul_124 = mul(x = mul_123, y = mul_120)[name = string("mul_124")];
            tensor<fp16, [256, 960]> mul_125 = mul(x = mul_124, y = mul_124)[name = string("mul_125")];
            tensor<int32, [1]> reduce_mean_26_axes_0 = const()[name = string("reduce_mean_26_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_26_keep_dims_0 = const()[name = string("reduce_mean_26_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_26 = reduce_mean(axes = reduce_mean_26_axes_0, keep_dims = reduce_mean_26_keep_dims_0, x = mul_125)[name = string("reduce_mean_26")];
            fp32 rsqrt_26_epsilon_0 = const()[name = string("rsqrt_26_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_26 = rsqrt(epsilon = rsqrt_26_epsilon_0, x = reduce_mean_26)[name = string("rsqrt_26")];
            tensor<fp16, [256, 960]> mul_126 = mul(x = mul_124, y = rsqrt_26)[name = string("mul_126")];
            tensor<fp16, [960]> mul_127_y_0 = const()[name = string("mul_127_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3260928)))];
            tensor<fp16, [256, 960]> mul_127 = mul(x = mul_126, y = mul_127_y_0)[name = string("mul_127")];
            tensor<fp16, [352, 960]> tern_2_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3262912))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_2_w2_weight_0_palettized")];
            tensor<fp16, [256, 352]> tern_2_w2 = linear(bias = linear_0_bias_0, weight = tern_2_w2_weight_0_palettized, x = mul_127)[name = string("tern_2_w2")];
            tensor<fp16, [352]> mul_128_y_0 = const()[name = string("mul_128_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3347456)))];
            tensor<fp16, [256, 352]> mul_128 = mul(x = tern_2_w2, y = mul_128_y_0)[name = string("mul_128")];
            tensor<fp16, [256, 352]> add_17 = add(x = add_15, y = mul_128)[name = string("add_17")];
            tensor<fp16, [256, 352]> mul_129 = mul(x = add_17, y = add_17)[name = string("mul_129")];
            tensor<int32, [1]> reduce_mean_27_axes_0 = const()[name = string("reduce_mean_27_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_27_keep_dims_0 = const()[name = string("reduce_mean_27_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_27 = reduce_mean(axes = reduce_mean_27_axes_0, keep_dims = reduce_mean_27_keep_dims_0, x = mul_129)[name = string("reduce_mean_27")];
            fp32 rsqrt_27_epsilon_0 = const()[name = string("rsqrt_27_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_27 = rsqrt(epsilon = rsqrt_27_epsilon_0, x = reduce_mean_27)[name = string("rsqrt_27")];
            tensor<fp16, [256, 352]> mul_130 = mul(x = add_17, y = rsqrt_27)[name = string("mul_130")];
            tensor<fp16, [352]> mul_131_y_0 = const()[name = string("mul_131_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3348224)))];
            tensor<fp16, [256, 352]> mul_131 = mul(x = mul_130, y = mul_131_y_0)[name = string("mul_131")];
            tensor<fp16, [256, 352]> mul_132 = mul(x = mul_131, y = mul_131)[name = string("mul_132")];
            tensor<int32, [1]> reduce_mean_28_axes_0 = const()[name = string("reduce_mean_28_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_28_keep_dims_0 = const()[name = string("reduce_mean_28_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_28 = reduce_mean(axes = reduce_mean_28_axes_0, keep_dims = reduce_mean_28_keep_dims_0, x = mul_132)[name = string("reduce_mean_28")];
            fp32 rsqrt_28_epsilon_0 = const()[name = string("rsqrt_28_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_28 = rsqrt(epsilon = rsqrt_28_epsilon_0, x = reduce_mean_28)[name = string("rsqrt_28")];
            tensor<fp16, [256, 352]> mul_133 = mul(x = mul_131, y = rsqrt_28)[name = string("mul_133")];
            tensor<fp16, [352]> mul_134_y_0 = const()[name = string("mul_134_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3348992)))];
            tensor<fp16, [256, 352]> mul_134 = mul(x = mul_133, y = mul_134_y_0)[name = string("mul_134")];
            tensor<fp16, [352, 352]> tern_3_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3349760))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_3_q_weight_0_palettized")];
            tensor<fp16, [256, 352]> tern_3_q = linear(bias = linear_0_bias_0, weight = tern_3_q_weight_0_palettized, x = mul_134)[name = string("tern_3_q")];
            tensor<fp16, [352]> mul_135_y_0 = const()[name = string("mul_135_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3380800)))];
            tensor<fp16, [256, 352]> mul_135 = mul(x = tern_3_q, y = mul_135_y_0)[name = string("mul_135")];
            tensor<int32, [3]> reshape_26_shape_0 = const()[name = string("reshape_26_shape_0"), val = tensor<int32, [3]>([256, 8, 44])];
            tensor<fp16, [256, 8, 44]> reshape_26 = reshape(shape = reshape_26_shape_0, x = mul_135)[name = string("reshape_26")];
            tensor<int32, [3]> transpose_12_perm_0 = const()[name = string("transpose_12_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_138_y_0 = const()[name = string("mul_138_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3381568)))];
            tensor<fp16, [256, 352]> mul_138 = mul(x = mul_133, y = mul_138_y_0)[name = string("mul_138")];
            tensor<fp16, [88, 352]> tern_3_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3382336))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_3_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_3_k_bias_0 = const()[name = string("tern_3_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [256, 88]> tern_3_k = linear(bias = tern_3_k_bias_0, weight = tern_3_k_weight_0_palettized, x = mul_138)[name = string("tern_3_k")];
            tensor<fp16, [88]> mul_139_y_0 = const()[name = string("mul_139_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3390144)))];
            tensor<fp16, [256, 88]> mul_139 = mul(x = tern_3_k, y = mul_139_y_0)[name = string("mul_139")];
            tensor<int32, [3]> reshape_27_shape_0 = const()[name = string("reshape_27_shape_0"), val = tensor<int32, [3]>([256, 2, 44])];
            tensor<fp16, [256, 2, 44]> reshape_27 = reshape(shape = reshape_27_shape_0, x = mul_139)[name = string("reshape_27")];
            tensor<int32, [3]> transpose_13_perm_0 = const()[name = string("transpose_13_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_142_y_0 = const()[name = string("mul_142_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3390400)))];
            tensor<fp16, [256, 352]> mul_142 = mul(x = mul_133, y = mul_142_y_0)[name = string("mul_142")];
            tensor<fp16, [88, 352]> tern_3_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3391168))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_3_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_3_v_bias_0 = const()[name = string("tern_3_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [256, 88]> tern_3_v = linear(bias = tern_3_v_bias_0, weight = tern_3_v_weight_0_palettized, x = mul_142)[name = string("tern_3_v")];
            tensor<fp16, [88]> mul_143_y_0 = const()[name = string("mul_143_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3398976)))];
            tensor<fp16, [256, 88]> mul_143 = mul(x = tern_3_v, y = mul_143_y_0)[name = string("mul_143")];
            tensor<int32, [3]> reshape_28_shape_0 = const()[name = string("reshape_28_shape_0"), val = tensor<int32, [3]>([256, 2, 44])];
            tensor<fp16, [256, 2, 44]> reshape_28 = reshape(shape = reshape_28_shape_0, x = mul_143)[name = string("reshape_28")];
            tensor<int32, [3]> transpose_14_perm_0 = const()[name = string("transpose_14_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 256, 44]> transpose_12 = transpose(perm = transpose_12_perm_0, x = reshape_26)[name = string("transpose_51")];
            tensor<fp16, [8, 256, 44]> mul_144 = mul(x = transpose_12, y = transpose_12)[name = string("mul_144")];
            tensor<int32, [1]> reduce_mean_31_axes_0 = const()[name = string("reduce_mean_31_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_31_keep_dims_0 = const()[name = string("reduce_mean_31_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 256, 1]> reduce_mean_31 = reduce_mean(axes = reduce_mean_31_axes_0, keep_dims = reduce_mean_31_keep_dims_0, x = mul_144)[name = string("reduce_mean_31")];
            fp32 rsqrt_31_epsilon_0 = const()[name = string("rsqrt_31_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 256, 1]> rsqrt_31 = rsqrt(epsilon = rsqrt_31_epsilon_0, x = reduce_mean_31)[name = string("rsqrt_31")];
            tensor<fp16, [8, 256, 44]> mul_145 = mul(x = transpose_12, y = rsqrt_31)[name = string("mul_145")];
            tensor<fp16, [44]> mul_146_y_0 = const()[name = string("mul_146_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3399232)))];
            tensor<fp16, [8, 256, 44]> mul_146 = mul(x = mul_145, y = mul_146_y_0)[name = string("mul_146")];
            tensor<int32, [3]> slice_by_index_12_begin_0 = const()[name = string("slice_by_index_12_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_12_end_0 = const()[name = string("slice_by_index_12_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_12_end_mask_0 = const()[name = string("slice_by_index_12_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 256, 22]> slice_by_index_12 = slice_by_index(begin = slice_by_index_12_begin_0, end = slice_by_index_12_end_0, end_mask = slice_by_index_12_end_mask_0, x = mul_146)[name = string("slice_by_index_12")];
            tensor<int32, [3]> slice_by_index_13_begin_0 = const()[name = string("slice_by_index_13_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_13_end_0 = const()[name = string("slice_by_index_13_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_13_end_mask_0 = const()[name = string("slice_by_index_13_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 256, 22]> slice_by_index_13 = slice_by_index(begin = slice_by_index_13_begin_0, end = slice_by_index_13_end_0, end_mask = slice_by_index_13_end_mask_0, x = mul_146)[name = string("slice_by_index_13")];
            int32 concat_6_axis_0 = const()[name = string("concat_6_axis_0"), val = int32(-1)];
            bool concat_6_interleave_0 = const()[name = string("concat_6_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 256, 44]> concat_6 = concat(axis = concat_6_axis_0, interleave = concat_6_interleave_0, values = (slice_by_index_13, slice_by_index_12))[name = string("concat_6")];
            tensor<fp16, [44]> mul_147_y_0 = const()[name = string("mul_147_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 256, 44]> mul_147 = mul(x = concat_6, y = mul_147_y_0)[name = string("mul_147")];
            tensor<fp16, [8, 256, 44]> mul_148 = mul(x = mul_146, y = mul_11_y_0)[name = string("mul_148")];
            tensor<fp16, [8, 256, 44]> mul_149 = mul(x = mul_147, y = mul_12_y_0)[name = string("mul_149")];
            tensor<fp16, [8, 256, 44]> add_18 = add(x = mul_148, y = mul_149)[name = string("add_18")];
            tensor<fp16, [2, 256, 44]> transpose_13 = transpose(perm = transpose_13_perm_0, x = reshape_27)[name = string("transpose_50")];
            tensor<fp16, [2, 256, 44]> mul_150 = mul(x = transpose_13, y = transpose_13)[name = string("mul_150")];
            tensor<int32, [1]> reduce_mean_32_axes_0 = const()[name = string("reduce_mean_32_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_32_keep_dims_0 = const()[name = string("reduce_mean_32_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 256, 1]> reduce_mean_32 = reduce_mean(axes = reduce_mean_32_axes_0, keep_dims = reduce_mean_32_keep_dims_0, x = mul_150)[name = string("reduce_mean_32")];
            fp32 rsqrt_32_epsilon_0 = const()[name = string("rsqrt_32_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 256, 1]> rsqrt_32 = rsqrt(epsilon = rsqrt_32_epsilon_0, x = reduce_mean_32)[name = string("rsqrt_32")];
            tensor<fp16, [2, 256, 44]> mul_151 = mul(x = transpose_13, y = rsqrt_32)[name = string("mul_151")];
            tensor<fp16, [44]> mul_152_y_0 = const()[name = string("mul_152_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3399424)))];
            tensor<fp16, [2, 256, 44]> mul_152 = mul(x = mul_151, y = mul_152_y_0)[name = string("mul_152")];
            tensor<int32, [3]> slice_by_index_14_begin_0 = const()[name = string("slice_by_index_14_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_14_end_0 = const()[name = string("slice_by_index_14_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_14_end_mask_0 = const()[name = string("slice_by_index_14_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 256, 22]> slice_by_index_14 = slice_by_index(begin = slice_by_index_14_begin_0, end = slice_by_index_14_end_0, end_mask = slice_by_index_14_end_mask_0, x = mul_152)[name = string("slice_by_index_14")];
            tensor<int32, [3]> slice_by_index_15_begin_0 = const()[name = string("slice_by_index_15_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_15_end_0 = const()[name = string("slice_by_index_15_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_15_end_mask_0 = const()[name = string("slice_by_index_15_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 256, 22]> slice_by_index_15 = slice_by_index(begin = slice_by_index_15_begin_0, end = slice_by_index_15_end_0, end_mask = slice_by_index_15_end_mask_0, x = mul_152)[name = string("slice_by_index_15")];
            int32 concat_7_axis_0 = const()[name = string("concat_7_axis_0"), val = int32(-1)];
            bool concat_7_interleave_0 = const()[name = string("concat_7_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 256, 44]> concat_7 = concat(axis = concat_7_axis_0, interleave = concat_7_interleave_0, values = (slice_by_index_15, slice_by_index_14))[name = string("concat_7")];
            tensor<fp16, [44]> mul_153_y_0 = const()[name = string("mul_153_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 256, 44]> mul_153 = mul(x = concat_7, y = mul_153_y_0)[name = string("mul_153")];
            tensor<fp16, [2, 256, 44]> mul_154 = mul(x = mul_152, y = mul_11_y_0)[name = string("mul_154")];
            tensor<fp16, [2, 256, 44]> mul_155 = mul(x = mul_153, y = mul_12_y_0)[name = string("mul_155")];
            tensor<fp16, [2, 256, 44]> add_19 = add(x = mul_154, y = mul_155)[name = string("add_19")];
            tensor<int32, [4]> reshape_29_shape_0 = const()[name = string("reshape_29_shape_0"), val = tensor<int32, [4]>([2, 1, 256, 44])];
            tensor<fp16, [2, 1, 256, 44]> reshape_29 = reshape(shape = reshape_29_shape_0, x = add_19)[name = string("reshape_29")];
            tensor<int32, [4]> tile_6_reps_0 = const()[name = string("tile_6_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 256, 44]> tile_6 = tile(reps = tile_6_reps_0, x = reshape_29)[name = string("tile_6")];
            tensor<int32, [3]> reshape_30_shape_0 = const()[name = string("reshape_30_shape_0"), val = tensor<int32, [3]>([8, 256, 44])];
            tensor<fp16, [8, 256, 44]> reshape_30 = reshape(shape = reshape_30_shape_0, x = tile_6)[name = string("reshape_30")];
            tensor<int32, [4]> reshape_31_shape_0 = const()[name = string("reshape_31_shape_0"), val = tensor<int32, [4]>([2, 1, 256, 44])];
            tensor<fp16, [2, 256, 44]> transpose_14 = transpose(perm = transpose_14_perm_0, x = reshape_28)[name = string("transpose_49")];
            tensor<fp16, [2, 1, 256, 44]> reshape_31 = reshape(shape = reshape_31_shape_0, x = transpose_14)[name = string("reshape_31")];
            tensor<int32, [4]> tile_7_reps_0 = const()[name = string("tile_7_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 256, 44]> tile_7 = tile(reps = tile_7_reps_0, x = reshape_31)[name = string("tile_7")];
            tensor<int32, [3]> reshape_32_shape_0 = const()[name = string("reshape_32_shape_0"), val = tensor<int32, [3]>([8, 256, 44])];
            tensor<fp16, [8, 256, 44]> reshape_32 = reshape(shape = reshape_32_shape_0, x = tile_7)[name = string("reshape_32")];
            fp16 mul_156_y_0 = const()[name = string("mul_156_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 256, 44]> mul_156 = mul(x = add_18, y = mul_156_y_0)[name = string("mul_156")];
            bool matmul_6_transpose_y_0 = const()[name = string("matmul_6_transpose_y_0"), val = bool(true)];
            bool matmul_6_transpose_x_0 = const()[name = string("matmul_6_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 256, 256]> matmul_6 = matmul(transpose_x = matmul_6_transpose_x_0, transpose_y = matmul_6_transpose_y_0, x = mul_156, y = reshape_30)[name = string("matmul_6")];
            tensor<fp16, [8, 256, 256]> add_20 = add(x = matmul_6, y = reshape_1)[name = string("add_20")];
            int32 softmax_3_axis_0 = const()[name = string("softmax_3_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 256, 256]> softmax_3 = softmax(axis = softmax_3_axis_0, x = add_20)[name = string("softmax_3")];
            bool matmul_7_transpose_x_0 = const()[name = string("matmul_7_transpose_x_0"), val = bool(false)];
            bool matmul_7_transpose_y_0 = const()[name = string("matmul_7_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 256, 44]> matmul_7 = matmul(transpose_x = matmul_7_transpose_x_0, transpose_y = matmul_7_transpose_y_0, x = softmax_3, y = reshape_32)[name = string("matmul_7")];
            tensor<int32, [3]> transpose_15_perm_0 = const()[name = string("transpose_15_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_33_shape_0 = const()[name = string("reshape_33_shape_0"), val = tensor<int32, [2]>([256, 352])];
            tensor<fp16, [256, 8, 44]> transpose_15 = transpose(perm = transpose_15_perm_0, x = matmul_7)[name = string("transpose_48")];
            tensor<fp16, [256, 352]> reshape_33 = reshape(shape = reshape_33_shape_0, x = transpose_15)[name = string("reshape_33")];
            tensor<fp16, [256, 352]> mul_157 = mul(x = reshape_33, y = reshape_33)[name = string("mul_157")];
            tensor<int32, [1]> reduce_mean_33_axes_0 = const()[name = string("reduce_mean_33_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_33_keep_dims_0 = const()[name = string("reduce_mean_33_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_33 = reduce_mean(axes = reduce_mean_33_axes_0, keep_dims = reduce_mean_33_keep_dims_0, x = mul_157)[name = string("reduce_mean_33")];
            fp32 rsqrt_33_epsilon_0 = const()[name = string("rsqrt_33_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_33 = rsqrt(epsilon = rsqrt_33_epsilon_0, x = reduce_mean_33)[name = string("rsqrt_33")];
            tensor<fp16, [256, 352]> mul_158 = mul(x = reshape_33, y = rsqrt_33)[name = string("mul_158")];
            tensor<fp16, [352]> mul_159_y_0 = const()[name = string("mul_159_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3399616)))];
            tensor<fp16, [256, 352]> mul_159 = mul(x = mul_158, y = mul_159_y_0)[name = string("mul_159")];
            tensor<fp16, [352, 352]> tern_3_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3400384))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_3_o_weight_0_palettized")];
            tensor<fp16, [256, 352]> tern_3_o = linear(bias = linear_0_bias_0, weight = tern_3_o_weight_0_palettized, x = mul_159)[name = string("tern_3_o")];
            tensor<fp16, [352]> mul_160_y_0 = const()[name = string("mul_160_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3431424)))];
            tensor<fp16, [256, 352]> mul_160 = mul(x = tern_3_o, y = mul_160_y_0)[name = string("mul_160")];
            tensor<fp16, [256, 352]> add_21 = add(x = add_17, y = mul_160)[name = string("add_21")];
            tensor<fp16, [256, 352]> mul_161 = mul(x = add_21, y = add_21)[name = string("mul_161")];
            tensor<int32, [1]> reduce_mean_34_axes_0 = const()[name = string("reduce_mean_34_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_34_keep_dims_0 = const()[name = string("reduce_mean_34_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_34 = reduce_mean(axes = reduce_mean_34_axes_0, keep_dims = reduce_mean_34_keep_dims_0, x = mul_161)[name = string("reduce_mean_34")];
            fp32 rsqrt_34_epsilon_0 = const()[name = string("rsqrt_34_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_34 = rsqrt(epsilon = rsqrt_34_epsilon_0, x = reduce_mean_34)[name = string("rsqrt_34")];
            tensor<fp16, [256, 352]> mul_162 = mul(x = add_21, y = rsqrt_34)[name = string("mul_162")];
            tensor<fp16, [352]> mul_163_y_0 = const()[name = string("mul_163_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3432192)))];
            tensor<fp16, [256, 352]> mul_163 = mul(x = mul_162, y = mul_163_y_0)[name = string("mul_163")];
            tensor<fp16, [256, 352]> mul_164 = mul(x = mul_163, y = mul_163)[name = string("mul_164")];
            tensor<int32, [1]> reduce_mean_35_axes_0 = const()[name = string("reduce_mean_35_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_35_keep_dims_0 = const()[name = string("reduce_mean_35_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_35 = reduce_mean(axes = reduce_mean_35_axes_0, keep_dims = reduce_mean_35_keep_dims_0, x = mul_164)[name = string("reduce_mean_35")];
            fp32 rsqrt_35_epsilon_0 = const()[name = string("rsqrt_35_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_35 = rsqrt(epsilon = rsqrt_35_epsilon_0, x = reduce_mean_35)[name = string("rsqrt_35")];
            tensor<fp16, [256, 352]> mul_165 = mul(x = mul_163, y = rsqrt_35)[name = string("mul_165")];
            tensor<fp16, [352]> mul_166_y_0 = const()[name = string("mul_166_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3432960)))];
            tensor<fp16, [256, 352]> mul_166 = mul(x = mul_165, y = mul_166_y_0)[name = string("mul_166")];
            tensor<fp16, [960, 352]> tern_3_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3433728))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_3_w1_weight_0_palettized")];
            tensor<fp16, [256, 960]> tern_3_w1 = linear(bias = linear_4_bias_0, weight = tern_3_w1_weight_0_palettized, x = mul_166)[name = string("tern_3_w1")];
            tensor<fp16, [960]> mul_167_y_0 = const()[name = string("mul_167_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3518272)))];
            tensor<fp16, [256, 960]> mul_167 = mul(x = tern_3_w1, y = mul_167_y_0)[name = string("mul_167")];
            tensor<fp16, [352]> mul_170_y_0 = const()[name = string("mul_170_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3520256)))];
            tensor<fp16, [256, 352]> mul_170 = mul(x = mul_165, y = mul_170_y_0)[name = string("mul_170")];
            tensor<fp16, [960, 352]> tern_3_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3521024))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_3_w3_weight_0_palettized")];
            tensor<fp16, [256, 960]> tern_3_w3 = linear(bias = linear_4_bias_0, weight = tern_3_w3_weight_0_palettized, x = mul_170)[name = string("tern_3_w3")];
            tensor<fp16, [960]> mul_171_y_0 = const()[name = string("mul_171_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3605568)))];
            tensor<fp16, [256, 960]> mul_171 = mul(x = tern_3_w3, y = mul_171_y_0)[name = string("mul_171")];
            fp16 mul_172_y_0 = const()[name = string("mul_172_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [256, 960]> mul_172 = mul(x = mul_167, y = mul_172_y_0)[name = string("mul_172")];
            tensor<fp16, [256, 960]> tanh_3 = tanh(x = mul_172)[name = string("tanh_3")];
            fp16 mul_173_x_0 = const()[name = string("mul_173_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [256, 960]> mul_173 = mul(x = mul_173_x_0, y = tanh_3)[name = string("mul_173")];
            fp16 add_22_x_0 = const()[name = string("add_22_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [256, 960]> add_22 = add(x = add_22_x_0, y = mul_173)[name = string("add_22")];
            tensor<fp16, [256, 960]> mul_174 = mul(x = mul_167, y = add_22)[name = string("mul_174")];
            tensor<fp16, [256, 960]> mul_175 = mul(x = mul_174, y = mul_171)[name = string("mul_175")];
            tensor<fp16, [256, 960]> mul_176 = mul(x = mul_175, y = mul_175)[name = string("mul_176")];
            tensor<int32, [1]> reduce_mean_37_axes_0 = const()[name = string("reduce_mean_37_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_37_keep_dims_0 = const()[name = string("reduce_mean_37_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_37 = reduce_mean(axes = reduce_mean_37_axes_0, keep_dims = reduce_mean_37_keep_dims_0, x = mul_176)[name = string("reduce_mean_37")];
            fp32 rsqrt_37_epsilon_0 = const()[name = string("rsqrt_37_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_37 = rsqrt(epsilon = rsqrt_37_epsilon_0, x = reduce_mean_37)[name = string("rsqrt_37")];
            tensor<fp16, [256, 960]> mul_177 = mul(x = mul_175, y = rsqrt_37)[name = string("mul_177")];
            tensor<fp16, [960]> mul_178_y_0 = const()[name = string("mul_178_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3607552)))];
            tensor<fp16, [256, 960]> mul_178 = mul(x = mul_177, y = mul_178_y_0)[name = string("mul_178")];
            tensor<fp16, [352, 960]> tern_3_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3609536))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_3_w2_weight_0_palettized")];
            tensor<fp16, [256, 352]> tern_3_w2 = linear(bias = linear_0_bias_0, weight = tern_3_w2_weight_0_palettized, x = mul_178)[name = string("tern_3_w2")];
            tensor<fp16, [352]> mul_179_y_0 = const()[name = string("mul_179_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3694080)))];
            tensor<fp16, [256, 352]> mul_179 = mul(x = tern_3_w2, y = mul_179_y_0)[name = string("mul_179")];
            tensor<fp16, [256, 352]> add_23 = add(x = add_21, y = mul_179)[name = string("add_23")];
            tensor<fp16, [256, 352]> mul_180 = mul(x = add_23, y = add_23)[name = string("mul_180")];
            tensor<int32, [1]> reduce_mean_38_axes_0 = const()[name = string("reduce_mean_38_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_38_keep_dims_0 = const()[name = string("reduce_mean_38_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_38 = reduce_mean(axes = reduce_mean_38_axes_0, keep_dims = reduce_mean_38_keep_dims_0, x = mul_180)[name = string("reduce_mean_38")];
            fp32 rsqrt_38_epsilon_0 = const()[name = string("rsqrt_38_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_38 = rsqrt(epsilon = rsqrt_38_epsilon_0, x = reduce_mean_38)[name = string("rsqrt_38")];
            tensor<fp16, [256, 352]> mul_181 = mul(x = add_23, y = rsqrt_38)[name = string("mul_181")];
            tensor<fp16, [352]> mul_182_y_0 = const()[name = string("mul_182_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3694848)))];
            tensor<fp16, [256, 352]> mul_182 = mul(x = mul_181, y = mul_182_y_0)[name = string("mul_182")];
            tensor<fp16, [256, 352]> mul_183 = mul(x = mul_182, y = mul_182)[name = string("mul_183")];
            tensor<int32, [1]> reduce_mean_39_axes_0 = const()[name = string("reduce_mean_39_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_39_keep_dims_0 = const()[name = string("reduce_mean_39_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_39 = reduce_mean(axes = reduce_mean_39_axes_0, keep_dims = reduce_mean_39_keep_dims_0, x = mul_183)[name = string("reduce_mean_39")];
            fp32 rsqrt_39_epsilon_0 = const()[name = string("rsqrt_39_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_39 = rsqrt(epsilon = rsqrt_39_epsilon_0, x = reduce_mean_39)[name = string("rsqrt_39")];
            tensor<fp16, [256, 352]> mul_184 = mul(x = mul_182, y = rsqrt_39)[name = string("mul_184")];
            tensor<fp16, [352]> mul_185_y_0 = const()[name = string("mul_185_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3695616)))];
            tensor<fp16, [256, 352]> mul_185 = mul(x = mul_184, y = mul_185_y_0)[name = string("mul_185")];
            tensor<fp16, [352, 352]> tern_4_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3696384))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_4_q_weight_0_palettized")];
            tensor<fp16, [256, 352]> tern_4_q = linear(bias = linear_0_bias_0, weight = tern_4_q_weight_0_palettized, x = mul_185)[name = string("tern_4_q")];
            tensor<fp16, [352]> mul_186_y_0 = const()[name = string("mul_186_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3727424)))];
            tensor<fp16, [256, 352]> mul_186 = mul(x = tern_4_q, y = mul_186_y_0)[name = string("mul_186")];
            tensor<int32, [3]> reshape_34_shape_0 = const()[name = string("reshape_34_shape_0"), val = tensor<int32, [3]>([256, 8, 44])];
            tensor<fp16, [256, 8, 44]> reshape_34 = reshape(shape = reshape_34_shape_0, x = mul_186)[name = string("reshape_34")];
            tensor<int32, [3]> transpose_16_perm_0 = const()[name = string("transpose_16_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_189_y_0 = const()[name = string("mul_189_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3728192)))];
            tensor<fp16, [256, 352]> mul_189 = mul(x = mul_184, y = mul_189_y_0)[name = string("mul_189")];
            tensor<fp16, [88, 352]> tern_4_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3728960))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_4_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_4_k_bias_0 = const()[name = string("tern_4_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [256, 88]> tern_4_k = linear(bias = tern_4_k_bias_0, weight = tern_4_k_weight_0_palettized, x = mul_189)[name = string("tern_4_k")];
            tensor<fp16, [88]> mul_190_y_0 = const()[name = string("mul_190_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3736768)))];
            tensor<fp16, [256, 88]> mul_190 = mul(x = tern_4_k, y = mul_190_y_0)[name = string("mul_190")];
            tensor<int32, [3]> reshape_35_shape_0 = const()[name = string("reshape_35_shape_0"), val = tensor<int32, [3]>([256, 2, 44])];
            tensor<fp16, [256, 2, 44]> reshape_35 = reshape(shape = reshape_35_shape_0, x = mul_190)[name = string("reshape_35")];
            tensor<int32, [3]> transpose_17_perm_0 = const()[name = string("transpose_17_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_193_y_0 = const()[name = string("mul_193_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3737024)))];
            tensor<fp16, [256, 352]> mul_193 = mul(x = mul_184, y = mul_193_y_0)[name = string("mul_193")];
            tensor<fp16, [88, 352]> tern_4_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3737792))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_4_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_4_v_bias_0 = const()[name = string("tern_4_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [256, 88]> tern_4_v = linear(bias = tern_4_v_bias_0, weight = tern_4_v_weight_0_palettized, x = mul_193)[name = string("tern_4_v")];
            tensor<fp16, [88]> mul_194_y_0 = const()[name = string("mul_194_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3745600)))];
            tensor<fp16, [256, 88]> mul_194 = mul(x = tern_4_v, y = mul_194_y_0)[name = string("mul_194")];
            tensor<int32, [3]> reshape_36_shape_0 = const()[name = string("reshape_36_shape_0"), val = tensor<int32, [3]>([256, 2, 44])];
            tensor<fp16, [256, 2, 44]> reshape_36 = reshape(shape = reshape_36_shape_0, x = mul_194)[name = string("reshape_36")];
            tensor<int32, [3]> transpose_18_perm_0 = const()[name = string("transpose_18_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 256, 44]> transpose_16 = transpose(perm = transpose_16_perm_0, x = reshape_34)[name = string("transpose_47")];
            tensor<fp16, [8, 256, 44]> mul_195 = mul(x = transpose_16, y = transpose_16)[name = string("mul_195")];
            tensor<int32, [1]> reduce_mean_42_axes_0 = const()[name = string("reduce_mean_42_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_42_keep_dims_0 = const()[name = string("reduce_mean_42_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 256, 1]> reduce_mean_42 = reduce_mean(axes = reduce_mean_42_axes_0, keep_dims = reduce_mean_42_keep_dims_0, x = mul_195)[name = string("reduce_mean_42")];
            fp32 rsqrt_42_epsilon_0 = const()[name = string("rsqrt_42_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 256, 1]> rsqrt_42 = rsqrt(epsilon = rsqrt_42_epsilon_0, x = reduce_mean_42)[name = string("rsqrt_42")];
            tensor<fp16, [8, 256, 44]> mul_196 = mul(x = transpose_16, y = rsqrt_42)[name = string("mul_196")];
            tensor<fp16, [44]> mul_197_y_0 = const()[name = string("mul_197_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3745856)))];
            tensor<fp16, [8, 256, 44]> mul_197 = mul(x = mul_196, y = mul_197_y_0)[name = string("mul_197")];
            tensor<int32, [3]> slice_by_index_16_begin_0 = const()[name = string("slice_by_index_16_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_16_end_0 = const()[name = string("slice_by_index_16_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_16_end_mask_0 = const()[name = string("slice_by_index_16_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 256, 22]> slice_by_index_16 = slice_by_index(begin = slice_by_index_16_begin_0, end = slice_by_index_16_end_0, end_mask = slice_by_index_16_end_mask_0, x = mul_197)[name = string("slice_by_index_16")];
            tensor<int32, [3]> slice_by_index_17_begin_0 = const()[name = string("slice_by_index_17_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_17_end_0 = const()[name = string("slice_by_index_17_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_17_end_mask_0 = const()[name = string("slice_by_index_17_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 256, 22]> slice_by_index_17 = slice_by_index(begin = slice_by_index_17_begin_0, end = slice_by_index_17_end_0, end_mask = slice_by_index_17_end_mask_0, x = mul_197)[name = string("slice_by_index_17")];
            int32 concat_8_axis_0 = const()[name = string("concat_8_axis_0"), val = int32(-1)];
            bool concat_8_interleave_0 = const()[name = string("concat_8_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 256, 44]> concat_8 = concat(axis = concat_8_axis_0, interleave = concat_8_interleave_0, values = (slice_by_index_17, slice_by_index_16))[name = string("concat_8")];
            tensor<fp16, [44]> mul_198_y_0 = const()[name = string("mul_198_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 256, 44]> mul_198 = mul(x = concat_8, y = mul_198_y_0)[name = string("mul_198")];
            tensor<fp16, [8, 256, 44]> mul_199 = mul(x = mul_197, y = mul_11_y_0)[name = string("mul_199")];
            tensor<fp16, [8, 256, 44]> mul_200 = mul(x = mul_198, y = mul_12_y_0)[name = string("mul_200")];
            tensor<fp16, [8, 256, 44]> add_24 = add(x = mul_199, y = mul_200)[name = string("add_24")];
            tensor<fp16, [2, 256, 44]> transpose_17 = transpose(perm = transpose_17_perm_0, x = reshape_35)[name = string("transpose_46")];
            tensor<fp16, [2, 256, 44]> mul_201 = mul(x = transpose_17, y = transpose_17)[name = string("mul_201")];
            tensor<int32, [1]> reduce_mean_43_axes_0 = const()[name = string("reduce_mean_43_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_43_keep_dims_0 = const()[name = string("reduce_mean_43_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 256, 1]> reduce_mean_43 = reduce_mean(axes = reduce_mean_43_axes_0, keep_dims = reduce_mean_43_keep_dims_0, x = mul_201)[name = string("reduce_mean_43")];
            fp32 rsqrt_43_epsilon_0 = const()[name = string("rsqrt_43_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 256, 1]> rsqrt_43 = rsqrt(epsilon = rsqrt_43_epsilon_0, x = reduce_mean_43)[name = string("rsqrt_43")];
            tensor<fp16, [2, 256, 44]> mul_202 = mul(x = transpose_17, y = rsqrt_43)[name = string("mul_202")];
            tensor<fp16, [44]> mul_203_y_0 = const()[name = string("mul_203_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3746048)))];
            tensor<fp16, [2, 256, 44]> mul_203 = mul(x = mul_202, y = mul_203_y_0)[name = string("mul_203")];
            tensor<int32, [3]> slice_by_index_18_begin_0 = const()[name = string("slice_by_index_18_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_18_end_0 = const()[name = string("slice_by_index_18_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_18_end_mask_0 = const()[name = string("slice_by_index_18_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 256, 22]> slice_by_index_18 = slice_by_index(begin = slice_by_index_18_begin_0, end = slice_by_index_18_end_0, end_mask = slice_by_index_18_end_mask_0, x = mul_203)[name = string("slice_by_index_18")];
            tensor<int32, [3]> slice_by_index_19_begin_0 = const()[name = string("slice_by_index_19_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_19_end_0 = const()[name = string("slice_by_index_19_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_19_end_mask_0 = const()[name = string("slice_by_index_19_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 256, 22]> slice_by_index_19 = slice_by_index(begin = slice_by_index_19_begin_0, end = slice_by_index_19_end_0, end_mask = slice_by_index_19_end_mask_0, x = mul_203)[name = string("slice_by_index_19")];
            int32 concat_9_axis_0 = const()[name = string("concat_9_axis_0"), val = int32(-1)];
            bool concat_9_interleave_0 = const()[name = string("concat_9_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 256, 44]> concat_9 = concat(axis = concat_9_axis_0, interleave = concat_9_interleave_0, values = (slice_by_index_19, slice_by_index_18))[name = string("concat_9")];
            tensor<fp16, [44]> mul_204_y_0 = const()[name = string("mul_204_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 256, 44]> mul_204 = mul(x = concat_9, y = mul_204_y_0)[name = string("mul_204")];
            tensor<fp16, [2, 256, 44]> mul_205 = mul(x = mul_203, y = mul_11_y_0)[name = string("mul_205")];
            tensor<fp16, [2, 256, 44]> mul_206 = mul(x = mul_204, y = mul_12_y_0)[name = string("mul_206")];
            tensor<fp16, [2, 256, 44]> add_25 = add(x = mul_205, y = mul_206)[name = string("add_25")];
            tensor<int32, [4]> reshape_37_shape_0 = const()[name = string("reshape_37_shape_0"), val = tensor<int32, [4]>([2, 1, 256, 44])];
            tensor<fp16, [2, 1, 256, 44]> reshape_37 = reshape(shape = reshape_37_shape_0, x = add_25)[name = string("reshape_37")];
            tensor<int32, [4]> tile_8_reps_0 = const()[name = string("tile_8_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 256, 44]> tile_8 = tile(reps = tile_8_reps_0, x = reshape_37)[name = string("tile_8")];
            tensor<int32, [3]> reshape_38_shape_0 = const()[name = string("reshape_38_shape_0"), val = tensor<int32, [3]>([8, 256, 44])];
            tensor<fp16, [8, 256, 44]> reshape_38 = reshape(shape = reshape_38_shape_0, x = tile_8)[name = string("reshape_38")];
            tensor<int32, [4]> reshape_39_shape_0 = const()[name = string("reshape_39_shape_0"), val = tensor<int32, [4]>([2, 1, 256, 44])];
            tensor<fp16, [2, 256, 44]> transpose_18 = transpose(perm = transpose_18_perm_0, x = reshape_36)[name = string("transpose_45")];
            tensor<fp16, [2, 1, 256, 44]> reshape_39 = reshape(shape = reshape_39_shape_0, x = transpose_18)[name = string("reshape_39")];
            tensor<int32, [4]> tile_9_reps_0 = const()[name = string("tile_9_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 256, 44]> tile_9 = tile(reps = tile_9_reps_0, x = reshape_39)[name = string("tile_9")];
            tensor<int32, [3]> reshape_40_shape_0 = const()[name = string("reshape_40_shape_0"), val = tensor<int32, [3]>([8, 256, 44])];
            tensor<fp16, [8, 256, 44]> reshape_40 = reshape(shape = reshape_40_shape_0, x = tile_9)[name = string("reshape_40")];
            fp16 mul_207_y_0 = const()[name = string("mul_207_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 256, 44]> mul_207 = mul(x = add_24, y = mul_207_y_0)[name = string("mul_207")];
            bool matmul_8_transpose_y_0 = const()[name = string("matmul_8_transpose_y_0"), val = bool(true)];
            bool matmul_8_transpose_x_0 = const()[name = string("matmul_8_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 256, 256]> matmul_8 = matmul(transpose_x = matmul_8_transpose_x_0, transpose_y = matmul_8_transpose_y_0, x = mul_207, y = reshape_38)[name = string("matmul_8")];
            tensor<fp16, [8, 256, 256]> add_26 = add(x = matmul_8, y = reshape_1)[name = string("add_26")];
            int32 softmax_4_axis_0 = const()[name = string("softmax_4_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 256, 256]> softmax_4 = softmax(axis = softmax_4_axis_0, x = add_26)[name = string("softmax_4")];
            bool matmul_9_transpose_x_0 = const()[name = string("matmul_9_transpose_x_0"), val = bool(false)];
            bool matmul_9_transpose_y_0 = const()[name = string("matmul_9_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 256, 44]> matmul_9 = matmul(transpose_x = matmul_9_transpose_x_0, transpose_y = matmul_9_transpose_y_0, x = softmax_4, y = reshape_40)[name = string("matmul_9")];
            tensor<int32, [3]> transpose_19_perm_0 = const()[name = string("transpose_19_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_41_shape_0 = const()[name = string("reshape_41_shape_0"), val = tensor<int32, [2]>([256, 352])];
            tensor<fp16, [256, 8, 44]> transpose_19 = transpose(perm = transpose_19_perm_0, x = matmul_9)[name = string("transpose_44")];
            tensor<fp16, [256, 352]> reshape_41 = reshape(shape = reshape_41_shape_0, x = transpose_19)[name = string("reshape_41")];
            tensor<fp16, [256, 352]> mul_208 = mul(x = reshape_41, y = reshape_41)[name = string("mul_208")];
            tensor<int32, [1]> reduce_mean_44_axes_0 = const()[name = string("reduce_mean_44_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_44_keep_dims_0 = const()[name = string("reduce_mean_44_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_44 = reduce_mean(axes = reduce_mean_44_axes_0, keep_dims = reduce_mean_44_keep_dims_0, x = mul_208)[name = string("reduce_mean_44")];
            fp32 rsqrt_44_epsilon_0 = const()[name = string("rsqrt_44_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_44 = rsqrt(epsilon = rsqrt_44_epsilon_0, x = reduce_mean_44)[name = string("rsqrt_44")];
            tensor<fp16, [256, 352]> mul_209 = mul(x = reshape_41, y = rsqrt_44)[name = string("mul_209")];
            tensor<fp16, [352]> mul_210_y_0 = const()[name = string("mul_210_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3746240)))];
            tensor<fp16, [256, 352]> mul_210 = mul(x = mul_209, y = mul_210_y_0)[name = string("mul_210")];
            tensor<fp16, [352, 352]> tern_4_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3747008))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_4_o_weight_0_palettized")];
            tensor<fp16, [256, 352]> tern_4_o = linear(bias = linear_0_bias_0, weight = tern_4_o_weight_0_palettized, x = mul_210)[name = string("tern_4_o")];
            tensor<fp16, [352]> mul_211_y_0 = const()[name = string("mul_211_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3778048)))];
            tensor<fp16, [256, 352]> mul_211 = mul(x = tern_4_o, y = mul_211_y_0)[name = string("mul_211")];
            tensor<fp16, [256, 352]> add_27 = add(x = add_23, y = mul_211)[name = string("add_27")];
            tensor<fp16, [256, 352]> mul_212 = mul(x = add_27, y = add_27)[name = string("mul_212")];
            tensor<int32, [1]> reduce_mean_45_axes_0 = const()[name = string("reduce_mean_45_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_45_keep_dims_0 = const()[name = string("reduce_mean_45_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_45 = reduce_mean(axes = reduce_mean_45_axes_0, keep_dims = reduce_mean_45_keep_dims_0, x = mul_212)[name = string("reduce_mean_45")];
            fp32 rsqrt_45_epsilon_0 = const()[name = string("rsqrt_45_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_45 = rsqrt(epsilon = rsqrt_45_epsilon_0, x = reduce_mean_45)[name = string("rsqrt_45")];
            tensor<fp16, [256, 352]> mul_213 = mul(x = add_27, y = rsqrt_45)[name = string("mul_213")];
            tensor<fp16, [352]> mul_214_y_0 = const()[name = string("mul_214_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3778816)))];
            tensor<fp16, [256, 352]> mul_214 = mul(x = mul_213, y = mul_214_y_0)[name = string("mul_214")];
            tensor<fp16, [256, 352]> mul_215 = mul(x = mul_214, y = mul_214)[name = string("mul_215")];
            tensor<int32, [1]> reduce_mean_46_axes_0 = const()[name = string("reduce_mean_46_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_46_keep_dims_0 = const()[name = string("reduce_mean_46_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_46 = reduce_mean(axes = reduce_mean_46_axes_0, keep_dims = reduce_mean_46_keep_dims_0, x = mul_215)[name = string("reduce_mean_46")];
            fp32 rsqrt_46_epsilon_0 = const()[name = string("rsqrt_46_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_46 = rsqrt(epsilon = rsqrt_46_epsilon_0, x = reduce_mean_46)[name = string("rsqrt_46")];
            tensor<fp16, [256, 352]> mul_216 = mul(x = mul_214, y = rsqrt_46)[name = string("mul_216")];
            tensor<fp16, [352]> mul_217_y_0 = const()[name = string("mul_217_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3779584)))];
            tensor<fp16, [256, 352]> mul_217 = mul(x = mul_216, y = mul_217_y_0)[name = string("mul_217")];
            tensor<fp16, [960, 352]> tern_4_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3780352))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_4_w1_weight_0_palettized")];
            tensor<fp16, [256, 960]> tern_4_w1 = linear(bias = linear_4_bias_0, weight = tern_4_w1_weight_0_palettized, x = mul_217)[name = string("tern_4_w1")];
            tensor<fp16, [960]> mul_218_y_0 = const()[name = string("mul_218_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3864896)))];
            tensor<fp16, [256, 960]> mul_218 = mul(x = tern_4_w1, y = mul_218_y_0)[name = string("mul_218")];
            tensor<fp16, [352]> mul_221_y_0 = const()[name = string("mul_221_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3866880)))];
            tensor<fp16, [256, 352]> mul_221 = mul(x = mul_216, y = mul_221_y_0)[name = string("mul_221")];
            tensor<fp16, [960, 352]> tern_4_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3867648))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_4_w3_weight_0_palettized")];
            tensor<fp16, [256, 960]> tern_4_w3 = linear(bias = linear_4_bias_0, weight = tern_4_w3_weight_0_palettized, x = mul_221)[name = string("tern_4_w3")];
            tensor<fp16, [960]> mul_222_y_0 = const()[name = string("mul_222_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3952192)))];
            tensor<fp16, [256, 960]> mul_222 = mul(x = tern_4_w3, y = mul_222_y_0)[name = string("mul_222")];
            fp16 mul_223_y_0 = const()[name = string("mul_223_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [256, 960]> mul_223 = mul(x = mul_218, y = mul_223_y_0)[name = string("mul_223")];
            tensor<fp16, [256, 960]> tanh_4 = tanh(x = mul_223)[name = string("tanh_4")];
            fp16 mul_224_x_0 = const()[name = string("mul_224_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [256, 960]> mul_224 = mul(x = mul_224_x_0, y = tanh_4)[name = string("mul_224")];
            fp16 add_28_x_0 = const()[name = string("add_28_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [256, 960]> add_28 = add(x = add_28_x_0, y = mul_224)[name = string("add_28")];
            tensor<fp16, [256, 960]> mul_225 = mul(x = mul_218, y = add_28)[name = string("mul_225")];
            tensor<fp16, [256, 960]> mul_226 = mul(x = mul_225, y = mul_222)[name = string("mul_226")];
            tensor<fp16, [256, 960]> mul_227 = mul(x = mul_226, y = mul_226)[name = string("mul_227")];
            tensor<int32, [1]> reduce_mean_48_axes_0 = const()[name = string("reduce_mean_48_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_48_keep_dims_0 = const()[name = string("reduce_mean_48_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_48 = reduce_mean(axes = reduce_mean_48_axes_0, keep_dims = reduce_mean_48_keep_dims_0, x = mul_227)[name = string("reduce_mean_48")];
            fp32 rsqrt_48_epsilon_0 = const()[name = string("rsqrt_48_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_48 = rsqrt(epsilon = rsqrt_48_epsilon_0, x = reduce_mean_48)[name = string("rsqrt_48")];
            tensor<fp16, [256, 960]> mul_228 = mul(x = mul_226, y = rsqrt_48)[name = string("mul_228")];
            tensor<fp16, [960]> mul_229_y_0 = const()[name = string("mul_229_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3954176)))];
            tensor<fp16, [256, 960]> mul_229 = mul(x = mul_228, y = mul_229_y_0)[name = string("mul_229")];
            tensor<fp16, [352, 960]> tern_4_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3956160))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_4_w2_weight_0_palettized")];
            tensor<fp16, [256, 352]> tern_4_w2 = linear(bias = linear_0_bias_0, weight = tern_4_w2_weight_0_palettized, x = mul_229)[name = string("tern_4_w2")];
            tensor<fp16, [352]> mul_230_y_0 = const()[name = string("mul_230_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4040704)))];
            tensor<fp16, [256, 352]> mul_230 = mul(x = tern_4_w2, y = mul_230_y_0)[name = string("mul_230")];
            tensor<fp16, [256, 352]> add_29 = add(x = add_27, y = mul_230)[name = string("add_29")];
            tensor<fp16, [256, 352]> mul_231 = mul(x = add_29, y = add_29)[name = string("mul_231")];
            tensor<int32, [1]> reduce_mean_49_axes_0 = const()[name = string("reduce_mean_49_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_49_keep_dims_0 = const()[name = string("reduce_mean_49_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_49 = reduce_mean(axes = reduce_mean_49_axes_0, keep_dims = reduce_mean_49_keep_dims_0, x = mul_231)[name = string("reduce_mean_49")];
            fp32 rsqrt_49_epsilon_0 = const()[name = string("rsqrt_49_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_49 = rsqrt(epsilon = rsqrt_49_epsilon_0, x = reduce_mean_49)[name = string("rsqrt_49")];
            tensor<fp16, [256, 352]> mul_232 = mul(x = add_29, y = rsqrt_49)[name = string("mul_232")];
            tensor<fp16, [352]> mul_233_y_0 = const()[name = string("mul_233_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4041472)))];
            tensor<fp16, [256, 352]> mul_233 = mul(x = mul_232, y = mul_233_y_0)[name = string("mul_233")];
            tensor<fp16, [256, 352]> mul_234 = mul(x = mul_233, y = mul_233)[name = string("mul_234")];
            tensor<int32, [1]> reduce_mean_50_axes_0 = const()[name = string("reduce_mean_50_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_50_keep_dims_0 = const()[name = string("reduce_mean_50_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_50 = reduce_mean(axes = reduce_mean_50_axes_0, keep_dims = reduce_mean_50_keep_dims_0, x = mul_234)[name = string("reduce_mean_50")];
            fp32 rsqrt_50_epsilon_0 = const()[name = string("rsqrt_50_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_50 = rsqrt(epsilon = rsqrt_50_epsilon_0, x = reduce_mean_50)[name = string("rsqrt_50")];
            tensor<fp16, [256, 352]> mul_235 = mul(x = mul_233, y = rsqrt_50)[name = string("mul_235")];
            tensor<fp16, [352]> mul_236_y_0 = const()[name = string("mul_236_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4042240)))];
            tensor<fp16, [256, 352]> mul_236 = mul(x = mul_235, y = mul_236_y_0)[name = string("mul_236")];
            tensor<fp16, [352, 352]> tern_5_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4043008))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_5_q_weight_0_palettized")];
            tensor<fp16, [256, 352]> tern_5_q = linear(bias = linear_0_bias_0, weight = tern_5_q_weight_0_palettized, x = mul_236)[name = string("tern_5_q")];
            tensor<fp16, [352]> mul_237_y_0 = const()[name = string("mul_237_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4074048)))];
            tensor<fp16, [256, 352]> mul_237 = mul(x = tern_5_q, y = mul_237_y_0)[name = string("mul_237")];
            tensor<int32, [3]> reshape_42_shape_0 = const()[name = string("reshape_42_shape_0"), val = tensor<int32, [3]>([256, 8, 44])];
            tensor<fp16, [256, 8, 44]> reshape_42 = reshape(shape = reshape_42_shape_0, x = mul_237)[name = string("reshape_42")];
            tensor<int32, [3]> transpose_20_perm_0 = const()[name = string("transpose_20_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_240_y_0 = const()[name = string("mul_240_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4074816)))];
            tensor<fp16, [256, 352]> mul_240 = mul(x = mul_235, y = mul_240_y_0)[name = string("mul_240")];
            tensor<fp16, [88, 352]> tern_5_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4075584))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_5_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_5_k_bias_0 = const()[name = string("tern_5_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [256, 88]> tern_5_k = linear(bias = tern_5_k_bias_0, weight = tern_5_k_weight_0_palettized, x = mul_240)[name = string("tern_5_k")];
            tensor<fp16, [88]> mul_241_y_0 = const()[name = string("mul_241_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4083392)))];
            tensor<fp16, [256, 88]> mul_241 = mul(x = tern_5_k, y = mul_241_y_0)[name = string("mul_241")];
            tensor<int32, [3]> reshape_43_shape_0 = const()[name = string("reshape_43_shape_0"), val = tensor<int32, [3]>([256, 2, 44])];
            tensor<fp16, [256, 2, 44]> reshape_43 = reshape(shape = reshape_43_shape_0, x = mul_241)[name = string("reshape_43")];
            tensor<int32, [3]> transpose_21_perm_0 = const()[name = string("transpose_21_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_244_y_0 = const()[name = string("mul_244_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4083648)))];
            tensor<fp16, [256, 352]> mul_244 = mul(x = mul_235, y = mul_244_y_0)[name = string("mul_244")];
            tensor<fp16, [88, 352]> tern_5_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4084416))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_5_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_5_v_bias_0 = const()[name = string("tern_5_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [256, 88]> tern_5_v = linear(bias = tern_5_v_bias_0, weight = tern_5_v_weight_0_palettized, x = mul_244)[name = string("tern_5_v")];
            tensor<fp16, [88]> mul_245_y_0 = const()[name = string("mul_245_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4092224)))];
            tensor<fp16, [256, 88]> mul_245 = mul(x = tern_5_v, y = mul_245_y_0)[name = string("mul_245")];
            tensor<int32, [3]> reshape_44_shape_0 = const()[name = string("reshape_44_shape_0"), val = tensor<int32, [3]>([256, 2, 44])];
            tensor<fp16, [256, 2, 44]> reshape_44 = reshape(shape = reshape_44_shape_0, x = mul_245)[name = string("reshape_44")];
            tensor<int32, [3]> transpose_22_perm_0 = const()[name = string("transpose_22_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 256, 44]> transpose_20 = transpose(perm = transpose_20_perm_0, x = reshape_42)[name = string("transpose_43")];
            tensor<fp16, [8, 256, 44]> mul_246 = mul(x = transpose_20, y = transpose_20)[name = string("mul_246")];
            tensor<int32, [1]> reduce_mean_53_axes_0 = const()[name = string("reduce_mean_53_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_53_keep_dims_0 = const()[name = string("reduce_mean_53_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 256, 1]> reduce_mean_53 = reduce_mean(axes = reduce_mean_53_axes_0, keep_dims = reduce_mean_53_keep_dims_0, x = mul_246)[name = string("reduce_mean_53")];
            fp32 rsqrt_53_epsilon_0 = const()[name = string("rsqrt_53_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 256, 1]> rsqrt_53 = rsqrt(epsilon = rsqrt_53_epsilon_0, x = reduce_mean_53)[name = string("rsqrt_53")];
            tensor<fp16, [8, 256, 44]> mul_247 = mul(x = transpose_20, y = rsqrt_53)[name = string("mul_247")];
            tensor<fp16, [44]> mul_248_y_0 = const()[name = string("mul_248_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4092480)))];
            tensor<fp16, [8, 256, 44]> mul_248 = mul(x = mul_247, y = mul_248_y_0)[name = string("mul_248")];
            tensor<int32, [3]> slice_by_index_20_begin_0 = const()[name = string("slice_by_index_20_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_20_end_0 = const()[name = string("slice_by_index_20_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_20_end_mask_0 = const()[name = string("slice_by_index_20_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 256, 22]> slice_by_index_20 = slice_by_index(begin = slice_by_index_20_begin_0, end = slice_by_index_20_end_0, end_mask = slice_by_index_20_end_mask_0, x = mul_248)[name = string("slice_by_index_20")];
            tensor<int32, [3]> slice_by_index_21_begin_0 = const()[name = string("slice_by_index_21_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_21_end_0 = const()[name = string("slice_by_index_21_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_21_end_mask_0 = const()[name = string("slice_by_index_21_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 256, 22]> slice_by_index_21 = slice_by_index(begin = slice_by_index_21_begin_0, end = slice_by_index_21_end_0, end_mask = slice_by_index_21_end_mask_0, x = mul_248)[name = string("slice_by_index_21")];
            int32 concat_10_axis_0 = const()[name = string("concat_10_axis_0"), val = int32(-1)];
            bool concat_10_interleave_0 = const()[name = string("concat_10_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 256, 44]> concat_10 = concat(axis = concat_10_axis_0, interleave = concat_10_interleave_0, values = (slice_by_index_21, slice_by_index_20))[name = string("concat_10")];
            tensor<fp16, [44]> mul_249_y_0 = const()[name = string("mul_249_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 256, 44]> mul_249 = mul(x = concat_10, y = mul_249_y_0)[name = string("mul_249")];
            tensor<fp16, [8, 256, 44]> mul_250 = mul(x = mul_248, y = mul_11_y_0)[name = string("mul_250")];
            tensor<fp16, [8, 256, 44]> mul_251 = mul(x = mul_249, y = mul_12_y_0)[name = string("mul_251")];
            tensor<fp16, [8, 256, 44]> add_30 = add(x = mul_250, y = mul_251)[name = string("add_30")];
            tensor<fp16, [2, 256, 44]> transpose_21 = transpose(perm = transpose_21_perm_0, x = reshape_43)[name = string("transpose_42")];
            tensor<fp16, [2, 256, 44]> mul_252 = mul(x = transpose_21, y = transpose_21)[name = string("mul_252")];
            tensor<int32, [1]> reduce_mean_54_axes_0 = const()[name = string("reduce_mean_54_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_54_keep_dims_0 = const()[name = string("reduce_mean_54_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 256, 1]> reduce_mean_54 = reduce_mean(axes = reduce_mean_54_axes_0, keep_dims = reduce_mean_54_keep_dims_0, x = mul_252)[name = string("reduce_mean_54")];
            fp32 rsqrt_54_epsilon_0 = const()[name = string("rsqrt_54_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 256, 1]> rsqrt_54 = rsqrt(epsilon = rsqrt_54_epsilon_0, x = reduce_mean_54)[name = string("rsqrt_54")];
            tensor<fp16, [2, 256, 44]> mul_253 = mul(x = transpose_21, y = rsqrt_54)[name = string("mul_253")];
            tensor<fp16, [44]> mul_254_y_0 = const()[name = string("mul_254_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4092672)))];
            tensor<fp16, [2, 256, 44]> mul_254 = mul(x = mul_253, y = mul_254_y_0)[name = string("mul_254")];
            tensor<int32, [3]> slice_by_index_22_begin_0 = const()[name = string("slice_by_index_22_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_22_end_0 = const()[name = string("slice_by_index_22_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_22_end_mask_0 = const()[name = string("slice_by_index_22_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 256, 22]> slice_by_index_22 = slice_by_index(begin = slice_by_index_22_begin_0, end = slice_by_index_22_end_0, end_mask = slice_by_index_22_end_mask_0, x = mul_254)[name = string("slice_by_index_22")];
            tensor<int32, [3]> slice_by_index_23_begin_0 = const()[name = string("slice_by_index_23_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_23_end_0 = const()[name = string("slice_by_index_23_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_23_end_mask_0 = const()[name = string("slice_by_index_23_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 256, 22]> slice_by_index_23 = slice_by_index(begin = slice_by_index_23_begin_0, end = slice_by_index_23_end_0, end_mask = slice_by_index_23_end_mask_0, x = mul_254)[name = string("slice_by_index_23")];
            int32 concat_11_axis_0 = const()[name = string("concat_11_axis_0"), val = int32(-1)];
            bool concat_11_interleave_0 = const()[name = string("concat_11_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 256, 44]> concat_11 = concat(axis = concat_11_axis_0, interleave = concat_11_interleave_0, values = (slice_by_index_23, slice_by_index_22))[name = string("concat_11")];
            tensor<fp16, [44]> mul_255_y_0 = const()[name = string("mul_255_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 256, 44]> mul_255 = mul(x = concat_11, y = mul_255_y_0)[name = string("mul_255")];
            tensor<fp16, [2, 256, 44]> mul_256 = mul(x = mul_254, y = mul_11_y_0)[name = string("mul_256")];
            tensor<fp16, [2, 256, 44]> mul_257 = mul(x = mul_255, y = mul_12_y_0)[name = string("mul_257")];
            tensor<fp16, [2, 256, 44]> add_31 = add(x = mul_256, y = mul_257)[name = string("add_31")];
            tensor<int32, [4]> reshape_45_shape_0 = const()[name = string("reshape_45_shape_0"), val = tensor<int32, [4]>([2, 1, 256, 44])];
            tensor<fp16, [2, 1, 256, 44]> reshape_45 = reshape(shape = reshape_45_shape_0, x = add_31)[name = string("reshape_45")];
            tensor<int32, [4]> tile_10_reps_0 = const()[name = string("tile_10_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 256, 44]> tile_10 = tile(reps = tile_10_reps_0, x = reshape_45)[name = string("tile_10")];
            tensor<int32, [3]> reshape_46_shape_0 = const()[name = string("reshape_46_shape_0"), val = tensor<int32, [3]>([8, 256, 44])];
            tensor<fp16, [8, 256, 44]> reshape_46 = reshape(shape = reshape_46_shape_0, x = tile_10)[name = string("reshape_46")];
            tensor<int32, [4]> reshape_47_shape_0 = const()[name = string("reshape_47_shape_0"), val = tensor<int32, [4]>([2, 1, 256, 44])];
            tensor<fp16, [2, 256, 44]> transpose_22 = transpose(perm = transpose_22_perm_0, x = reshape_44)[name = string("transpose_41")];
            tensor<fp16, [2, 1, 256, 44]> reshape_47 = reshape(shape = reshape_47_shape_0, x = transpose_22)[name = string("reshape_47")];
            tensor<int32, [4]> tile_11_reps_0 = const()[name = string("tile_11_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 256, 44]> tile_11 = tile(reps = tile_11_reps_0, x = reshape_47)[name = string("tile_11")];
            tensor<int32, [3]> reshape_48_shape_0 = const()[name = string("reshape_48_shape_0"), val = tensor<int32, [3]>([8, 256, 44])];
            tensor<fp16, [8, 256, 44]> reshape_48 = reshape(shape = reshape_48_shape_0, x = tile_11)[name = string("reshape_48")];
            fp16 mul_258_y_0 = const()[name = string("mul_258_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 256, 44]> mul_258 = mul(x = add_30, y = mul_258_y_0)[name = string("mul_258")];
            bool matmul_10_transpose_y_0 = const()[name = string("matmul_10_transpose_y_0"), val = bool(true)];
            bool matmul_10_transpose_x_0 = const()[name = string("matmul_10_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 256, 256]> matmul_10 = matmul(transpose_x = matmul_10_transpose_x_0, transpose_y = matmul_10_transpose_y_0, x = mul_258, y = reshape_46)[name = string("matmul_10")];
            tensor<fp16, [8, 256, 256]> add_32 = add(x = matmul_10, y = reshape_1)[name = string("add_32")];
            int32 softmax_5_axis_0 = const()[name = string("softmax_5_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 256, 256]> softmax_5 = softmax(axis = softmax_5_axis_0, x = add_32)[name = string("softmax_5")];
            bool matmul_11_transpose_x_0 = const()[name = string("matmul_11_transpose_x_0"), val = bool(false)];
            bool matmul_11_transpose_y_0 = const()[name = string("matmul_11_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 256, 44]> matmul_11 = matmul(transpose_x = matmul_11_transpose_x_0, transpose_y = matmul_11_transpose_y_0, x = softmax_5, y = reshape_48)[name = string("matmul_11")];
            tensor<int32, [3]> transpose_23_perm_0 = const()[name = string("transpose_23_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_49_shape_0 = const()[name = string("reshape_49_shape_0"), val = tensor<int32, [2]>([256, 352])];
            tensor<fp16, [256, 8, 44]> transpose_23 = transpose(perm = transpose_23_perm_0, x = matmul_11)[name = string("transpose_40")];
            tensor<fp16, [256, 352]> reshape_49 = reshape(shape = reshape_49_shape_0, x = transpose_23)[name = string("reshape_49")];
            tensor<fp16, [256, 352]> mul_259 = mul(x = reshape_49, y = reshape_49)[name = string("mul_259")];
            tensor<int32, [1]> reduce_mean_55_axes_0 = const()[name = string("reduce_mean_55_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_55_keep_dims_0 = const()[name = string("reduce_mean_55_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_55 = reduce_mean(axes = reduce_mean_55_axes_0, keep_dims = reduce_mean_55_keep_dims_0, x = mul_259)[name = string("reduce_mean_55")];
            fp32 rsqrt_55_epsilon_0 = const()[name = string("rsqrt_55_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_55 = rsqrt(epsilon = rsqrt_55_epsilon_0, x = reduce_mean_55)[name = string("rsqrt_55")];
            tensor<fp16, [256, 352]> mul_260 = mul(x = reshape_49, y = rsqrt_55)[name = string("mul_260")];
            tensor<fp16, [352]> mul_261_y_0 = const()[name = string("mul_261_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4092864)))];
            tensor<fp16, [256, 352]> mul_261 = mul(x = mul_260, y = mul_261_y_0)[name = string("mul_261")];
            tensor<fp16, [352, 352]> tern_5_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4093632))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_5_o_weight_0_palettized")];
            tensor<fp16, [256, 352]> tern_5_o = linear(bias = linear_0_bias_0, weight = tern_5_o_weight_0_palettized, x = mul_261)[name = string("tern_5_o")];
            tensor<fp16, [352]> mul_262_y_0 = const()[name = string("mul_262_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4124672)))];
            tensor<fp16, [256, 352]> mul_262 = mul(x = tern_5_o, y = mul_262_y_0)[name = string("mul_262")];
            tensor<fp16, [256, 352]> add_33 = add(x = add_29, y = mul_262)[name = string("add_33")];
            tensor<fp16, [256, 352]> mul_263 = mul(x = add_33, y = add_33)[name = string("mul_263")];
            tensor<int32, [1]> reduce_mean_56_axes_0 = const()[name = string("reduce_mean_56_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_56_keep_dims_0 = const()[name = string("reduce_mean_56_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_56 = reduce_mean(axes = reduce_mean_56_axes_0, keep_dims = reduce_mean_56_keep_dims_0, x = mul_263)[name = string("reduce_mean_56")];
            fp32 rsqrt_56_epsilon_0 = const()[name = string("rsqrt_56_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_56 = rsqrt(epsilon = rsqrt_56_epsilon_0, x = reduce_mean_56)[name = string("rsqrt_56")];
            tensor<fp16, [256, 352]> mul_264 = mul(x = add_33, y = rsqrt_56)[name = string("mul_264")];
            tensor<fp16, [352]> mul_265_y_0 = const()[name = string("mul_265_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4125440)))];
            tensor<fp16, [256, 352]> mul_265 = mul(x = mul_264, y = mul_265_y_0)[name = string("mul_265")];
            tensor<fp16, [256, 352]> mul_266 = mul(x = mul_265, y = mul_265)[name = string("mul_266")];
            tensor<int32, [1]> reduce_mean_57_axes_0 = const()[name = string("reduce_mean_57_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_57_keep_dims_0 = const()[name = string("reduce_mean_57_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_57 = reduce_mean(axes = reduce_mean_57_axes_0, keep_dims = reduce_mean_57_keep_dims_0, x = mul_266)[name = string("reduce_mean_57")];
            fp32 rsqrt_57_epsilon_0 = const()[name = string("rsqrt_57_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_57 = rsqrt(epsilon = rsqrt_57_epsilon_0, x = reduce_mean_57)[name = string("rsqrt_57")];
            tensor<fp16, [256, 352]> mul_267 = mul(x = mul_265, y = rsqrt_57)[name = string("mul_267")];
            tensor<fp16, [352]> mul_268_y_0 = const()[name = string("mul_268_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4126208)))];
            tensor<fp16, [256, 352]> mul_268 = mul(x = mul_267, y = mul_268_y_0)[name = string("mul_268")];
            tensor<fp16, [960, 352]> tern_5_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4126976))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_5_w1_weight_0_palettized")];
            tensor<fp16, [256, 960]> tern_5_w1 = linear(bias = linear_4_bias_0, weight = tern_5_w1_weight_0_palettized, x = mul_268)[name = string("tern_5_w1")];
            tensor<fp16, [960]> mul_269_y_0 = const()[name = string("mul_269_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4211520)))];
            tensor<fp16, [256, 960]> mul_269 = mul(x = tern_5_w1, y = mul_269_y_0)[name = string("mul_269")];
            tensor<fp16, [352]> mul_272_y_0 = const()[name = string("mul_272_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4213504)))];
            tensor<fp16, [256, 352]> mul_272 = mul(x = mul_267, y = mul_272_y_0)[name = string("mul_272")];
            tensor<fp16, [960, 352]> tern_5_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4214272))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_5_w3_weight_0_palettized")];
            tensor<fp16, [256, 960]> tern_5_w3 = linear(bias = linear_4_bias_0, weight = tern_5_w3_weight_0_palettized, x = mul_272)[name = string("tern_5_w3")];
            tensor<fp16, [960]> mul_273_y_0 = const()[name = string("mul_273_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4298816)))];
            tensor<fp16, [256, 960]> mul_273 = mul(x = tern_5_w3, y = mul_273_y_0)[name = string("mul_273")];
            fp16 mul_274_y_0 = const()[name = string("mul_274_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [256, 960]> mul_274 = mul(x = mul_269, y = mul_274_y_0)[name = string("mul_274")];
            tensor<fp16, [256, 960]> tanh_5 = tanh(x = mul_274)[name = string("tanh_5")];
            fp16 mul_275_x_0 = const()[name = string("mul_275_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [256, 960]> mul_275 = mul(x = mul_275_x_0, y = tanh_5)[name = string("mul_275")];
            fp16 add_34_x_0 = const()[name = string("add_34_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [256, 960]> add_34 = add(x = add_34_x_0, y = mul_275)[name = string("add_34")];
            tensor<fp16, [256, 960]> mul_276 = mul(x = mul_269, y = add_34)[name = string("mul_276")];
            tensor<fp16, [256, 960]> mul_277 = mul(x = mul_276, y = mul_273)[name = string("mul_277")];
            tensor<fp16, [256, 960]> mul_278 = mul(x = mul_277, y = mul_277)[name = string("mul_278")];
            tensor<int32, [1]> reduce_mean_59_axes_0 = const()[name = string("reduce_mean_59_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_59_keep_dims_0 = const()[name = string("reduce_mean_59_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_59 = reduce_mean(axes = reduce_mean_59_axes_0, keep_dims = reduce_mean_59_keep_dims_0, x = mul_278)[name = string("reduce_mean_59")];
            fp32 rsqrt_59_epsilon_0 = const()[name = string("rsqrt_59_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_59 = rsqrt(epsilon = rsqrt_59_epsilon_0, x = reduce_mean_59)[name = string("rsqrt_59")];
            tensor<fp16, [256, 960]> mul_279 = mul(x = mul_277, y = rsqrt_59)[name = string("mul_279")];
            tensor<fp16, [960]> mul_280_y_0 = const()[name = string("mul_280_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4300800)))];
            tensor<fp16, [256, 960]> mul_280 = mul(x = mul_279, y = mul_280_y_0)[name = string("mul_280")];
            tensor<fp16, [352, 960]> tern_5_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4302784))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_5_w2_weight_0_palettized")];
            tensor<fp16, [256, 352]> tern_5_w2 = linear(bias = linear_0_bias_0, weight = tern_5_w2_weight_0_palettized, x = mul_280)[name = string("tern_5_w2")];
            tensor<fp16, [352]> mul_281_y_0 = const()[name = string("mul_281_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4387328)))];
            tensor<fp16, [256, 352]> mul_281 = mul(x = tern_5_w2, y = mul_281_y_0)[name = string("mul_281")];
            tensor<fp16, [256, 352]> add_35 = add(x = add_33, y = mul_281)[name = string("add_35")];
            tensor<fp16, [256, 352]> mul_282 = mul(x = add_35, y = add_35)[name = string("mul_282")];
            tensor<int32, [1]> reduce_mean_60_axes_0 = const()[name = string("reduce_mean_60_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_60_keep_dims_0 = const()[name = string("reduce_mean_60_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_60 = reduce_mean(axes = reduce_mean_60_axes_0, keep_dims = reduce_mean_60_keep_dims_0, x = mul_282)[name = string("reduce_mean_60")];
            fp32 rsqrt_60_epsilon_0 = const()[name = string("rsqrt_60_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_60 = rsqrt(epsilon = rsqrt_60_epsilon_0, x = reduce_mean_60)[name = string("rsqrt_60")];
            tensor<fp16, [256, 352]> mul_283 = mul(x = add_35, y = rsqrt_60)[name = string("mul_283")];
            tensor<fp16, [352]> mul_284_y_0 = const()[name = string("mul_284_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4388096)))];
            tensor<fp16, [256, 352]> mul_284 = mul(x = mul_283, y = mul_284_y_0)[name = string("mul_284")];
            tensor<fp16, [256, 352]> mul_285 = mul(x = mul_284, y = mul_284)[name = string("mul_285")];
            tensor<int32, [1]> reduce_mean_61_axes_0 = const()[name = string("reduce_mean_61_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_61_keep_dims_0 = const()[name = string("reduce_mean_61_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_61 = reduce_mean(axes = reduce_mean_61_axes_0, keep_dims = reduce_mean_61_keep_dims_0, x = mul_285)[name = string("reduce_mean_61")];
            fp32 rsqrt_61_epsilon_0 = const()[name = string("rsqrt_61_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_61 = rsqrt(epsilon = rsqrt_61_epsilon_0, x = reduce_mean_61)[name = string("rsqrt_61")];
            tensor<fp16, [256, 352]> mul_286 = mul(x = mul_284, y = rsqrt_61)[name = string("mul_286")];
            tensor<fp16, [352]> mul_287_y_0 = const()[name = string("mul_287_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4388864)))];
            tensor<fp16, [256, 352]> mul_287 = mul(x = mul_286, y = mul_287_y_0)[name = string("mul_287")];
            tensor<fp16, [352, 352]> tern_6_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4389632))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_6_q_weight_0_palettized")];
            tensor<fp16, [256, 352]> tern_6_q = linear(bias = linear_0_bias_0, weight = tern_6_q_weight_0_palettized, x = mul_287)[name = string("tern_6_q")];
            tensor<fp16, [352]> mul_288_y_0 = const()[name = string("mul_288_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4420672)))];
            tensor<fp16, [256, 352]> mul_288 = mul(x = tern_6_q, y = mul_288_y_0)[name = string("mul_288")];
            tensor<int32, [3]> reshape_50_shape_0 = const()[name = string("reshape_50_shape_0"), val = tensor<int32, [3]>([256, 8, 44])];
            tensor<fp16, [256, 8, 44]> reshape_50 = reshape(shape = reshape_50_shape_0, x = mul_288)[name = string("reshape_50")];
            tensor<int32, [3]> transpose_24_perm_0 = const()[name = string("transpose_24_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_291_y_0 = const()[name = string("mul_291_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4421440)))];
            tensor<fp16, [256, 352]> mul_291 = mul(x = mul_286, y = mul_291_y_0)[name = string("mul_291")];
            tensor<fp16, [88, 352]> tern_6_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4422208))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_6_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_6_k_bias_0 = const()[name = string("tern_6_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [256, 88]> tern_6_k = linear(bias = tern_6_k_bias_0, weight = tern_6_k_weight_0_palettized, x = mul_291)[name = string("tern_6_k")];
            tensor<fp16, [88]> mul_292_y_0 = const()[name = string("mul_292_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4430016)))];
            tensor<fp16, [256, 88]> mul_292 = mul(x = tern_6_k, y = mul_292_y_0)[name = string("mul_292")];
            tensor<int32, [3]> reshape_51_shape_0 = const()[name = string("reshape_51_shape_0"), val = tensor<int32, [3]>([256, 2, 44])];
            tensor<fp16, [256, 2, 44]> reshape_51 = reshape(shape = reshape_51_shape_0, x = mul_292)[name = string("reshape_51")];
            tensor<int32, [3]> transpose_25_perm_0 = const()[name = string("transpose_25_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_295_y_0 = const()[name = string("mul_295_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4430272)))];
            tensor<fp16, [256, 352]> mul_295 = mul(x = mul_286, y = mul_295_y_0)[name = string("mul_295")];
            tensor<fp16, [88, 352]> tern_6_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4431040))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_6_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_6_v_bias_0 = const()[name = string("tern_6_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [256, 88]> tern_6_v = linear(bias = tern_6_v_bias_0, weight = tern_6_v_weight_0_palettized, x = mul_295)[name = string("tern_6_v")];
            tensor<fp16, [88]> mul_296_y_0 = const()[name = string("mul_296_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4438848)))];
            tensor<fp16, [256, 88]> mul_296 = mul(x = tern_6_v, y = mul_296_y_0)[name = string("mul_296")];
            tensor<int32, [3]> reshape_52_shape_0 = const()[name = string("reshape_52_shape_0"), val = tensor<int32, [3]>([256, 2, 44])];
            tensor<fp16, [256, 2, 44]> reshape_52 = reshape(shape = reshape_52_shape_0, x = mul_296)[name = string("reshape_52")];
            tensor<int32, [3]> transpose_26_perm_0 = const()[name = string("transpose_26_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 256, 44]> transpose_24 = transpose(perm = transpose_24_perm_0, x = reshape_50)[name = string("transpose_39")];
            tensor<fp16, [8, 256, 44]> mul_297 = mul(x = transpose_24, y = transpose_24)[name = string("mul_297")];
            tensor<int32, [1]> reduce_mean_64_axes_0 = const()[name = string("reduce_mean_64_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_64_keep_dims_0 = const()[name = string("reduce_mean_64_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 256, 1]> reduce_mean_64 = reduce_mean(axes = reduce_mean_64_axes_0, keep_dims = reduce_mean_64_keep_dims_0, x = mul_297)[name = string("reduce_mean_64")];
            fp32 rsqrt_64_epsilon_0 = const()[name = string("rsqrt_64_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 256, 1]> rsqrt_64 = rsqrt(epsilon = rsqrt_64_epsilon_0, x = reduce_mean_64)[name = string("rsqrt_64")];
            tensor<fp16, [8, 256, 44]> mul_298 = mul(x = transpose_24, y = rsqrt_64)[name = string("mul_298")];
            tensor<fp16, [44]> mul_299_y_0 = const()[name = string("mul_299_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4439104)))];
            tensor<fp16, [8, 256, 44]> mul_299 = mul(x = mul_298, y = mul_299_y_0)[name = string("mul_299")];
            tensor<int32, [3]> slice_by_index_24_begin_0 = const()[name = string("slice_by_index_24_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_24_end_0 = const()[name = string("slice_by_index_24_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_24_end_mask_0 = const()[name = string("slice_by_index_24_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 256, 22]> slice_by_index_24 = slice_by_index(begin = slice_by_index_24_begin_0, end = slice_by_index_24_end_0, end_mask = slice_by_index_24_end_mask_0, x = mul_299)[name = string("slice_by_index_24")];
            tensor<int32, [3]> slice_by_index_25_begin_0 = const()[name = string("slice_by_index_25_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_25_end_0 = const()[name = string("slice_by_index_25_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_25_end_mask_0 = const()[name = string("slice_by_index_25_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 256, 22]> slice_by_index_25 = slice_by_index(begin = slice_by_index_25_begin_0, end = slice_by_index_25_end_0, end_mask = slice_by_index_25_end_mask_0, x = mul_299)[name = string("slice_by_index_25")];
            int32 concat_12_axis_0 = const()[name = string("concat_12_axis_0"), val = int32(-1)];
            bool concat_12_interleave_0 = const()[name = string("concat_12_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 256, 44]> concat_12 = concat(axis = concat_12_axis_0, interleave = concat_12_interleave_0, values = (slice_by_index_25, slice_by_index_24))[name = string("concat_12")];
            tensor<fp16, [44]> mul_300_y_0 = const()[name = string("mul_300_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 256, 44]> mul_300 = mul(x = concat_12, y = mul_300_y_0)[name = string("mul_300")];
            tensor<fp16, [8, 256, 44]> mul_301 = mul(x = mul_299, y = mul_11_y_0)[name = string("mul_301")];
            tensor<fp16, [8, 256, 44]> mul_302 = mul(x = mul_300, y = mul_12_y_0)[name = string("mul_302")];
            tensor<fp16, [8, 256, 44]> add_36 = add(x = mul_301, y = mul_302)[name = string("add_36")];
            tensor<fp16, [2, 256, 44]> transpose_25 = transpose(perm = transpose_25_perm_0, x = reshape_51)[name = string("transpose_38")];
            tensor<fp16, [2, 256, 44]> mul_303 = mul(x = transpose_25, y = transpose_25)[name = string("mul_303")];
            tensor<int32, [1]> reduce_mean_65_axes_0 = const()[name = string("reduce_mean_65_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_65_keep_dims_0 = const()[name = string("reduce_mean_65_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 256, 1]> reduce_mean_65 = reduce_mean(axes = reduce_mean_65_axes_0, keep_dims = reduce_mean_65_keep_dims_0, x = mul_303)[name = string("reduce_mean_65")];
            fp32 rsqrt_65_epsilon_0 = const()[name = string("rsqrt_65_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 256, 1]> rsqrt_65 = rsqrt(epsilon = rsqrt_65_epsilon_0, x = reduce_mean_65)[name = string("rsqrt_65")];
            tensor<fp16, [2, 256, 44]> mul_304 = mul(x = transpose_25, y = rsqrt_65)[name = string("mul_304")];
            tensor<fp16, [44]> mul_305_y_0 = const()[name = string("mul_305_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4439296)))];
            tensor<fp16, [2, 256, 44]> mul_305 = mul(x = mul_304, y = mul_305_y_0)[name = string("mul_305")];
            tensor<int32, [3]> slice_by_index_26_begin_0 = const()[name = string("slice_by_index_26_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_26_end_0 = const()[name = string("slice_by_index_26_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_26_end_mask_0 = const()[name = string("slice_by_index_26_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 256, 22]> slice_by_index_26 = slice_by_index(begin = slice_by_index_26_begin_0, end = slice_by_index_26_end_0, end_mask = slice_by_index_26_end_mask_0, x = mul_305)[name = string("slice_by_index_26")];
            tensor<int32, [3]> slice_by_index_27_begin_0 = const()[name = string("slice_by_index_27_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_27_end_0 = const()[name = string("slice_by_index_27_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_27_end_mask_0 = const()[name = string("slice_by_index_27_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 256, 22]> slice_by_index_27 = slice_by_index(begin = slice_by_index_27_begin_0, end = slice_by_index_27_end_0, end_mask = slice_by_index_27_end_mask_0, x = mul_305)[name = string("slice_by_index_27")];
            int32 concat_13_axis_0 = const()[name = string("concat_13_axis_0"), val = int32(-1)];
            bool concat_13_interleave_0 = const()[name = string("concat_13_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 256, 44]> concat_13 = concat(axis = concat_13_axis_0, interleave = concat_13_interleave_0, values = (slice_by_index_27, slice_by_index_26))[name = string("concat_13")];
            tensor<fp16, [44]> mul_306_y_0 = const()[name = string("mul_306_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 256, 44]> mul_306 = mul(x = concat_13, y = mul_306_y_0)[name = string("mul_306")];
            tensor<fp16, [2, 256, 44]> mul_307 = mul(x = mul_305, y = mul_11_y_0)[name = string("mul_307")];
            tensor<fp16, [2, 256, 44]> mul_308 = mul(x = mul_306, y = mul_12_y_0)[name = string("mul_308")];
            tensor<fp16, [2, 256, 44]> add_37 = add(x = mul_307, y = mul_308)[name = string("add_37")];
            tensor<int32, [4]> reshape_53_shape_0 = const()[name = string("reshape_53_shape_0"), val = tensor<int32, [4]>([2, 1, 256, 44])];
            tensor<fp16, [2, 1, 256, 44]> reshape_53 = reshape(shape = reshape_53_shape_0, x = add_37)[name = string("reshape_53")];
            tensor<int32, [4]> tile_12_reps_0 = const()[name = string("tile_12_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 256, 44]> tile_12 = tile(reps = tile_12_reps_0, x = reshape_53)[name = string("tile_12")];
            tensor<int32, [3]> reshape_54_shape_0 = const()[name = string("reshape_54_shape_0"), val = tensor<int32, [3]>([8, 256, 44])];
            tensor<fp16, [8, 256, 44]> reshape_54 = reshape(shape = reshape_54_shape_0, x = tile_12)[name = string("reshape_54")];
            tensor<int32, [4]> reshape_55_shape_0 = const()[name = string("reshape_55_shape_0"), val = tensor<int32, [4]>([2, 1, 256, 44])];
            tensor<fp16, [2, 256, 44]> transpose_26 = transpose(perm = transpose_26_perm_0, x = reshape_52)[name = string("transpose_37")];
            tensor<fp16, [2, 1, 256, 44]> reshape_55 = reshape(shape = reshape_55_shape_0, x = transpose_26)[name = string("reshape_55")];
            tensor<int32, [4]> tile_13_reps_0 = const()[name = string("tile_13_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 256, 44]> tile_13 = tile(reps = tile_13_reps_0, x = reshape_55)[name = string("tile_13")];
            tensor<int32, [3]> reshape_56_shape_0 = const()[name = string("reshape_56_shape_0"), val = tensor<int32, [3]>([8, 256, 44])];
            tensor<fp16, [8, 256, 44]> reshape_56 = reshape(shape = reshape_56_shape_0, x = tile_13)[name = string("reshape_56")];
            fp16 mul_309_y_0 = const()[name = string("mul_309_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 256, 44]> mul_309 = mul(x = add_36, y = mul_309_y_0)[name = string("mul_309")];
            bool matmul_12_transpose_y_0 = const()[name = string("matmul_12_transpose_y_0"), val = bool(true)];
            bool matmul_12_transpose_x_0 = const()[name = string("matmul_12_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 256, 256]> matmul_12 = matmul(transpose_x = matmul_12_transpose_x_0, transpose_y = matmul_12_transpose_y_0, x = mul_309, y = reshape_54)[name = string("matmul_12")];
            tensor<fp16, [8, 256, 256]> add_38 = add(x = matmul_12, y = reshape_1)[name = string("add_38")];
            int32 softmax_6_axis_0 = const()[name = string("softmax_6_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 256, 256]> softmax_6 = softmax(axis = softmax_6_axis_0, x = add_38)[name = string("softmax_6")];
            bool matmul_13_transpose_x_0 = const()[name = string("matmul_13_transpose_x_0"), val = bool(false)];
            bool matmul_13_transpose_y_0 = const()[name = string("matmul_13_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 256, 44]> matmul_13 = matmul(transpose_x = matmul_13_transpose_x_0, transpose_y = matmul_13_transpose_y_0, x = softmax_6, y = reshape_56)[name = string("matmul_13")];
            tensor<int32, [3]> transpose_27_perm_0 = const()[name = string("transpose_27_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_57_shape_0 = const()[name = string("reshape_57_shape_0"), val = tensor<int32, [2]>([256, 352])];
            tensor<fp16, [256, 8, 44]> transpose_27 = transpose(perm = transpose_27_perm_0, x = matmul_13)[name = string("transpose_36")];
            tensor<fp16, [256, 352]> reshape_57 = reshape(shape = reshape_57_shape_0, x = transpose_27)[name = string("reshape_57")];
            tensor<fp16, [256, 352]> mul_310 = mul(x = reshape_57, y = reshape_57)[name = string("mul_310")];
            tensor<int32, [1]> reduce_mean_66_axes_0 = const()[name = string("reduce_mean_66_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_66_keep_dims_0 = const()[name = string("reduce_mean_66_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_66 = reduce_mean(axes = reduce_mean_66_axes_0, keep_dims = reduce_mean_66_keep_dims_0, x = mul_310)[name = string("reduce_mean_66")];
            fp32 rsqrt_66_epsilon_0 = const()[name = string("rsqrt_66_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_66 = rsqrt(epsilon = rsqrt_66_epsilon_0, x = reduce_mean_66)[name = string("rsqrt_66")];
            tensor<fp16, [256, 352]> mul_311 = mul(x = reshape_57, y = rsqrt_66)[name = string("mul_311")];
            tensor<fp16, [352]> mul_312_y_0 = const()[name = string("mul_312_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4439488)))];
            tensor<fp16, [256, 352]> mul_312 = mul(x = mul_311, y = mul_312_y_0)[name = string("mul_312")];
            tensor<fp16, [352, 352]> tern_6_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4440256))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_6_o_weight_0_palettized")];
            tensor<fp16, [256, 352]> tern_6_o = linear(bias = linear_0_bias_0, weight = tern_6_o_weight_0_palettized, x = mul_312)[name = string("tern_6_o")];
            tensor<fp16, [352]> mul_313_y_0 = const()[name = string("mul_313_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4471296)))];
            tensor<fp16, [256, 352]> mul_313 = mul(x = tern_6_o, y = mul_313_y_0)[name = string("mul_313")];
            tensor<fp16, [256, 352]> add_39 = add(x = add_35, y = mul_313)[name = string("add_39")];
            tensor<fp16, [256, 352]> mul_314 = mul(x = add_39, y = add_39)[name = string("mul_314")];
            tensor<int32, [1]> reduce_mean_67_axes_0 = const()[name = string("reduce_mean_67_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_67_keep_dims_0 = const()[name = string("reduce_mean_67_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_67 = reduce_mean(axes = reduce_mean_67_axes_0, keep_dims = reduce_mean_67_keep_dims_0, x = mul_314)[name = string("reduce_mean_67")];
            fp32 rsqrt_67_epsilon_0 = const()[name = string("rsqrt_67_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_67 = rsqrt(epsilon = rsqrt_67_epsilon_0, x = reduce_mean_67)[name = string("rsqrt_67")];
            tensor<fp16, [256, 352]> mul_315 = mul(x = add_39, y = rsqrt_67)[name = string("mul_315")];
            tensor<fp16, [352]> mul_316_y_0 = const()[name = string("mul_316_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4472064)))];
            tensor<fp16, [256, 352]> mul_316 = mul(x = mul_315, y = mul_316_y_0)[name = string("mul_316")];
            tensor<fp16, [256, 352]> mul_317 = mul(x = mul_316, y = mul_316)[name = string("mul_317")];
            tensor<int32, [1]> reduce_mean_68_axes_0 = const()[name = string("reduce_mean_68_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_68_keep_dims_0 = const()[name = string("reduce_mean_68_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_68 = reduce_mean(axes = reduce_mean_68_axes_0, keep_dims = reduce_mean_68_keep_dims_0, x = mul_317)[name = string("reduce_mean_68")];
            fp32 rsqrt_68_epsilon_0 = const()[name = string("rsqrt_68_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_68 = rsqrt(epsilon = rsqrt_68_epsilon_0, x = reduce_mean_68)[name = string("rsqrt_68")];
            tensor<fp16, [256, 352]> mul_318 = mul(x = mul_316, y = rsqrt_68)[name = string("mul_318")];
            tensor<fp16, [352]> mul_319_y_0 = const()[name = string("mul_319_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4472832)))];
            tensor<fp16, [256, 352]> mul_319 = mul(x = mul_318, y = mul_319_y_0)[name = string("mul_319")];
            tensor<fp16, [960, 352]> tern_6_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4473600))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_6_w1_weight_0_palettized")];
            tensor<fp16, [256, 960]> tern_6_w1 = linear(bias = linear_4_bias_0, weight = tern_6_w1_weight_0_palettized, x = mul_319)[name = string("tern_6_w1")];
            tensor<fp16, [960]> mul_320_y_0 = const()[name = string("mul_320_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4558144)))];
            tensor<fp16, [256, 960]> mul_320 = mul(x = tern_6_w1, y = mul_320_y_0)[name = string("mul_320")];
            tensor<fp16, [352]> mul_323_y_0 = const()[name = string("mul_323_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4560128)))];
            tensor<fp16, [256, 352]> mul_323 = mul(x = mul_318, y = mul_323_y_0)[name = string("mul_323")];
            tensor<fp16, [960, 352]> tern_6_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4560896))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_6_w3_weight_0_palettized")];
            tensor<fp16, [256, 960]> tern_6_w3 = linear(bias = linear_4_bias_0, weight = tern_6_w3_weight_0_palettized, x = mul_323)[name = string("tern_6_w3")];
            tensor<fp16, [960]> mul_324_y_0 = const()[name = string("mul_324_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4645440)))];
            tensor<fp16, [256, 960]> mul_324 = mul(x = tern_6_w3, y = mul_324_y_0)[name = string("mul_324")];
            fp16 mul_325_y_0 = const()[name = string("mul_325_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [256, 960]> mul_325 = mul(x = mul_320, y = mul_325_y_0)[name = string("mul_325")];
            tensor<fp16, [256, 960]> tanh_6 = tanh(x = mul_325)[name = string("tanh_6")];
            fp16 mul_326_x_0 = const()[name = string("mul_326_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [256, 960]> mul_326 = mul(x = mul_326_x_0, y = tanh_6)[name = string("mul_326")];
            fp16 add_40_x_0 = const()[name = string("add_40_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [256, 960]> add_40 = add(x = add_40_x_0, y = mul_326)[name = string("add_40")];
            tensor<fp16, [256, 960]> mul_327 = mul(x = mul_320, y = add_40)[name = string("mul_327")];
            tensor<fp16, [256, 960]> mul_328 = mul(x = mul_327, y = mul_324)[name = string("mul_328")];
            tensor<fp16, [256, 960]> mul_329 = mul(x = mul_328, y = mul_328)[name = string("mul_329")];
            tensor<int32, [1]> reduce_mean_70_axes_0 = const()[name = string("reduce_mean_70_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_70_keep_dims_0 = const()[name = string("reduce_mean_70_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_70 = reduce_mean(axes = reduce_mean_70_axes_0, keep_dims = reduce_mean_70_keep_dims_0, x = mul_329)[name = string("reduce_mean_70")];
            fp32 rsqrt_70_epsilon_0 = const()[name = string("rsqrt_70_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_70 = rsqrt(epsilon = rsqrt_70_epsilon_0, x = reduce_mean_70)[name = string("rsqrt_70")];
            tensor<fp16, [256, 960]> mul_330 = mul(x = mul_328, y = rsqrt_70)[name = string("mul_330")];
            tensor<fp16, [960]> mul_331_y_0 = const()[name = string("mul_331_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4647424)))];
            tensor<fp16, [256, 960]> mul_331 = mul(x = mul_330, y = mul_331_y_0)[name = string("mul_331")];
            tensor<fp16, [352, 960]> tern_6_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4649408))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_6_w2_weight_0_palettized")];
            tensor<fp16, [256, 352]> tern_6_w2 = linear(bias = linear_0_bias_0, weight = tern_6_w2_weight_0_palettized, x = mul_331)[name = string("tern_6_w2")];
            tensor<fp16, [352]> mul_332_y_0 = const()[name = string("mul_332_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4733952)))];
            tensor<fp16, [256, 352]> mul_332 = mul(x = tern_6_w2, y = mul_332_y_0)[name = string("mul_332")];
            tensor<fp16, [256, 352]> add_41 = add(x = add_39, y = mul_332)[name = string("add_41")];
            tensor<fp16, [256, 352]> mul_333 = mul(x = add_41, y = add_41)[name = string("mul_333")];
            tensor<int32, [1]> reduce_mean_71_axes_0 = const()[name = string("reduce_mean_71_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_71_keep_dims_0 = const()[name = string("reduce_mean_71_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_71 = reduce_mean(axes = reduce_mean_71_axes_0, keep_dims = reduce_mean_71_keep_dims_0, x = mul_333)[name = string("reduce_mean_71")];
            fp32 rsqrt_71_epsilon_0 = const()[name = string("rsqrt_71_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_71 = rsqrt(epsilon = rsqrt_71_epsilon_0, x = reduce_mean_71)[name = string("rsqrt_71")];
            tensor<fp16, [256, 352]> mul_334 = mul(x = add_41, y = rsqrt_71)[name = string("mul_334")];
            tensor<fp16, [352]> mul_335_y_0 = const()[name = string("mul_335_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4734720)))];
            tensor<fp16, [256, 352]> mul_335 = mul(x = mul_334, y = mul_335_y_0)[name = string("mul_335")];
            tensor<fp16, [256, 352]> mul_336 = mul(x = mul_335, y = mul_335)[name = string("mul_336")];
            tensor<int32, [1]> reduce_mean_72_axes_0 = const()[name = string("reduce_mean_72_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_72_keep_dims_0 = const()[name = string("reduce_mean_72_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_72 = reduce_mean(axes = reduce_mean_72_axes_0, keep_dims = reduce_mean_72_keep_dims_0, x = mul_336)[name = string("reduce_mean_72")];
            fp32 rsqrt_72_epsilon_0 = const()[name = string("rsqrt_72_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_72 = rsqrt(epsilon = rsqrt_72_epsilon_0, x = reduce_mean_72)[name = string("rsqrt_72")];
            tensor<fp16, [256, 352]> mul_337 = mul(x = mul_335, y = rsqrt_72)[name = string("mul_337")];
            tensor<fp16, [352]> mul_338_y_0 = const()[name = string("mul_338_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4735488)))];
            tensor<fp16, [256, 352]> mul_338 = mul(x = mul_337, y = mul_338_y_0)[name = string("mul_338")];
            tensor<fp16, [352, 352]> tern_7_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4736256))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_7_q_weight_0_palettized")];
            tensor<fp16, [256, 352]> tern_7_q = linear(bias = linear_0_bias_0, weight = tern_7_q_weight_0_palettized, x = mul_338)[name = string("tern_7_q")];
            tensor<fp16, [352]> mul_339_y_0 = const()[name = string("mul_339_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4767296)))];
            tensor<fp16, [256, 352]> mul_339 = mul(x = tern_7_q, y = mul_339_y_0)[name = string("mul_339")];
            tensor<int32, [3]> reshape_58_shape_0 = const()[name = string("reshape_58_shape_0"), val = tensor<int32, [3]>([256, 8, 44])];
            tensor<fp16, [256, 8, 44]> reshape_58 = reshape(shape = reshape_58_shape_0, x = mul_339)[name = string("reshape_58")];
            tensor<int32, [3]> transpose_28_perm_0 = const()[name = string("transpose_28_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_342_y_0 = const()[name = string("mul_342_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4768064)))];
            tensor<fp16, [256, 352]> mul_342 = mul(x = mul_337, y = mul_342_y_0)[name = string("mul_342")];
            tensor<fp16, [88, 352]> tern_7_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4768832))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_7_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_7_k_bias_0 = const()[name = string("tern_7_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [256, 88]> tern_7_k = linear(bias = tern_7_k_bias_0, weight = tern_7_k_weight_0_palettized, x = mul_342)[name = string("tern_7_k")];
            tensor<fp16, [88]> mul_343_y_0 = const()[name = string("mul_343_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4776640)))];
            tensor<fp16, [256, 88]> mul_343 = mul(x = tern_7_k, y = mul_343_y_0)[name = string("mul_343")];
            tensor<int32, [3]> reshape_59_shape_0 = const()[name = string("reshape_59_shape_0"), val = tensor<int32, [3]>([256, 2, 44])];
            tensor<fp16, [256, 2, 44]> reshape_59 = reshape(shape = reshape_59_shape_0, x = mul_343)[name = string("reshape_59")];
            tensor<int32, [3]> transpose_29_perm_0 = const()[name = string("transpose_29_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_346_y_0 = const()[name = string("mul_346_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4776896)))];
            tensor<fp16, [256, 352]> mul_346 = mul(x = mul_337, y = mul_346_y_0)[name = string("mul_346")];
            tensor<fp16, [88, 352]> tern_7_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4777664))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_7_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_7_v_bias_0 = const()[name = string("tern_7_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [256, 88]> tern_7_v = linear(bias = tern_7_v_bias_0, weight = tern_7_v_weight_0_palettized, x = mul_346)[name = string("tern_7_v")];
            tensor<fp16, [88]> mul_347_y_0 = const()[name = string("mul_347_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4785472)))];
            tensor<fp16, [256, 88]> mul_347 = mul(x = tern_7_v, y = mul_347_y_0)[name = string("mul_347")];
            tensor<int32, [3]> reshape_60_shape_0 = const()[name = string("reshape_60_shape_0"), val = tensor<int32, [3]>([256, 2, 44])];
            tensor<fp16, [256, 2, 44]> reshape_60 = reshape(shape = reshape_60_shape_0, x = mul_347)[name = string("reshape_60")];
            tensor<int32, [3]> transpose_30_perm_0 = const()[name = string("transpose_30_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 256, 44]> transpose_28 = transpose(perm = transpose_28_perm_0, x = reshape_58)[name = string("transpose_35")];
            tensor<fp16, [8, 256, 44]> mul_348 = mul(x = transpose_28, y = transpose_28)[name = string("mul_348")];
            tensor<int32, [1]> reduce_mean_75_axes_0 = const()[name = string("reduce_mean_75_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_75_keep_dims_0 = const()[name = string("reduce_mean_75_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 256, 1]> reduce_mean_75 = reduce_mean(axes = reduce_mean_75_axes_0, keep_dims = reduce_mean_75_keep_dims_0, x = mul_348)[name = string("reduce_mean_75")];
            fp32 rsqrt_75_epsilon_0 = const()[name = string("rsqrt_75_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 256, 1]> rsqrt_75 = rsqrt(epsilon = rsqrt_75_epsilon_0, x = reduce_mean_75)[name = string("rsqrt_75")];
            tensor<fp16, [8, 256, 44]> mul_349 = mul(x = transpose_28, y = rsqrt_75)[name = string("mul_349")];
            tensor<fp16, [44]> mul_350_y_0 = const()[name = string("mul_350_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4785728)))];
            tensor<fp16, [8, 256, 44]> mul_350 = mul(x = mul_349, y = mul_350_y_0)[name = string("mul_350")];
            tensor<int32, [3]> slice_by_index_28_begin_0 = const()[name = string("slice_by_index_28_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_28_end_0 = const()[name = string("slice_by_index_28_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_28_end_mask_0 = const()[name = string("slice_by_index_28_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 256, 22]> slice_by_index_28 = slice_by_index(begin = slice_by_index_28_begin_0, end = slice_by_index_28_end_0, end_mask = slice_by_index_28_end_mask_0, x = mul_350)[name = string("slice_by_index_28")];
            tensor<int32, [3]> slice_by_index_29_begin_0 = const()[name = string("slice_by_index_29_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_29_end_0 = const()[name = string("slice_by_index_29_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_29_end_mask_0 = const()[name = string("slice_by_index_29_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 256, 22]> slice_by_index_29 = slice_by_index(begin = slice_by_index_29_begin_0, end = slice_by_index_29_end_0, end_mask = slice_by_index_29_end_mask_0, x = mul_350)[name = string("slice_by_index_29")];
            int32 concat_14_axis_0 = const()[name = string("concat_14_axis_0"), val = int32(-1)];
            bool concat_14_interleave_0 = const()[name = string("concat_14_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 256, 44]> concat_14 = concat(axis = concat_14_axis_0, interleave = concat_14_interleave_0, values = (slice_by_index_29, slice_by_index_28))[name = string("concat_14")];
            tensor<fp16, [44]> mul_351_y_0 = const()[name = string("mul_351_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 256, 44]> mul_351 = mul(x = concat_14, y = mul_351_y_0)[name = string("mul_351")];
            tensor<fp16, [8, 256, 44]> mul_352 = mul(x = mul_350, y = mul_11_y_0)[name = string("mul_352")];
            tensor<fp16, [8, 256, 44]> mul_353 = mul(x = mul_351, y = mul_12_y_0)[name = string("mul_353")];
            tensor<fp16, [8, 256, 44]> add_42 = add(x = mul_352, y = mul_353)[name = string("add_42")];
            tensor<fp16, [2, 256, 44]> transpose_29 = transpose(perm = transpose_29_perm_0, x = reshape_59)[name = string("transpose_34")];
            tensor<fp16, [2, 256, 44]> mul_354 = mul(x = transpose_29, y = transpose_29)[name = string("mul_354")];
            tensor<int32, [1]> reduce_mean_76_axes_0 = const()[name = string("reduce_mean_76_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_76_keep_dims_0 = const()[name = string("reduce_mean_76_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 256, 1]> reduce_mean_76 = reduce_mean(axes = reduce_mean_76_axes_0, keep_dims = reduce_mean_76_keep_dims_0, x = mul_354)[name = string("reduce_mean_76")];
            fp32 rsqrt_76_epsilon_0 = const()[name = string("rsqrt_76_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 256, 1]> rsqrt_76 = rsqrt(epsilon = rsqrt_76_epsilon_0, x = reduce_mean_76)[name = string("rsqrt_76")];
            tensor<fp16, [2, 256, 44]> mul_355 = mul(x = transpose_29, y = rsqrt_76)[name = string("mul_355")];
            tensor<fp16, [44]> mul_356_y_0 = const()[name = string("mul_356_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4785920)))];
            tensor<fp16, [2, 256, 44]> mul_356 = mul(x = mul_355, y = mul_356_y_0)[name = string("mul_356")];
            tensor<int32, [3]> slice_by_index_30_begin_0 = const()[name = string("slice_by_index_30_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_30_end_0 = const()[name = string("slice_by_index_30_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_30_end_mask_0 = const()[name = string("slice_by_index_30_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 256, 22]> slice_by_index_30 = slice_by_index(begin = slice_by_index_30_begin_0, end = slice_by_index_30_end_0, end_mask = slice_by_index_30_end_mask_0, x = mul_356)[name = string("slice_by_index_30")];
            tensor<int32, [3]> slice_by_index_31_begin_0 = const()[name = string("slice_by_index_31_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_31_end_0 = const()[name = string("slice_by_index_31_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_31_end_mask_0 = const()[name = string("slice_by_index_31_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 256, 22]> slice_by_index_31 = slice_by_index(begin = slice_by_index_31_begin_0, end = slice_by_index_31_end_0, end_mask = slice_by_index_31_end_mask_0, x = mul_356)[name = string("slice_by_index_31")];
            int32 concat_15_axis_0 = const()[name = string("concat_15_axis_0"), val = int32(-1)];
            bool concat_15_interleave_0 = const()[name = string("concat_15_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 256, 44]> concat_15 = concat(axis = concat_15_axis_0, interleave = concat_15_interleave_0, values = (slice_by_index_31, slice_by_index_30))[name = string("concat_15")];
            tensor<fp16, [44]> mul_357_y_0 = const()[name = string("mul_357_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 256, 44]> mul_357 = mul(x = concat_15, y = mul_357_y_0)[name = string("mul_357")];
            tensor<fp16, [2, 256, 44]> mul_358 = mul(x = mul_356, y = mul_11_y_0)[name = string("mul_358")];
            tensor<fp16, [2, 256, 44]> mul_359 = mul(x = mul_357, y = mul_12_y_0)[name = string("mul_359")];
            tensor<fp16, [2, 256, 44]> add_43 = add(x = mul_358, y = mul_359)[name = string("add_43")];
            tensor<int32, [4]> reshape_61_shape_0 = const()[name = string("reshape_61_shape_0"), val = tensor<int32, [4]>([2, 1, 256, 44])];
            tensor<fp16, [2, 1, 256, 44]> reshape_61 = reshape(shape = reshape_61_shape_0, x = add_43)[name = string("reshape_61")];
            tensor<int32, [4]> tile_14_reps_0 = const()[name = string("tile_14_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 256, 44]> tile_14 = tile(reps = tile_14_reps_0, x = reshape_61)[name = string("tile_14")];
            tensor<int32, [3]> reshape_62_shape_0 = const()[name = string("reshape_62_shape_0"), val = tensor<int32, [3]>([8, 256, 44])];
            tensor<fp16, [8, 256, 44]> reshape_62 = reshape(shape = reshape_62_shape_0, x = tile_14)[name = string("reshape_62")];
            tensor<int32, [4]> reshape_63_shape_0 = const()[name = string("reshape_63_shape_0"), val = tensor<int32, [4]>([2, 1, 256, 44])];
            tensor<fp16, [2, 256, 44]> transpose_30 = transpose(perm = transpose_30_perm_0, x = reshape_60)[name = string("transpose_33")];
            tensor<fp16, [2, 1, 256, 44]> reshape_63 = reshape(shape = reshape_63_shape_0, x = transpose_30)[name = string("reshape_63")];
            tensor<int32, [4]> tile_15_reps_0 = const()[name = string("tile_15_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 256, 44]> tile_15 = tile(reps = tile_15_reps_0, x = reshape_63)[name = string("tile_15")];
            tensor<int32, [3]> reshape_64_shape_0 = const()[name = string("reshape_64_shape_0"), val = tensor<int32, [3]>([8, 256, 44])];
            tensor<fp16, [8, 256, 44]> reshape_64 = reshape(shape = reshape_64_shape_0, x = tile_15)[name = string("reshape_64")];
            fp16 mul_360_y_0 = const()[name = string("mul_360_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 256, 44]> mul_360 = mul(x = add_42, y = mul_360_y_0)[name = string("mul_360")];
            bool matmul_14_transpose_y_0 = const()[name = string("matmul_14_transpose_y_0"), val = bool(true)];
            bool matmul_14_transpose_x_0 = const()[name = string("matmul_14_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 256, 256]> matmul_14 = matmul(transpose_x = matmul_14_transpose_x_0, transpose_y = matmul_14_transpose_y_0, x = mul_360, y = reshape_62)[name = string("matmul_14")];
            tensor<fp16, [8, 256, 256]> add_44 = add(x = matmul_14, y = reshape_1)[name = string("add_44")];
            int32 softmax_7_axis_0 = const()[name = string("softmax_7_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 256, 256]> softmax_7 = softmax(axis = softmax_7_axis_0, x = add_44)[name = string("softmax_7")];
            bool matmul_15_transpose_x_0 = const()[name = string("matmul_15_transpose_x_0"), val = bool(false)];
            bool matmul_15_transpose_y_0 = const()[name = string("matmul_15_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 256, 44]> matmul_15 = matmul(transpose_x = matmul_15_transpose_x_0, transpose_y = matmul_15_transpose_y_0, x = softmax_7, y = reshape_64)[name = string("matmul_15")];
            tensor<int32, [3]> transpose_31_perm_0 = const()[name = string("transpose_31_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_65_shape_0 = const()[name = string("reshape_65_shape_0"), val = tensor<int32, [2]>([256, 352])];
            tensor<fp16, [256, 8, 44]> transpose_31 = transpose(perm = transpose_31_perm_0, x = matmul_15)[name = string("transpose_32")];
            tensor<fp16, [256, 352]> reshape_65 = reshape(shape = reshape_65_shape_0, x = transpose_31)[name = string("reshape_65")];
            tensor<fp16, [256, 352]> mul_361 = mul(x = reshape_65, y = reshape_65)[name = string("mul_361")];
            tensor<int32, [1]> reduce_mean_77_axes_0 = const()[name = string("reduce_mean_77_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_77_keep_dims_0 = const()[name = string("reduce_mean_77_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_77 = reduce_mean(axes = reduce_mean_77_axes_0, keep_dims = reduce_mean_77_keep_dims_0, x = mul_361)[name = string("reduce_mean_77")];
            fp32 rsqrt_77_epsilon_0 = const()[name = string("rsqrt_77_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_77 = rsqrt(epsilon = rsqrt_77_epsilon_0, x = reduce_mean_77)[name = string("rsqrt_77")];
            tensor<fp16, [256, 352]> mul_362 = mul(x = reshape_65, y = rsqrt_77)[name = string("mul_362")];
            tensor<fp16, [352]> mul_363_y_0 = const()[name = string("mul_363_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4786112)))];
            tensor<fp16, [256, 352]> mul_363 = mul(x = mul_362, y = mul_363_y_0)[name = string("mul_363")];
            tensor<fp16, [352, 352]> tern_7_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4786880))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_7_o_weight_0_palettized")];
            tensor<fp16, [256, 352]> tern_7_o = linear(bias = linear_0_bias_0, weight = tern_7_o_weight_0_palettized, x = mul_363)[name = string("tern_7_o")];
            tensor<fp16, [352]> mul_364_y_0 = const()[name = string("mul_364_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4817920)))];
            tensor<fp16, [256, 352]> mul_364 = mul(x = tern_7_o, y = mul_364_y_0)[name = string("mul_364")];
            tensor<fp16, [256, 352]> add_45 = add(x = add_41, y = mul_364)[name = string("add_45")];
            tensor<fp16, [256, 352]> mul_365 = mul(x = add_45, y = add_45)[name = string("mul_365")];
            tensor<int32, [1]> reduce_mean_78_axes_0 = const()[name = string("reduce_mean_78_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_78_keep_dims_0 = const()[name = string("reduce_mean_78_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_78 = reduce_mean(axes = reduce_mean_78_axes_0, keep_dims = reduce_mean_78_keep_dims_0, x = mul_365)[name = string("reduce_mean_78")];
            fp32 rsqrt_78_epsilon_0 = const()[name = string("rsqrt_78_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_78 = rsqrt(epsilon = rsqrt_78_epsilon_0, x = reduce_mean_78)[name = string("rsqrt_78")];
            tensor<fp16, [256, 352]> mul_366 = mul(x = add_45, y = rsqrt_78)[name = string("mul_366")];
            tensor<fp16, [352]> mul_367_y_0 = const()[name = string("mul_367_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4818688)))];
            tensor<fp16, [256, 352]> mul_367 = mul(x = mul_366, y = mul_367_y_0)[name = string("mul_367")];
            tensor<fp16, [256, 352]> mul_368 = mul(x = mul_367, y = mul_367)[name = string("mul_368")];
            tensor<int32, [1]> reduce_mean_79_axes_0 = const()[name = string("reduce_mean_79_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_79_keep_dims_0 = const()[name = string("reduce_mean_79_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_79 = reduce_mean(axes = reduce_mean_79_axes_0, keep_dims = reduce_mean_79_keep_dims_0, x = mul_368)[name = string("reduce_mean_79")];
            fp32 rsqrt_79_epsilon_0 = const()[name = string("rsqrt_79_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_79 = rsqrt(epsilon = rsqrt_79_epsilon_0, x = reduce_mean_79)[name = string("rsqrt_79")];
            tensor<fp16, [256, 352]> mul_369 = mul(x = mul_367, y = rsqrt_79)[name = string("mul_369")];
            tensor<fp16, [352]> mul_370_y_0 = const()[name = string("mul_370_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4819456)))];
            tensor<fp16, [256, 352]> mul_370 = mul(x = mul_369, y = mul_370_y_0)[name = string("mul_370")];
            tensor<fp16, [960, 352]> tern_7_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4820224))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_7_w1_weight_0_palettized")];
            tensor<fp16, [256, 960]> tern_7_w1 = linear(bias = linear_4_bias_0, weight = tern_7_w1_weight_0_palettized, x = mul_370)[name = string("tern_7_w1")];
            tensor<fp16, [960]> mul_371_y_0 = const()[name = string("mul_371_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4904768)))];
            tensor<fp16, [256, 960]> mul_371 = mul(x = tern_7_w1, y = mul_371_y_0)[name = string("mul_371")];
            tensor<fp16, [352]> mul_374_y_0 = const()[name = string("mul_374_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4906752)))];
            tensor<fp16, [256, 352]> mul_374 = mul(x = mul_369, y = mul_374_y_0)[name = string("mul_374")];
            tensor<fp16, [960, 352]> tern_7_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4907520))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_7_w3_weight_0_palettized")];
            tensor<fp16, [256, 960]> tern_7_w3 = linear(bias = linear_4_bias_0, weight = tern_7_w3_weight_0_palettized, x = mul_374)[name = string("tern_7_w3")];
            tensor<fp16, [960]> mul_375_y_0 = const()[name = string("mul_375_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4992064)))];
            tensor<fp16, [256, 960]> mul_375 = mul(x = tern_7_w3, y = mul_375_y_0)[name = string("mul_375")];
            fp16 mul_376_y_0 = const()[name = string("mul_376_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [256, 960]> mul_376 = mul(x = mul_371, y = mul_376_y_0)[name = string("mul_376")];
            tensor<fp16, [256, 960]> tanh_7 = tanh(x = mul_376)[name = string("tanh_7")];
            fp16 mul_377_x_0 = const()[name = string("mul_377_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [256, 960]> mul_377 = mul(x = mul_377_x_0, y = tanh_7)[name = string("mul_377")];
            fp16 add_46_x_0 = const()[name = string("add_46_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [256, 960]> add_46 = add(x = add_46_x_0, y = mul_377)[name = string("add_46")];
            tensor<fp16, [256, 960]> mul_378 = mul(x = mul_371, y = add_46)[name = string("mul_378")];
            tensor<fp16, [256, 960]> mul_379 = mul(x = mul_378, y = mul_375)[name = string("mul_379")];
            tensor<fp16, [256, 960]> mul_380 = mul(x = mul_379, y = mul_379)[name = string("mul_380")];
            tensor<int32, [1]> reduce_mean_81_axes_0 = const()[name = string("reduce_mean_81_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_81_keep_dims_0 = const()[name = string("reduce_mean_81_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_81 = reduce_mean(axes = reduce_mean_81_axes_0, keep_dims = reduce_mean_81_keep_dims_0, x = mul_380)[name = string("reduce_mean_81")];
            fp32 rsqrt_81_epsilon_0 = const()[name = string("rsqrt_81_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_81 = rsqrt(epsilon = rsqrt_81_epsilon_0, x = reduce_mean_81)[name = string("rsqrt_81")];
            tensor<fp16, [256, 960]> mul_381 = mul(x = mul_379, y = rsqrt_81)[name = string("mul_381")];
            tensor<fp16, [960]> mul_382_y_0 = const()[name = string("mul_382_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4994048)))];
            tensor<fp16, [256, 960]> mul_382 = mul(x = mul_381, y = mul_382_y_0)[name = string("mul_382")];
            tensor<fp16, [352, 960]> tern_7_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4996032))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_7_w2_weight_0_palettized")];
            tensor<fp16, [256, 352]> tern_7_w2 = linear(bias = linear_0_bias_0, weight = tern_7_w2_weight_0_palettized, x = mul_382)[name = string("tern_7_w2")];
            tensor<fp16, [352]> mul_383_y_0 = const()[name = string("mul_383_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5080576)))];
            tensor<fp16, [256, 352]> mul_383 = mul(x = tern_7_w2, y = mul_383_y_0)[name = string("mul_383")];
            tensor<fp16, [256, 352]> add_47 = add(x = add_45, y = mul_383)[name = string("add_47")];
            tensor<fp16, [256, 352]> mul_384 = mul(x = add_47, y = add_47)[name = string("mul_384")];
            tensor<int32, [1]> reduce_mean_82_axes_0 = const()[name = string("reduce_mean_82_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_82_keep_dims_0 = const()[name = string("reduce_mean_82_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_82 = reduce_mean(axes = reduce_mean_82_axes_0, keep_dims = reduce_mean_82_keep_dims_0, x = mul_384)[name = string("reduce_mean_82")];
            fp32 rsqrt_82_epsilon_0 = const()[name = string("rsqrt_82_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_82 = rsqrt(epsilon = rsqrt_82_epsilon_0, x = reduce_mean_82)[name = string("rsqrt_82")];
            tensor<fp16, [256, 352]> mul_385 = mul(x = add_47, y = rsqrt_82)[name = string("mul_385")];
            tensor<fp16, [352]> mul_386_y_0 = const()[name = string("mul_386_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5081344)))];
            tensor<fp16, [256, 352]> mul_386 = mul(x = mul_385, y = mul_386_y_0)[name = string("mul_386")];
            tensor<fp16, [256, 352]> mul_387 = mul(x = mul_386, y = mul_386)[name = string("mul_387")];
            tensor<int32, [1]> reduce_mean_83_axes_0 = const()[name = string("reduce_mean_83_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_83_keep_dims_0 = const()[name = string("reduce_mean_83_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_83 = reduce_mean(axes = reduce_mean_83_axes_0, keep_dims = reduce_mean_83_keep_dims_0, x = mul_387)[name = string("reduce_mean_83")];
            fp32 rsqrt_83_epsilon_0 = const()[name = string("rsqrt_83_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_83 = rsqrt(epsilon = rsqrt_83_epsilon_0, x = reduce_mean_83)[name = string("rsqrt_83")];
            tensor<fp16, [256, 352]> mul_388 = mul(x = mul_386, y = rsqrt_83)[name = string("mul_388")];
            tensor<fp16, [352]> mul_389_y_0 = const()[name = string("mul_389_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5082112)))];
            tensor<fp16, [256, 352]> mul_389 = mul(x = mul_388, y = mul_389_y_0)[name = string("mul_389")];
            tensor<fp16, [352, 352]> tern_8_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5082880))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_8_q_weight_0_palettized")];
            tensor<fp16, [256, 352]> tern_8_q = linear(bias = linear_0_bias_0, weight = tern_8_q_weight_0_palettized, x = mul_389)[name = string("tern_8_q")];
            tensor<fp16, [352]> mul_390_y_0 = const()[name = string("mul_390_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5113920)))];
            tensor<fp16, [256, 352]> mul_390 = mul(x = tern_8_q, y = mul_390_y_0)[name = string("mul_390")];
            tensor<int32, [3]> reshape_66_shape_0 = const()[name = string("reshape_66_shape_0"), val = tensor<int32, [3]>([256, 8, 44])];
            tensor<fp16, [256, 8, 44]> reshape_66 = reshape(shape = reshape_66_shape_0, x = mul_390)[name = string("reshape_66")];
            tensor<int32, [3]> transpose_32_perm_0 = const()[name = string("transpose_32_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_393_y_0 = const()[name = string("mul_393_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5114688)))];
            tensor<fp16, [256, 352]> mul_393 = mul(x = mul_388, y = mul_393_y_0)[name = string("mul_393")];
            tensor<fp16, [88, 352]> tern_8_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5115456))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_8_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_8_k_bias_0 = const()[name = string("tern_8_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [256, 88]> tern_8_k = linear(bias = tern_8_k_bias_0, weight = tern_8_k_weight_0_palettized, x = mul_393)[name = string("tern_8_k")];
            tensor<fp16, [88]> mul_394_y_0 = const()[name = string("mul_394_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5123264)))];
            tensor<fp16, [256, 88]> mul_394 = mul(x = tern_8_k, y = mul_394_y_0)[name = string("mul_394")];
            tensor<int32, [3]> reshape_67_shape_0 = const()[name = string("reshape_67_shape_0"), val = tensor<int32, [3]>([256, 2, 44])];
            tensor<fp16, [256, 2, 44]> reshape_67 = reshape(shape = reshape_67_shape_0, x = mul_394)[name = string("reshape_67")];
            tensor<int32, [3]> transpose_33_perm_0 = const()[name = string("transpose_33_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_397_y_0 = const()[name = string("mul_397_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5123520)))];
            tensor<fp16, [256, 352]> mul_397 = mul(x = mul_388, y = mul_397_y_0)[name = string("mul_397")];
            tensor<fp16, [88, 352]> tern_8_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5124288))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_8_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_8_v_bias_0 = const()[name = string("tern_8_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [256, 88]> tern_8_v = linear(bias = tern_8_v_bias_0, weight = tern_8_v_weight_0_palettized, x = mul_397)[name = string("tern_8_v")];
            tensor<fp16, [88]> mul_398_y_0 = const()[name = string("mul_398_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5132096)))];
            tensor<fp16, [256, 88]> mul_398 = mul(x = tern_8_v, y = mul_398_y_0)[name = string("mul_398")];
            tensor<int32, [3]> reshape_68_shape_0 = const()[name = string("reshape_68_shape_0"), val = tensor<int32, [3]>([256, 2, 44])];
            tensor<fp16, [256, 2, 44]> reshape_68 = reshape(shape = reshape_68_shape_0, x = mul_398)[name = string("reshape_68")];
            tensor<int32, [3]> transpose_34_perm_0 = const()[name = string("transpose_34_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 256, 44]> transpose_32 = transpose(perm = transpose_32_perm_0, x = reshape_66)[name = string("transpose_31")];
            tensor<fp16, [8, 256, 44]> mul_399 = mul(x = transpose_32, y = transpose_32)[name = string("mul_399")];
            tensor<int32, [1]> reduce_mean_86_axes_0 = const()[name = string("reduce_mean_86_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_86_keep_dims_0 = const()[name = string("reduce_mean_86_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 256, 1]> reduce_mean_86 = reduce_mean(axes = reduce_mean_86_axes_0, keep_dims = reduce_mean_86_keep_dims_0, x = mul_399)[name = string("reduce_mean_86")];
            fp32 rsqrt_86_epsilon_0 = const()[name = string("rsqrt_86_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 256, 1]> rsqrt_86 = rsqrt(epsilon = rsqrt_86_epsilon_0, x = reduce_mean_86)[name = string("rsqrt_86")];
            tensor<fp16, [8, 256, 44]> mul_400 = mul(x = transpose_32, y = rsqrt_86)[name = string("mul_400")];
            tensor<fp16, [44]> mul_401_y_0 = const()[name = string("mul_401_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5132352)))];
            tensor<fp16, [8, 256, 44]> mul_401 = mul(x = mul_400, y = mul_401_y_0)[name = string("mul_401")];
            tensor<int32, [3]> slice_by_index_32_begin_0 = const()[name = string("slice_by_index_32_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_32_end_0 = const()[name = string("slice_by_index_32_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_32_end_mask_0 = const()[name = string("slice_by_index_32_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 256, 22]> slice_by_index_32 = slice_by_index(begin = slice_by_index_32_begin_0, end = slice_by_index_32_end_0, end_mask = slice_by_index_32_end_mask_0, x = mul_401)[name = string("slice_by_index_32")];
            tensor<int32, [3]> slice_by_index_33_begin_0 = const()[name = string("slice_by_index_33_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_33_end_0 = const()[name = string("slice_by_index_33_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_33_end_mask_0 = const()[name = string("slice_by_index_33_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 256, 22]> slice_by_index_33 = slice_by_index(begin = slice_by_index_33_begin_0, end = slice_by_index_33_end_0, end_mask = slice_by_index_33_end_mask_0, x = mul_401)[name = string("slice_by_index_33")];
            int32 concat_16_axis_0 = const()[name = string("concat_16_axis_0"), val = int32(-1)];
            bool concat_16_interleave_0 = const()[name = string("concat_16_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 256, 44]> concat_16 = concat(axis = concat_16_axis_0, interleave = concat_16_interleave_0, values = (slice_by_index_33, slice_by_index_32))[name = string("concat_16")];
            tensor<fp16, [44]> mul_402_y_0 = const()[name = string("mul_402_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 256, 44]> mul_402 = mul(x = concat_16, y = mul_402_y_0)[name = string("mul_402")];
            tensor<fp16, [8, 256, 44]> mul_403 = mul(x = mul_401, y = mul_11_y_0)[name = string("mul_403")];
            tensor<fp16, [8, 256, 44]> mul_404 = mul(x = mul_402, y = mul_12_y_0)[name = string("mul_404")];
            tensor<fp16, [8, 256, 44]> add_48 = add(x = mul_403, y = mul_404)[name = string("add_48")];
            tensor<fp16, [2, 256, 44]> transpose_33 = transpose(perm = transpose_33_perm_0, x = reshape_67)[name = string("transpose_30")];
            tensor<fp16, [2, 256, 44]> mul_405 = mul(x = transpose_33, y = transpose_33)[name = string("mul_405")];
            tensor<int32, [1]> reduce_mean_87_axes_0 = const()[name = string("reduce_mean_87_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_87_keep_dims_0 = const()[name = string("reduce_mean_87_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 256, 1]> reduce_mean_87 = reduce_mean(axes = reduce_mean_87_axes_0, keep_dims = reduce_mean_87_keep_dims_0, x = mul_405)[name = string("reduce_mean_87")];
            fp32 rsqrt_87_epsilon_0 = const()[name = string("rsqrt_87_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 256, 1]> rsqrt_87 = rsqrt(epsilon = rsqrt_87_epsilon_0, x = reduce_mean_87)[name = string("rsqrt_87")];
            tensor<fp16, [2, 256, 44]> mul_406 = mul(x = transpose_33, y = rsqrt_87)[name = string("mul_406")];
            tensor<fp16, [44]> mul_407_y_0 = const()[name = string("mul_407_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5132544)))];
            tensor<fp16, [2, 256, 44]> mul_407 = mul(x = mul_406, y = mul_407_y_0)[name = string("mul_407")];
            tensor<int32, [3]> slice_by_index_34_begin_0 = const()[name = string("slice_by_index_34_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_34_end_0 = const()[name = string("slice_by_index_34_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_34_end_mask_0 = const()[name = string("slice_by_index_34_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 256, 22]> slice_by_index_34 = slice_by_index(begin = slice_by_index_34_begin_0, end = slice_by_index_34_end_0, end_mask = slice_by_index_34_end_mask_0, x = mul_407)[name = string("slice_by_index_34")];
            tensor<int32, [3]> slice_by_index_35_begin_0 = const()[name = string("slice_by_index_35_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_35_end_0 = const()[name = string("slice_by_index_35_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_35_end_mask_0 = const()[name = string("slice_by_index_35_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 256, 22]> slice_by_index_35 = slice_by_index(begin = slice_by_index_35_begin_0, end = slice_by_index_35_end_0, end_mask = slice_by_index_35_end_mask_0, x = mul_407)[name = string("slice_by_index_35")];
            int32 concat_17_axis_0 = const()[name = string("concat_17_axis_0"), val = int32(-1)];
            bool concat_17_interleave_0 = const()[name = string("concat_17_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 256, 44]> concat_17 = concat(axis = concat_17_axis_0, interleave = concat_17_interleave_0, values = (slice_by_index_35, slice_by_index_34))[name = string("concat_17")];
            tensor<fp16, [44]> mul_408_y_0 = const()[name = string("mul_408_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 256, 44]> mul_408 = mul(x = concat_17, y = mul_408_y_0)[name = string("mul_408")];
            tensor<fp16, [2, 256, 44]> mul_409 = mul(x = mul_407, y = mul_11_y_0)[name = string("mul_409")];
            tensor<fp16, [2, 256, 44]> mul_410 = mul(x = mul_408, y = mul_12_y_0)[name = string("mul_410")];
            tensor<fp16, [2, 256, 44]> add_49 = add(x = mul_409, y = mul_410)[name = string("add_49")];
            tensor<int32, [4]> reshape_69_shape_0 = const()[name = string("reshape_69_shape_0"), val = tensor<int32, [4]>([2, 1, 256, 44])];
            tensor<fp16, [2, 1, 256, 44]> reshape_69 = reshape(shape = reshape_69_shape_0, x = add_49)[name = string("reshape_69")];
            tensor<int32, [4]> tile_16_reps_0 = const()[name = string("tile_16_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 256, 44]> tile_16 = tile(reps = tile_16_reps_0, x = reshape_69)[name = string("tile_16")];
            tensor<int32, [3]> reshape_70_shape_0 = const()[name = string("reshape_70_shape_0"), val = tensor<int32, [3]>([8, 256, 44])];
            tensor<fp16, [8, 256, 44]> reshape_70 = reshape(shape = reshape_70_shape_0, x = tile_16)[name = string("reshape_70")];
            tensor<int32, [4]> reshape_71_shape_0 = const()[name = string("reshape_71_shape_0"), val = tensor<int32, [4]>([2, 1, 256, 44])];
            tensor<fp16, [2, 256, 44]> transpose_34 = transpose(perm = transpose_34_perm_0, x = reshape_68)[name = string("transpose_29")];
            tensor<fp16, [2, 1, 256, 44]> reshape_71 = reshape(shape = reshape_71_shape_0, x = transpose_34)[name = string("reshape_71")];
            tensor<int32, [4]> tile_17_reps_0 = const()[name = string("tile_17_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 256, 44]> tile_17 = tile(reps = tile_17_reps_0, x = reshape_71)[name = string("tile_17")];
            tensor<int32, [3]> reshape_72_shape_0 = const()[name = string("reshape_72_shape_0"), val = tensor<int32, [3]>([8, 256, 44])];
            tensor<fp16, [8, 256, 44]> reshape_72 = reshape(shape = reshape_72_shape_0, x = tile_17)[name = string("reshape_72")];
            fp16 mul_411_y_0 = const()[name = string("mul_411_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 256, 44]> mul_411 = mul(x = add_48, y = mul_411_y_0)[name = string("mul_411")];
            bool matmul_16_transpose_y_0 = const()[name = string("matmul_16_transpose_y_0"), val = bool(true)];
            bool matmul_16_transpose_x_0 = const()[name = string("matmul_16_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 256, 256]> matmul_16 = matmul(transpose_x = matmul_16_transpose_x_0, transpose_y = matmul_16_transpose_y_0, x = mul_411, y = reshape_70)[name = string("matmul_16")];
            tensor<fp16, [8, 256, 256]> add_50 = add(x = matmul_16, y = reshape_1)[name = string("add_50")];
            int32 softmax_8_axis_0 = const()[name = string("softmax_8_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 256, 256]> softmax_8 = softmax(axis = softmax_8_axis_0, x = add_50)[name = string("softmax_8")];
            bool matmul_17_transpose_x_0 = const()[name = string("matmul_17_transpose_x_0"), val = bool(false)];
            bool matmul_17_transpose_y_0 = const()[name = string("matmul_17_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 256, 44]> matmul_17 = matmul(transpose_x = matmul_17_transpose_x_0, transpose_y = matmul_17_transpose_y_0, x = softmax_8, y = reshape_72)[name = string("matmul_17")];
            tensor<int32, [3]> transpose_35_perm_0 = const()[name = string("transpose_35_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_73_shape_0 = const()[name = string("reshape_73_shape_0"), val = tensor<int32, [2]>([256, 352])];
            tensor<fp16, [256, 8, 44]> transpose_35 = transpose(perm = transpose_35_perm_0, x = matmul_17)[name = string("transpose_28")];
            tensor<fp16, [256, 352]> reshape_73 = reshape(shape = reshape_73_shape_0, x = transpose_35)[name = string("reshape_73")];
            tensor<fp16, [256, 352]> mul_412 = mul(x = reshape_73, y = reshape_73)[name = string("mul_412")];
            tensor<int32, [1]> reduce_mean_88_axes_0 = const()[name = string("reduce_mean_88_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_88_keep_dims_0 = const()[name = string("reduce_mean_88_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_88 = reduce_mean(axes = reduce_mean_88_axes_0, keep_dims = reduce_mean_88_keep_dims_0, x = mul_412)[name = string("reduce_mean_88")];
            fp32 rsqrt_88_epsilon_0 = const()[name = string("rsqrt_88_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_88 = rsqrt(epsilon = rsqrt_88_epsilon_0, x = reduce_mean_88)[name = string("rsqrt_88")];
            tensor<fp16, [256, 352]> mul_413 = mul(x = reshape_73, y = rsqrt_88)[name = string("mul_413")];
            tensor<fp16, [352]> mul_414_y_0 = const()[name = string("mul_414_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5132736)))];
            tensor<fp16, [256, 352]> mul_414 = mul(x = mul_413, y = mul_414_y_0)[name = string("mul_414")];
            tensor<fp16, [352, 352]> tern_8_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5133504))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_8_o_weight_0_palettized")];
            tensor<fp16, [256, 352]> tern_8_o = linear(bias = linear_0_bias_0, weight = tern_8_o_weight_0_palettized, x = mul_414)[name = string("tern_8_o")];
            tensor<fp16, [352]> mul_415_y_0 = const()[name = string("mul_415_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5164544)))];
            tensor<fp16, [256, 352]> mul_415 = mul(x = tern_8_o, y = mul_415_y_0)[name = string("mul_415")];
            tensor<fp16, [256, 352]> add_51 = add(x = add_47, y = mul_415)[name = string("add_51")];
            tensor<fp16, [256, 352]> mul_416 = mul(x = add_51, y = add_51)[name = string("mul_416")];
            tensor<int32, [1]> reduce_mean_89_axes_0 = const()[name = string("reduce_mean_89_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_89_keep_dims_0 = const()[name = string("reduce_mean_89_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_89 = reduce_mean(axes = reduce_mean_89_axes_0, keep_dims = reduce_mean_89_keep_dims_0, x = mul_416)[name = string("reduce_mean_89")];
            fp32 rsqrt_89_epsilon_0 = const()[name = string("rsqrt_89_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_89 = rsqrt(epsilon = rsqrt_89_epsilon_0, x = reduce_mean_89)[name = string("rsqrt_89")];
            tensor<fp16, [256, 352]> mul_417 = mul(x = add_51, y = rsqrt_89)[name = string("mul_417")];
            tensor<fp16, [352]> mul_418_y_0 = const()[name = string("mul_418_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5165312)))];
            tensor<fp16, [256, 352]> mul_418 = mul(x = mul_417, y = mul_418_y_0)[name = string("mul_418")];
            tensor<fp16, [256, 352]> mul_419 = mul(x = mul_418, y = mul_418)[name = string("mul_419")];
            tensor<int32, [1]> reduce_mean_90_axes_0 = const()[name = string("reduce_mean_90_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_90_keep_dims_0 = const()[name = string("reduce_mean_90_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_90 = reduce_mean(axes = reduce_mean_90_axes_0, keep_dims = reduce_mean_90_keep_dims_0, x = mul_419)[name = string("reduce_mean_90")];
            fp32 rsqrt_90_epsilon_0 = const()[name = string("rsqrt_90_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_90 = rsqrt(epsilon = rsqrt_90_epsilon_0, x = reduce_mean_90)[name = string("rsqrt_90")];
            tensor<fp16, [256, 352]> mul_420 = mul(x = mul_418, y = rsqrt_90)[name = string("mul_420")];
            tensor<fp16, [352]> mul_421_y_0 = const()[name = string("mul_421_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5166080)))];
            tensor<fp16, [256, 352]> mul_421 = mul(x = mul_420, y = mul_421_y_0)[name = string("mul_421")];
            tensor<fp16, [960, 352]> tern_8_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5166848))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_8_w1_weight_0_palettized")];
            tensor<fp16, [256, 960]> tern_8_w1 = linear(bias = linear_4_bias_0, weight = tern_8_w1_weight_0_palettized, x = mul_421)[name = string("tern_8_w1")];
            tensor<fp16, [960]> mul_422_y_0 = const()[name = string("mul_422_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5251392)))];
            tensor<fp16, [256, 960]> mul_422 = mul(x = tern_8_w1, y = mul_422_y_0)[name = string("mul_422")];
            tensor<fp16, [352]> mul_425_y_0 = const()[name = string("mul_425_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5253376)))];
            tensor<fp16, [256, 352]> mul_425 = mul(x = mul_420, y = mul_425_y_0)[name = string("mul_425")];
            tensor<fp16, [960, 352]> tern_8_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5254144))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_8_w3_weight_0_palettized")];
            tensor<fp16, [256, 960]> tern_8_w3 = linear(bias = linear_4_bias_0, weight = tern_8_w3_weight_0_palettized, x = mul_425)[name = string("tern_8_w3")];
            tensor<fp16, [960]> mul_426_y_0 = const()[name = string("mul_426_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5338688)))];
            tensor<fp16, [256, 960]> mul_426 = mul(x = tern_8_w3, y = mul_426_y_0)[name = string("mul_426")];
            fp16 mul_427_y_0 = const()[name = string("mul_427_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [256, 960]> mul_427 = mul(x = mul_422, y = mul_427_y_0)[name = string("mul_427")];
            tensor<fp16, [256, 960]> tanh_8 = tanh(x = mul_427)[name = string("tanh_8")];
            fp16 mul_428_x_0 = const()[name = string("mul_428_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [256, 960]> mul_428 = mul(x = mul_428_x_0, y = tanh_8)[name = string("mul_428")];
            fp16 add_52_x_0 = const()[name = string("add_52_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [256, 960]> add_52 = add(x = add_52_x_0, y = mul_428)[name = string("add_52")];
            tensor<fp16, [256, 960]> mul_429 = mul(x = mul_422, y = add_52)[name = string("mul_429")];
            tensor<fp16, [256, 960]> mul_430 = mul(x = mul_429, y = mul_426)[name = string("mul_430")];
            tensor<fp16, [256, 960]> mul_431 = mul(x = mul_430, y = mul_430)[name = string("mul_431")];
            tensor<int32, [1]> reduce_mean_92_axes_0 = const()[name = string("reduce_mean_92_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_92_keep_dims_0 = const()[name = string("reduce_mean_92_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_92 = reduce_mean(axes = reduce_mean_92_axes_0, keep_dims = reduce_mean_92_keep_dims_0, x = mul_431)[name = string("reduce_mean_92")];
            fp32 rsqrt_92_epsilon_0 = const()[name = string("rsqrt_92_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_92 = rsqrt(epsilon = rsqrt_92_epsilon_0, x = reduce_mean_92)[name = string("rsqrt_92")];
            tensor<fp16, [256, 960]> mul_432 = mul(x = mul_430, y = rsqrt_92)[name = string("mul_432")];
            tensor<fp16, [960]> mul_433_y_0 = const()[name = string("mul_433_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5340672)))];
            tensor<fp16, [256, 960]> mul_433 = mul(x = mul_432, y = mul_433_y_0)[name = string("mul_433")];
            tensor<fp16, [352, 960]> tern_8_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5342656))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_8_w2_weight_0_palettized")];
            tensor<fp16, [256, 352]> tern_8_w2 = linear(bias = linear_0_bias_0, weight = tern_8_w2_weight_0_palettized, x = mul_433)[name = string("tern_8_w2")];
            tensor<fp16, [352]> mul_434_y_0 = const()[name = string("mul_434_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5427200)))];
            tensor<fp16, [256, 352]> mul_434 = mul(x = tern_8_w2, y = mul_434_y_0)[name = string("mul_434")];
            tensor<fp16, [256, 352]> add_53 = add(x = add_51, y = mul_434)[name = string("add_53")];
            tensor<fp16, [256, 352]> mul_435 = mul(x = add_53, y = add_53)[name = string("mul_435")];
            tensor<int32, [1]> reduce_mean_93_axes_0 = const()[name = string("reduce_mean_93_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_93_keep_dims_0 = const()[name = string("reduce_mean_93_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_93 = reduce_mean(axes = reduce_mean_93_axes_0, keep_dims = reduce_mean_93_keep_dims_0, x = mul_435)[name = string("reduce_mean_93")];
            fp32 rsqrt_93_epsilon_0 = const()[name = string("rsqrt_93_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_93 = rsqrt(epsilon = rsqrt_93_epsilon_0, x = reduce_mean_93)[name = string("rsqrt_93")];
            tensor<fp16, [256, 352]> mul_436 = mul(x = add_53, y = rsqrt_93)[name = string("mul_436")];
            tensor<fp16, [352]> mul_437_y_0 = const()[name = string("mul_437_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5427968)))];
            tensor<fp16, [256, 352]> mul_437 = mul(x = mul_436, y = mul_437_y_0)[name = string("mul_437")];
            tensor<fp16, [256, 352]> mul_438 = mul(x = mul_437, y = mul_437)[name = string("mul_438")];
            tensor<int32, [1]> reduce_mean_94_axes_0 = const()[name = string("reduce_mean_94_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_94_keep_dims_0 = const()[name = string("reduce_mean_94_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_94 = reduce_mean(axes = reduce_mean_94_axes_0, keep_dims = reduce_mean_94_keep_dims_0, x = mul_438)[name = string("reduce_mean_94")];
            fp32 rsqrt_94_epsilon_0 = const()[name = string("rsqrt_94_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_94 = rsqrt(epsilon = rsqrt_94_epsilon_0, x = reduce_mean_94)[name = string("rsqrt_94")];
            tensor<fp16, [256, 352]> mul_439 = mul(x = mul_437, y = rsqrt_94)[name = string("mul_439")];
            tensor<fp16, [352]> mul_440_y_0 = const()[name = string("mul_440_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5428736)))];
            tensor<fp16, [256, 352]> mul_440 = mul(x = mul_439, y = mul_440_y_0)[name = string("mul_440")];
            tensor<fp16, [352, 352]> tern_9_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5429504))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_9_q_weight_0_palettized")];
            tensor<fp16, [256, 352]> tern_9_q = linear(bias = linear_0_bias_0, weight = tern_9_q_weight_0_palettized, x = mul_440)[name = string("tern_9_q")];
            tensor<fp16, [352]> mul_441_y_0 = const()[name = string("mul_441_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5460544)))];
            tensor<fp16, [256, 352]> mul_441 = mul(x = tern_9_q, y = mul_441_y_0)[name = string("mul_441")];
            tensor<int32, [3]> reshape_74_shape_0 = const()[name = string("reshape_74_shape_0"), val = tensor<int32, [3]>([256, 8, 44])];
            tensor<fp16, [256, 8, 44]> reshape_74 = reshape(shape = reshape_74_shape_0, x = mul_441)[name = string("reshape_74")];
            tensor<int32, [3]> transpose_36_perm_0 = const()[name = string("transpose_36_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_444_y_0 = const()[name = string("mul_444_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5461312)))];
            tensor<fp16, [256, 352]> mul_444 = mul(x = mul_439, y = mul_444_y_0)[name = string("mul_444")];
            tensor<fp16, [88, 352]> tern_9_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5462080))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_9_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_9_k_bias_0 = const()[name = string("tern_9_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [256, 88]> tern_9_k = linear(bias = tern_9_k_bias_0, weight = tern_9_k_weight_0_palettized, x = mul_444)[name = string("tern_9_k")];
            tensor<fp16, [88]> mul_445_y_0 = const()[name = string("mul_445_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5469888)))];
            tensor<fp16, [256, 88]> mul_445 = mul(x = tern_9_k, y = mul_445_y_0)[name = string("mul_445")];
            tensor<int32, [3]> reshape_75_shape_0 = const()[name = string("reshape_75_shape_0"), val = tensor<int32, [3]>([256, 2, 44])];
            tensor<fp16, [256, 2, 44]> reshape_75 = reshape(shape = reshape_75_shape_0, x = mul_445)[name = string("reshape_75")];
            tensor<int32, [3]> transpose_37_perm_0 = const()[name = string("transpose_37_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_448_y_0 = const()[name = string("mul_448_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5470144)))];
            tensor<fp16, [256, 352]> mul_448 = mul(x = mul_439, y = mul_448_y_0)[name = string("mul_448")];
            tensor<fp16, [88, 352]> tern_9_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5470912))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_9_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_9_v_bias_0 = const()[name = string("tern_9_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [256, 88]> tern_9_v = linear(bias = tern_9_v_bias_0, weight = tern_9_v_weight_0_palettized, x = mul_448)[name = string("tern_9_v")];
            tensor<fp16, [88]> mul_449_y_0 = const()[name = string("mul_449_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5478720)))];
            tensor<fp16, [256, 88]> mul_449 = mul(x = tern_9_v, y = mul_449_y_0)[name = string("mul_449")];
            tensor<int32, [3]> reshape_76_shape_0 = const()[name = string("reshape_76_shape_0"), val = tensor<int32, [3]>([256, 2, 44])];
            tensor<fp16, [256, 2, 44]> reshape_76 = reshape(shape = reshape_76_shape_0, x = mul_449)[name = string("reshape_76")];
            tensor<int32, [3]> transpose_38_perm_0 = const()[name = string("transpose_38_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 256, 44]> transpose_36 = transpose(perm = transpose_36_perm_0, x = reshape_74)[name = string("transpose_27")];
            tensor<fp16, [8, 256, 44]> mul_450 = mul(x = transpose_36, y = transpose_36)[name = string("mul_450")];
            tensor<int32, [1]> reduce_mean_97_axes_0 = const()[name = string("reduce_mean_97_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_97_keep_dims_0 = const()[name = string("reduce_mean_97_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 256, 1]> reduce_mean_97 = reduce_mean(axes = reduce_mean_97_axes_0, keep_dims = reduce_mean_97_keep_dims_0, x = mul_450)[name = string("reduce_mean_97")];
            fp32 rsqrt_97_epsilon_0 = const()[name = string("rsqrt_97_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 256, 1]> rsqrt_97 = rsqrt(epsilon = rsqrt_97_epsilon_0, x = reduce_mean_97)[name = string("rsqrt_97")];
            tensor<fp16, [8, 256, 44]> mul_451 = mul(x = transpose_36, y = rsqrt_97)[name = string("mul_451")];
            tensor<fp16, [44]> mul_452_y_0 = const()[name = string("mul_452_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5478976)))];
            tensor<fp16, [8, 256, 44]> mul_452 = mul(x = mul_451, y = mul_452_y_0)[name = string("mul_452")];
            tensor<int32, [3]> slice_by_index_36_begin_0 = const()[name = string("slice_by_index_36_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_36_end_0 = const()[name = string("slice_by_index_36_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_36_end_mask_0 = const()[name = string("slice_by_index_36_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 256, 22]> slice_by_index_36 = slice_by_index(begin = slice_by_index_36_begin_0, end = slice_by_index_36_end_0, end_mask = slice_by_index_36_end_mask_0, x = mul_452)[name = string("slice_by_index_36")];
            tensor<int32, [3]> slice_by_index_37_begin_0 = const()[name = string("slice_by_index_37_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_37_end_0 = const()[name = string("slice_by_index_37_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_37_end_mask_0 = const()[name = string("slice_by_index_37_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 256, 22]> slice_by_index_37 = slice_by_index(begin = slice_by_index_37_begin_0, end = slice_by_index_37_end_0, end_mask = slice_by_index_37_end_mask_0, x = mul_452)[name = string("slice_by_index_37")];
            int32 concat_18_axis_0 = const()[name = string("concat_18_axis_0"), val = int32(-1)];
            bool concat_18_interleave_0 = const()[name = string("concat_18_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 256, 44]> concat_18 = concat(axis = concat_18_axis_0, interleave = concat_18_interleave_0, values = (slice_by_index_37, slice_by_index_36))[name = string("concat_18")];
            tensor<fp16, [44]> mul_453_y_0 = const()[name = string("mul_453_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 256, 44]> mul_453 = mul(x = concat_18, y = mul_453_y_0)[name = string("mul_453")];
            tensor<fp16, [8, 256, 44]> mul_454 = mul(x = mul_452, y = mul_11_y_0)[name = string("mul_454")];
            tensor<fp16, [8, 256, 44]> mul_455 = mul(x = mul_453, y = mul_12_y_0)[name = string("mul_455")];
            tensor<fp16, [8, 256, 44]> add_54 = add(x = mul_454, y = mul_455)[name = string("add_54")];
            tensor<fp16, [2, 256, 44]> transpose_37 = transpose(perm = transpose_37_perm_0, x = reshape_75)[name = string("transpose_26")];
            tensor<fp16, [2, 256, 44]> mul_456 = mul(x = transpose_37, y = transpose_37)[name = string("mul_456")];
            tensor<int32, [1]> reduce_mean_98_axes_0 = const()[name = string("reduce_mean_98_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_98_keep_dims_0 = const()[name = string("reduce_mean_98_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 256, 1]> reduce_mean_98 = reduce_mean(axes = reduce_mean_98_axes_0, keep_dims = reduce_mean_98_keep_dims_0, x = mul_456)[name = string("reduce_mean_98")];
            fp32 rsqrt_98_epsilon_0 = const()[name = string("rsqrt_98_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 256, 1]> rsqrt_98 = rsqrt(epsilon = rsqrt_98_epsilon_0, x = reduce_mean_98)[name = string("rsqrt_98")];
            tensor<fp16, [2, 256, 44]> mul_457 = mul(x = transpose_37, y = rsqrt_98)[name = string("mul_457")];
            tensor<fp16, [44]> mul_458_y_0 = const()[name = string("mul_458_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5479168)))];
            tensor<fp16, [2, 256, 44]> mul_458 = mul(x = mul_457, y = mul_458_y_0)[name = string("mul_458")];
            tensor<int32, [3]> slice_by_index_38_begin_0 = const()[name = string("slice_by_index_38_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_38_end_0 = const()[name = string("slice_by_index_38_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_38_end_mask_0 = const()[name = string("slice_by_index_38_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 256, 22]> slice_by_index_38 = slice_by_index(begin = slice_by_index_38_begin_0, end = slice_by_index_38_end_0, end_mask = slice_by_index_38_end_mask_0, x = mul_458)[name = string("slice_by_index_38")];
            tensor<int32, [3]> slice_by_index_39_begin_0 = const()[name = string("slice_by_index_39_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_39_end_0 = const()[name = string("slice_by_index_39_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_39_end_mask_0 = const()[name = string("slice_by_index_39_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 256, 22]> slice_by_index_39 = slice_by_index(begin = slice_by_index_39_begin_0, end = slice_by_index_39_end_0, end_mask = slice_by_index_39_end_mask_0, x = mul_458)[name = string("slice_by_index_39")];
            int32 concat_19_axis_0 = const()[name = string("concat_19_axis_0"), val = int32(-1)];
            bool concat_19_interleave_0 = const()[name = string("concat_19_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 256, 44]> concat_19 = concat(axis = concat_19_axis_0, interleave = concat_19_interleave_0, values = (slice_by_index_39, slice_by_index_38))[name = string("concat_19")];
            tensor<fp16, [44]> mul_459_y_0 = const()[name = string("mul_459_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 256, 44]> mul_459 = mul(x = concat_19, y = mul_459_y_0)[name = string("mul_459")];
            tensor<fp16, [2, 256, 44]> mul_460 = mul(x = mul_458, y = mul_11_y_0)[name = string("mul_460")];
            tensor<fp16, [2, 256, 44]> mul_461 = mul(x = mul_459, y = mul_12_y_0)[name = string("mul_461")];
            tensor<fp16, [2, 256, 44]> add_55 = add(x = mul_460, y = mul_461)[name = string("add_55")];
            tensor<int32, [4]> reshape_77_shape_0 = const()[name = string("reshape_77_shape_0"), val = tensor<int32, [4]>([2, 1, 256, 44])];
            tensor<fp16, [2, 1, 256, 44]> reshape_77 = reshape(shape = reshape_77_shape_0, x = add_55)[name = string("reshape_77")];
            tensor<int32, [4]> tile_18_reps_0 = const()[name = string("tile_18_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 256, 44]> tile_18 = tile(reps = tile_18_reps_0, x = reshape_77)[name = string("tile_18")];
            tensor<int32, [3]> reshape_78_shape_0 = const()[name = string("reshape_78_shape_0"), val = tensor<int32, [3]>([8, 256, 44])];
            tensor<fp16, [8, 256, 44]> reshape_78 = reshape(shape = reshape_78_shape_0, x = tile_18)[name = string("reshape_78")];
            tensor<int32, [4]> reshape_79_shape_0 = const()[name = string("reshape_79_shape_0"), val = tensor<int32, [4]>([2, 1, 256, 44])];
            tensor<fp16, [2, 256, 44]> transpose_38 = transpose(perm = transpose_38_perm_0, x = reshape_76)[name = string("transpose_25")];
            tensor<fp16, [2, 1, 256, 44]> reshape_79 = reshape(shape = reshape_79_shape_0, x = transpose_38)[name = string("reshape_79")];
            tensor<int32, [4]> tile_19_reps_0 = const()[name = string("tile_19_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 256, 44]> tile_19 = tile(reps = tile_19_reps_0, x = reshape_79)[name = string("tile_19")];
            tensor<int32, [3]> reshape_80_shape_0 = const()[name = string("reshape_80_shape_0"), val = tensor<int32, [3]>([8, 256, 44])];
            tensor<fp16, [8, 256, 44]> reshape_80 = reshape(shape = reshape_80_shape_0, x = tile_19)[name = string("reshape_80")];
            fp16 mul_462_y_0 = const()[name = string("mul_462_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 256, 44]> mul_462 = mul(x = add_54, y = mul_462_y_0)[name = string("mul_462")];
            bool matmul_18_transpose_y_0 = const()[name = string("matmul_18_transpose_y_0"), val = bool(true)];
            bool matmul_18_transpose_x_0 = const()[name = string("matmul_18_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 256, 256]> matmul_18 = matmul(transpose_x = matmul_18_transpose_x_0, transpose_y = matmul_18_transpose_y_0, x = mul_462, y = reshape_78)[name = string("matmul_18")];
            tensor<fp16, [8, 256, 256]> add_56 = add(x = matmul_18, y = reshape_1)[name = string("add_56")];
            int32 softmax_9_axis_0 = const()[name = string("softmax_9_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 256, 256]> softmax_9 = softmax(axis = softmax_9_axis_0, x = add_56)[name = string("softmax_9")];
            bool matmul_19_transpose_x_0 = const()[name = string("matmul_19_transpose_x_0"), val = bool(false)];
            bool matmul_19_transpose_y_0 = const()[name = string("matmul_19_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 256, 44]> matmul_19 = matmul(transpose_x = matmul_19_transpose_x_0, transpose_y = matmul_19_transpose_y_0, x = softmax_9, y = reshape_80)[name = string("matmul_19")];
            tensor<int32, [3]> transpose_39_perm_0 = const()[name = string("transpose_39_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_81_shape_0 = const()[name = string("reshape_81_shape_0"), val = tensor<int32, [2]>([256, 352])];
            tensor<fp16, [256, 8, 44]> transpose_39 = transpose(perm = transpose_39_perm_0, x = matmul_19)[name = string("transpose_24")];
            tensor<fp16, [256, 352]> reshape_81 = reshape(shape = reshape_81_shape_0, x = transpose_39)[name = string("reshape_81")];
            tensor<fp16, [256, 352]> mul_463 = mul(x = reshape_81, y = reshape_81)[name = string("mul_463")];
            tensor<int32, [1]> reduce_mean_99_axes_0 = const()[name = string("reduce_mean_99_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_99_keep_dims_0 = const()[name = string("reduce_mean_99_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_99 = reduce_mean(axes = reduce_mean_99_axes_0, keep_dims = reduce_mean_99_keep_dims_0, x = mul_463)[name = string("reduce_mean_99")];
            fp32 rsqrt_99_epsilon_0 = const()[name = string("rsqrt_99_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_99 = rsqrt(epsilon = rsqrt_99_epsilon_0, x = reduce_mean_99)[name = string("rsqrt_99")];
            tensor<fp16, [256, 352]> mul_464 = mul(x = reshape_81, y = rsqrt_99)[name = string("mul_464")];
            tensor<fp16, [352]> mul_465_y_0 = const()[name = string("mul_465_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5479360)))];
            tensor<fp16, [256, 352]> mul_465 = mul(x = mul_464, y = mul_465_y_0)[name = string("mul_465")];
            tensor<fp16, [352, 352]> tern_9_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5480128))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_9_o_weight_0_palettized")];
            tensor<fp16, [256, 352]> tern_9_o = linear(bias = linear_0_bias_0, weight = tern_9_o_weight_0_palettized, x = mul_465)[name = string("tern_9_o")];
            tensor<fp16, [352]> mul_466_y_0 = const()[name = string("mul_466_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5511168)))];
            tensor<fp16, [256, 352]> mul_466 = mul(x = tern_9_o, y = mul_466_y_0)[name = string("mul_466")];
            tensor<fp16, [256, 352]> add_57 = add(x = add_53, y = mul_466)[name = string("add_57")];
            tensor<fp16, [256, 352]> mul_467 = mul(x = add_57, y = add_57)[name = string("mul_467")];
            tensor<int32, [1]> reduce_mean_100_axes_0 = const()[name = string("reduce_mean_100_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_100_keep_dims_0 = const()[name = string("reduce_mean_100_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_100 = reduce_mean(axes = reduce_mean_100_axes_0, keep_dims = reduce_mean_100_keep_dims_0, x = mul_467)[name = string("reduce_mean_100")];
            fp32 rsqrt_100_epsilon_0 = const()[name = string("rsqrt_100_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_100 = rsqrt(epsilon = rsqrt_100_epsilon_0, x = reduce_mean_100)[name = string("rsqrt_100")];
            tensor<fp16, [256, 352]> mul_468 = mul(x = add_57, y = rsqrt_100)[name = string("mul_468")];
            tensor<fp16, [352]> mul_469_y_0 = const()[name = string("mul_469_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5511936)))];
            tensor<fp16, [256, 352]> mul_469 = mul(x = mul_468, y = mul_469_y_0)[name = string("mul_469")];
            tensor<fp16, [256, 352]> mul_470 = mul(x = mul_469, y = mul_469)[name = string("mul_470")];
            tensor<int32, [1]> reduce_mean_101_axes_0 = const()[name = string("reduce_mean_101_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_101_keep_dims_0 = const()[name = string("reduce_mean_101_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_101 = reduce_mean(axes = reduce_mean_101_axes_0, keep_dims = reduce_mean_101_keep_dims_0, x = mul_470)[name = string("reduce_mean_101")];
            fp32 rsqrt_101_epsilon_0 = const()[name = string("rsqrt_101_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_101 = rsqrt(epsilon = rsqrt_101_epsilon_0, x = reduce_mean_101)[name = string("rsqrt_101")];
            tensor<fp16, [256, 352]> mul_471 = mul(x = mul_469, y = rsqrt_101)[name = string("mul_471")];
            tensor<fp16, [352]> mul_472_y_0 = const()[name = string("mul_472_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5512704)))];
            tensor<fp16, [256, 352]> mul_472 = mul(x = mul_471, y = mul_472_y_0)[name = string("mul_472")];
            tensor<fp16, [960, 352]> tern_9_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5513472))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_9_w1_weight_0_palettized")];
            tensor<fp16, [256, 960]> tern_9_w1 = linear(bias = linear_4_bias_0, weight = tern_9_w1_weight_0_palettized, x = mul_472)[name = string("tern_9_w1")];
            tensor<fp16, [960]> mul_473_y_0 = const()[name = string("mul_473_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5598016)))];
            tensor<fp16, [256, 960]> mul_473 = mul(x = tern_9_w1, y = mul_473_y_0)[name = string("mul_473")];
            tensor<fp16, [352]> mul_476_y_0 = const()[name = string("mul_476_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5600000)))];
            tensor<fp16, [256, 352]> mul_476 = mul(x = mul_471, y = mul_476_y_0)[name = string("mul_476")];
            tensor<fp16, [960, 352]> tern_9_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5600768))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_9_w3_weight_0_palettized")];
            tensor<fp16, [256, 960]> tern_9_w3 = linear(bias = linear_4_bias_0, weight = tern_9_w3_weight_0_palettized, x = mul_476)[name = string("tern_9_w3")];
            tensor<fp16, [960]> mul_477_y_0 = const()[name = string("mul_477_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5685312)))];
            tensor<fp16, [256, 960]> mul_477 = mul(x = tern_9_w3, y = mul_477_y_0)[name = string("mul_477")];
            fp16 mul_478_y_0 = const()[name = string("mul_478_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [256, 960]> mul_478 = mul(x = mul_473, y = mul_478_y_0)[name = string("mul_478")];
            tensor<fp16, [256, 960]> tanh_9 = tanh(x = mul_478)[name = string("tanh_9")];
            fp16 mul_479_x_0 = const()[name = string("mul_479_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [256, 960]> mul_479 = mul(x = mul_479_x_0, y = tanh_9)[name = string("mul_479")];
            fp16 add_58_x_0 = const()[name = string("add_58_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [256, 960]> add_58 = add(x = add_58_x_0, y = mul_479)[name = string("add_58")];
            tensor<fp16, [256, 960]> mul_480 = mul(x = mul_473, y = add_58)[name = string("mul_480")];
            tensor<fp16, [256, 960]> mul_481 = mul(x = mul_480, y = mul_477)[name = string("mul_481")];
            tensor<fp16, [256, 960]> mul_482 = mul(x = mul_481, y = mul_481)[name = string("mul_482")];
            tensor<int32, [1]> reduce_mean_103_axes_0 = const()[name = string("reduce_mean_103_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_103_keep_dims_0 = const()[name = string("reduce_mean_103_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_103 = reduce_mean(axes = reduce_mean_103_axes_0, keep_dims = reduce_mean_103_keep_dims_0, x = mul_482)[name = string("reduce_mean_103")];
            fp32 rsqrt_103_epsilon_0 = const()[name = string("rsqrt_103_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_103 = rsqrt(epsilon = rsqrt_103_epsilon_0, x = reduce_mean_103)[name = string("rsqrt_103")];
            tensor<fp16, [256, 960]> mul_483 = mul(x = mul_481, y = rsqrt_103)[name = string("mul_483")];
            tensor<fp16, [960]> mul_484_y_0 = const()[name = string("mul_484_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5687296)))];
            tensor<fp16, [256, 960]> mul_484 = mul(x = mul_483, y = mul_484_y_0)[name = string("mul_484")];
            tensor<fp16, [352, 960]> tern_9_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5689280))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_9_w2_weight_0_palettized")];
            tensor<fp16, [256, 352]> tern_9_w2 = linear(bias = linear_0_bias_0, weight = tern_9_w2_weight_0_palettized, x = mul_484)[name = string("tern_9_w2")];
            tensor<fp16, [352]> mul_485_y_0 = const()[name = string("mul_485_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5773824)))];
            tensor<fp16, [256, 352]> mul_485 = mul(x = tern_9_w2, y = mul_485_y_0)[name = string("mul_485")];
            tensor<fp16, [256, 352]> add_59 = add(x = add_57, y = mul_485)[name = string("add_59")];
            tensor<fp16, [256, 352]> mul_486 = mul(x = add_59, y = add_59)[name = string("mul_486")];
            tensor<int32, [1]> reduce_mean_104_axes_0 = const()[name = string("reduce_mean_104_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_104_keep_dims_0 = const()[name = string("reduce_mean_104_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_104 = reduce_mean(axes = reduce_mean_104_axes_0, keep_dims = reduce_mean_104_keep_dims_0, x = mul_486)[name = string("reduce_mean_104")];
            fp32 rsqrt_104_epsilon_0 = const()[name = string("rsqrt_104_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_104 = rsqrt(epsilon = rsqrt_104_epsilon_0, x = reduce_mean_104)[name = string("rsqrt_104")];
            tensor<fp16, [256, 352]> mul_487 = mul(x = add_59, y = rsqrt_104)[name = string("mul_487")];
            tensor<fp16, [352]> mul_488_y_0 = const()[name = string("mul_488_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5774592)))];
            tensor<fp16, [256, 352]> mul_488 = mul(x = mul_487, y = mul_488_y_0)[name = string("mul_488")];
            tensor<fp16, [256, 352]> mul_489 = mul(x = mul_488, y = mul_488)[name = string("mul_489")];
            tensor<int32, [1]> reduce_mean_105_axes_0 = const()[name = string("reduce_mean_105_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_105_keep_dims_0 = const()[name = string("reduce_mean_105_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_105 = reduce_mean(axes = reduce_mean_105_axes_0, keep_dims = reduce_mean_105_keep_dims_0, x = mul_489)[name = string("reduce_mean_105")];
            fp32 rsqrt_105_epsilon_0 = const()[name = string("rsqrt_105_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_105 = rsqrt(epsilon = rsqrt_105_epsilon_0, x = reduce_mean_105)[name = string("rsqrt_105")];
            tensor<fp16, [256, 352]> mul_490 = mul(x = mul_488, y = rsqrt_105)[name = string("mul_490")];
            tensor<fp16, [352]> mul_491_y_0 = const()[name = string("mul_491_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5775360)))];
            tensor<fp16, [256, 352]> mul_491 = mul(x = mul_490, y = mul_491_y_0)[name = string("mul_491")];
            tensor<fp16, [352, 352]> tern_10_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5776128))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_10_q_weight_0_palettized")];
            tensor<fp16, [256, 352]> tern_10_q = linear(bias = linear_0_bias_0, weight = tern_10_q_weight_0_palettized, x = mul_491)[name = string("tern_10_q")];
            tensor<fp16, [352]> mul_492_y_0 = const()[name = string("mul_492_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5807168)))];
            tensor<fp16, [256, 352]> mul_492 = mul(x = tern_10_q, y = mul_492_y_0)[name = string("mul_492")];
            tensor<int32, [3]> reshape_82_shape_0 = const()[name = string("reshape_82_shape_0"), val = tensor<int32, [3]>([256, 8, 44])];
            tensor<fp16, [256, 8, 44]> reshape_82 = reshape(shape = reshape_82_shape_0, x = mul_492)[name = string("reshape_82")];
            tensor<int32, [3]> transpose_40_perm_0 = const()[name = string("transpose_40_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_495_y_0 = const()[name = string("mul_495_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5807936)))];
            tensor<fp16, [256, 352]> mul_495 = mul(x = mul_490, y = mul_495_y_0)[name = string("mul_495")];
            tensor<fp16, [88, 352]> tern_10_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5808704))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_10_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_10_k_bias_0 = const()[name = string("tern_10_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [256, 88]> tern_10_k = linear(bias = tern_10_k_bias_0, weight = tern_10_k_weight_0_palettized, x = mul_495)[name = string("tern_10_k")];
            tensor<fp16, [88]> mul_496_y_0 = const()[name = string("mul_496_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5816512)))];
            tensor<fp16, [256, 88]> mul_496 = mul(x = tern_10_k, y = mul_496_y_0)[name = string("mul_496")];
            tensor<int32, [3]> reshape_83_shape_0 = const()[name = string("reshape_83_shape_0"), val = tensor<int32, [3]>([256, 2, 44])];
            tensor<fp16, [256, 2, 44]> reshape_83 = reshape(shape = reshape_83_shape_0, x = mul_496)[name = string("reshape_83")];
            tensor<int32, [3]> transpose_41_perm_0 = const()[name = string("transpose_41_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_499_y_0 = const()[name = string("mul_499_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5816768)))];
            tensor<fp16, [256, 352]> mul_499 = mul(x = mul_490, y = mul_499_y_0)[name = string("mul_499")];
            tensor<fp16, [88, 352]> tern_10_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5817536))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_10_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_10_v_bias_0 = const()[name = string("tern_10_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [256, 88]> tern_10_v = linear(bias = tern_10_v_bias_0, weight = tern_10_v_weight_0_palettized, x = mul_499)[name = string("tern_10_v")];
            tensor<fp16, [88]> mul_500_y_0 = const()[name = string("mul_500_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5825344)))];
            tensor<fp16, [256, 88]> mul_500 = mul(x = tern_10_v, y = mul_500_y_0)[name = string("mul_500")];
            tensor<int32, [3]> reshape_84_shape_0 = const()[name = string("reshape_84_shape_0"), val = tensor<int32, [3]>([256, 2, 44])];
            tensor<fp16, [256, 2, 44]> reshape_84 = reshape(shape = reshape_84_shape_0, x = mul_500)[name = string("reshape_84")];
            tensor<int32, [3]> transpose_42_perm_0 = const()[name = string("transpose_42_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 256, 44]> transpose_40 = transpose(perm = transpose_40_perm_0, x = reshape_82)[name = string("transpose_23")];
            tensor<fp16, [8, 256, 44]> mul_501 = mul(x = transpose_40, y = transpose_40)[name = string("mul_501")];
            tensor<int32, [1]> reduce_mean_108_axes_0 = const()[name = string("reduce_mean_108_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_108_keep_dims_0 = const()[name = string("reduce_mean_108_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 256, 1]> reduce_mean_108 = reduce_mean(axes = reduce_mean_108_axes_0, keep_dims = reduce_mean_108_keep_dims_0, x = mul_501)[name = string("reduce_mean_108")];
            fp32 rsqrt_108_epsilon_0 = const()[name = string("rsqrt_108_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 256, 1]> rsqrt_108 = rsqrt(epsilon = rsqrt_108_epsilon_0, x = reduce_mean_108)[name = string("rsqrt_108")];
            tensor<fp16, [8, 256, 44]> mul_502 = mul(x = transpose_40, y = rsqrt_108)[name = string("mul_502")];
            tensor<fp16, [44]> mul_503_y_0 = const()[name = string("mul_503_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5825600)))];
            tensor<fp16, [8, 256, 44]> mul_503 = mul(x = mul_502, y = mul_503_y_0)[name = string("mul_503")];
            tensor<int32, [3]> slice_by_index_40_begin_0 = const()[name = string("slice_by_index_40_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_40_end_0 = const()[name = string("slice_by_index_40_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_40_end_mask_0 = const()[name = string("slice_by_index_40_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 256, 22]> slice_by_index_40 = slice_by_index(begin = slice_by_index_40_begin_0, end = slice_by_index_40_end_0, end_mask = slice_by_index_40_end_mask_0, x = mul_503)[name = string("slice_by_index_40")];
            tensor<int32, [3]> slice_by_index_41_begin_0 = const()[name = string("slice_by_index_41_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_41_end_0 = const()[name = string("slice_by_index_41_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_41_end_mask_0 = const()[name = string("slice_by_index_41_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 256, 22]> slice_by_index_41 = slice_by_index(begin = slice_by_index_41_begin_0, end = slice_by_index_41_end_0, end_mask = slice_by_index_41_end_mask_0, x = mul_503)[name = string("slice_by_index_41")];
            int32 concat_20_axis_0 = const()[name = string("concat_20_axis_0"), val = int32(-1)];
            bool concat_20_interleave_0 = const()[name = string("concat_20_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 256, 44]> concat_20 = concat(axis = concat_20_axis_0, interleave = concat_20_interleave_0, values = (slice_by_index_41, slice_by_index_40))[name = string("concat_20")];
            tensor<fp16, [44]> mul_504_y_0 = const()[name = string("mul_504_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 256, 44]> mul_504 = mul(x = concat_20, y = mul_504_y_0)[name = string("mul_504")];
            tensor<fp16, [8, 256, 44]> mul_505 = mul(x = mul_503, y = mul_11_y_0)[name = string("mul_505")];
            tensor<fp16, [8, 256, 44]> mul_506 = mul(x = mul_504, y = mul_12_y_0)[name = string("mul_506")];
            tensor<fp16, [8, 256, 44]> add_60 = add(x = mul_505, y = mul_506)[name = string("add_60")];
            tensor<fp16, [2, 256, 44]> transpose_41 = transpose(perm = transpose_41_perm_0, x = reshape_83)[name = string("transpose_22")];
            tensor<fp16, [2, 256, 44]> mul_507 = mul(x = transpose_41, y = transpose_41)[name = string("mul_507")];
            tensor<int32, [1]> reduce_mean_109_axes_0 = const()[name = string("reduce_mean_109_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_109_keep_dims_0 = const()[name = string("reduce_mean_109_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 256, 1]> reduce_mean_109 = reduce_mean(axes = reduce_mean_109_axes_0, keep_dims = reduce_mean_109_keep_dims_0, x = mul_507)[name = string("reduce_mean_109")];
            fp32 rsqrt_109_epsilon_0 = const()[name = string("rsqrt_109_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 256, 1]> rsqrt_109 = rsqrt(epsilon = rsqrt_109_epsilon_0, x = reduce_mean_109)[name = string("rsqrt_109")];
            tensor<fp16, [2, 256, 44]> mul_508 = mul(x = transpose_41, y = rsqrt_109)[name = string("mul_508")];
            tensor<fp16, [44]> mul_509_y_0 = const()[name = string("mul_509_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5825792)))];
            tensor<fp16, [2, 256, 44]> mul_509 = mul(x = mul_508, y = mul_509_y_0)[name = string("mul_509")];
            tensor<int32, [3]> slice_by_index_42_begin_0 = const()[name = string("slice_by_index_42_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_42_end_0 = const()[name = string("slice_by_index_42_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_42_end_mask_0 = const()[name = string("slice_by_index_42_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 256, 22]> slice_by_index_42 = slice_by_index(begin = slice_by_index_42_begin_0, end = slice_by_index_42_end_0, end_mask = slice_by_index_42_end_mask_0, x = mul_509)[name = string("slice_by_index_42")];
            tensor<int32, [3]> slice_by_index_43_begin_0 = const()[name = string("slice_by_index_43_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_43_end_0 = const()[name = string("slice_by_index_43_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_43_end_mask_0 = const()[name = string("slice_by_index_43_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 256, 22]> slice_by_index_43 = slice_by_index(begin = slice_by_index_43_begin_0, end = slice_by_index_43_end_0, end_mask = slice_by_index_43_end_mask_0, x = mul_509)[name = string("slice_by_index_43")];
            int32 concat_21_axis_0 = const()[name = string("concat_21_axis_0"), val = int32(-1)];
            bool concat_21_interleave_0 = const()[name = string("concat_21_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 256, 44]> concat_21 = concat(axis = concat_21_axis_0, interleave = concat_21_interleave_0, values = (slice_by_index_43, slice_by_index_42))[name = string("concat_21")];
            tensor<fp16, [44]> mul_510_y_0 = const()[name = string("mul_510_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 256, 44]> mul_510 = mul(x = concat_21, y = mul_510_y_0)[name = string("mul_510")];
            tensor<fp16, [2, 256, 44]> mul_511 = mul(x = mul_509, y = mul_11_y_0)[name = string("mul_511")];
            tensor<fp16, [2, 256, 44]> mul_512 = mul(x = mul_510, y = mul_12_y_0)[name = string("mul_512")];
            tensor<fp16, [2, 256, 44]> add_61 = add(x = mul_511, y = mul_512)[name = string("add_61")];
            tensor<int32, [4]> reshape_85_shape_0 = const()[name = string("reshape_85_shape_0"), val = tensor<int32, [4]>([2, 1, 256, 44])];
            tensor<fp16, [2, 1, 256, 44]> reshape_85 = reshape(shape = reshape_85_shape_0, x = add_61)[name = string("reshape_85")];
            tensor<int32, [4]> tile_20_reps_0 = const()[name = string("tile_20_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 256, 44]> tile_20 = tile(reps = tile_20_reps_0, x = reshape_85)[name = string("tile_20")];
            tensor<int32, [3]> reshape_86_shape_0 = const()[name = string("reshape_86_shape_0"), val = tensor<int32, [3]>([8, 256, 44])];
            tensor<fp16, [8, 256, 44]> reshape_86 = reshape(shape = reshape_86_shape_0, x = tile_20)[name = string("reshape_86")];
            tensor<int32, [4]> reshape_87_shape_0 = const()[name = string("reshape_87_shape_0"), val = tensor<int32, [4]>([2, 1, 256, 44])];
            tensor<fp16, [2, 256, 44]> transpose_42 = transpose(perm = transpose_42_perm_0, x = reshape_84)[name = string("transpose_21")];
            tensor<fp16, [2, 1, 256, 44]> reshape_87 = reshape(shape = reshape_87_shape_0, x = transpose_42)[name = string("reshape_87")];
            tensor<int32, [4]> tile_21_reps_0 = const()[name = string("tile_21_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 256, 44]> tile_21 = tile(reps = tile_21_reps_0, x = reshape_87)[name = string("tile_21")];
            tensor<int32, [3]> reshape_88_shape_0 = const()[name = string("reshape_88_shape_0"), val = tensor<int32, [3]>([8, 256, 44])];
            tensor<fp16, [8, 256, 44]> reshape_88 = reshape(shape = reshape_88_shape_0, x = tile_21)[name = string("reshape_88")];
            fp16 mul_513_y_0 = const()[name = string("mul_513_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 256, 44]> mul_513 = mul(x = add_60, y = mul_513_y_0)[name = string("mul_513")];
            bool matmul_20_transpose_y_0 = const()[name = string("matmul_20_transpose_y_0"), val = bool(true)];
            bool matmul_20_transpose_x_0 = const()[name = string("matmul_20_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 256, 256]> matmul_20 = matmul(transpose_x = matmul_20_transpose_x_0, transpose_y = matmul_20_transpose_y_0, x = mul_513, y = reshape_86)[name = string("matmul_20")];
            tensor<fp16, [8, 256, 256]> add_62 = add(x = matmul_20, y = reshape_1)[name = string("add_62")];
            int32 softmax_10_axis_0 = const()[name = string("softmax_10_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 256, 256]> softmax_10 = softmax(axis = softmax_10_axis_0, x = add_62)[name = string("softmax_10")];
            bool matmul_21_transpose_x_0 = const()[name = string("matmul_21_transpose_x_0"), val = bool(false)];
            bool matmul_21_transpose_y_0 = const()[name = string("matmul_21_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 256, 44]> matmul_21 = matmul(transpose_x = matmul_21_transpose_x_0, transpose_y = matmul_21_transpose_y_0, x = softmax_10, y = reshape_88)[name = string("matmul_21")];
            tensor<int32, [3]> transpose_43_perm_0 = const()[name = string("transpose_43_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_89_shape_0 = const()[name = string("reshape_89_shape_0"), val = tensor<int32, [2]>([256, 352])];
            tensor<fp16, [256, 8, 44]> transpose_43 = transpose(perm = transpose_43_perm_0, x = matmul_21)[name = string("transpose_20")];
            tensor<fp16, [256, 352]> reshape_89 = reshape(shape = reshape_89_shape_0, x = transpose_43)[name = string("reshape_89")];
            tensor<fp16, [256, 352]> mul_514 = mul(x = reshape_89, y = reshape_89)[name = string("mul_514")];
            tensor<int32, [1]> reduce_mean_110_axes_0 = const()[name = string("reduce_mean_110_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_110_keep_dims_0 = const()[name = string("reduce_mean_110_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_110 = reduce_mean(axes = reduce_mean_110_axes_0, keep_dims = reduce_mean_110_keep_dims_0, x = mul_514)[name = string("reduce_mean_110")];
            fp32 rsqrt_110_epsilon_0 = const()[name = string("rsqrt_110_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_110 = rsqrt(epsilon = rsqrt_110_epsilon_0, x = reduce_mean_110)[name = string("rsqrt_110")];
            tensor<fp16, [256, 352]> mul_515 = mul(x = reshape_89, y = rsqrt_110)[name = string("mul_515")];
            tensor<fp16, [352]> mul_516_y_0 = const()[name = string("mul_516_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5825984)))];
            tensor<fp16, [256, 352]> mul_516 = mul(x = mul_515, y = mul_516_y_0)[name = string("mul_516")];
            tensor<fp16, [352, 352]> tern_10_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5826752))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_10_o_weight_0_palettized")];
            tensor<fp16, [256, 352]> tern_10_o = linear(bias = linear_0_bias_0, weight = tern_10_o_weight_0_palettized, x = mul_516)[name = string("tern_10_o")];
            tensor<fp16, [352]> mul_517_y_0 = const()[name = string("mul_517_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5857792)))];
            tensor<fp16, [256, 352]> mul_517 = mul(x = tern_10_o, y = mul_517_y_0)[name = string("mul_517")];
            tensor<fp16, [256, 352]> add_63 = add(x = add_59, y = mul_517)[name = string("add_63")];
            tensor<fp16, [256, 352]> mul_518 = mul(x = add_63, y = add_63)[name = string("mul_518")];
            tensor<int32, [1]> reduce_mean_111_axes_0 = const()[name = string("reduce_mean_111_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_111_keep_dims_0 = const()[name = string("reduce_mean_111_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_111 = reduce_mean(axes = reduce_mean_111_axes_0, keep_dims = reduce_mean_111_keep_dims_0, x = mul_518)[name = string("reduce_mean_111")];
            fp32 rsqrt_111_epsilon_0 = const()[name = string("rsqrt_111_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_111 = rsqrt(epsilon = rsqrt_111_epsilon_0, x = reduce_mean_111)[name = string("rsqrt_111")];
            tensor<fp16, [256, 352]> mul_519 = mul(x = add_63, y = rsqrt_111)[name = string("mul_519")];
            tensor<fp16, [352]> mul_520_y_0 = const()[name = string("mul_520_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5858560)))];
            tensor<fp16, [256, 352]> mul_520 = mul(x = mul_519, y = mul_520_y_0)[name = string("mul_520")];
            tensor<fp16, [256, 352]> mul_521 = mul(x = mul_520, y = mul_520)[name = string("mul_521")];
            tensor<int32, [1]> reduce_mean_112_axes_0 = const()[name = string("reduce_mean_112_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_112_keep_dims_0 = const()[name = string("reduce_mean_112_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_112 = reduce_mean(axes = reduce_mean_112_axes_0, keep_dims = reduce_mean_112_keep_dims_0, x = mul_521)[name = string("reduce_mean_112")];
            fp32 rsqrt_112_epsilon_0 = const()[name = string("rsqrt_112_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_112 = rsqrt(epsilon = rsqrt_112_epsilon_0, x = reduce_mean_112)[name = string("rsqrt_112")];
            tensor<fp16, [256, 352]> mul_522 = mul(x = mul_520, y = rsqrt_112)[name = string("mul_522")];
            tensor<fp16, [352]> mul_523_y_0 = const()[name = string("mul_523_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5859328)))];
            tensor<fp16, [256, 352]> mul_523 = mul(x = mul_522, y = mul_523_y_0)[name = string("mul_523")];
            tensor<fp16, [960, 352]> tern_10_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5860096))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_10_w1_weight_0_palettized")];
            tensor<fp16, [256, 960]> tern_10_w1 = linear(bias = linear_4_bias_0, weight = tern_10_w1_weight_0_palettized, x = mul_523)[name = string("tern_10_w1")];
            tensor<fp16, [960]> mul_524_y_0 = const()[name = string("mul_524_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5944640)))];
            tensor<fp16, [256, 960]> mul_524 = mul(x = tern_10_w1, y = mul_524_y_0)[name = string("mul_524")];
            tensor<fp16, [352]> mul_527_y_0 = const()[name = string("mul_527_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5946624)))];
            tensor<fp16, [256, 352]> mul_527 = mul(x = mul_522, y = mul_527_y_0)[name = string("mul_527")];
            tensor<fp16, [960, 352]> tern_10_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5947392))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_10_w3_weight_0_palettized")];
            tensor<fp16, [256, 960]> tern_10_w3 = linear(bias = linear_4_bias_0, weight = tern_10_w3_weight_0_palettized, x = mul_527)[name = string("tern_10_w3")];
            tensor<fp16, [960]> mul_528_y_0 = const()[name = string("mul_528_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6031936)))];
            tensor<fp16, [256, 960]> mul_528 = mul(x = tern_10_w3, y = mul_528_y_0)[name = string("mul_528")];
            fp16 mul_529_y_0 = const()[name = string("mul_529_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [256, 960]> mul_529 = mul(x = mul_524, y = mul_529_y_0)[name = string("mul_529")];
            tensor<fp16, [256, 960]> tanh_10 = tanh(x = mul_529)[name = string("tanh_10")];
            fp16 mul_530_x_0 = const()[name = string("mul_530_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [256, 960]> mul_530 = mul(x = mul_530_x_0, y = tanh_10)[name = string("mul_530")];
            fp16 add_64_x_0 = const()[name = string("add_64_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [256, 960]> add_64 = add(x = add_64_x_0, y = mul_530)[name = string("add_64")];
            tensor<fp16, [256, 960]> mul_531 = mul(x = mul_524, y = add_64)[name = string("mul_531")];
            tensor<fp16, [256, 960]> mul_532 = mul(x = mul_531, y = mul_528)[name = string("mul_532")];
            tensor<fp16, [256, 960]> mul_533 = mul(x = mul_532, y = mul_532)[name = string("mul_533")];
            tensor<int32, [1]> reduce_mean_114_axes_0 = const()[name = string("reduce_mean_114_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_114_keep_dims_0 = const()[name = string("reduce_mean_114_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_114 = reduce_mean(axes = reduce_mean_114_axes_0, keep_dims = reduce_mean_114_keep_dims_0, x = mul_533)[name = string("reduce_mean_114")];
            fp32 rsqrt_114_epsilon_0 = const()[name = string("rsqrt_114_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_114 = rsqrt(epsilon = rsqrt_114_epsilon_0, x = reduce_mean_114)[name = string("rsqrt_114")];
            tensor<fp16, [256, 960]> mul_534 = mul(x = mul_532, y = rsqrt_114)[name = string("mul_534")];
            tensor<fp16, [960]> mul_535_y_0 = const()[name = string("mul_535_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6033920)))];
            tensor<fp16, [256, 960]> mul_535 = mul(x = mul_534, y = mul_535_y_0)[name = string("mul_535")];
            tensor<fp16, [352, 960]> tern_10_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6035904))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_10_w2_weight_0_palettized")];
            tensor<fp16, [256, 352]> tern_10_w2 = linear(bias = linear_0_bias_0, weight = tern_10_w2_weight_0_palettized, x = mul_535)[name = string("tern_10_w2")];
            tensor<fp16, [352]> mul_536_y_0 = const()[name = string("mul_536_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6120448)))];
            tensor<fp16, [256, 352]> mul_536 = mul(x = tern_10_w2, y = mul_536_y_0)[name = string("mul_536")];
            tensor<fp16, [256, 352]> add_65 = add(x = add_63, y = mul_536)[name = string("add_65")];
            tensor<fp16, [256, 352]> mul_537 = mul(x = add_65, y = add_65)[name = string("mul_537")];
            tensor<int32, [1]> reduce_mean_115_axes_0 = const()[name = string("reduce_mean_115_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_115_keep_dims_0 = const()[name = string("reduce_mean_115_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_115 = reduce_mean(axes = reduce_mean_115_axes_0, keep_dims = reduce_mean_115_keep_dims_0, x = mul_537)[name = string("reduce_mean_115")];
            fp32 rsqrt_115_epsilon_0 = const()[name = string("rsqrt_115_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_115 = rsqrt(epsilon = rsqrt_115_epsilon_0, x = reduce_mean_115)[name = string("rsqrt_115")];
            tensor<fp16, [256, 352]> mul_538 = mul(x = add_65, y = rsqrt_115)[name = string("mul_538")];
            tensor<fp16, [352]> mul_539_y_0 = const()[name = string("mul_539_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6121216)))];
            tensor<fp16, [256, 352]> mul_539 = mul(x = mul_538, y = mul_539_y_0)[name = string("mul_539")];
            tensor<fp16, [256, 352]> mul_540 = mul(x = mul_539, y = mul_539)[name = string("mul_540")];
            tensor<int32, [1]> reduce_mean_116_axes_0 = const()[name = string("reduce_mean_116_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_116_keep_dims_0 = const()[name = string("reduce_mean_116_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_116 = reduce_mean(axes = reduce_mean_116_axes_0, keep_dims = reduce_mean_116_keep_dims_0, x = mul_540)[name = string("reduce_mean_116")];
            fp32 rsqrt_116_epsilon_0 = const()[name = string("rsqrt_116_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_116 = rsqrt(epsilon = rsqrt_116_epsilon_0, x = reduce_mean_116)[name = string("rsqrt_116")];
            tensor<fp16, [256, 352]> mul_541 = mul(x = mul_539, y = rsqrt_116)[name = string("mul_541")];
            tensor<fp16, [352]> mul_542_y_0 = const()[name = string("mul_542_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6121984)))];
            tensor<fp16, [256, 352]> mul_542 = mul(x = mul_541, y = mul_542_y_0)[name = string("mul_542")];
            tensor<fp16, [352, 352]> tern_11_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6122752))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_11_q_weight_0_palettized")];
            tensor<fp16, [256, 352]> tern_11_q = linear(bias = linear_0_bias_0, weight = tern_11_q_weight_0_palettized, x = mul_542)[name = string("tern_11_q")];
            tensor<fp16, [352]> mul_543_y_0 = const()[name = string("mul_543_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6153792)))];
            tensor<fp16, [256, 352]> mul_543 = mul(x = tern_11_q, y = mul_543_y_0)[name = string("mul_543")];
            tensor<int32, [3]> reshape_90_shape_0 = const()[name = string("reshape_90_shape_0"), val = tensor<int32, [3]>([256, 8, 44])];
            tensor<fp16, [256, 8, 44]> reshape_90 = reshape(shape = reshape_90_shape_0, x = mul_543)[name = string("reshape_90")];
            tensor<int32, [3]> transpose_44_perm_0 = const()[name = string("transpose_44_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_546_y_0 = const()[name = string("mul_546_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6154560)))];
            tensor<fp16, [256, 352]> mul_546 = mul(x = mul_541, y = mul_546_y_0)[name = string("mul_546")];
            tensor<fp16, [88, 352]> tern_11_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6155328))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_11_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_11_k_bias_0 = const()[name = string("tern_11_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [256, 88]> tern_11_k = linear(bias = tern_11_k_bias_0, weight = tern_11_k_weight_0_palettized, x = mul_546)[name = string("tern_11_k")];
            tensor<fp16, [88]> mul_547_y_0 = const()[name = string("mul_547_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6163136)))];
            tensor<fp16, [256, 88]> mul_547 = mul(x = tern_11_k, y = mul_547_y_0)[name = string("mul_547")];
            tensor<int32, [3]> reshape_91_shape_0 = const()[name = string("reshape_91_shape_0"), val = tensor<int32, [3]>([256, 2, 44])];
            tensor<fp16, [256, 2, 44]> reshape_91 = reshape(shape = reshape_91_shape_0, x = mul_547)[name = string("reshape_91")];
            tensor<int32, [3]> transpose_45_perm_0 = const()[name = string("transpose_45_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_550_y_0 = const()[name = string("mul_550_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6163392)))];
            tensor<fp16, [256, 352]> mul_550 = mul(x = mul_541, y = mul_550_y_0)[name = string("mul_550")];
            tensor<fp16, [88, 352]> tern_11_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6164160))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_11_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_11_v_bias_0 = const()[name = string("tern_11_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [256, 88]> tern_11_v = linear(bias = tern_11_v_bias_0, weight = tern_11_v_weight_0_palettized, x = mul_550)[name = string("tern_11_v")];
            tensor<fp16, [88]> mul_551_y_0 = const()[name = string("mul_551_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6171968)))];
            tensor<fp16, [256, 88]> mul_551 = mul(x = tern_11_v, y = mul_551_y_0)[name = string("mul_551")];
            tensor<int32, [3]> reshape_92_shape_0 = const()[name = string("reshape_92_shape_0"), val = tensor<int32, [3]>([256, 2, 44])];
            tensor<fp16, [256, 2, 44]> reshape_92 = reshape(shape = reshape_92_shape_0, x = mul_551)[name = string("reshape_92")];
            tensor<int32, [3]> transpose_46_perm_0 = const()[name = string("transpose_46_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 256, 44]> transpose_44 = transpose(perm = transpose_44_perm_0, x = reshape_90)[name = string("transpose_19")];
            tensor<fp16, [8, 256, 44]> mul_552 = mul(x = transpose_44, y = transpose_44)[name = string("mul_552")];
            tensor<int32, [1]> reduce_mean_119_axes_0 = const()[name = string("reduce_mean_119_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_119_keep_dims_0 = const()[name = string("reduce_mean_119_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 256, 1]> reduce_mean_119 = reduce_mean(axes = reduce_mean_119_axes_0, keep_dims = reduce_mean_119_keep_dims_0, x = mul_552)[name = string("reduce_mean_119")];
            fp32 rsqrt_119_epsilon_0 = const()[name = string("rsqrt_119_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 256, 1]> rsqrt_119 = rsqrt(epsilon = rsqrt_119_epsilon_0, x = reduce_mean_119)[name = string("rsqrt_119")];
            tensor<fp16, [8, 256, 44]> mul_553 = mul(x = transpose_44, y = rsqrt_119)[name = string("mul_553")];
            tensor<fp16, [44]> mul_554_y_0 = const()[name = string("mul_554_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6172224)))];
            tensor<fp16, [8, 256, 44]> mul_554 = mul(x = mul_553, y = mul_554_y_0)[name = string("mul_554")];
            tensor<int32, [3]> slice_by_index_44_begin_0 = const()[name = string("slice_by_index_44_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_44_end_0 = const()[name = string("slice_by_index_44_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_44_end_mask_0 = const()[name = string("slice_by_index_44_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 256, 22]> slice_by_index_44 = slice_by_index(begin = slice_by_index_44_begin_0, end = slice_by_index_44_end_0, end_mask = slice_by_index_44_end_mask_0, x = mul_554)[name = string("slice_by_index_44")];
            tensor<int32, [3]> slice_by_index_45_begin_0 = const()[name = string("slice_by_index_45_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_45_end_0 = const()[name = string("slice_by_index_45_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_45_end_mask_0 = const()[name = string("slice_by_index_45_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 256, 22]> slice_by_index_45 = slice_by_index(begin = slice_by_index_45_begin_0, end = slice_by_index_45_end_0, end_mask = slice_by_index_45_end_mask_0, x = mul_554)[name = string("slice_by_index_45")];
            int32 concat_22_axis_0 = const()[name = string("concat_22_axis_0"), val = int32(-1)];
            bool concat_22_interleave_0 = const()[name = string("concat_22_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 256, 44]> concat_22 = concat(axis = concat_22_axis_0, interleave = concat_22_interleave_0, values = (slice_by_index_45, slice_by_index_44))[name = string("concat_22")];
            tensor<fp16, [44]> mul_555_y_0 = const()[name = string("mul_555_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 256, 44]> mul_555 = mul(x = concat_22, y = mul_555_y_0)[name = string("mul_555")];
            tensor<fp16, [8, 256, 44]> mul_556 = mul(x = mul_554, y = mul_11_y_0)[name = string("mul_556")];
            tensor<fp16, [8, 256, 44]> mul_557 = mul(x = mul_555, y = mul_12_y_0)[name = string("mul_557")];
            tensor<fp16, [8, 256, 44]> add_66 = add(x = mul_556, y = mul_557)[name = string("add_66")];
            tensor<fp16, [2, 256, 44]> transpose_45 = transpose(perm = transpose_45_perm_0, x = reshape_91)[name = string("transpose_18")];
            tensor<fp16, [2, 256, 44]> mul_558 = mul(x = transpose_45, y = transpose_45)[name = string("mul_558")];
            tensor<int32, [1]> reduce_mean_120_axes_0 = const()[name = string("reduce_mean_120_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_120_keep_dims_0 = const()[name = string("reduce_mean_120_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 256, 1]> reduce_mean_120 = reduce_mean(axes = reduce_mean_120_axes_0, keep_dims = reduce_mean_120_keep_dims_0, x = mul_558)[name = string("reduce_mean_120")];
            fp32 rsqrt_120_epsilon_0 = const()[name = string("rsqrt_120_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 256, 1]> rsqrt_120 = rsqrt(epsilon = rsqrt_120_epsilon_0, x = reduce_mean_120)[name = string("rsqrt_120")];
            tensor<fp16, [2, 256, 44]> mul_559 = mul(x = transpose_45, y = rsqrt_120)[name = string("mul_559")];
            tensor<fp16, [44]> mul_560_y_0 = const()[name = string("mul_560_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6172416)))];
            tensor<fp16, [2, 256, 44]> mul_560 = mul(x = mul_559, y = mul_560_y_0)[name = string("mul_560")];
            tensor<int32, [3]> slice_by_index_46_begin_0 = const()[name = string("slice_by_index_46_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_46_end_0 = const()[name = string("slice_by_index_46_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_46_end_mask_0 = const()[name = string("slice_by_index_46_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 256, 22]> slice_by_index_46 = slice_by_index(begin = slice_by_index_46_begin_0, end = slice_by_index_46_end_0, end_mask = slice_by_index_46_end_mask_0, x = mul_560)[name = string("slice_by_index_46")];
            tensor<int32, [3]> slice_by_index_47_begin_0 = const()[name = string("slice_by_index_47_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_47_end_0 = const()[name = string("slice_by_index_47_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_47_end_mask_0 = const()[name = string("slice_by_index_47_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 256, 22]> slice_by_index_47 = slice_by_index(begin = slice_by_index_47_begin_0, end = slice_by_index_47_end_0, end_mask = slice_by_index_47_end_mask_0, x = mul_560)[name = string("slice_by_index_47")];
            int32 concat_23_axis_0 = const()[name = string("concat_23_axis_0"), val = int32(-1)];
            bool concat_23_interleave_0 = const()[name = string("concat_23_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 256, 44]> concat_23 = concat(axis = concat_23_axis_0, interleave = concat_23_interleave_0, values = (slice_by_index_47, slice_by_index_46))[name = string("concat_23")];
            tensor<fp16, [44]> mul_561_y_0 = const()[name = string("mul_561_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 256, 44]> mul_561 = mul(x = concat_23, y = mul_561_y_0)[name = string("mul_561")];
            tensor<fp16, [2, 256, 44]> mul_562 = mul(x = mul_560, y = mul_11_y_0)[name = string("mul_562")];
            tensor<fp16, [2, 256, 44]> mul_563 = mul(x = mul_561, y = mul_12_y_0)[name = string("mul_563")];
            tensor<fp16, [2, 256, 44]> add_67 = add(x = mul_562, y = mul_563)[name = string("add_67")];
            tensor<int32, [4]> reshape_93_shape_0 = const()[name = string("reshape_93_shape_0"), val = tensor<int32, [4]>([2, 1, 256, 44])];
            tensor<fp16, [2, 1, 256, 44]> reshape_93 = reshape(shape = reshape_93_shape_0, x = add_67)[name = string("reshape_93")];
            tensor<int32, [4]> tile_22_reps_0 = const()[name = string("tile_22_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 256, 44]> tile_22 = tile(reps = tile_22_reps_0, x = reshape_93)[name = string("tile_22")];
            tensor<int32, [3]> reshape_94_shape_0 = const()[name = string("reshape_94_shape_0"), val = tensor<int32, [3]>([8, 256, 44])];
            tensor<fp16, [8, 256, 44]> reshape_94 = reshape(shape = reshape_94_shape_0, x = tile_22)[name = string("reshape_94")];
            tensor<int32, [4]> reshape_95_shape_0 = const()[name = string("reshape_95_shape_0"), val = tensor<int32, [4]>([2, 1, 256, 44])];
            tensor<fp16, [2, 256, 44]> transpose_46 = transpose(perm = transpose_46_perm_0, x = reshape_92)[name = string("transpose_17")];
            tensor<fp16, [2, 1, 256, 44]> reshape_95 = reshape(shape = reshape_95_shape_0, x = transpose_46)[name = string("reshape_95")];
            tensor<int32, [4]> tile_23_reps_0 = const()[name = string("tile_23_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 256, 44]> tile_23 = tile(reps = tile_23_reps_0, x = reshape_95)[name = string("tile_23")];
            tensor<int32, [3]> reshape_96_shape_0 = const()[name = string("reshape_96_shape_0"), val = tensor<int32, [3]>([8, 256, 44])];
            tensor<fp16, [8, 256, 44]> reshape_96 = reshape(shape = reshape_96_shape_0, x = tile_23)[name = string("reshape_96")];
            fp16 mul_564_y_0 = const()[name = string("mul_564_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 256, 44]> mul_564 = mul(x = add_66, y = mul_564_y_0)[name = string("mul_564")];
            bool matmul_22_transpose_y_0 = const()[name = string("matmul_22_transpose_y_0"), val = bool(true)];
            bool matmul_22_transpose_x_0 = const()[name = string("matmul_22_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 256, 256]> matmul_22 = matmul(transpose_x = matmul_22_transpose_x_0, transpose_y = matmul_22_transpose_y_0, x = mul_564, y = reshape_94)[name = string("matmul_22")];
            tensor<fp16, [8, 256, 256]> add_68 = add(x = matmul_22, y = reshape_1)[name = string("add_68")];
            int32 softmax_11_axis_0 = const()[name = string("softmax_11_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 256, 256]> softmax_11 = softmax(axis = softmax_11_axis_0, x = add_68)[name = string("softmax_11")];
            bool matmul_23_transpose_x_0 = const()[name = string("matmul_23_transpose_x_0"), val = bool(false)];
            bool matmul_23_transpose_y_0 = const()[name = string("matmul_23_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 256, 44]> matmul_23 = matmul(transpose_x = matmul_23_transpose_x_0, transpose_y = matmul_23_transpose_y_0, x = softmax_11, y = reshape_96)[name = string("matmul_23")];
            tensor<int32, [3]> transpose_47_perm_0 = const()[name = string("transpose_47_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_97_shape_0 = const()[name = string("reshape_97_shape_0"), val = tensor<int32, [2]>([256, 352])];
            tensor<fp16, [256, 8, 44]> transpose_47 = transpose(perm = transpose_47_perm_0, x = matmul_23)[name = string("transpose_16")];
            tensor<fp16, [256, 352]> reshape_97 = reshape(shape = reshape_97_shape_0, x = transpose_47)[name = string("reshape_97")];
            tensor<fp16, [256, 352]> mul_565 = mul(x = reshape_97, y = reshape_97)[name = string("mul_565")];
            tensor<int32, [1]> reduce_mean_121_axes_0 = const()[name = string("reduce_mean_121_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_121_keep_dims_0 = const()[name = string("reduce_mean_121_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_121 = reduce_mean(axes = reduce_mean_121_axes_0, keep_dims = reduce_mean_121_keep_dims_0, x = mul_565)[name = string("reduce_mean_121")];
            fp32 rsqrt_121_epsilon_0 = const()[name = string("rsqrt_121_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_121 = rsqrt(epsilon = rsqrt_121_epsilon_0, x = reduce_mean_121)[name = string("rsqrt_121")];
            tensor<fp16, [256, 352]> mul_566 = mul(x = reshape_97, y = rsqrt_121)[name = string("mul_566")];
            tensor<fp16, [352]> mul_567_y_0 = const()[name = string("mul_567_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6172608)))];
            tensor<fp16, [256, 352]> mul_567 = mul(x = mul_566, y = mul_567_y_0)[name = string("mul_567")];
            tensor<fp16, [352, 352]> tern_11_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6173376))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_11_o_weight_0_palettized")];
            tensor<fp16, [256, 352]> tern_11_o = linear(bias = linear_0_bias_0, weight = tern_11_o_weight_0_palettized, x = mul_567)[name = string("tern_11_o")];
            tensor<fp16, [352]> mul_568_y_0 = const()[name = string("mul_568_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6204416)))];
            tensor<fp16, [256, 352]> mul_568 = mul(x = tern_11_o, y = mul_568_y_0)[name = string("mul_568")];
            tensor<fp16, [256, 352]> add_69 = add(x = add_65, y = mul_568)[name = string("add_69")];
            tensor<fp16, [256, 352]> mul_569 = mul(x = add_69, y = add_69)[name = string("mul_569")];
            tensor<int32, [1]> reduce_mean_122_axes_0 = const()[name = string("reduce_mean_122_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_122_keep_dims_0 = const()[name = string("reduce_mean_122_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_122 = reduce_mean(axes = reduce_mean_122_axes_0, keep_dims = reduce_mean_122_keep_dims_0, x = mul_569)[name = string("reduce_mean_122")];
            fp32 rsqrt_122_epsilon_0 = const()[name = string("rsqrt_122_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_122 = rsqrt(epsilon = rsqrt_122_epsilon_0, x = reduce_mean_122)[name = string("rsqrt_122")];
            tensor<fp16, [256, 352]> mul_570 = mul(x = add_69, y = rsqrt_122)[name = string("mul_570")];
            tensor<fp16, [352]> mul_571_y_0 = const()[name = string("mul_571_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6205184)))];
            tensor<fp16, [256, 352]> mul_571 = mul(x = mul_570, y = mul_571_y_0)[name = string("mul_571")];
            tensor<fp16, [256, 352]> mul_572 = mul(x = mul_571, y = mul_571)[name = string("mul_572")];
            tensor<int32, [1]> reduce_mean_123_axes_0 = const()[name = string("reduce_mean_123_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_123_keep_dims_0 = const()[name = string("reduce_mean_123_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_123 = reduce_mean(axes = reduce_mean_123_axes_0, keep_dims = reduce_mean_123_keep_dims_0, x = mul_572)[name = string("reduce_mean_123")];
            fp32 rsqrt_123_epsilon_0 = const()[name = string("rsqrt_123_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_123 = rsqrt(epsilon = rsqrt_123_epsilon_0, x = reduce_mean_123)[name = string("rsqrt_123")];
            tensor<fp16, [256, 352]> mul_573 = mul(x = mul_571, y = rsqrt_123)[name = string("mul_573")];
            tensor<fp16, [352]> mul_574_y_0 = const()[name = string("mul_574_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6205952)))];
            tensor<fp16, [256, 352]> mul_574 = mul(x = mul_573, y = mul_574_y_0)[name = string("mul_574")];
            tensor<fp16, [960, 352]> tern_11_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6206720))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_11_w1_weight_0_palettized")];
            tensor<fp16, [256, 960]> tern_11_w1 = linear(bias = linear_4_bias_0, weight = tern_11_w1_weight_0_palettized, x = mul_574)[name = string("tern_11_w1")];
            tensor<fp16, [960]> mul_575_y_0 = const()[name = string("mul_575_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6291264)))];
            tensor<fp16, [256, 960]> mul_575 = mul(x = tern_11_w1, y = mul_575_y_0)[name = string("mul_575")];
            tensor<fp16, [352]> mul_578_y_0 = const()[name = string("mul_578_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6293248)))];
            tensor<fp16, [256, 352]> mul_578 = mul(x = mul_573, y = mul_578_y_0)[name = string("mul_578")];
            tensor<fp16, [960, 352]> tern_11_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6294016))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_11_w3_weight_0_palettized")];
            tensor<fp16, [256, 960]> tern_11_w3 = linear(bias = linear_4_bias_0, weight = tern_11_w3_weight_0_palettized, x = mul_578)[name = string("tern_11_w3")];
            tensor<fp16, [960]> mul_579_y_0 = const()[name = string("mul_579_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6378560)))];
            tensor<fp16, [256, 960]> mul_579 = mul(x = tern_11_w3, y = mul_579_y_0)[name = string("mul_579")];
            fp16 mul_580_y_0 = const()[name = string("mul_580_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [256, 960]> mul_580 = mul(x = mul_575, y = mul_580_y_0)[name = string("mul_580")];
            tensor<fp16, [256, 960]> tanh_11 = tanh(x = mul_580)[name = string("tanh_11")];
            fp16 mul_581_x_0 = const()[name = string("mul_581_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [256, 960]> mul_581 = mul(x = mul_581_x_0, y = tanh_11)[name = string("mul_581")];
            fp16 add_70_x_0 = const()[name = string("add_70_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [256, 960]> add_70 = add(x = add_70_x_0, y = mul_581)[name = string("add_70")];
            tensor<fp16, [256, 960]> mul_582 = mul(x = mul_575, y = add_70)[name = string("mul_582")];
            tensor<fp16, [256, 960]> mul_583 = mul(x = mul_582, y = mul_579)[name = string("mul_583")];
            tensor<fp16, [256, 960]> mul_584 = mul(x = mul_583, y = mul_583)[name = string("mul_584")];
            tensor<int32, [1]> reduce_mean_125_axes_0 = const()[name = string("reduce_mean_125_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_125_keep_dims_0 = const()[name = string("reduce_mean_125_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_125 = reduce_mean(axes = reduce_mean_125_axes_0, keep_dims = reduce_mean_125_keep_dims_0, x = mul_584)[name = string("reduce_mean_125")];
            fp32 rsqrt_125_epsilon_0 = const()[name = string("rsqrt_125_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_125 = rsqrt(epsilon = rsqrt_125_epsilon_0, x = reduce_mean_125)[name = string("rsqrt_125")];
            tensor<fp16, [256, 960]> mul_585 = mul(x = mul_583, y = rsqrt_125)[name = string("mul_585")];
            tensor<fp16, [960]> mul_586_y_0 = const()[name = string("mul_586_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6380544)))];
            tensor<fp16, [256, 960]> mul_586 = mul(x = mul_585, y = mul_586_y_0)[name = string("mul_586")];
            tensor<fp16, [352, 960]> tern_11_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6382528))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_11_w2_weight_0_palettized")];
            tensor<fp16, [256, 352]> tern_11_w2 = linear(bias = linear_0_bias_0, weight = tern_11_w2_weight_0_palettized, x = mul_586)[name = string("tern_11_w2")];
            tensor<fp16, [352]> mul_587_y_0 = const()[name = string("mul_587_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6467072)))];
            tensor<fp16, [256, 352]> mul_587 = mul(x = tern_11_w2, y = mul_587_y_0)[name = string("mul_587")];
            tensor<fp16, [256, 352]> add_71 = add(x = add_69, y = mul_587)[name = string("add_71")];
            tensor<fp16, [256, 352]> mul_588 = mul(x = add_71, y = add_71)[name = string("mul_588")];
            tensor<int32, [1]> reduce_mean_126_axes_0 = const()[name = string("reduce_mean_126_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_126_keep_dims_0 = const()[name = string("reduce_mean_126_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_126 = reduce_mean(axes = reduce_mean_126_axes_0, keep_dims = reduce_mean_126_keep_dims_0, x = mul_588)[name = string("reduce_mean_126")];
            fp32 rsqrt_126_epsilon_0 = const()[name = string("rsqrt_126_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_126 = rsqrt(epsilon = rsqrt_126_epsilon_0, x = reduce_mean_126)[name = string("rsqrt_126")];
            tensor<fp16, [256, 352]> mul_589 = mul(x = add_71, y = rsqrt_126)[name = string("mul_589")];
            tensor<fp16, [352]> mul_590_y_0 = const()[name = string("mul_590_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6467840)))];
            tensor<fp16, [256, 352]> mul_590 = mul(x = mul_589, y = mul_590_y_0)[name = string("mul_590")];
            tensor<fp16, [256, 352]> mul_591 = mul(x = mul_590, y = mul_590)[name = string("mul_591")];
            tensor<int32, [1]> reduce_mean_127_axes_0 = const()[name = string("reduce_mean_127_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_127_keep_dims_0 = const()[name = string("reduce_mean_127_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_127 = reduce_mean(axes = reduce_mean_127_axes_0, keep_dims = reduce_mean_127_keep_dims_0, x = mul_591)[name = string("reduce_mean_127")];
            fp32 rsqrt_127_epsilon_0 = const()[name = string("rsqrt_127_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_127 = rsqrt(epsilon = rsqrt_127_epsilon_0, x = reduce_mean_127)[name = string("rsqrt_127")];
            tensor<fp16, [256, 352]> mul_592 = mul(x = mul_590, y = rsqrt_127)[name = string("mul_592")];
            tensor<fp16, [352]> mul_593_y_0 = const()[name = string("mul_593_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6468608)))];
            tensor<fp16, [256, 352]> mul_593 = mul(x = mul_592, y = mul_593_y_0)[name = string("mul_593")];
            tensor<fp16, [352, 352]> tern_12_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6469376))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_12_q_weight_0_palettized")];
            tensor<fp16, [256, 352]> tern_12_q = linear(bias = linear_0_bias_0, weight = tern_12_q_weight_0_palettized, x = mul_593)[name = string("tern_12_q")];
            tensor<fp16, [352]> mul_594_y_0 = const()[name = string("mul_594_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6500416)))];
            tensor<fp16, [256, 352]> mul_594 = mul(x = tern_12_q, y = mul_594_y_0)[name = string("mul_594")];
            tensor<int32, [3]> reshape_98_shape_0 = const()[name = string("reshape_98_shape_0"), val = tensor<int32, [3]>([256, 8, 44])];
            tensor<fp16, [256, 8, 44]> reshape_98 = reshape(shape = reshape_98_shape_0, x = mul_594)[name = string("reshape_98")];
            tensor<int32, [3]> transpose_48_perm_0 = const()[name = string("transpose_48_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_597_y_0 = const()[name = string("mul_597_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6501184)))];
            tensor<fp16, [256, 352]> mul_597 = mul(x = mul_592, y = mul_597_y_0)[name = string("mul_597")];
            tensor<fp16, [88, 352]> tern_12_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6501952))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_12_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_12_k_bias_0 = const()[name = string("tern_12_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [256, 88]> tern_12_k = linear(bias = tern_12_k_bias_0, weight = tern_12_k_weight_0_palettized, x = mul_597)[name = string("tern_12_k")];
            tensor<fp16, [88]> mul_598_y_0 = const()[name = string("mul_598_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6509760)))];
            tensor<fp16, [256, 88]> mul_598 = mul(x = tern_12_k, y = mul_598_y_0)[name = string("mul_598")];
            tensor<int32, [3]> reshape_99_shape_0 = const()[name = string("reshape_99_shape_0"), val = tensor<int32, [3]>([256, 2, 44])];
            tensor<fp16, [256, 2, 44]> reshape_99 = reshape(shape = reshape_99_shape_0, x = mul_598)[name = string("reshape_99")];
            tensor<int32, [3]> transpose_49_perm_0 = const()[name = string("transpose_49_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_601_y_0 = const()[name = string("mul_601_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6510016)))];
            tensor<fp16, [256, 352]> mul_601 = mul(x = mul_592, y = mul_601_y_0)[name = string("mul_601")];
            tensor<fp16, [88, 352]> tern_12_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6510784))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_12_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_12_v_bias_0 = const()[name = string("tern_12_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [256, 88]> tern_12_v = linear(bias = tern_12_v_bias_0, weight = tern_12_v_weight_0_palettized, x = mul_601)[name = string("tern_12_v")];
            tensor<fp16, [88]> mul_602_y_0 = const()[name = string("mul_602_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6518592)))];
            tensor<fp16, [256, 88]> mul_602 = mul(x = tern_12_v, y = mul_602_y_0)[name = string("mul_602")];
            tensor<int32, [3]> reshape_100_shape_0 = const()[name = string("reshape_100_shape_0"), val = tensor<int32, [3]>([256, 2, 44])];
            tensor<fp16, [256, 2, 44]> reshape_100 = reshape(shape = reshape_100_shape_0, x = mul_602)[name = string("reshape_100")];
            tensor<int32, [3]> transpose_50_perm_0 = const()[name = string("transpose_50_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 256, 44]> transpose_48 = transpose(perm = transpose_48_perm_0, x = reshape_98)[name = string("transpose_15")];
            tensor<fp16, [8, 256, 44]> mul_603 = mul(x = transpose_48, y = transpose_48)[name = string("mul_603")];
            tensor<int32, [1]> reduce_mean_130_axes_0 = const()[name = string("reduce_mean_130_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_130_keep_dims_0 = const()[name = string("reduce_mean_130_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 256, 1]> reduce_mean_130 = reduce_mean(axes = reduce_mean_130_axes_0, keep_dims = reduce_mean_130_keep_dims_0, x = mul_603)[name = string("reduce_mean_130")];
            fp32 rsqrt_130_epsilon_0 = const()[name = string("rsqrt_130_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 256, 1]> rsqrt_130 = rsqrt(epsilon = rsqrt_130_epsilon_0, x = reduce_mean_130)[name = string("rsqrt_130")];
            tensor<fp16, [8, 256, 44]> mul_604 = mul(x = transpose_48, y = rsqrt_130)[name = string("mul_604")];
            tensor<fp16, [44]> mul_605_y_0 = const()[name = string("mul_605_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6518848)))];
            tensor<fp16, [8, 256, 44]> mul_605 = mul(x = mul_604, y = mul_605_y_0)[name = string("mul_605")];
            tensor<int32, [3]> slice_by_index_48_begin_0 = const()[name = string("slice_by_index_48_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_48_end_0 = const()[name = string("slice_by_index_48_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_48_end_mask_0 = const()[name = string("slice_by_index_48_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 256, 22]> slice_by_index_48 = slice_by_index(begin = slice_by_index_48_begin_0, end = slice_by_index_48_end_0, end_mask = slice_by_index_48_end_mask_0, x = mul_605)[name = string("slice_by_index_48")];
            tensor<int32, [3]> slice_by_index_49_begin_0 = const()[name = string("slice_by_index_49_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_49_end_0 = const()[name = string("slice_by_index_49_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_49_end_mask_0 = const()[name = string("slice_by_index_49_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 256, 22]> slice_by_index_49 = slice_by_index(begin = slice_by_index_49_begin_0, end = slice_by_index_49_end_0, end_mask = slice_by_index_49_end_mask_0, x = mul_605)[name = string("slice_by_index_49")];
            int32 concat_24_axis_0 = const()[name = string("concat_24_axis_0"), val = int32(-1)];
            bool concat_24_interleave_0 = const()[name = string("concat_24_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 256, 44]> concat_24 = concat(axis = concat_24_axis_0, interleave = concat_24_interleave_0, values = (slice_by_index_49, slice_by_index_48))[name = string("concat_24")];
            tensor<fp16, [44]> mul_606_y_0 = const()[name = string("mul_606_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 256, 44]> mul_606 = mul(x = concat_24, y = mul_606_y_0)[name = string("mul_606")];
            tensor<fp16, [8, 256, 44]> mul_607 = mul(x = mul_605, y = mul_11_y_0)[name = string("mul_607")];
            tensor<fp16, [8, 256, 44]> mul_608 = mul(x = mul_606, y = mul_12_y_0)[name = string("mul_608")];
            tensor<fp16, [8, 256, 44]> add_72 = add(x = mul_607, y = mul_608)[name = string("add_72")];
            tensor<fp16, [2, 256, 44]> transpose_49 = transpose(perm = transpose_49_perm_0, x = reshape_99)[name = string("transpose_14")];
            tensor<fp16, [2, 256, 44]> mul_609 = mul(x = transpose_49, y = transpose_49)[name = string("mul_609")];
            tensor<int32, [1]> reduce_mean_131_axes_0 = const()[name = string("reduce_mean_131_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_131_keep_dims_0 = const()[name = string("reduce_mean_131_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 256, 1]> reduce_mean_131 = reduce_mean(axes = reduce_mean_131_axes_0, keep_dims = reduce_mean_131_keep_dims_0, x = mul_609)[name = string("reduce_mean_131")];
            fp32 rsqrt_131_epsilon_0 = const()[name = string("rsqrt_131_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 256, 1]> rsqrt_131 = rsqrt(epsilon = rsqrt_131_epsilon_0, x = reduce_mean_131)[name = string("rsqrt_131")];
            tensor<fp16, [2, 256, 44]> mul_610 = mul(x = transpose_49, y = rsqrt_131)[name = string("mul_610")];
            tensor<fp16, [44]> mul_611_y_0 = const()[name = string("mul_611_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6519040)))];
            tensor<fp16, [2, 256, 44]> mul_611 = mul(x = mul_610, y = mul_611_y_0)[name = string("mul_611")];
            tensor<int32, [3]> slice_by_index_50_begin_0 = const()[name = string("slice_by_index_50_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_50_end_0 = const()[name = string("slice_by_index_50_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_50_end_mask_0 = const()[name = string("slice_by_index_50_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 256, 22]> slice_by_index_50 = slice_by_index(begin = slice_by_index_50_begin_0, end = slice_by_index_50_end_0, end_mask = slice_by_index_50_end_mask_0, x = mul_611)[name = string("slice_by_index_50")];
            tensor<int32, [3]> slice_by_index_51_begin_0 = const()[name = string("slice_by_index_51_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_51_end_0 = const()[name = string("slice_by_index_51_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_51_end_mask_0 = const()[name = string("slice_by_index_51_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 256, 22]> slice_by_index_51 = slice_by_index(begin = slice_by_index_51_begin_0, end = slice_by_index_51_end_0, end_mask = slice_by_index_51_end_mask_0, x = mul_611)[name = string("slice_by_index_51")];
            int32 concat_25_axis_0 = const()[name = string("concat_25_axis_0"), val = int32(-1)];
            bool concat_25_interleave_0 = const()[name = string("concat_25_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 256, 44]> concat_25 = concat(axis = concat_25_axis_0, interleave = concat_25_interleave_0, values = (slice_by_index_51, slice_by_index_50))[name = string("concat_25")];
            tensor<fp16, [44]> mul_612_y_0 = const()[name = string("mul_612_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 256, 44]> mul_612 = mul(x = concat_25, y = mul_612_y_0)[name = string("mul_612")];
            tensor<fp16, [2, 256, 44]> mul_613 = mul(x = mul_611, y = mul_11_y_0)[name = string("mul_613")];
            tensor<fp16, [2, 256, 44]> mul_614 = mul(x = mul_612, y = mul_12_y_0)[name = string("mul_614")];
            tensor<fp16, [2, 256, 44]> add_73 = add(x = mul_613, y = mul_614)[name = string("add_73")];
            tensor<int32, [4]> reshape_101_shape_0 = const()[name = string("reshape_101_shape_0"), val = tensor<int32, [4]>([2, 1, 256, 44])];
            tensor<fp16, [2, 1, 256, 44]> reshape_101 = reshape(shape = reshape_101_shape_0, x = add_73)[name = string("reshape_101")];
            tensor<int32, [4]> tile_24_reps_0 = const()[name = string("tile_24_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 256, 44]> tile_24 = tile(reps = tile_24_reps_0, x = reshape_101)[name = string("tile_24")];
            tensor<int32, [3]> reshape_102_shape_0 = const()[name = string("reshape_102_shape_0"), val = tensor<int32, [3]>([8, 256, 44])];
            tensor<fp16, [8, 256, 44]> reshape_102 = reshape(shape = reshape_102_shape_0, x = tile_24)[name = string("reshape_102")];
            tensor<int32, [4]> reshape_103_shape_0 = const()[name = string("reshape_103_shape_0"), val = tensor<int32, [4]>([2, 1, 256, 44])];
            tensor<fp16, [2, 256, 44]> transpose_50 = transpose(perm = transpose_50_perm_0, x = reshape_100)[name = string("transpose_13")];
            tensor<fp16, [2, 1, 256, 44]> reshape_103 = reshape(shape = reshape_103_shape_0, x = transpose_50)[name = string("reshape_103")];
            tensor<int32, [4]> tile_25_reps_0 = const()[name = string("tile_25_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 256, 44]> tile_25 = tile(reps = tile_25_reps_0, x = reshape_103)[name = string("tile_25")];
            tensor<int32, [3]> reshape_104_shape_0 = const()[name = string("reshape_104_shape_0"), val = tensor<int32, [3]>([8, 256, 44])];
            tensor<fp16, [8, 256, 44]> reshape_104 = reshape(shape = reshape_104_shape_0, x = tile_25)[name = string("reshape_104")];
            fp16 mul_615_y_0 = const()[name = string("mul_615_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 256, 44]> mul_615 = mul(x = add_72, y = mul_615_y_0)[name = string("mul_615")];
            bool matmul_24_transpose_y_0 = const()[name = string("matmul_24_transpose_y_0"), val = bool(true)];
            bool matmul_24_transpose_x_0 = const()[name = string("matmul_24_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 256, 256]> matmul_24 = matmul(transpose_x = matmul_24_transpose_x_0, transpose_y = matmul_24_transpose_y_0, x = mul_615, y = reshape_102)[name = string("matmul_24")];
            tensor<fp16, [8, 256, 256]> add_74 = add(x = matmul_24, y = reshape_1)[name = string("add_74")];
            int32 softmax_12_axis_0 = const()[name = string("softmax_12_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 256, 256]> softmax_12 = softmax(axis = softmax_12_axis_0, x = add_74)[name = string("softmax_12")];
            bool matmul_25_transpose_x_0 = const()[name = string("matmul_25_transpose_x_0"), val = bool(false)];
            bool matmul_25_transpose_y_0 = const()[name = string("matmul_25_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 256, 44]> matmul_25 = matmul(transpose_x = matmul_25_transpose_x_0, transpose_y = matmul_25_transpose_y_0, x = softmax_12, y = reshape_104)[name = string("matmul_25")];
            tensor<int32, [3]> transpose_51_perm_0 = const()[name = string("transpose_51_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_105_shape_0 = const()[name = string("reshape_105_shape_0"), val = tensor<int32, [2]>([256, 352])];
            tensor<fp16, [256, 8, 44]> transpose_51 = transpose(perm = transpose_51_perm_0, x = matmul_25)[name = string("transpose_12")];
            tensor<fp16, [256, 352]> reshape_105 = reshape(shape = reshape_105_shape_0, x = transpose_51)[name = string("reshape_105")];
            tensor<fp16, [256, 352]> mul_616 = mul(x = reshape_105, y = reshape_105)[name = string("mul_616")];
            tensor<int32, [1]> reduce_mean_132_axes_0 = const()[name = string("reduce_mean_132_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_132_keep_dims_0 = const()[name = string("reduce_mean_132_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_132 = reduce_mean(axes = reduce_mean_132_axes_0, keep_dims = reduce_mean_132_keep_dims_0, x = mul_616)[name = string("reduce_mean_132")];
            fp32 rsqrt_132_epsilon_0 = const()[name = string("rsqrt_132_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_132 = rsqrt(epsilon = rsqrt_132_epsilon_0, x = reduce_mean_132)[name = string("rsqrt_132")];
            tensor<fp16, [256, 352]> mul_617 = mul(x = reshape_105, y = rsqrt_132)[name = string("mul_617")];
            tensor<fp16, [352]> mul_618_y_0 = const()[name = string("mul_618_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6519232)))];
            tensor<fp16, [256, 352]> mul_618 = mul(x = mul_617, y = mul_618_y_0)[name = string("mul_618")];
            tensor<fp16, [352, 352]> tern_12_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6520000))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_12_o_weight_0_palettized")];
            tensor<fp16, [256, 352]> tern_12_o = linear(bias = linear_0_bias_0, weight = tern_12_o_weight_0_palettized, x = mul_618)[name = string("tern_12_o")];
            tensor<fp16, [352]> mul_619_y_0 = const()[name = string("mul_619_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6551040)))];
            tensor<fp16, [256, 352]> mul_619 = mul(x = tern_12_o, y = mul_619_y_0)[name = string("mul_619")];
            tensor<fp16, [256, 352]> add_75 = add(x = add_71, y = mul_619)[name = string("add_75")];
            tensor<fp16, [256, 352]> mul_620 = mul(x = add_75, y = add_75)[name = string("mul_620")];
            tensor<int32, [1]> reduce_mean_133_axes_0 = const()[name = string("reduce_mean_133_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_133_keep_dims_0 = const()[name = string("reduce_mean_133_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_133 = reduce_mean(axes = reduce_mean_133_axes_0, keep_dims = reduce_mean_133_keep_dims_0, x = mul_620)[name = string("reduce_mean_133")];
            fp32 rsqrt_133_epsilon_0 = const()[name = string("rsqrt_133_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_133 = rsqrt(epsilon = rsqrt_133_epsilon_0, x = reduce_mean_133)[name = string("rsqrt_133")];
            tensor<fp16, [256, 352]> mul_621 = mul(x = add_75, y = rsqrt_133)[name = string("mul_621")];
            tensor<fp16, [352]> mul_622_y_0 = const()[name = string("mul_622_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6551808)))];
            tensor<fp16, [256, 352]> mul_622 = mul(x = mul_621, y = mul_622_y_0)[name = string("mul_622")];
            tensor<fp16, [256, 352]> mul_623 = mul(x = mul_622, y = mul_622)[name = string("mul_623")];
            tensor<int32, [1]> reduce_mean_134_axes_0 = const()[name = string("reduce_mean_134_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_134_keep_dims_0 = const()[name = string("reduce_mean_134_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_134 = reduce_mean(axes = reduce_mean_134_axes_0, keep_dims = reduce_mean_134_keep_dims_0, x = mul_623)[name = string("reduce_mean_134")];
            fp32 rsqrt_134_epsilon_0 = const()[name = string("rsqrt_134_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_134 = rsqrt(epsilon = rsqrt_134_epsilon_0, x = reduce_mean_134)[name = string("rsqrt_134")];
            tensor<fp16, [256, 352]> mul_624 = mul(x = mul_622, y = rsqrt_134)[name = string("mul_624")];
            tensor<fp16, [352]> mul_625_y_0 = const()[name = string("mul_625_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6552576)))];
            tensor<fp16, [256, 352]> mul_625 = mul(x = mul_624, y = mul_625_y_0)[name = string("mul_625")];
            tensor<fp16, [960, 352]> tern_12_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6553344))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_12_w1_weight_0_palettized")];
            tensor<fp16, [256, 960]> tern_12_w1 = linear(bias = linear_4_bias_0, weight = tern_12_w1_weight_0_palettized, x = mul_625)[name = string("tern_12_w1")];
            tensor<fp16, [960]> mul_626_y_0 = const()[name = string("mul_626_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6637888)))];
            tensor<fp16, [256, 960]> mul_626 = mul(x = tern_12_w1, y = mul_626_y_0)[name = string("mul_626")];
            tensor<fp16, [352]> mul_629_y_0 = const()[name = string("mul_629_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6639872)))];
            tensor<fp16, [256, 352]> mul_629 = mul(x = mul_624, y = mul_629_y_0)[name = string("mul_629")];
            tensor<fp16, [960, 352]> tern_12_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6640640))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_12_w3_weight_0_palettized")];
            tensor<fp16, [256, 960]> tern_12_w3 = linear(bias = linear_4_bias_0, weight = tern_12_w3_weight_0_palettized, x = mul_629)[name = string("tern_12_w3")];
            tensor<fp16, [960]> mul_630_y_0 = const()[name = string("mul_630_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6725184)))];
            tensor<fp16, [256, 960]> mul_630 = mul(x = tern_12_w3, y = mul_630_y_0)[name = string("mul_630")];
            fp16 mul_631_y_0 = const()[name = string("mul_631_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [256, 960]> mul_631 = mul(x = mul_626, y = mul_631_y_0)[name = string("mul_631")];
            tensor<fp16, [256, 960]> tanh_12 = tanh(x = mul_631)[name = string("tanh_12")];
            fp16 mul_632_x_0 = const()[name = string("mul_632_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [256, 960]> mul_632 = mul(x = mul_632_x_0, y = tanh_12)[name = string("mul_632")];
            fp16 add_76_x_0 = const()[name = string("add_76_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [256, 960]> add_76 = add(x = add_76_x_0, y = mul_632)[name = string("add_76")];
            tensor<fp16, [256, 960]> mul_633 = mul(x = mul_626, y = add_76)[name = string("mul_633")];
            tensor<fp16, [256, 960]> mul_634 = mul(x = mul_633, y = mul_630)[name = string("mul_634")];
            tensor<fp16, [256, 960]> mul_635 = mul(x = mul_634, y = mul_634)[name = string("mul_635")];
            tensor<int32, [1]> reduce_mean_136_axes_0 = const()[name = string("reduce_mean_136_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_136_keep_dims_0 = const()[name = string("reduce_mean_136_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_136 = reduce_mean(axes = reduce_mean_136_axes_0, keep_dims = reduce_mean_136_keep_dims_0, x = mul_635)[name = string("reduce_mean_136")];
            fp32 rsqrt_136_epsilon_0 = const()[name = string("rsqrt_136_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_136 = rsqrt(epsilon = rsqrt_136_epsilon_0, x = reduce_mean_136)[name = string("rsqrt_136")];
            tensor<fp16, [256, 960]> mul_636 = mul(x = mul_634, y = rsqrt_136)[name = string("mul_636")];
            tensor<fp16, [960]> mul_637_y_0 = const()[name = string("mul_637_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6727168)))];
            tensor<fp16, [256, 960]> mul_637 = mul(x = mul_636, y = mul_637_y_0)[name = string("mul_637")];
            tensor<fp16, [352, 960]> tern_12_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6729152))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_12_w2_weight_0_palettized")];
            tensor<fp16, [256, 352]> tern_12_w2 = linear(bias = linear_0_bias_0, weight = tern_12_w2_weight_0_palettized, x = mul_637)[name = string("tern_12_w2")];
            tensor<fp16, [352]> mul_638_y_0 = const()[name = string("mul_638_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6813696)))];
            tensor<fp16, [256, 352]> mul_638 = mul(x = tern_12_w2, y = mul_638_y_0)[name = string("mul_638")];
            tensor<fp16, [256, 352]> add_77 = add(x = add_75, y = mul_638)[name = string("add_77")];
            tensor<fp16, [256, 352]> mul_639 = mul(x = add_77, y = add_77)[name = string("mul_639")];
            tensor<int32, [1]> reduce_mean_137_axes_0 = const()[name = string("reduce_mean_137_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_137_keep_dims_0 = const()[name = string("reduce_mean_137_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_137 = reduce_mean(axes = reduce_mean_137_axes_0, keep_dims = reduce_mean_137_keep_dims_0, x = mul_639)[name = string("reduce_mean_137")];
            fp32 rsqrt_137_epsilon_0 = const()[name = string("rsqrt_137_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_137 = rsqrt(epsilon = rsqrt_137_epsilon_0, x = reduce_mean_137)[name = string("rsqrt_137")];
            tensor<fp16, [256, 352]> mul_640 = mul(x = add_77, y = rsqrt_137)[name = string("mul_640")];
            tensor<fp16, [352]> mul_641_y_0 = const()[name = string("mul_641_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6814464)))];
            tensor<fp16, [256, 352]> mul_641 = mul(x = mul_640, y = mul_641_y_0)[name = string("mul_641")];
            tensor<fp16, [256, 352]> mul_642 = mul(x = mul_641, y = mul_641)[name = string("mul_642")];
            tensor<int32, [1]> reduce_mean_138_axes_0 = const()[name = string("reduce_mean_138_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_138_keep_dims_0 = const()[name = string("reduce_mean_138_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_138 = reduce_mean(axes = reduce_mean_138_axes_0, keep_dims = reduce_mean_138_keep_dims_0, x = mul_642)[name = string("reduce_mean_138")];
            fp32 rsqrt_138_epsilon_0 = const()[name = string("rsqrt_138_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_138 = rsqrt(epsilon = rsqrt_138_epsilon_0, x = reduce_mean_138)[name = string("rsqrt_138")];
            tensor<fp16, [256, 352]> mul_643 = mul(x = mul_641, y = rsqrt_138)[name = string("mul_643")];
            tensor<fp16, [352]> mul_644_y_0 = const()[name = string("mul_644_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6815232)))];
            tensor<fp16, [256, 352]> mul_644 = mul(x = mul_643, y = mul_644_y_0)[name = string("mul_644")];
            tensor<fp16, [352, 352]> tern_13_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6816000))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_13_q_weight_0_palettized")];
            tensor<fp16, [256, 352]> tern_13_q = linear(bias = linear_0_bias_0, weight = tern_13_q_weight_0_palettized, x = mul_644)[name = string("tern_13_q")];
            tensor<fp16, [352]> mul_645_y_0 = const()[name = string("mul_645_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6847040)))];
            tensor<fp16, [256, 352]> mul_645 = mul(x = tern_13_q, y = mul_645_y_0)[name = string("mul_645")];
            tensor<int32, [3]> reshape_106_shape_0 = const()[name = string("reshape_106_shape_0"), val = tensor<int32, [3]>([256, 8, 44])];
            tensor<fp16, [256, 8, 44]> reshape_106 = reshape(shape = reshape_106_shape_0, x = mul_645)[name = string("reshape_106")];
            tensor<int32, [3]> transpose_52_perm_0 = const()[name = string("transpose_52_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_648_y_0 = const()[name = string("mul_648_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6847808)))];
            tensor<fp16, [256, 352]> mul_648 = mul(x = mul_643, y = mul_648_y_0)[name = string("mul_648")];
            tensor<fp16, [88, 352]> tern_13_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6848576))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_13_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_13_k_bias_0 = const()[name = string("tern_13_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [256, 88]> tern_13_k = linear(bias = tern_13_k_bias_0, weight = tern_13_k_weight_0_palettized, x = mul_648)[name = string("tern_13_k")];
            tensor<fp16, [88]> mul_649_y_0 = const()[name = string("mul_649_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6856384)))];
            tensor<fp16, [256, 88]> mul_649 = mul(x = tern_13_k, y = mul_649_y_0)[name = string("mul_649")];
            tensor<int32, [3]> reshape_107_shape_0 = const()[name = string("reshape_107_shape_0"), val = tensor<int32, [3]>([256, 2, 44])];
            tensor<fp16, [256, 2, 44]> reshape_107 = reshape(shape = reshape_107_shape_0, x = mul_649)[name = string("reshape_107")];
            tensor<int32, [3]> transpose_53_perm_0 = const()[name = string("transpose_53_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_652_y_0 = const()[name = string("mul_652_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6856640)))];
            tensor<fp16, [256, 352]> mul_652 = mul(x = mul_643, y = mul_652_y_0)[name = string("mul_652")];
            tensor<fp16, [88, 352]> tern_13_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6857408))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_13_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_13_v_bias_0 = const()[name = string("tern_13_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [256, 88]> tern_13_v = linear(bias = tern_13_v_bias_0, weight = tern_13_v_weight_0_palettized, x = mul_652)[name = string("tern_13_v")];
            tensor<fp16, [88]> mul_653_y_0 = const()[name = string("mul_653_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6865216)))];
            tensor<fp16, [256, 88]> mul_653 = mul(x = tern_13_v, y = mul_653_y_0)[name = string("mul_653")];
            tensor<int32, [3]> reshape_108_shape_0 = const()[name = string("reshape_108_shape_0"), val = tensor<int32, [3]>([256, 2, 44])];
            tensor<fp16, [256, 2, 44]> reshape_108 = reshape(shape = reshape_108_shape_0, x = mul_653)[name = string("reshape_108")];
            tensor<int32, [3]> transpose_54_perm_0 = const()[name = string("transpose_54_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 256, 44]> transpose_52 = transpose(perm = transpose_52_perm_0, x = reshape_106)[name = string("transpose_11")];
            tensor<fp16, [8, 256, 44]> mul_654 = mul(x = transpose_52, y = transpose_52)[name = string("mul_654")];
            tensor<int32, [1]> reduce_mean_141_axes_0 = const()[name = string("reduce_mean_141_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_141_keep_dims_0 = const()[name = string("reduce_mean_141_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 256, 1]> reduce_mean_141 = reduce_mean(axes = reduce_mean_141_axes_0, keep_dims = reduce_mean_141_keep_dims_0, x = mul_654)[name = string("reduce_mean_141")];
            fp32 rsqrt_141_epsilon_0 = const()[name = string("rsqrt_141_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 256, 1]> rsqrt_141 = rsqrt(epsilon = rsqrt_141_epsilon_0, x = reduce_mean_141)[name = string("rsqrt_141")];
            tensor<fp16, [8, 256, 44]> mul_655 = mul(x = transpose_52, y = rsqrt_141)[name = string("mul_655")];
            tensor<fp16, [44]> mul_656_y_0 = const()[name = string("mul_656_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6865472)))];
            tensor<fp16, [8, 256, 44]> mul_656 = mul(x = mul_655, y = mul_656_y_0)[name = string("mul_656")];
            tensor<int32, [3]> slice_by_index_52_begin_0 = const()[name = string("slice_by_index_52_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_52_end_0 = const()[name = string("slice_by_index_52_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_52_end_mask_0 = const()[name = string("slice_by_index_52_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 256, 22]> slice_by_index_52 = slice_by_index(begin = slice_by_index_52_begin_0, end = slice_by_index_52_end_0, end_mask = slice_by_index_52_end_mask_0, x = mul_656)[name = string("slice_by_index_52")];
            tensor<int32, [3]> slice_by_index_53_begin_0 = const()[name = string("slice_by_index_53_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_53_end_0 = const()[name = string("slice_by_index_53_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_53_end_mask_0 = const()[name = string("slice_by_index_53_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 256, 22]> slice_by_index_53 = slice_by_index(begin = slice_by_index_53_begin_0, end = slice_by_index_53_end_0, end_mask = slice_by_index_53_end_mask_0, x = mul_656)[name = string("slice_by_index_53")];
            int32 concat_26_axis_0 = const()[name = string("concat_26_axis_0"), val = int32(-1)];
            bool concat_26_interleave_0 = const()[name = string("concat_26_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 256, 44]> concat_26 = concat(axis = concat_26_axis_0, interleave = concat_26_interleave_0, values = (slice_by_index_53, slice_by_index_52))[name = string("concat_26")];
            tensor<fp16, [44]> mul_657_y_0 = const()[name = string("mul_657_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 256, 44]> mul_657 = mul(x = concat_26, y = mul_657_y_0)[name = string("mul_657")];
            tensor<fp16, [8, 256, 44]> mul_658 = mul(x = mul_656, y = mul_11_y_0)[name = string("mul_658")];
            tensor<fp16, [8, 256, 44]> mul_659 = mul(x = mul_657, y = mul_12_y_0)[name = string("mul_659")];
            tensor<fp16, [8, 256, 44]> add_78 = add(x = mul_658, y = mul_659)[name = string("add_78")];
            tensor<fp16, [2, 256, 44]> transpose_53 = transpose(perm = transpose_53_perm_0, x = reshape_107)[name = string("transpose_10")];
            tensor<fp16, [2, 256, 44]> mul_660 = mul(x = transpose_53, y = transpose_53)[name = string("mul_660")];
            tensor<int32, [1]> reduce_mean_142_axes_0 = const()[name = string("reduce_mean_142_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_142_keep_dims_0 = const()[name = string("reduce_mean_142_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 256, 1]> reduce_mean_142 = reduce_mean(axes = reduce_mean_142_axes_0, keep_dims = reduce_mean_142_keep_dims_0, x = mul_660)[name = string("reduce_mean_142")];
            fp32 rsqrt_142_epsilon_0 = const()[name = string("rsqrt_142_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 256, 1]> rsqrt_142 = rsqrt(epsilon = rsqrt_142_epsilon_0, x = reduce_mean_142)[name = string("rsqrt_142")];
            tensor<fp16, [2, 256, 44]> mul_661 = mul(x = transpose_53, y = rsqrt_142)[name = string("mul_661")];
            tensor<fp16, [44]> mul_662_y_0 = const()[name = string("mul_662_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6865664)))];
            tensor<fp16, [2, 256, 44]> mul_662 = mul(x = mul_661, y = mul_662_y_0)[name = string("mul_662")];
            tensor<int32, [3]> slice_by_index_54_begin_0 = const()[name = string("slice_by_index_54_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_54_end_0 = const()[name = string("slice_by_index_54_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_54_end_mask_0 = const()[name = string("slice_by_index_54_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 256, 22]> slice_by_index_54 = slice_by_index(begin = slice_by_index_54_begin_0, end = slice_by_index_54_end_0, end_mask = slice_by_index_54_end_mask_0, x = mul_662)[name = string("slice_by_index_54")];
            tensor<int32, [3]> slice_by_index_55_begin_0 = const()[name = string("slice_by_index_55_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_55_end_0 = const()[name = string("slice_by_index_55_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_55_end_mask_0 = const()[name = string("slice_by_index_55_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 256, 22]> slice_by_index_55 = slice_by_index(begin = slice_by_index_55_begin_0, end = slice_by_index_55_end_0, end_mask = slice_by_index_55_end_mask_0, x = mul_662)[name = string("slice_by_index_55")];
            int32 concat_27_axis_0 = const()[name = string("concat_27_axis_0"), val = int32(-1)];
            bool concat_27_interleave_0 = const()[name = string("concat_27_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 256, 44]> concat_27 = concat(axis = concat_27_axis_0, interleave = concat_27_interleave_0, values = (slice_by_index_55, slice_by_index_54))[name = string("concat_27")];
            tensor<fp16, [44]> mul_663_y_0 = const()[name = string("mul_663_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 256, 44]> mul_663 = mul(x = concat_27, y = mul_663_y_0)[name = string("mul_663")];
            tensor<fp16, [2, 256, 44]> mul_664 = mul(x = mul_662, y = mul_11_y_0)[name = string("mul_664")];
            tensor<fp16, [2, 256, 44]> mul_665 = mul(x = mul_663, y = mul_12_y_0)[name = string("mul_665")];
            tensor<fp16, [2, 256, 44]> add_79 = add(x = mul_664, y = mul_665)[name = string("add_79")];
            tensor<int32, [4]> reshape_109_shape_0 = const()[name = string("reshape_109_shape_0"), val = tensor<int32, [4]>([2, 1, 256, 44])];
            tensor<fp16, [2, 1, 256, 44]> reshape_109 = reshape(shape = reshape_109_shape_0, x = add_79)[name = string("reshape_109")];
            tensor<int32, [4]> tile_26_reps_0 = const()[name = string("tile_26_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 256, 44]> tile_26 = tile(reps = tile_26_reps_0, x = reshape_109)[name = string("tile_26")];
            tensor<int32, [3]> reshape_110_shape_0 = const()[name = string("reshape_110_shape_0"), val = tensor<int32, [3]>([8, 256, 44])];
            tensor<fp16, [8, 256, 44]> reshape_110 = reshape(shape = reshape_110_shape_0, x = tile_26)[name = string("reshape_110")];
            tensor<int32, [4]> reshape_111_shape_0 = const()[name = string("reshape_111_shape_0"), val = tensor<int32, [4]>([2, 1, 256, 44])];
            tensor<fp16, [2, 256, 44]> transpose_54 = transpose(perm = transpose_54_perm_0, x = reshape_108)[name = string("transpose_9")];
            tensor<fp16, [2, 1, 256, 44]> reshape_111 = reshape(shape = reshape_111_shape_0, x = transpose_54)[name = string("reshape_111")];
            tensor<int32, [4]> tile_27_reps_0 = const()[name = string("tile_27_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 256, 44]> tile_27 = tile(reps = tile_27_reps_0, x = reshape_111)[name = string("tile_27")];
            tensor<int32, [3]> reshape_112_shape_0 = const()[name = string("reshape_112_shape_0"), val = tensor<int32, [3]>([8, 256, 44])];
            tensor<fp16, [8, 256, 44]> reshape_112 = reshape(shape = reshape_112_shape_0, x = tile_27)[name = string("reshape_112")];
            fp16 mul_666_y_0 = const()[name = string("mul_666_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 256, 44]> mul_666 = mul(x = add_78, y = mul_666_y_0)[name = string("mul_666")];
            bool matmul_26_transpose_y_0 = const()[name = string("matmul_26_transpose_y_0"), val = bool(true)];
            bool matmul_26_transpose_x_0 = const()[name = string("matmul_26_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 256, 256]> matmul_26 = matmul(transpose_x = matmul_26_transpose_x_0, transpose_y = matmul_26_transpose_y_0, x = mul_666, y = reshape_110)[name = string("matmul_26")];
            tensor<fp16, [8, 256, 256]> add_80 = add(x = matmul_26, y = reshape_1)[name = string("add_80")];
            int32 softmax_13_axis_0 = const()[name = string("softmax_13_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 256, 256]> softmax_13 = softmax(axis = softmax_13_axis_0, x = add_80)[name = string("softmax_13")];
            bool matmul_27_transpose_x_0 = const()[name = string("matmul_27_transpose_x_0"), val = bool(false)];
            bool matmul_27_transpose_y_0 = const()[name = string("matmul_27_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 256, 44]> matmul_27 = matmul(transpose_x = matmul_27_transpose_x_0, transpose_y = matmul_27_transpose_y_0, x = softmax_13, y = reshape_112)[name = string("matmul_27")];
            tensor<int32, [3]> transpose_55_perm_0 = const()[name = string("transpose_55_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_113_shape_0 = const()[name = string("reshape_113_shape_0"), val = tensor<int32, [2]>([256, 352])];
            tensor<fp16, [256, 8, 44]> transpose_55 = transpose(perm = transpose_55_perm_0, x = matmul_27)[name = string("transpose_8")];
            tensor<fp16, [256, 352]> reshape_113 = reshape(shape = reshape_113_shape_0, x = transpose_55)[name = string("reshape_113")];
            tensor<fp16, [256, 352]> mul_667 = mul(x = reshape_113, y = reshape_113)[name = string("mul_667")];
            tensor<int32, [1]> reduce_mean_143_axes_0 = const()[name = string("reduce_mean_143_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_143_keep_dims_0 = const()[name = string("reduce_mean_143_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_143 = reduce_mean(axes = reduce_mean_143_axes_0, keep_dims = reduce_mean_143_keep_dims_0, x = mul_667)[name = string("reduce_mean_143")];
            fp32 rsqrt_143_epsilon_0 = const()[name = string("rsqrt_143_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_143 = rsqrt(epsilon = rsqrt_143_epsilon_0, x = reduce_mean_143)[name = string("rsqrt_143")];
            tensor<fp16, [256, 352]> mul_668 = mul(x = reshape_113, y = rsqrt_143)[name = string("mul_668")];
            tensor<fp16, [352]> mul_669_y_0 = const()[name = string("mul_669_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6865856)))];
            tensor<fp16, [256, 352]> mul_669 = mul(x = mul_668, y = mul_669_y_0)[name = string("mul_669")];
            tensor<fp16, [352, 352]> tern_13_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6866624))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_13_o_weight_0_palettized")];
            tensor<fp16, [256, 352]> tern_13_o = linear(bias = linear_0_bias_0, weight = tern_13_o_weight_0_palettized, x = mul_669)[name = string("tern_13_o")];
            tensor<fp16, [352]> mul_670_y_0 = const()[name = string("mul_670_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6897664)))];
            tensor<fp16, [256, 352]> mul_670 = mul(x = tern_13_o, y = mul_670_y_0)[name = string("mul_670")];
            tensor<fp16, [256, 352]> add_81 = add(x = add_77, y = mul_670)[name = string("add_81")];
            tensor<fp16, [256, 352]> mul_671 = mul(x = add_81, y = add_81)[name = string("mul_671")];
            tensor<int32, [1]> reduce_mean_144_axes_0 = const()[name = string("reduce_mean_144_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_144_keep_dims_0 = const()[name = string("reduce_mean_144_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_144 = reduce_mean(axes = reduce_mean_144_axes_0, keep_dims = reduce_mean_144_keep_dims_0, x = mul_671)[name = string("reduce_mean_144")];
            fp32 rsqrt_144_epsilon_0 = const()[name = string("rsqrt_144_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_144 = rsqrt(epsilon = rsqrt_144_epsilon_0, x = reduce_mean_144)[name = string("rsqrt_144")];
            tensor<fp16, [256, 352]> mul_672 = mul(x = add_81, y = rsqrt_144)[name = string("mul_672")];
            tensor<fp16, [352]> mul_673_y_0 = const()[name = string("mul_673_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6898432)))];
            tensor<fp16, [256, 352]> mul_673 = mul(x = mul_672, y = mul_673_y_0)[name = string("mul_673")];
            tensor<fp16, [256, 352]> mul_674 = mul(x = mul_673, y = mul_673)[name = string("mul_674")];
            tensor<int32, [1]> reduce_mean_145_axes_0 = const()[name = string("reduce_mean_145_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_145_keep_dims_0 = const()[name = string("reduce_mean_145_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_145 = reduce_mean(axes = reduce_mean_145_axes_0, keep_dims = reduce_mean_145_keep_dims_0, x = mul_674)[name = string("reduce_mean_145")];
            fp32 rsqrt_145_epsilon_0 = const()[name = string("rsqrt_145_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_145 = rsqrt(epsilon = rsqrt_145_epsilon_0, x = reduce_mean_145)[name = string("rsqrt_145")];
            tensor<fp16, [256, 352]> mul_675 = mul(x = mul_673, y = rsqrt_145)[name = string("mul_675")];
            tensor<fp16, [352]> mul_676_y_0 = const()[name = string("mul_676_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6899200)))];
            tensor<fp16, [256, 352]> mul_676 = mul(x = mul_675, y = mul_676_y_0)[name = string("mul_676")];
            tensor<fp16, [960, 352]> tern_13_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6899968))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_13_w1_weight_0_palettized")];
            tensor<fp16, [256, 960]> tern_13_w1 = linear(bias = linear_4_bias_0, weight = tern_13_w1_weight_0_palettized, x = mul_676)[name = string("tern_13_w1")];
            tensor<fp16, [960]> mul_677_y_0 = const()[name = string("mul_677_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6984512)))];
            tensor<fp16, [256, 960]> mul_677 = mul(x = tern_13_w1, y = mul_677_y_0)[name = string("mul_677")];
            tensor<fp16, [352]> mul_680_y_0 = const()[name = string("mul_680_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6986496)))];
            tensor<fp16, [256, 352]> mul_680 = mul(x = mul_675, y = mul_680_y_0)[name = string("mul_680")];
            tensor<fp16, [960, 352]> tern_13_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6987264))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_13_w3_weight_0_palettized")];
            tensor<fp16, [256, 960]> tern_13_w3 = linear(bias = linear_4_bias_0, weight = tern_13_w3_weight_0_palettized, x = mul_680)[name = string("tern_13_w3")];
            tensor<fp16, [960]> mul_681_y_0 = const()[name = string("mul_681_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7071808)))];
            tensor<fp16, [256, 960]> mul_681 = mul(x = tern_13_w3, y = mul_681_y_0)[name = string("mul_681")];
            fp16 mul_682_y_0 = const()[name = string("mul_682_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [256, 960]> mul_682 = mul(x = mul_677, y = mul_682_y_0)[name = string("mul_682")];
            tensor<fp16, [256, 960]> tanh_13 = tanh(x = mul_682)[name = string("tanh_13")];
            fp16 mul_683_x_0 = const()[name = string("mul_683_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [256, 960]> mul_683 = mul(x = mul_683_x_0, y = tanh_13)[name = string("mul_683")];
            fp16 add_82_x_0 = const()[name = string("add_82_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [256, 960]> add_82 = add(x = add_82_x_0, y = mul_683)[name = string("add_82")];
            tensor<fp16, [256, 960]> mul_684 = mul(x = mul_677, y = add_82)[name = string("mul_684")];
            tensor<fp16, [256, 960]> mul_685 = mul(x = mul_684, y = mul_681)[name = string("mul_685")];
            tensor<fp16, [256, 960]> mul_686 = mul(x = mul_685, y = mul_685)[name = string("mul_686")];
            tensor<int32, [1]> reduce_mean_147_axes_0 = const()[name = string("reduce_mean_147_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_147_keep_dims_0 = const()[name = string("reduce_mean_147_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_147 = reduce_mean(axes = reduce_mean_147_axes_0, keep_dims = reduce_mean_147_keep_dims_0, x = mul_686)[name = string("reduce_mean_147")];
            fp32 rsqrt_147_epsilon_0 = const()[name = string("rsqrt_147_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_147 = rsqrt(epsilon = rsqrt_147_epsilon_0, x = reduce_mean_147)[name = string("rsqrt_147")];
            tensor<fp16, [256, 960]> mul_687 = mul(x = mul_685, y = rsqrt_147)[name = string("mul_687")];
            tensor<fp16, [960]> mul_688_y_0 = const()[name = string("mul_688_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7073792)))];
            tensor<fp16, [256, 960]> mul_688 = mul(x = mul_687, y = mul_688_y_0)[name = string("mul_688")];
            tensor<fp16, [352, 960]> tern_13_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7075776))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_13_w2_weight_0_palettized")];
            tensor<fp16, [256, 352]> tern_13_w2 = linear(bias = linear_0_bias_0, weight = tern_13_w2_weight_0_palettized, x = mul_688)[name = string("tern_13_w2")];
            tensor<fp16, [352]> mul_689_y_0 = const()[name = string("mul_689_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7160320)))];
            tensor<fp16, [256, 352]> mul_689 = mul(x = tern_13_w2, y = mul_689_y_0)[name = string("mul_689")];
            tensor<fp16, [256, 352]> add_83 = add(x = add_81, y = mul_689)[name = string("add_83")];
            tensor<fp16, [256, 352]> mul_690 = mul(x = add_83, y = add_83)[name = string("mul_690")];
            tensor<int32, [1]> reduce_mean_148_axes_0 = const()[name = string("reduce_mean_148_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_148_keep_dims_0 = const()[name = string("reduce_mean_148_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_148 = reduce_mean(axes = reduce_mean_148_axes_0, keep_dims = reduce_mean_148_keep_dims_0, x = mul_690)[name = string("reduce_mean_148")];
            fp32 rsqrt_148_epsilon_0 = const()[name = string("rsqrt_148_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_148 = rsqrt(epsilon = rsqrt_148_epsilon_0, x = reduce_mean_148)[name = string("rsqrt_148")];
            tensor<fp16, [256, 352]> mul_691 = mul(x = add_83, y = rsqrt_148)[name = string("mul_691")];
            tensor<fp16, [352]> mul_692_y_0 = const()[name = string("mul_692_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7161088)))];
            tensor<fp16, [256, 352]> mul_692 = mul(x = mul_691, y = mul_692_y_0)[name = string("mul_692")];
            tensor<fp16, [256, 352]> mul_693 = mul(x = mul_692, y = mul_692)[name = string("mul_693")];
            tensor<int32, [1]> reduce_mean_149_axes_0 = const()[name = string("reduce_mean_149_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_149_keep_dims_0 = const()[name = string("reduce_mean_149_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_149 = reduce_mean(axes = reduce_mean_149_axes_0, keep_dims = reduce_mean_149_keep_dims_0, x = mul_693)[name = string("reduce_mean_149")];
            fp32 rsqrt_149_epsilon_0 = const()[name = string("rsqrt_149_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_149 = rsqrt(epsilon = rsqrt_149_epsilon_0, x = reduce_mean_149)[name = string("rsqrt_149")];
            tensor<fp16, [256, 352]> mul_694 = mul(x = mul_692, y = rsqrt_149)[name = string("mul_694")];
            tensor<fp16, [352]> mul_695_y_0 = const()[name = string("mul_695_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7161856)))];
            tensor<fp16, [256, 352]> mul_695 = mul(x = mul_694, y = mul_695_y_0)[name = string("mul_695")];
            tensor<fp16, [352, 352]> tern_14_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7162624))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_14_q_weight_0_palettized")];
            tensor<fp16, [256, 352]> tern_14_q = linear(bias = linear_0_bias_0, weight = tern_14_q_weight_0_palettized, x = mul_695)[name = string("tern_14_q")];
            tensor<fp16, [352]> mul_696_y_0 = const()[name = string("mul_696_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7193664)))];
            tensor<fp16, [256, 352]> mul_696 = mul(x = tern_14_q, y = mul_696_y_0)[name = string("mul_696")];
            tensor<int32, [3]> reshape_114_shape_0 = const()[name = string("reshape_114_shape_0"), val = tensor<int32, [3]>([256, 8, 44])];
            tensor<fp16, [256, 8, 44]> reshape_114 = reshape(shape = reshape_114_shape_0, x = mul_696)[name = string("reshape_114")];
            tensor<int32, [3]> transpose_56_perm_0 = const()[name = string("transpose_56_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_699_y_0 = const()[name = string("mul_699_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7194432)))];
            tensor<fp16, [256, 352]> mul_699 = mul(x = mul_694, y = mul_699_y_0)[name = string("mul_699")];
            tensor<fp16, [88, 352]> tern_14_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7195200))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_14_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_14_k_bias_0 = const()[name = string("tern_14_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [256, 88]> tern_14_k = linear(bias = tern_14_k_bias_0, weight = tern_14_k_weight_0_palettized, x = mul_699)[name = string("tern_14_k")];
            tensor<fp16, [88]> mul_700_y_0 = const()[name = string("mul_700_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7203008)))];
            tensor<fp16, [256, 88]> mul_700 = mul(x = tern_14_k, y = mul_700_y_0)[name = string("mul_700")];
            tensor<int32, [3]> reshape_115_shape_0 = const()[name = string("reshape_115_shape_0"), val = tensor<int32, [3]>([256, 2, 44])];
            tensor<fp16, [256, 2, 44]> reshape_115 = reshape(shape = reshape_115_shape_0, x = mul_700)[name = string("reshape_115")];
            tensor<int32, [3]> transpose_57_perm_0 = const()[name = string("transpose_57_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_703_y_0 = const()[name = string("mul_703_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7203264)))];
            tensor<fp16, [256, 352]> mul_703 = mul(x = mul_694, y = mul_703_y_0)[name = string("mul_703")];
            tensor<fp16, [88, 352]> tern_14_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7204032))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_14_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_14_v_bias_0 = const()[name = string("tern_14_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [256, 88]> tern_14_v = linear(bias = tern_14_v_bias_0, weight = tern_14_v_weight_0_palettized, x = mul_703)[name = string("tern_14_v")];
            tensor<fp16, [88]> mul_704_y_0 = const()[name = string("mul_704_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7211840)))];
            tensor<fp16, [256, 88]> mul_704 = mul(x = tern_14_v, y = mul_704_y_0)[name = string("mul_704")];
            tensor<int32, [3]> reshape_116_shape_0 = const()[name = string("reshape_116_shape_0"), val = tensor<int32, [3]>([256, 2, 44])];
            tensor<fp16, [256, 2, 44]> reshape_116 = reshape(shape = reshape_116_shape_0, x = mul_704)[name = string("reshape_116")];
            tensor<int32, [3]> transpose_58_perm_0 = const()[name = string("transpose_58_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 256, 44]> transpose_56 = transpose(perm = transpose_56_perm_0, x = reshape_114)[name = string("transpose_7")];
            tensor<fp16, [8, 256, 44]> mul_705 = mul(x = transpose_56, y = transpose_56)[name = string("mul_705")];
            tensor<int32, [1]> reduce_mean_152_axes_0 = const()[name = string("reduce_mean_152_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_152_keep_dims_0 = const()[name = string("reduce_mean_152_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 256, 1]> reduce_mean_152 = reduce_mean(axes = reduce_mean_152_axes_0, keep_dims = reduce_mean_152_keep_dims_0, x = mul_705)[name = string("reduce_mean_152")];
            fp32 rsqrt_152_epsilon_0 = const()[name = string("rsqrt_152_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 256, 1]> rsqrt_152 = rsqrt(epsilon = rsqrt_152_epsilon_0, x = reduce_mean_152)[name = string("rsqrt_152")];
            tensor<fp16, [8, 256, 44]> mul_706 = mul(x = transpose_56, y = rsqrt_152)[name = string("mul_706")];
            tensor<fp16, [44]> mul_707_y_0 = const()[name = string("mul_707_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7212096)))];
            tensor<fp16, [8, 256, 44]> mul_707 = mul(x = mul_706, y = mul_707_y_0)[name = string("mul_707")];
            tensor<int32, [3]> slice_by_index_56_begin_0 = const()[name = string("slice_by_index_56_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_56_end_0 = const()[name = string("slice_by_index_56_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_56_end_mask_0 = const()[name = string("slice_by_index_56_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 256, 22]> slice_by_index_56 = slice_by_index(begin = slice_by_index_56_begin_0, end = slice_by_index_56_end_0, end_mask = slice_by_index_56_end_mask_0, x = mul_707)[name = string("slice_by_index_56")];
            tensor<int32, [3]> slice_by_index_57_begin_0 = const()[name = string("slice_by_index_57_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_57_end_0 = const()[name = string("slice_by_index_57_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_57_end_mask_0 = const()[name = string("slice_by_index_57_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 256, 22]> slice_by_index_57 = slice_by_index(begin = slice_by_index_57_begin_0, end = slice_by_index_57_end_0, end_mask = slice_by_index_57_end_mask_0, x = mul_707)[name = string("slice_by_index_57")];
            int32 concat_28_axis_0 = const()[name = string("concat_28_axis_0"), val = int32(-1)];
            bool concat_28_interleave_0 = const()[name = string("concat_28_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 256, 44]> concat_28 = concat(axis = concat_28_axis_0, interleave = concat_28_interleave_0, values = (slice_by_index_57, slice_by_index_56))[name = string("concat_28")];
            tensor<fp16, [44]> mul_708_y_0 = const()[name = string("mul_708_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 256, 44]> mul_708 = mul(x = concat_28, y = mul_708_y_0)[name = string("mul_708")];
            tensor<fp16, [8, 256, 44]> mul_709 = mul(x = mul_707, y = mul_11_y_0)[name = string("mul_709")];
            tensor<fp16, [8, 256, 44]> mul_710 = mul(x = mul_708, y = mul_12_y_0)[name = string("mul_710")];
            tensor<fp16, [8, 256, 44]> add_84 = add(x = mul_709, y = mul_710)[name = string("add_84")];
            tensor<fp16, [2, 256, 44]> transpose_57 = transpose(perm = transpose_57_perm_0, x = reshape_115)[name = string("transpose_6")];
            tensor<fp16, [2, 256, 44]> mul_711 = mul(x = transpose_57, y = transpose_57)[name = string("mul_711")];
            tensor<int32, [1]> reduce_mean_153_axes_0 = const()[name = string("reduce_mean_153_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_153_keep_dims_0 = const()[name = string("reduce_mean_153_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 256, 1]> reduce_mean_153 = reduce_mean(axes = reduce_mean_153_axes_0, keep_dims = reduce_mean_153_keep_dims_0, x = mul_711)[name = string("reduce_mean_153")];
            fp32 rsqrt_153_epsilon_0 = const()[name = string("rsqrt_153_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 256, 1]> rsqrt_153 = rsqrt(epsilon = rsqrt_153_epsilon_0, x = reduce_mean_153)[name = string("rsqrt_153")];
            tensor<fp16, [2, 256, 44]> mul_712 = mul(x = transpose_57, y = rsqrt_153)[name = string("mul_712")];
            tensor<fp16, [44]> mul_713_y_0 = const()[name = string("mul_713_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7212288)))];
            tensor<fp16, [2, 256, 44]> mul_713 = mul(x = mul_712, y = mul_713_y_0)[name = string("mul_713")];
            tensor<int32, [3]> slice_by_index_58_begin_0 = const()[name = string("slice_by_index_58_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_58_end_0 = const()[name = string("slice_by_index_58_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_58_end_mask_0 = const()[name = string("slice_by_index_58_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 256, 22]> slice_by_index_58 = slice_by_index(begin = slice_by_index_58_begin_0, end = slice_by_index_58_end_0, end_mask = slice_by_index_58_end_mask_0, x = mul_713)[name = string("slice_by_index_58")];
            tensor<int32, [3]> slice_by_index_59_begin_0 = const()[name = string("slice_by_index_59_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_59_end_0 = const()[name = string("slice_by_index_59_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_59_end_mask_0 = const()[name = string("slice_by_index_59_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 256, 22]> slice_by_index_59 = slice_by_index(begin = slice_by_index_59_begin_0, end = slice_by_index_59_end_0, end_mask = slice_by_index_59_end_mask_0, x = mul_713)[name = string("slice_by_index_59")];
            int32 concat_29_axis_0 = const()[name = string("concat_29_axis_0"), val = int32(-1)];
            bool concat_29_interleave_0 = const()[name = string("concat_29_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 256, 44]> concat_29 = concat(axis = concat_29_axis_0, interleave = concat_29_interleave_0, values = (slice_by_index_59, slice_by_index_58))[name = string("concat_29")];
            tensor<fp16, [44]> mul_714_y_0 = const()[name = string("mul_714_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 256, 44]> mul_714 = mul(x = concat_29, y = mul_714_y_0)[name = string("mul_714")];
            tensor<fp16, [2, 256, 44]> mul_715 = mul(x = mul_713, y = mul_11_y_0)[name = string("mul_715")];
            tensor<fp16, [2, 256, 44]> mul_716 = mul(x = mul_714, y = mul_12_y_0)[name = string("mul_716")];
            tensor<fp16, [2, 256, 44]> add_85 = add(x = mul_715, y = mul_716)[name = string("add_85")];
            tensor<int32, [4]> reshape_117_shape_0 = const()[name = string("reshape_117_shape_0"), val = tensor<int32, [4]>([2, 1, 256, 44])];
            tensor<fp16, [2, 1, 256, 44]> reshape_117 = reshape(shape = reshape_117_shape_0, x = add_85)[name = string("reshape_117")];
            tensor<int32, [4]> tile_28_reps_0 = const()[name = string("tile_28_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 256, 44]> tile_28 = tile(reps = tile_28_reps_0, x = reshape_117)[name = string("tile_28")];
            tensor<int32, [3]> reshape_118_shape_0 = const()[name = string("reshape_118_shape_0"), val = tensor<int32, [3]>([8, 256, 44])];
            tensor<fp16, [8, 256, 44]> reshape_118 = reshape(shape = reshape_118_shape_0, x = tile_28)[name = string("reshape_118")];
            tensor<int32, [4]> reshape_119_shape_0 = const()[name = string("reshape_119_shape_0"), val = tensor<int32, [4]>([2, 1, 256, 44])];
            tensor<fp16, [2, 256, 44]> transpose_58 = transpose(perm = transpose_58_perm_0, x = reshape_116)[name = string("transpose_5")];
            tensor<fp16, [2, 1, 256, 44]> reshape_119 = reshape(shape = reshape_119_shape_0, x = transpose_58)[name = string("reshape_119")];
            tensor<int32, [4]> tile_29_reps_0 = const()[name = string("tile_29_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 256, 44]> tile_29 = tile(reps = tile_29_reps_0, x = reshape_119)[name = string("tile_29")];
            tensor<int32, [3]> reshape_120_shape_0 = const()[name = string("reshape_120_shape_0"), val = tensor<int32, [3]>([8, 256, 44])];
            tensor<fp16, [8, 256, 44]> reshape_120 = reshape(shape = reshape_120_shape_0, x = tile_29)[name = string("reshape_120")];
            fp16 mul_717_y_0 = const()[name = string("mul_717_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 256, 44]> mul_717 = mul(x = add_84, y = mul_717_y_0)[name = string("mul_717")];
            bool matmul_28_transpose_y_0 = const()[name = string("matmul_28_transpose_y_0"), val = bool(true)];
            bool matmul_28_transpose_x_0 = const()[name = string("matmul_28_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 256, 256]> matmul_28 = matmul(transpose_x = matmul_28_transpose_x_0, transpose_y = matmul_28_transpose_y_0, x = mul_717, y = reshape_118)[name = string("matmul_28")];
            tensor<fp16, [8, 256, 256]> add_86 = add(x = matmul_28, y = reshape_1)[name = string("add_86")];
            int32 softmax_14_axis_0 = const()[name = string("softmax_14_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 256, 256]> softmax_14 = softmax(axis = softmax_14_axis_0, x = add_86)[name = string("softmax_14")];
            bool matmul_29_transpose_x_0 = const()[name = string("matmul_29_transpose_x_0"), val = bool(false)];
            bool matmul_29_transpose_y_0 = const()[name = string("matmul_29_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 256, 44]> matmul_29 = matmul(transpose_x = matmul_29_transpose_x_0, transpose_y = matmul_29_transpose_y_0, x = softmax_14, y = reshape_120)[name = string("matmul_29")];
            tensor<int32, [3]> transpose_59_perm_0 = const()[name = string("transpose_59_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_121_shape_0 = const()[name = string("reshape_121_shape_0"), val = tensor<int32, [2]>([256, 352])];
            tensor<fp16, [256, 8, 44]> transpose_59 = transpose(perm = transpose_59_perm_0, x = matmul_29)[name = string("transpose_4")];
            tensor<fp16, [256, 352]> reshape_121 = reshape(shape = reshape_121_shape_0, x = transpose_59)[name = string("reshape_121")];
            tensor<fp16, [256, 352]> mul_718 = mul(x = reshape_121, y = reshape_121)[name = string("mul_718")];
            tensor<int32, [1]> reduce_mean_154_axes_0 = const()[name = string("reduce_mean_154_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_154_keep_dims_0 = const()[name = string("reduce_mean_154_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_154 = reduce_mean(axes = reduce_mean_154_axes_0, keep_dims = reduce_mean_154_keep_dims_0, x = mul_718)[name = string("reduce_mean_154")];
            fp32 rsqrt_154_epsilon_0 = const()[name = string("rsqrt_154_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_154 = rsqrt(epsilon = rsqrt_154_epsilon_0, x = reduce_mean_154)[name = string("rsqrt_154")];
            tensor<fp16, [256, 352]> mul_719 = mul(x = reshape_121, y = rsqrt_154)[name = string("mul_719")];
            tensor<fp16, [352]> mul_720_y_0 = const()[name = string("mul_720_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7212480)))];
            tensor<fp16, [256, 352]> mul_720 = mul(x = mul_719, y = mul_720_y_0)[name = string("mul_720")];
            tensor<fp16, [352, 352]> tern_14_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7213248))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_14_o_weight_0_palettized")];
            tensor<fp16, [256, 352]> tern_14_o = linear(bias = linear_0_bias_0, weight = tern_14_o_weight_0_palettized, x = mul_720)[name = string("tern_14_o")];
            tensor<fp16, [352]> mul_721_y_0 = const()[name = string("mul_721_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7244288)))];
            tensor<fp16, [256, 352]> mul_721 = mul(x = tern_14_o, y = mul_721_y_0)[name = string("mul_721")];
            tensor<fp16, [256, 352]> add_87 = add(x = add_83, y = mul_721)[name = string("add_87")];
            tensor<fp16, [256, 352]> mul_722 = mul(x = add_87, y = add_87)[name = string("mul_722")];
            tensor<int32, [1]> reduce_mean_155_axes_0 = const()[name = string("reduce_mean_155_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_155_keep_dims_0 = const()[name = string("reduce_mean_155_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_155 = reduce_mean(axes = reduce_mean_155_axes_0, keep_dims = reduce_mean_155_keep_dims_0, x = mul_722)[name = string("reduce_mean_155")];
            fp32 rsqrt_155_epsilon_0 = const()[name = string("rsqrt_155_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_155 = rsqrt(epsilon = rsqrt_155_epsilon_0, x = reduce_mean_155)[name = string("rsqrt_155")];
            tensor<fp16, [256, 352]> mul_723 = mul(x = add_87, y = rsqrt_155)[name = string("mul_723")];
            tensor<fp16, [352]> mul_724_y_0 = const()[name = string("mul_724_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7245056)))];
            tensor<fp16, [256, 352]> mul_724 = mul(x = mul_723, y = mul_724_y_0)[name = string("mul_724")];
            tensor<fp16, [256, 352]> mul_725 = mul(x = mul_724, y = mul_724)[name = string("mul_725")];
            tensor<int32, [1]> reduce_mean_156_axes_0 = const()[name = string("reduce_mean_156_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_156_keep_dims_0 = const()[name = string("reduce_mean_156_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_156 = reduce_mean(axes = reduce_mean_156_axes_0, keep_dims = reduce_mean_156_keep_dims_0, x = mul_725)[name = string("reduce_mean_156")];
            fp32 rsqrt_156_epsilon_0 = const()[name = string("rsqrt_156_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_156 = rsqrt(epsilon = rsqrt_156_epsilon_0, x = reduce_mean_156)[name = string("rsqrt_156")];
            tensor<fp16, [256, 352]> mul_726 = mul(x = mul_724, y = rsqrt_156)[name = string("mul_726")];
            tensor<fp16, [352]> mul_727_y_0 = const()[name = string("mul_727_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7245824)))];
            tensor<fp16, [256, 352]> mul_727 = mul(x = mul_726, y = mul_727_y_0)[name = string("mul_727")];
            tensor<fp16, [960, 352]> tern_14_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7246592))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_14_w1_weight_0_palettized")];
            tensor<fp16, [256, 960]> tern_14_w1 = linear(bias = linear_4_bias_0, weight = tern_14_w1_weight_0_palettized, x = mul_727)[name = string("tern_14_w1")];
            tensor<fp16, [960]> mul_728_y_0 = const()[name = string("mul_728_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7331136)))];
            tensor<fp16, [256, 960]> mul_728 = mul(x = tern_14_w1, y = mul_728_y_0)[name = string("mul_728")];
            tensor<fp16, [352]> mul_731_y_0 = const()[name = string("mul_731_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7333120)))];
            tensor<fp16, [256, 352]> mul_731 = mul(x = mul_726, y = mul_731_y_0)[name = string("mul_731")];
            tensor<fp16, [960, 352]> tern_14_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7333888))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_14_w3_weight_0_palettized")];
            tensor<fp16, [256, 960]> tern_14_w3 = linear(bias = linear_4_bias_0, weight = tern_14_w3_weight_0_palettized, x = mul_731)[name = string("tern_14_w3")];
            tensor<fp16, [960]> mul_732_y_0 = const()[name = string("mul_732_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7418432)))];
            tensor<fp16, [256, 960]> mul_732 = mul(x = tern_14_w3, y = mul_732_y_0)[name = string("mul_732")];
            fp16 mul_733_y_0 = const()[name = string("mul_733_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [256, 960]> mul_733 = mul(x = mul_728, y = mul_733_y_0)[name = string("mul_733")];
            tensor<fp16, [256, 960]> tanh_14 = tanh(x = mul_733)[name = string("tanh_14")];
            fp16 mul_734_x_0 = const()[name = string("mul_734_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [256, 960]> mul_734 = mul(x = mul_734_x_0, y = tanh_14)[name = string("mul_734")];
            fp16 add_88_x_0 = const()[name = string("add_88_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [256, 960]> add_88 = add(x = add_88_x_0, y = mul_734)[name = string("add_88")];
            tensor<fp16, [256, 960]> mul_735 = mul(x = mul_728, y = add_88)[name = string("mul_735")];
            tensor<fp16, [256, 960]> mul_736 = mul(x = mul_735, y = mul_732)[name = string("mul_736")];
            tensor<fp16, [256, 960]> mul_737 = mul(x = mul_736, y = mul_736)[name = string("mul_737")];
            tensor<int32, [1]> reduce_mean_158_axes_0 = const()[name = string("reduce_mean_158_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_158_keep_dims_0 = const()[name = string("reduce_mean_158_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_158 = reduce_mean(axes = reduce_mean_158_axes_0, keep_dims = reduce_mean_158_keep_dims_0, x = mul_737)[name = string("reduce_mean_158")];
            fp32 rsqrt_158_epsilon_0 = const()[name = string("rsqrt_158_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_158 = rsqrt(epsilon = rsqrt_158_epsilon_0, x = reduce_mean_158)[name = string("rsqrt_158")];
            tensor<fp16, [256, 960]> mul_738 = mul(x = mul_736, y = rsqrt_158)[name = string("mul_738")];
            tensor<fp16, [960]> mul_739_y_0 = const()[name = string("mul_739_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7420416)))];
            tensor<fp16, [256, 960]> mul_739 = mul(x = mul_738, y = mul_739_y_0)[name = string("mul_739")];
            tensor<fp16, [352, 960]> tern_14_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7422400))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_14_w2_weight_0_palettized")];
            tensor<fp16, [256, 352]> tern_14_w2 = linear(bias = linear_0_bias_0, weight = tern_14_w2_weight_0_palettized, x = mul_739)[name = string("tern_14_w2")];
            tensor<fp16, [352]> mul_740_y_0 = const()[name = string("mul_740_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7506944)))];
            tensor<fp16, [256, 352]> mul_740 = mul(x = tern_14_w2, y = mul_740_y_0)[name = string("mul_740")];
            tensor<fp16, [256, 352]> add_89 = add(x = add_87, y = mul_740)[name = string("add_89")];
            tensor<fp16, [256, 352]> mul_741 = mul(x = add_89, y = add_89)[name = string("mul_741")];
            tensor<int32, [1]> reduce_mean_159_axes_0 = const()[name = string("reduce_mean_159_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_159_keep_dims_0 = const()[name = string("reduce_mean_159_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_159 = reduce_mean(axes = reduce_mean_159_axes_0, keep_dims = reduce_mean_159_keep_dims_0, x = mul_741)[name = string("reduce_mean_159")];
            fp32 rsqrt_159_epsilon_0 = const()[name = string("rsqrt_159_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_159 = rsqrt(epsilon = rsqrt_159_epsilon_0, x = reduce_mean_159)[name = string("rsqrt_159")];
            tensor<fp16, [256, 352]> mul_742 = mul(x = add_89, y = rsqrt_159)[name = string("mul_742")];
            tensor<fp16, [352]> mul_743_y_0 = const()[name = string("mul_743_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7507712)))];
            tensor<fp16, [256, 352]> mul_743 = mul(x = mul_742, y = mul_743_y_0)[name = string("mul_743")];
            tensor<fp16, [352, 352]> linear_7_weight_0 = const()[name = string("linear_7_weight_0"), val = tensor<fp16, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7508480)))];
            tensor<fp16, [256, 352]> linear_7 = linear(bias = linear_0_bias_0, weight = linear_7_weight_0, x = mul_743)[name = string("linear_7")];
            tensor<int32, [3]> reshape_122_shape_0 = const()[name = string("reshape_122_shape_0"), val = tensor<int32, [3]>([256, 8, 44])];
            tensor<fp16, [256, 8, 44]> reshape_122 = reshape(shape = reshape_122_shape_0, x = linear_7)[name = string("reshape_122")];
            tensor<int32, [3]> transpose_60_perm_0 = const()[name = string("transpose_60_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [88, 352]> linear_8_weight_0 = const()[name = string("linear_8_weight_0"), val = tensor<fp16, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7756352)))];
            tensor<fp16, [88]> linear_8_bias_0 = const()[name = string("linear_8_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [256, 88]> linear_8 = linear(bias = linear_8_bias_0, weight = linear_8_weight_0, x = mul_743)[name = string("linear_8")];
            tensor<int32, [3]> reshape_123_shape_0 = const()[name = string("reshape_123_shape_0"), val = tensor<int32, [3]>([256, 2, 44])];
            tensor<fp16, [256, 2, 44]> reshape_123 = reshape(shape = reshape_123_shape_0, x = linear_8)[name = string("reshape_123")];
            tensor<int32, [3]> transpose_61_perm_0 = const()[name = string("transpose_61_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [88, 352]> linear_9_weight_0 = const()[name = string("linear_9_weight_0"), val = tensor<fp16, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7818368)))];
            tensor<fp16, [88]> linear_9_bias_0 = const()[name = string("linear_9_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [256, 88]> linear_9 = linear(bias = linear_9_bias_0, weight = linear_9_weight_0, x = mul_743)[name = string("linear_9")];
            tensor<int32, [3]> reshape_124_shape_0 = const()[name = string("reshape_124_shape_0"), val = tensor<int32, [3]>([256, 2, 44])];
            tensor<fp16, [256, 2, 44]> reshape_124 = reshape(shape = reshape_124_shape_0, x = linear_9)[name = string("reshape_124")];
            tensor<int32, [3]> transpose_62_perm_0 = const()[name = string("transpose_62_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 256, 44]> transpose_60 = transpose(perm = transpose_60_perm_0, x = reshape_122)[name = string("transpose_3")];
            tensor<fp16, [8, 256, 44]> mul_744 = mul(x = transpose_60, y = transpose_60)[name = string("mul_744")];
            tensor<int32, [1]> reduce_mean_160_axes_0 = const()[name = string("reduce_mean_160_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_160_keep_dims_0 = const()[name = string("reduce_mean_160_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 256, 1]> reduce_mean_160 = reduce_mean(axes = reduce_mean_160_axes_0, keep_dims = reduce_mean_160_keep_dims_0, x = mul_744)[name = string("reduce_mean_160")];
            fp32 rsqrt_160_epsilon_0 = const()[name = string("rsqrt_160_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 256, 1]> rsqrt_160 = rsqrt(epsilon = rsqrt_160_epsilon_0, x = reduce_mean_160)[name = string("rsqrt_160")];
            tensor<fp16, [8, 256, 44]> mul_745 = mul(x = transpose_60, y = rsqrt_160)[name = string("mul_745")];
            tensor<fp16, [44]> mul_746_y_0 = const()[name = string("mul_746_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7880384)))];
            tensor<fp16, [8, 256, 44]> mul_746 = mul(x = mul_745, y = mul_746_y_0)[name = string("mul_746")];
            tensor<int32, [3]> slice_by_index_60_begin_0 = const()[name = string("slice_by_index_60_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_60_end_0 = const()[name = string("slice_by_index_60_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_60_end_mask_0 = const()[name = string("slice_by_index_60_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 256, 22]> slice_by_index_60 = slice_by_index(begin = slice_by_index_60_begin_0, end = slice_by_index_60_end_0, end_mask = slice_by_index_60_end_mask_0, x = mul_746)[name = string("slice_by_index_60")];
            tensor<int32, [3]> slice_by_index_61_begin_0 = const()[name = string("slice_by_index_61_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_61_end_0 = const()[name = string("slice_by_index_61_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_61_end_mask_0 = const()[name = string("slice_by_index_61_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 256, 22]> slice_by_index_61 = slice_by_index(begin = slice_by_index_61_begin_0, end = slice_by_index_61_end_0, end_mask = slice_by_index_61_end_mask_0, x = mul_746)[name = string("slice_by_index_61")];
            int32 concat_30_axis_0 = const()[name = string("concat_30_axis_0"), val = int32(-1)];
            bool concat_30_interleave_0 = const()[name = string("concat_30_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 256, 44]> concat_30 = concat(axis = concat_30_axis_0, interleave = concat_30_interleave_0, values = (slice_by_index_61, slice_by_index_60))[name = string("concat_30")];
            tensor<fp16, [44]> mul_747_y_0 = const()[name = string("mul_747_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 256, 44]> mul_747 = mul(x = concat_30, y = mul_747_y_0)[name = string("mul_747")];
            tensor<fp16, [8, 256, 44]> mul_748 = mul(x = mul_746, y = mul_11_y_0)[name = string("mul_748")];
            tensor<fp16, [8, 256, 44]> mul_749 = mul(x = mul_747, y = mul_12_y_0)[name = string("mul_749")];
            tensor<fp16, [8, 256, 44]> add_90 = add(x = mul_748, y = mul_749)[name = string("add_90")];
            tensor<fp16, [2, 256, 44]> transpose_61 = transpose(perm = transpose_61_perm_0, x = reshape_123)[name = string("transpose_2")];
            tensor<fp16, [2, 256, 44]> mul_750 = mul(x = transpose_61, y = transpose_61)[name = string("mul_750")];
            tensor<int32, [1]> reduce_mean_161_axes_0 = const()[name = string("reduce_mean_161_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_161_keep_dims_0 = const()[name = string("reduce_mean_161_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 256, 1]> reduce_mean_161 = reduce_mean(axes = reduce_mean_161_axes_0, keep_dims = reduce_mean_161_keep_dims_0, x = mul_750)[name = string("reduce_mean_161")];
            fp32 rsqrt_161_epsilon_0 = const()[name = string("rsqrt_161_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 256, 1]> rsqrt_161 = rsqrt(epsilon = rsqrt_161_epsilon_0, x = reduce_mean_161)[name = string("rsqrt_161")];
            tensor<fp16, [2, 256, 44]> mul_751 = mul(x = transpose_61, y = rsqrt_161)[name = string("mul_751")];
            tensor<fp16, [44]> mul_752_y_0 = const()[name = string("mul_752_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7880576)))];
            tensor<fp16, [2, 256, 44]> mul_752 = mul(x = mul_751, y = mul_752_y_0)[name = string("mul_752")];
            tensor<int32, [3]> slice_by_index_62_begin_0 = const()[name = string("slice_by_index_62_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_62_end_0 = const()[name = string("slice_by_index_62_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_62_end_mask_0 = const()[name = string("slice_by_index_62_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 256, 22]> slice_by_index_62 = slice_by_index(begin = slice_by_index_62_begin_0, end = slice_by_index_62_end_0, end_mask = slice_by_index_62_end_mask_0, x = mul_752)[name = string("slice_by_index_62")];
            tensor<int32, [3]> slice_by_index_63_begin_0 = const()[name = string("slice_by_index_63_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_63_end_0 = const()[name = string("slice_by_index_63_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_63_end_mask_0 = const()[name = string("slice_by_index_63_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 256, 22]> slice_by_index_63 = slice_by_index(begin = slice_by_index_63_begin_0, end = slice_by_index_63_end_0, end_mask = slice_by_index_63_end_mask_0, x = mul_752)[name = string("slice_by_index_63")];
            int32 concat_31_axis_0 = const()[name = string("concat_31_axis_0"), val = int32(-1)];
            bool concat_31_interleave_0 = const()[name = string("concat_31_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 256, 44]> concat_31 = concat(axis = concat_31_axis_0, interleave = concat_31_interleave_0, values = (slice_by_index_63, slice_by_index_62))[name = string("concat_31")];
            tensor<fp16, [44]> mul_753_y_0 = const()[name = string("mul_753_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 256, 44]> mul_753 = mul(x = concat_31, y = mul_753_y_0)[name = string("mul_753")];
            tensor<fp16, [2, 256, 44]> mul_754 = mul(x = mul_752, y = mul_11_y_0)[name = string("mul_754")];
            tensor<fp16, [2, 256, 44]> mul_755 = mul(x = mul_753, y = mul_12_y_0)[name = string("mul_755")];
            tensor<fp16, [2, 256, 44]> add_91 = add(x = mul_754, y = mul_755)[name = string("add_91")];
            tensor<int32, [4]> reshape_125_shape_0 = const()[name = string("reshape_125_shape_0"), val = tensor<int32, [4]>([2, 1, 256, 44])];
            tensor<fp16, [2, 1, 256, 44]> reshape_125 = reshape(shape = reshape_125_shape_0, x = add_91)[name = string("reshape_125")];
            tensor<int32, [4]> tile_30_reps_0 = const()[name = string("tile_30_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 256, 44]> tile_30 = tile(reps = tile_30_reps_0, x = reshape_125)[name = string("tile_30")];
            tensor<int32, [3]> reshape_126_shape_0 = const()[name = string("reshape_126_shape_0"), val = tensor<int32, [3]>([8, 256, 44])];
            tensor<fp16, [8, 256, 44]> reshape_126 = reshape(shape = reshape_126_shape_0, x = tile_30)[name = string("reshape_126")];
            tensor<int32, [4]> reshape_127_shape_0 = const()[name = string("reshape_127_shape_0"), val = tensor<int32, [4]>([2, 1, 256, 44])];
            tensor<fp16, [2, 256, 44]> transpose_62 = transpose(perm = transpose_62_perm_0, x = reshape_124)[name = string("transpose_1")];
            tensor<fp16, [2, 1, 256, 44]> reshape_127 = reshape(shape = reshape_127_shape_0, x = transpose_62)[name = string("reshape_127")];
            tensor<int32, [4]> tile_31_reps_0 = const()[name = string("tile_31_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 256, 44]> tile_31 = tile(reps = tile_31_reps_0, x = reshape_127)[name = string("tile_31")];
            tensor<int32, [3]> reshape_128_shape_0 = const()[name = string("reshape_128_shape_0"), val = tensor<int32, [3]>([8, 256, 44])];
            tensor<fp16, [8, 256, 44]> reshape_128 = reshape(shape = reshape_128_shape_0, x = tile_31)[name = string("reshape_128")];
            fp16 mul_756_y_0 = const()[name = string("mul_756_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 256, 44]> mul_756 = mul(x = add_90, y = mul_756_y_0)[name = string("mul_756")];
            bool matmul_30_transpose_y_0 = const()[name = string("matmul_30_transpose_y_0"), val = bool(true)];
            bool matmul_30_transpose_x_0 = const()[name = string("matmul_30_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 256, 256]> matmul_30 = matmul(transpose_x = matmul_30_transpose_x_0, transpose_y = matmul_30_transpose_y_0, x = mul_756, y = reshape_126)[name = string("matmul_30")];
            tensor<fp16, [8, 256, 256]> add_92 = add(x = matmul_30, y = reshape_1)[name = string("add_92")];
            int32 softmax_15_axis_0 = const()[name = string("softmax_15_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 256, 256]> softmax_15 = softmax(axis = softmax_15_axis_0, x = add_92)[name = string("softmax_15")];
            bool matmul_31_transpose_x_0 = const()[name = string("matmul_31_transpose_x_0"), val = bool(false)];
            bool matmul_31_transpose_y_0 = const()[name = string("matmul_31_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 256, 44]> matmul_31 = matmul(transpose_x = matmul_31_transpose_x_0, transpose_y = matmul_31_transpose_y_0, x = softmax_15, y = reshape_128)[name = string("matmul_31")];
            tensor<int32, [3]> transpose_63_perm_0 = const()[name = string("transpose_63_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_129_shape_0 = const()[name = string("reshape_129_shape_0"), val = tensor<int32, [2]>([256, 352])];
            tensor<fp16, [256, 8, 44]> transpose_63 = transpose(perm = transpose_63_perm_0, x = matmul_31)[name = string("transpose_0")];
            tensor<fp16, [256, 352]> reshape_129 = reshape(shape = reshape_129_shape_0, x = transpose_63)[name = string("reshape_129")];
            tensor<fp16, [352, 352]> linear_10_weight_0 = const()[name = string("linear_10_weight_0"), val = tensor<fp16, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7880768)))];
            tensor<fp16, [256, 352]> linear_10 = linear(bias = linear_0_bias_0, weight = linear_10_weight_0, x = reshape_129)[name = string("linear_10")];
            tensor<fp16, [256, 352]> add_93 = add(x = add_89, y = linear_10)[name = string("add_93")];
            tensor<fp16, [256, 352]> mul_757 = mul(x = add_93, y = add_93)[name = string("mul_757")];
            tensor<int32, [1]> reduce_mean_162_axes_0 = const()[name = string("reduce_mean_162_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_162_keep_dims_0 = const()[name = string("reduce_mean_162_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_162 = reduce_mean(axes = reduce_mean_162_axes_0, keep_dims = reduce_mean_162_keep_dims_0, x = mul_757)[name = string("reduce_mean_162")];
            fp32 rsqrt_162_epsilon_0 = const()[name = string("rsqrt_162_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_162 = rsqrt(epsilon = rsqrt_162_epsilon_0, x = reduce_mean_162)[name = string("rsqrt_162")];
            tensor<fp16, [256, 352]> mul_758 = mul(x = add_93, y = rsqrt_162)[name = string("mul_758")];
            tensor<fp16, [352]> mul_759_y_0 = const()[name = string("mul_759_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8128640)))];
            tensor<fp16, [256, 352]> mul_759 = mul(x = mul_758, y = mul_759_y_0)[name = string("mul_759")];
            tensor<fp16, [960, 352]> linear_11_weight_0 = const()[name = string("linear_11_weight_0"), val = tensor<fp16, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8129408)))];
            tensor<fp16, [256, 960]> linear_11 = linear(bias = linear_4_bias_0, weight = linear_11_weight_0, x = mul_759)[name = string("linear_11")];
            tensor<fp16, [960, 352]> linear_12_weight_0 = const()[name = string("linear_12_weight_0"), val = tensor<fp16, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8805312)))];
            tensor<fp16, [256, 960]> linear_12 = linear(bias = linear_4_bias_0, weight = linear_12_weight_0, x = mul_759)[name = string("linear_12")];
            fp16 mul_760_y_0 = const()[name = string("mul_760_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [256, 960]> mul_760 = mul(x = linear_11, y = mul_760_y_0)[name = string("mul_760")];
            tensor<fp16, [256, 960]> tanh_15 = tanh(x = mul_760)[name = string("tanh_15")];
            fp16 mul_761_x_0 = const()[name = string("mul_761_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [256, 960]> mul_761 = mul(x = mul_761_x_0, y = tanh_15)[name = string("mul_761")];
            fp16 add_94_x_0 = const()[name = string("add_94_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [256, 960]> add_94 = add(x = add_94_x_0, y = mul_761)[name = string("add_94")];
            tensor<fp16, [256, 960]> mul_762 = mul(x = linear_11, y = add_94)[name = string("mul_762")];
            tensor<fp16, [256, 960]> mul_763 = mul(x = mul_762, y = linear_12)[name = string("mul_763")];
            tensor<fp16, [352, 960]> linear_13_weight_0 = const()[name = string("linear_13_weight_0"), val = tensor<fp16, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9481216)))];
            tensor<fp16, [256, 352]> linear_13 = linear(bias = linear_0_bias_0, weight = linear_13_weight_0, x = mul_763)[name = string("linear_13")];
            tensor<fp16, [256, 352]> add_95 = add(x = add_93, y = linear_13)[name = string("add_95")];
            tensor<fp16, [256, 352]> mul_764 = mul(x = add_95, y = add_95)[name = string("mul_764")];
            tensor<int32, [1]> reduce_mean_163_axes_0 = const()[name = string("reduce_mean_163_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_163_keep_dims_0 = const()[name = string("reduce_mean_163_keep_dims_0"), val = bool(true)];
            tensor<fp16, [256, 1]> reduce_mean_163 = reduce_mean(axes = reduce_mean_163_axes_0, keep_dims = reduce_mean_163_keep_dims_0, x = mul_764)[name = string("reduce_mean_163")];
            fp32 rsqrt_163_epsilon_0 = const()[name = string("rsqrt_163_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [256, 1]> rsqrt_163 = rsqrt(epsilon = rsqrt_163_epsilon_0, x = reduce_mean_163)[name = string("rsqrt_163")];
            tensor<fp16, [256, 352]> mul_765 = mul(x = add_95, y = rsqrt_163)[name = string("mul_765")];
            tensor<fp16, [352]> mul_766_y_0 = const()[name = string("mul_766_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10157120)))];
            tensor<fp16, [256, 352]> mul_766 = mul(x = mul_765, y = mul_766_y_0)[name = string("mul_766")];
            tensor<fp16, [8342, 352]> linear_14_weight_0 = const()[name = string("linear_14_weight_0"), val = tensor<fp16, [8342, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10157888)))];
            tensor<fp16, [8342]> linear_14_bias_0 = const()[name = string("linear_14_bias_0"), val = tensor<fp16, [8342]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16030720)))];
            tensor<fp16, [256, 8342]> linear_14 = linear(bias = linear_14_bias_0, weight = linear_14_weight_0, x = mul_766)[name = string("linear_14")];
            tensor<int32, [3]> logits_shape_0 = const()[name = string("logits_shape_0"), val = tensor<int32, [3]>([1, 256, 8342])];
            tensor<fp16, [1, 256, 8342]> logits = reshape(shape = logits_shape_0, x = linear_14)[name = string("logits")];
        } -> (logits);
    func L32<ios18>(tensor<fp16, [1, 32, 352]> ids, tensor<fp16, [1, 32]> mask) {
            tensor<int32, [2]> reshape_0_shape_0 = const()[name = string("reshape_0_shape_0"), val = tensor<int32, [2]>([32, 352])];
            tensor<fp16, [32, 352]> reshape_0 = reshape(shape = reshape_0_shape_0, x = ids)[name = string("reshape_0")];
            tensor<fp16, [32, 352]> mul_0 = mul(x = reshape_0, y = reshape_0)[name = string("mul_0")];
            tensor<int32, [1]> reduce_mean_0_axes_0 = const()[name = string("reduce_mean_0_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_0_keep_dims_0 = const()[name = string("reduce_mean_0_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_0 = reduce_mean(axes = reduce_mean_0_axes_0, keep_dims = reduce_mean_0_keep_dims_0, x = mul_0)[name = string("reduce_mean_0")];
            fp32 rsqrt_0_epsilon_0 = const()[name = string("rsqrt_0_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_0 = rsqrt(epsilon = rsqrt_0_epsilon_0, x = reduce_mean_0)[name = string("rsqrt_0")];
            tensor<fp16, [32, 352]> mul_1 = mul(x = reshape_0, y = rsqrt_0)[name = string("mul_1")];
            tensor<fp16, [352]> mul_2_y_0 = const()[name = string("mul_2_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(64)))];
            tensor<fp16, [32, 352]> mul_2 = mul(x = mul_1, y = mul_2_y_0)[name = string("mul_2")];
            fp16 sub_0_y_0 = const()[name = string("sub_0_y_0"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 32]> sub_0 = sub(x = mask, y = sub_0_y_0)[name = string("sub_0")];
            fp16 mul_3_y_0 = const()[name = string("mul_3_y_0"), val = fp16(0x1.388p+13)];
            tensor<fp16, [1, 32]> mul_3 = mul(x = sub_0, y = mul_3_y_0)[name = string("mul_3")];
            tensor<int32, [3]> reshape_1_shape_0 = const()[name = string("reshape_1_shape_0"), val = tensor<int32, [3]>([1, 1, 32])];
            tensor<fp16, [1, 1, 32]> reshape_1 = reshape(shape = reshape_1_shape_0, x = mul_3)[name = string("reshape_1")];
            tensor<fp16, [32, 352]> mul_4 = mul(x = mul_2, y = mul_2)[name = string("mul_4")];
            tensor<int32, [1]> reduce_mean_1_axes_0 = const()[name = string("reduce_mean_1_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_1_keep_dims_0 = const()[name = string("reduce_mean_1_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_1 = reduce_mean(axes = reduce_mean_1_axes_0, keep_dims = reduce_mean_1_keep_dims_0, x = mul_4)[name = string("reduce_mean_1")];
            fp32 rsqrt_1_epsilon_0 = const()[name = string("rsqrt_1_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_1 = rsqrt(epsilon = rsqrt_1_epsilon_0, x = reduce_mean_1)[name = string("rsqrt_1")];
            tensor<fp16, [32, 352]> mul_5 = mul(x = mul_2, y = rsqrt_1)[name = string("mul_5")];
            tensor<fp16, [352]> mul_6_y_0 = const()[name = string("mul_6_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(832)))];
            tensor<fp16, [32, 352]> mul_6 = mul(x = mul_5, y = mul_6_y_0)[name = string("mul_6")];
            tensor<fp16, [352, 352]> linear_0_weight_0 = const()[name = string("linear_0_weight_0"), val = tensor<fp16, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1600)))];
            tensor<fp16, [352]> linear_0_bias_0 = const()[name = string("linear_0_bias_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(249472)))];
            tensor<fp16, [32, 352]> linear_0 = linear(bias = linear_0_bias_0, weight = linear_0_weight_0, x = mul_6)[name = string("linear_0")];
            tensor<int32, [3]> reshape_2_shape_0 = const()[name = string("reshape_2_shape_0"), val = tensor<int32, [3]>([32, 8, 44])];
            tensor<fp16, [32, 8, 44]> reshape_2 = reshape(shape = reshape_2_shape_0, x = linear_0)[name = string("reshape_2")];
            tensor<int32, [3]> transpose_0_perm_0 = const()[name = string("transpose_0_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [88, 352]> linear_1_weight_0 = const()[name = string("linear_1_weight_0"), val = tensor<fp16, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(250240)))];
            tensor<fp16, [88]> linear_1_bias_0 = const()[name = string("linear_1_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [32, 88]> linear_1 = linear(bias = linear_1_bias_0, weight = linear_1_weight_0, x = mul_6)[name = string("linear_1")];
            tensor<int32, [3]> reshape_3_shape_0 = const()[name = string("reshape_3_shape_0"), val = tensor<int32, [3]>([32, 2, 44])];
            tensor<fp16, [32, 2, 44]> reshape_3 = reshape(shape = reshape_3_shape_0, x = linear_1)[name = string("reshape_3")];
            tensor<int32, [3]> transpose_1_perm_0 = const()[name = string("transpose_1_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [88, 352]> linear_2_weight_0 = const()[name = string("linear_2_weight_0"), val = tensor<fp16, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312512)))];
            tensor<fp16, [88]> linear_2_bias_0 = const()[name = string("linear_2_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [32, 88]> linear_2 = linear(bias = linear_2_bias_0, weight = linear_2_weight_0, x = mul_6)[name = string("linear_2")];
            tensor<int32, [3]> reshape_4_shape_0 = const()[name = string("reshape_4_shape_0"), val = tensor<int32, [3]>([32, 2, 44])];
            tensor<fp16, [32, 2, 44]> reshape_4 = reshape(shape = reshape_4_shape_0, x = linear_2)[name = string("reshape_4")];
            tensor<int32, [3]> transpose_2_perm_0 = const()[name = string("transpose_2_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 32, 44]> transpose_0 = transpose(perm = transpose_0_perm_0, x = reshape_2)[name = string("transpose_63")];
            tensor<fp16, [8, 32, 44]> mul_7 = mul(x = transpose_0, y = transpose_0)[name = string("mul_7")];
            tensor<int32, [1]> reduce_mean_2_axes_0 = const()[name = string("reduce_mean_2_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_2_keep_dims_0 = const()[name = string("reduce_mean_2_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 32, 1]> reduce_mean_2 = reduce_mean(axes = reduce_mean_2_axes_0, keep_dims = reduce_mean_2_keep_dims_0, x = mul_7)[name = string("reduce_mean_2")];
            fp32 rsqrt_2_epsilon_0 = const()[name = string("rsqrt_2_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 32, 1]> rsqrt_2 = rsqrt(epsilon = rsqrt_2_epsilon_0, x = reduce_mean_2)[name = string("rsqrt_2")];
            tensor<fp16, [8, 32, 44]> mul_8 = mul(x = transpose_0, y = rsqrt_2)[name = string("mul_8")];
            tensor<fp16, [44]> mul_9_y_0 = const()[name = string("mul_9_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374528)))];
            tensor<fp16, [8, 32, 44]> mul_9 = mul(x = mul_8, y = mul_9_y_0)[name = string("mul_9")];
            tensor<int32, [3]> slice_by_index_0_begin_0 = const()[name = string("slice_by_index_0_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_0_end_0 = const()[name = string("slice_by_index_0_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_0_end_mask_0 = const()[name = string("slice_by_index_0_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 32, 22]> slice_by_index_0 = slice_by_index(begin = slice_by_index_0_begin_0, end = slice_by_index_0_end_0, end_mask = slice_by_index_0_end_mask_0, x = mul_9)[name = string("slice_by_index_0")];
            tensor<int32, [3]> slice_by_index_1_begin_0 = const()[name = string("slice_by_index_1_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_1_end_0 = const()[name = string("slice_by_index_1_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_1_end_mask_0 = const()[name = string("slice_by_index_1_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 32, 22]> slice_by_index_1 = slice_by_index(begin = slice_by_index_1_begin_0, end = slice_by_index_1_end_0, end_mask = slice_by_index_1_end_mask_0, x = mul_9)[name = string("slice_by_index_1")];
            int32 concat_0_axis_0 = const()[name = string("concat_0_axis_0"), val = int32(-1)];
            bool concat_0_interleave_0 = const()[name = string("concat_0_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 32, 44]> concat_0 = concat(axis = concat_0_axis_0, interleave = concat_0_interleave_0, values = (slice_by_index_1, slice_by_index_0))[name = string("concat_0")];
            tensor<fp16, [44]> mul_10_y_0 = const()[name = string("mul_10_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 32, 44]> mul_10 = mul(x = concat_0, y = mul_10_y_0)[name = string("mul_10")];
            tensor<fp16, [1, 32, 44]> mul_11_y_0 = const()[name = string("mul_11_y_0"), val = tensor<fp16, [1, 32, 44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16050432)))];
            tensor<fp16, [8, 32, 44]> mul_11 = mul(x = mul_9, y = mul_11_y_0)[name = string("mul_11")];
            tensor<fp16, [1, 32, 44]> mul_12_y_0 = const()[name = string("mul_12_y_0"), val = tensor<fp16, [1, 32, 44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16053312)))];
            tensor<fp16, [8, 32, 44]> mul_12 = mul(x = mul_10, y = mul_12_y_0)[name = string("mul_12")];
            tensor<fp16, [8, 32, 44]> add_0 = add(x = mul_11, y = mul_12)[name = string("add_0")];
            tensor<fp16, [2, 32, 44]> transpose_1 = transpose(perm = transpose_1_perm_0, x = reshape_3)[name = string("transpose_62")];
            tensor<fp16, [2, 32, 44]> mul_13 = mul(x = transpose_1, y = transpose_1)[name = string("mul_13")];
            tensor<int32, [1]> reduce_mean_3_axes_0 = const()[name = string("reduce_mean_3_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_3_keep_dims_0 = const()[name = string("reduce_mean_3_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 32, 1]> reduce_mean_3 = reduce_mean(axes = reduce_mean_3_axes_0, keep_dims = reduce_mean_3_keep_dims_0, x = mul_13)[name = string("reduce_mean_3")];
            fp32 rsqrt_3_epsilon_0 = const()[name = string("rsqrt_3_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 32, 1]> rsqrt_3 = rsqrt(epsilon = rsqrt_3_epsilon_0, x = reduce_mean_3)[name = string("rsqrt_3")];
            tensor<fp16, [2, 32, 44]> mul_14 = mul(x = transpose_1, y = rsqrt_3)[name = string("mul_14")];
            tensor<fp16, [44]> mul_15_y_0 = const()[name = string("mul_15_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(376448)))];
            tensor<fp16, [2, 32, 44]> mul_15 = mul(x = mul_14, y = mul_15_y_0)[name = string("mul_15")];
            tensor<int32, [3]> slice_by_index_2_begin_0 = const()[name = string("slice_by_index_2_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_2_end_0 = const()[name = string("slice_by_index_2_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_2_end_mask_0 = const()[name = string("slice_by_index_2_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 32, 22]> slice_by_index_2 = slice_by_index(begin = slice_by_index_2_begin_0, end = slice_by_index_2_end_0, end_mask = slice_by_index_2_end_mask_0, x = mul_15)[name = string("slice_by_index_2")];
            tensor<int32, [3]> slice_by_index_3_begin_0 = const()[name = string("slice_by_index_3_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_3_end_0 = const()[name = string("slice_by_index_3_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_3_end_mask_0 = const()[name = string("slice_by_index_3_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 32, 22]> slice_by_index_3 = slice_by_index(begin = slice_by_index_3_begin_0, end = slice_by_index_3_end_0, end_mask = slice_by_index_3_end_mask_0, x = mul_15)[name = string("slice_by_index_3")];
            int32 concat_1_axis_0 = const()[name = string("concat_1_axis_0"), val = int32(-1)];
            bool concat_1_interleave_0 = const()[name = string("concat_1_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 32, 44]> concat_1 = concat(axis = concat_1_axis_0, interleave = concat_1_interleave_0, values = (slice_by_index_3, slice_by_index_2))[name = string("concat_1")];
            tensor<fp16, [44]> mul_16_y_0 = const()[name = string("mul_16_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 32, 44]> mul_16 = mul(x = concat_1, y = mul_16_y_0)[name = string("mul_16")];
            tensor<fp16, [2, 32, 44]> mul_17 = mul(x = mul_15, y = mul_11_y_0)[name = string("mul_17")];
            tensor<fp16, [2, 32, 44]> mul_18 = mul(x = mul_16, y = mul_12_y_0)[name = string("mul_18")];
            tensor<fp16, [2, 32, 44]> add_1 = add(x = mul_17, y = mul_18)[name = string("add_1")];
            tensor<int32, [4]> reshape_5_shape_0 = const()[name = string("reshape_5_shape_0"), val = tensor<int32, [4]>([2, 1, 32, 44])];
            tensor<fp16, [2, 1, 32, 44]> reshape_5 = reshape(shape = reshape_5_shape_0, x = add_1)[name = string("reshape_5")];
            tensor<int32, [4]> tile_0_reps_0 = const()[name = string("tile_0_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 32, 44]> tile_0 = tile(reps = tile_0_reps_0, x = reshape_5)[name = string("tile_0")];
            tensor<int32, [3]> reshape_6_shape_0 = const()[name = string("reshape_6_shape_0"), val = tensor<int32, [3]>([8, 32, 44])];
            tensor<fp16, [8, 32, 44]> reshape_6 = reshape(shape = reshape_6_shape_0, x = tile_0)[name = string("reshape_6")];
            tensor<int32, [4]> reshape_7_shape_0 = const()[name = string("reshape_7_shape_0"), val = tensor<int32, [4]>([2, 1, 32, 44])];
            tensor<fp16, [2, 32, 44]> transpose_2 = transpose(perm = transpose_2_perm_0, x = reshape_4)[name = string("transpose_61")];
            tensor<fp16, [2, 1, 32, 44]> reshape_7 = reshape(shape = reshape_7_shape_0, x = transpose_2)[name = string("reshape_7")];
            tensor<int32, [4]> tile_1_reps_0 = const()[name = string("tile_1_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 32, 44]> tile_1 = tile(reps = tile_1_reps_0, x = reshape_7)[name = string("tile_1")];
            tensor<int32, [3]> reshape_8_shape_0 = const()[name = string("reshape_8_shape_0"), val = tensor<int32, [3]>([8, 32, 44])];
            tensor<fp16, [8, 32, 44]> reshape_8 = reshape(shape = reshape_8_shape_0, x = tile_1)[name = string("reshape_8")];
            fp16 mul_19_y_0 = const()[name = string("mul_19_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 32, 44]> mul_19 = mul(x = add_0, y = mul_19_y_0)[name = string("mul_19")];
            bool matmul_0_transpose_y_0 = const()[name = string("matmul_0_transpose_y_0"), val = bool(true)];
            bool matmul_0_transpose_x_0 = const()[name = string("matmul_0_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 32, 32]> matmul_0 = matmul(transpose_x = matmul_0_transpose_x_0, transpose_y = matmul_0_transpose_y_0, x = mul_19, y = reshape_6)[name = string("matmul_0")];
            tensor<fp16, [8, 32, 32]> add_2 = add(x = matmul_0, y = reshape_1)[name = string("add_2")];
            int32 softmax_0_axis_0 = const()[name = string("softmax_0_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 32, 32]> softmax_0 = softmax(axis = softmax_0_axis_0, x = add_2)[name = string("softmax_0")];
            bool matmul_1_transpose_x_0 = const()[name = string("matmul_1_transpose_x_0"), val = bool(false)];
            bool matmul_1_transpose_y_0 = const()[name = string("matmul_1_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 32, 44]> matmul_1 = matmul(transpose_x = matmul_1_transpose_x_0, transpose_y = matmul_1_transpose_y_0, x = softmax_0, y = reshape_8)[name = string("matmul_1")];
            tensor<int32, [3]> transpose_3_perm_0 = const()[name = string("transpose_3_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_9_shape_0 = const()[name = string("reshape_9_shape_0"), val = tensor<int32, [2]>([32, 352])];
            tensor<fp16, [32, 8, 44]> transpose_3 = transpose(perm = transpose_3_perm_0, x = matmul_1)[name = string("transpose_60")];
            tensor<fp16, [32, 352]> reshape_9 = reshape(shape = reshape_9_shape_0, x = transpose_3)[name = string("reshape_9")];
            tensor<fp16, [352, 352]> linear_3_weight_0 = const()[name = string("linear_3_weight_0"), val = tensor<fp16, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(376640)))];
            tensor<fp16, [32, 352]> linear_3 = linear(bias = linear_0_bias_0, weight = linear_3_weight_0, x = reshape_9)[name = string("linear_3")];
            tensor<fp16, [32, 352]> add_3 = add(x = mul_2, y = linear_3)[name = string("add_3")];
            tensor<fp16, [32, 352]> mul_20 = mul(x = add_3, y = add_3)[name = string("mul_20")];
            tensor<int32, [1]> reduce_mean_4_axes_0 = const()[name = string("reduce_mean_4_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_4_keep_dims_0 = const()[name = string("reduce_mean_4_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_4 = reduce_mean(axes = reduce_mean_4_axes_0, keep_dims = reduce_mean_4_keep_dims_0, x = mul_20)[name = string("reduce_mean_4")];
            fp32 rsqrt_4_epsilon_0 = const()[name = string("rsqrt_4_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_4 = rsqrt(epsilon = rsqrt_4_epsilon_0, x = reduce_mean_4)[name = string("rsqrt_4")];
            tensor<fp16, [32, 352]> mul_21 = mul(x = add_3, y = rsqrt_4)[name = string("mul_21")];
            tensor<fp16, [352]> mul_22_y_0 = const()[name = string("mul_22_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(624512)))];
            tensor<fp16, [32, 352]> mul_22 = mul(x = mul_21, y = mul_22_y_0)[name = string("mul_22")];
            tensor<fp16, [960, 352]> linear_4_weight_0 = const()[name = string("linear_4_weight_0"), val = tensor<fp16, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(625280)))];
            tensor<fp16, [960]> linear_4_bias_0 = const()[name = string("linear_4_bias_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1301184)))];
            tensor<fp16, [32, 960]> linear_4 = linear(bias = linear_4_bias_0, weight = linear_4_weight_0, x = mul_22)[name = string("linear_4")];
            tensor<fp16, [960, 352]> linear_5_weight_0 = const()[name = string("linear_5_weight_0"), val = tensor<fp16, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1303168)))];
            tensor<fp16, [32, 960]> linear_5 = linear(bias = linear_4_bias_0, weight = linear_5_weight_0, x = mul_22)[name = string("linear_5")];
            fp16 mul_23_y_0 = const()[name = string("mul_23_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [32, 960]> mul_23 = mul(x = linear_4, y = mul_23_y_0)[name = string("mul_23")];
            tensor<fp16, [32, 960]> tanh_0 = tanh(x = mul_23)[name = string("tanh_0")];
            fp16 mul_24_x_0 = const()[name = string("mul_24_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [32, 960]> mul_24 = mul(x = mul_24_x_0, y = tanh_0)[name = string("mul_24")];
            fp16 add_4_x_0 = const()[name = string("add_4_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [32, 960]> add_4 = add(x = add_4_x_0, y = mul_24)[name = string("add_4")];
            tensor<fp16, [32, 960]> mul_25 = mul(x = linear_4, y = add_4)[name = string("mul_25")];
            tensor<fp16, [32, 960]> mul_26 = mul(x = mul_25, y = linear_5)[name = string("mul_26")];
            tensor<fp16, [352, 960]> linear_6_weight_0 = const()[name = string("linear_6_weight_0"), val = tensor<fp16, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1979072)))];
            tensor<fp16, [32, 352]> linear_6 = linear(bias = linear_0_bias_0, weight = linear_6_weight_0, x = mul_26)[name = string("linear_6")];
            tensor<fp16, [32, 352]> add_5 = add(x = add_3, y = linear_6)[name = string("add_5")];
            tensor<fp16, [32, 352]> mul_27 = mul(x = add_5, y = add_5)[name = string("mul_27")];
            tensor<int32, [1]> reduce_mean_5_axes_0 = const()[name = string("reduce_mean_5_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_5_keep_dims_0 = const()[name = string("reduce_mean_5_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_5 = reduce_mean(axes = reduce_mean_5_axes_0, keep_dims = reduce_mean_5_keep_dims_0, x = mul_27)[name = string("reduce_mean_5")];
            fp32 rsqrt_5_epsilon_0 = const()[name = string("rsqrt_5_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_5 = rsqrt(epsilon = rsqrt_5_epsilon_0, x = reduce_mean_5)[name = string("rsqrt_5")];
            tensor<fp16, [32, 352]> mul_28 = mul(x = add_5, y = rsqrt_5)[name = string("mul_28")];
            tensor<fp16, [352]> mul_29_y_0 = const()[name = string("mul_29_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2654976)))];
            tensor<fp16, [32, 352]> mul_29 = mul(x = mul_28, y = mul_29_y_0)[name = string("mul_29")];
            tensor<fp16, [32, 352]> mul_30 = mul(x = mul_29, y = mul_29)[name = string("mul_30")];
            tensor<int32, [1]> reduce_mean_6_axes_0 = const()[name = string("reduce_mean_6_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_6_keep_dims_0 = const()[name = string("reduce_mean_6_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_6 = reduce_mean(axes = reduce_mean_6_axes_0, keep_dims = reduce_mean_6_keep_dims_0, x = mul_30)[name = string("reduce_mean_6")];
            fp32 rsqrt_6_epsilon_0 = const()[name = string("rsqrt_6_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_6 = rsqrt(epsilon = rsqrt_6_epsilon_0, x = reduce_mean_6)[name = string("rsqrt_6")];
            tensor<fp16, [32, 352]> mul_31 = mul(x = mul_29, y = rsqrt_6)[name = string("mul_31")];
            tensor<fp16, [352]> mul_32_y_0 = const()[name = string("mul_32_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2655744)))];
            tensor<fp16, [32, 352]> mul_32 = mul(x = mul_31, y = mul_32_y_0)[name = string("mul_32")];
            tensor<fp16, [352, 352]> tern_1_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2656512))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_1_q_weight_0_palettized")];
            tensor<fp16, [32, 352]> tern_1_q = linear(bias = linear_0_bias_0, weight = tern_1_q_weight_0_palettized, x = mul_32)[name = string("tern_1_q")];
            tensor<fp16, [352]> mul_33_y_0 = const()[name = string("mul_33_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2687552)))];
            tensor<fp16, [32, 352]> mul_33 = mul(x = tern_1_q, y = mul_33_y_0)[name = string("mul_33")];
            tensor<int32, [3]> reshape_10_shape_0 = const()[name = string("reshape_10_shape_0"), val = tensor<int32, [3]>([32, 8, 44])];
            tensor<fp16, [32, 8, 44]> reshape_10 = reshape(shape = reshape_10_shape_0, x = mul_33)[name = string("reshape_10")];
            tensor<int32, [3]> transpose_4_perm_0 = const()[name = string("transpose_4_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_36_y_0 = const()[name = string("mul_36_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2688320)))];
            tensor<fp16, [32, 352]> mul_36 = mul(x = mul_31, y = mul_36_y_0)[name = string("mul_36")];
            tensor<fp16, [88, 352]> tern_1_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2689088))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_1_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_1_k_bias_0 = const()[name = string("tern_1_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [32, 88]> tern_1_k = linear(bias = tern_1_k_bias_0, weight = tern_1_k_weight_0_palettized, x = mul_36)[name = string("tern_1_k")];
            tensor<fp16, [88]> mul_37_y_0 = const()[name = string("mul_37_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2696896)))];
            tensor<fp16, [32, 88]> mul_37 = mul(x = tern_1_k, y = mul_37_y_0)[name = string("mul_37")];
            tensor<int32, [3]> reshape_11_shape_0 = const()[name = string("reshape_11_shape_0"), val = tensor<int32, [3]>([32, 2, 44])];
            tensor<fp16, [32, 2, 44]> reshape_11 = reshape(shape = reshape_11_shape_0, x = mul_37)[name = string("reshape_11")];
            tensor<int32, [3]> transpose_5_perm_0 = const()[name = string("transpose_5_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_40_y_0 = const()[name = string("mul_40_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2697152)))];
            tensor<fp16, [32, 352]> mul_40 = mul(x = mul_31, y = mul_40_y_0)[name = string("mul_40")];
            tensor<fp16, [88, 352]> tern_1_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2697920))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_1_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_1_v_bias_0 = const()[name = string("tern_1_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [32, 88]> tern_1_v = linear(bias = tern_1_v_bias_0, weight = tern_1_v_weight_0_palettized, x = mul_40)[name = string("tern_1_v")];
            tensor<fp16, [88]> mul_41_y_0 = const()[name = string("mul_41_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2705728)))];
            tensor<fp16, [32, 88]> mul_41 = mul(x = tern_1_v, y = mul_41_y_0)[name = string("mul_41")];
            tensor<int32, [3]> reshape_12_shape_0 = const()[name = string("reshape_12_shape_0"), val = tensor<int32, [3]>([32, 2, 44])];
            tensor<fp16, [32, 2, 44]> reshape_12 = reshape(shape = reshape_12_shape_0, x = mul_41)[name = string("reshape_12")];
            tensor<int32, [3]> transpose_6_perm_0 = const()[name = string("transpose_6_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 32, 44]> transpose_4 = transpose(perm = transpose_4_perm_0, x = reshape_10)[name = string("transpose_59")];
            tensor<fp16, [8, 32, 44]> mul_42 = mul(x = transpose_4, y = transpose_4)[name = string("mul_42")];
            tensor<int32, [1]> reduce_mean_9_axes_0 = const()[name = string("reduce_mean_9_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_9_keep_dims_0 = const()[name = string("reduce_mean_9_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 32, 1]> reduce_mean_9 = reduce_mean(axes = reduce_mean_9_axes_0, keep_dims = reduce_mean_9_keep_dims_0, x = mul_42)[name = string("reduce_mean_9")];
            fp32 rsqrt_9_epsilon_0 = const()[name = string("rsqrt_9_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 32, 1]> rsqrt_9 = rsqrt(epsilon = rsqrt_9_epsilon_0, x = reduce_mean_9)[name = string("rsqrt_9")];
            tensor<fp16, [8, 32, 44]> mul_43 = mul(x = transpose_4, y = rsqrt_9)[name = string("mul_43")];
            tensor<fp16, [44]> mul_44_y_0 = const()[name = string("mul_44_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2705984)))];
            tensor<fp16, [8, 32, 44]> mul_44 = mul(x = mul_43, y = mul_44_y_0)[name = string("mul_44")];
            tensor<int32, [3]> slice_by_index_4_begin_0 = const()[name = string("slice_by_index_4_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_4_end_0 = const()[name = string("slice_by_index_4_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_4_end_mask_0 = const()[name = string("slice_by_index_4_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 32, 22]> slice_by_index_4 = slice_by_index(begin = slice_by_index_4_begin_0, end = slice_by_index_4_end_0, end_mask = slice_by_index_4_end_mask_0, x = mul_44)[name = string("slice_by_index_4")];
            tensor<int32, [3]> slice_by_index_5_begin_0 = const()[name = string("slice_by_index_5_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_5_end_0 = const()[name = string("slice_by_index_5_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_5_end_mask_0 = const()[name = string("slice_by_index_5_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 32, 22]> slice_by_index_5 = slice_by_index(begin = slice_by_index_5_begin_0, end = slice_by_index_5_end_0, end_mask = slice_by_index_5_end_mask_0, x = mul_44)[name = string("slice_by_index_5")];
            int32 concat_2_axis_0 = const()[name = string("concat_2_axis_0"), val = int32(-1)];
            bool concat_2_interleave_0 = const()[name = string("concat_2_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 32, 44]> concat_2 = concat(axis = concat_2_axis_0, interleave = concat_2_interleave_0, values = (slice_by_index_5, slice_by_index_4))[name = string("concat_2")];
            tensor<fp16, [44]> mul_45_y_0 = const()[name = string("mul_45_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 32, 44]> mul_45 = mul(x = concat_2, y = mul_45_y_0)[name = string("mul_45")];
            tensor<fp16, [8, 32, 44]> mul_46 = mul(x = mul_44, y = mul_11_y_0)[name = string("mul_46")];
            tensor<fp16, [8, 32, 44]> mul_47 = mul(x = mul_45, y = mul_12_y_0)[name = string("mul_47")];
            tensor<fp16, [8, 32, 44]> add_6 = add(x = mul_46, y = mul_47)[name = string("add_6")];
            tensor<fp16, [2, 32, 44]> transpose_5 = transpose(perm = transpose_5_perm_0, x = reshape_11)[name = string("transpose_58")];
            tensor<fp16, [2, 32, 44]> mul_48 = mul(x = transpose_5, y = transpose_5)[name = string("mul_48")];
            tensor<int32, [1]> reduce_mean_10_axes_0 = const()[name = string("reduce_mean_10_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_10_keep_dims_0 = const()[name = string("reduce_mean_10_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 32, 1]> reduce_mean_10 = reduce_mean(axes = reduce_mean_10_axes_0, keep_dims = reduce_mean_10_keep_dims_0, x = mul_48)[name = string("reduce_mean_10")];
            fp32 rsqrt_10_epsilon_0 = const()[name = string("rsqrt_10_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 32, 1]> rsqrt_10 = rsqrt(epsilon = rsqrt_10_epsilon_0, x = reduce_mean_10)[name = string("rsqrt_10")];
            tensor<fp16, [2, 32, 44]> mul_49 = mul(x = transpose_5, y = rsqrt_10)[name = string("mul_49")];
            tensor<fp16, [44]> mul_50_y_0 = const()[name = string("mul_50_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2706176)))];
            tensor<fp16, [2, 32, 44]> mul_50 = mul(x = mul_49, y = mul_50_y_0)[name = string("mul_50")];
            tensor<int32, [3]> slice_by_index_6_begin_0 = const()[name = string("slice_by_index_6_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_6_end_0 = const()[name = string("slice_by_index_6_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_6_end_mask_0 = const()[name = string("slice_by_index_6_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 32, 22]> slice_by_index_6 = slice_by_index(begin = slice_by_index_6_begin_0, end = slice_by_index_6_end_0, end_mask = slice_by_index_6_end_mask_0, x = mul_50)[name = string("slice_by_index_6")];
            tensor<int32, [3]> slice_by_index_7_begin_0 = const()[name = string("slice_by_index_7_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_7_end_0 = const()[name = string("slice_by_index_7_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_7_end_mask_0 = const()[name = string("slice_by_index_7_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 32, 22]> slice_by_index_7 = slice_by_index(begin = slice_by_index_7_begin_0, end = slice_by_index_7_end_0, end_mask = slice_by_index_7_end_mask_0, x = mul_50)[name = string("slice_by_index_7")];
            int32 concat_3_axis_0 = const()[name = string("concat_3_axis_0"), val = int32(-1)];
            bool concat_3_interleave_0 = const()[name = string("concat_3_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 32, 44]> concat_3 = concat(axis = concat_3_axis_0, interleave = concat_3_interleave_0, values = (slice_by_index_7, slice_by_index_6))[name = string("concat_3")];
            tensor<fp16, [44]> mul_51_y_0 = const()[name = string("mul_51_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 32, 44]> mul_51 = mul(x = concat_3, y = mul_51_y_0)[name = string("mul_51")];
            tensor<fp16, [2, 32, 44]> mul_52 = mul(x = mul_50, y = mul_11_y_0)[name = string("mul_52")];
            tensor<fp16, [2, 32, 44]> mul_53 = mul(x = mul_51, y = mul_12_y_0)[name = string("mul_53")];
            tensor<fp16, [2, 32, 44]> add_7 = add(x = mul_52, y = mul_53)[name = string("add_7")];
            tensor<int32, [4]> reshape_13_shape_0 = const()[name = string("reshape_13_shape_0"), val = tensor<int32, [4]>([2, 1, 32, 44])];
            tensor<fp16, [2, 1, 32, 44]> reshape_13 = reshape(shape = reshape_13_shape_0, x = add_7)[name = string("reshape_13")];
            tensor<int32, [4]> tile_2_reps_0 = const()[name = string("tile_2_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 32, 44]> tile_2 = tile(reps = tile_2_reps_0, x = reshape_13)[name = string("tile_2")];
            tensor<int32, [3]> reshape_14_shape_0 = const()[name = string("reshape_14_shape_0"), val = tensor<int32, [3]>([8, 32, 44])];
            tensor<fp16, [8, 32, 44]> reshape_14 = reshape(shape = reshape_14_shape_0, x = tile_2)[name = string("reshape_14")];
            tensor<int32, [4]> reshape_15_shape_0 = const()[name = string("reshape_15_shape_0"), val = tensor<int32, [4]>([2, 1, 32, 44])];
            tensor<fp16, [2, 32, 44]> transpose_6 = transpose(perm = transpose_6_perm_0, x = reshape_12)[name = string("transpose_57")];
            tensor<fp16, [2, 1, 32, 44]> reshape_15 = reshape(shape = reshape_15_shape_0, x = transpose_6)[name = string("reshape_15")];
            tensor<int32, [4]> tile_3_reps_0 = const()[name = string("tile_3_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 32, 44]> tile_3 = tile(reps = tile_3_reps_0, x = reshape_15)[name = string("tile_3")];
            tensor<int32, [3]> reshape_16_shape_0 = const()[name = string("reshape_16_shape_0"), val = tensor<int32, [3]>([8, 32, 44])];
            tensor<fp16, [8, 32, 44]> reshape_16 = reshape(shape = reshape_16_shape_0, x = tile_3)[name = string("reshape_16")];
            fp16 mul_54_y_0 = const()[name = string("mul_54_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 32, 44]> mul_54 = mul(x = add_6, y = mul_54_y_0)[name = string("mul_54")];
            bool matmul_2_transpose_y_0 = const()[name = string("matmul_2_transpose_y_0"), val = bool(true)];
            bool matmul_2_transpose_x_0 = const()[name = string("matmul_2_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 32, 32]> matmul_2 = matmul(transpose_x = matmul_2_transpose_x_0, transpose_y = matmul_2_transpose_y_0, x = mul_54, y = reshape_14)[name = string("matmul_2")];
            tensor<fp16, [8, 32, 32]> add_8 = add(x = matmul_2, y = reshape_1)[name = string("add_8")];
            int32 softmax_1_axis_0 = const()[name = string("softmax_1_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 32, 32]> softmax_1 = softmax(axis = softmax_1_axis_0, x = add_8)[name = string("softmax_1")];
            bool matmul_3_transpose_x_0 = const()[name = string("matmul_3_transpose_x_0"), val = bool(false)];
            bool matmul_3_transpose_y_0 = const()[name = string("matmul_3_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 32, 44]> matmul_3 = matmul(transpose_x = matmul_3_transpose_x_0, transpose_y = matmul_3_transpose_y_0, x = softmax_1, y = reshape_16)[name = string("matmul_3")];
            tensor<int32, [3]> transpose_7_perm_0 = const()[name = string("transpose_7_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_17_shape_0 = const()[name = string("reshape_17_shape_0"), val = tensor<int32, [2]>([32, 352])];
            tensor<fp16, [32, 8, 44]> transpose_7 = transpose(perm = transpose_7_perm_0, x = matmul_3)[name = string("transpose_56")];
            tensor<fp16, [32, 352]> reshape_17 = reshape(shape = reshape_17_shape_0, x = transpose_7)[name = string("reshape_17")];
            tensor<fp16, [32, 352]> mul_55 = mul(x = reshape_17, y = reshape_17)[name = string("mul_55")];
            tensor<int32, [1]> reduce_mean_11_axes_0 = const()[name = string("reduce_mean_11_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_11_keep_dims_0 = const()[name = string("reduce_mean_11_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_11 = reduce_mean(axes = reduce_mean_11_axes_0, keep_dims = reduce_mean_11_keep_dims_0, x = mul_55)[name = string("reduce_mean_11")];
            fp32 rsqrt_11_epsilon_0 = const()[name = string("rsqrt_11_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_11 = rsqrt(epsilon = rsqrt_11_epsilon_0, x = reduce_mean_11)[name = string("rsqrt_11")];
            tensor<fp16, [32, 352]> mul_56 = mul(x = reshape_17, y = rsqrt_11)[name = string("mul_56")];
            tensor<fp16, [352]> mul_57_y_0 = const()[name = string("mul_57_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2706368)))];
            tensor<fp16, [32, 352]> mul_57 = mul(x = mul_56, y = mul_57_y_0)[name = string("mul_57")];
            tensor<fp16, [352, 352]> tern_1_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2707136))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_1_o_weight_0_palettized")];
            tensor<fp16, [32, 352]> tern_1_o = linear(bias = linear_0_bias_0, weight = tern_1_o_weight_0_palettized, x = mul_57)[name = string("tern_1_o")];
            tensor<fp16, [352]> mul_58_y_0 = const()[name = string("mul_58_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2738176)))];
            tensor<fp16, [32, 352]> mul_58 = mul(x = tern_1_o, y = mul_58_y_0)[name = string("mul_58")];
            tensor<fp16, [32, 352]> add_9 = add(x = add_5, y = mul_58)[name = string("add_9")];
            tensor<fp16, [32, 352]> mul_59 = mul(x = add_9, y = add_9)[name = string("mul_59")];
            tensor<int32, [1]> reduce_mean_12_axes_0 = const()[name = string("reduce_mean_12_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_12_keep_dims_0 = const()[name = string("reduce_mean_12_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_12 = reduce_mean(axes = reduce_mean_12_axes_0, keep_dims = reduce_mean_12_keep_dims_0, x = mul_59)[name = string("reduce_mean_12")];
            fp32 rsqrt_12_epsilon_0 = const()[name = string("rsqrt_12_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_12 = rsqrt(epsilon = rsqrt_12_epsilon_0, x = reduce_mean_12)[name = string("rsqrt_12")];
            tensor<fp16, [32, 352]> mul_60 = mul(x = add_9, y = rsqrt_12)[name = string("mul_60")];
            tensor<fp16, [352]> mul_61_y_0 = const()[name = string("mul_61_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2738944)))];
            tensor<fp16, [32, 352]> mul_61 = mul(x = mul_60, y = mul_61_y_0)[name = string("mul_61")];
            tensor<fp16, [32, 352]> mul_62 = mul(x = mul_61, y = mul_61)[name = string("mul_62")];
            tensor<int32, [1]> reduce_mean_13_axes_0 = const()[name = string("reduce_mean_13_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_13_keep_dims_0 = const()[name = string("reduce_mean_13_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_13 = reduce_mean(axes = reduce_mean_13_axes_0, keep_dims = reduce_mean_13_keep_dims_0, x = mul_62)[name = string("reduce_mean_13")];
            fp32 rsqrt_13_epsilon_0 = const()[name = string("rsqrt_13_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_13 = rsqrt(epsilon = rsqrt_13_epsilon_0, x = reduce_mean_13)[name = string("rsqrt_13")];
            tensor<fp16, [32, 352]> mul_63 = mul(x = mul_61, y = rsqrt_13)[name = string("mul_63")];
            tensor<fp16, [352]> mul_64_y_0 = const()[name = string("mul_64_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2739712)))];
            tensor<fp16, [32, 352]> mul_64 = mul(x = mul_63, y = mul_64_y_0)[name = string("mul_64")];
            tensor<fp16, [960, 352]> tern_1_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2740480))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_1_w1_weight_0_palettized")];
            tensor<fp16, [32, 960]> tern_1_w1 = linear(bias = linear_4_bias_0, weight = tern_1_w1_weight_0_palettized, x = mul_64)[name = string("tern_1_w1")];
            tensor<fp16, [960]> mul_65_y_0 = const()[name = string("mul_65_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2825024)))];
            tensor<fp16, [32, 960]> mul_65 = mul(x = tern_1_w1, y = mul_65_y_0)[name = string("mul_65")];
            tensor<fp16, [352]> mul_68_y_0 = const()[name = string("mul_68_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2827008)))];
            tensor<fp16, [32, 352]> mul_68 = mul(x = mul_63, y = mul_68_y_0)[name = string("mul_68")];
            tensor<fp16, [960, 352]> tern_1_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2827776))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_1_w3_weight_0_palettized")];
            tensor<fp16, [32, 960]> tern_1_w3 = linear(bias = linear_4_bias_0, weight = tern_1_w3_weight_0_palettized, x = mul_68)[name = string("tern_1_w3")];
            tensor<fp16, [960]> mul_69_y_0 = const()[name = string("mul_69_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2912320)))];
            tensor<fp16, [32, 960]> mul_69 = mul(x = tern_1_w3, y = mul_69_y_0)[name = string("mul_69")];
            fp16 mul_70_y_0 = const()[name = string("mul_70_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [32, 960]> mul_70 = mul(x = mul_65, y = mul_70_y_0)[name = string("mul_70")];
            tensor<fp16, [32, 960]> tanh_1 = tanh(x = mul_70)[name = string("tanh_1")];
            fp16 mul_71_x_0 = const()[name = string("mul_71_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [32, 960]> mul_71 = mul(x = mul_71_x_0, y = tanh_1)[name = string("mul_71")];
            fp16 add_10_x_0 = const()[name = string("add_10_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [32, 960]> add_10 = add(x = add_10_x_0, y = mul_71)[name = string("add_10")];
            tensor<fp16, [32, 960]> mul_72 = mul(x = mul_65, y = add_10)[name = string("mul_72")];
            tensor<fp16, [32, 960]> mul_73 = mul(x = mul_72, y = mul_69)[name = string("mul_73")];
            tensor<fp16, [32, 960]> mul_74 = mul(x = mul_73, y = mul_73)[name = string("mul_74")];
            tensor<int32, [1]> reduce_mean_15_axes_0 = const()[name = string("reduce_mean_15_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_15_keep_dims_0 = const()[name = string("reduce_mean_15_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_15 = reduce_mean(axes = reduce_mean_15_axes_0, keep_dims = reduce_mean_15_keep_dims_0, x = mul_74)[name = string("reduce_mean_15")];
            fp32 rsqrt_15_epsilon_0 = const()[name = string("rsqrt_15_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_15 = rsqrt(epsilon = rsqrt_15_epsilon_0, x = reduce_mean_15)[name = string("rsqrt_15")];
            tensor<fp16, [32, 960]> mul_75 = mul(x = mul_73, y = rsqrt_15)[name = string("mul_75")];
            tensor<fp16, [960]> mul_76_y_0 = const()[name = string("mul_76_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2914304)))];
            tensor<fp16, [32, 960]> mul_76 = mul(x = mul_75, y = mul_76_y_0)[name = string("mul_76")];
            tensor<fp16, [352, 960]> tern_1_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2916288))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_1_w2_weight_0_palettized")];
            tensor<fp16, [32, 352]> tern_1_w2 = linear(bias = linear_0_bias_0, weight = tern_1_w2_weight_0_palettized, x = mul_76)[name = string("tern_1_w2")];
            tensor<fp16, [352]> mul_77_y_0 = const()[name = string("mul_77_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3000832)))];
            tensor<fp16, [32, 352]> mul_77 = mul(x = tern_1_w2, y = mul_77_y_0)[name = string("mul_77")];
            tensor<fp16, [32, 352]> add_11 = add(x = add_9, y = mul_77)[name = string("add_11")];
            tensor<fp16, [32, 352]> mul_78 = mul(x = add_11, y = add_11)[name = string("mul_78")];
            tensor<int32, [1]> reduce_mean_16_axes_0 = const()[name = string("reduce_mean_16_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_16_keep_dims_0 = const()[name = string("reduce_mean_16_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_16 = reduce_mean(axes = reduce_mean_16_axes_0, keep_dims = reduce_mean_16_keep_dims_0, x = mul_78)[name = string("reduce_mean_16")];
            fp32 rsqrt_16_epsilon_0 = const()[name = string("rsqrt_16_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_16 = rsqrt(epsilon = rsqrt_16_epsilon_0, x = reduce_mean_16)[name = string("rsqrt_16")];
            tensor<fp16, [32, 352]> mul_79 = mul(x = add_11, y = rsqrt_16)[name = string("mul_79")];
            tensor<fp16, [352]> mul_80_y_0 = const()[name = string("mul_80_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3001600)))];
            tensor<fp16, [32, 352]> mul_80 = mul(x = mul_79, y = mul_80_y_0)[name = string("mul_80")];
            tensor<fp16, [32, 352]> mul_81 = mul(x = mul_80, y = mul_80)[name = string("mul_81")];
            tensor<int32, [1]> reduce_mean_17_axes_0 = const()[name = string("reduce_mean_17_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_17_keep_dims_0 = const()[name = string("reduce_mean_17_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_17 = reduce_mean(axes = reduce_mean_17_axes_0, keep_dims = reduce_mean_17_keep_dims_0, x = mul_81)[name = string("reduce_mean_17")];
            fp32 rsqrt_17_epsilon_0 = const()[name = string("rsqrt_17_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_17 = rsqrt(epsilon = rsqrt_17_epsilon_0, x = reduce_mean_17)[name = string("rsqrt_17")];
            tensor<fp16, [32, 352]> mul_82 = mul(x = mul_80, y = rsqrt_17)[name = string("mul_82")];
            tensor<fp16, [352]> mul_83_y_0 = const()[name = string("mul_83_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3002368)))];
            tensor<fp16, [32, 352]> mul_83 = mul(x = mul_82, y = mul_83_y_0)[name = string("mul_83")];
            tensor<fp16, [352, 352]> tern_2_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3003136))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_2_q_weight_0_palettized")];
            tensor<fp16, [32, 352]> tern_2_q = linear(bias = linear_0_bias_0, weight = tern_2_q_weight_0_palettized, x = mul_83)[name = string("tern_2_q")];
            tensor<fp16, [352]> mul_84_y_0 = const()[name = string("mul_84_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3034176)))];
            tensor<fp16, [32, 352]> mul_84 = mul(x = tern_2_q, y = mul_84_y_0)[name = string("mul_84")];
            tensor<int32, [3]> reshape_18_shape_0 = const()[name = string("reshape_18_shape_0"), val = tensor<int32, [3]>([32, 8, 44])];
            tensor<fp16, [32, 8, 44]> reshape_18 = reshape(shape = reshape_18_shape_0, x = mul_84)[name = string("reshape_18")];
            tensor<int32, [3]> transpose_8_perm_0 = const()[name = string("transpose_8_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_87_y_0 = const()[name = string("mul_87_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3034944)))];
            tensor<fp16, [32, 352]> mul_87 = mul(x = mul_82, y = mul_87_y_0)[name = string("mul_87")];
            tensor<fp16, [88, 352]> tern_2_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3035712))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_2_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_2_k_bias_0 = const()[name = string("tern_2_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [32, 88]> tern_2_k = linear(bias = tern_2_k_bias_0, weight = tern_2_k_weight_0_palettized, x = mul_87)[name = string("tern_2_k")];
            tensor<fp16, [88]> mul_88_y_0 = const()[name = string("mul_88_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3043520)))];
            tensor<fp16, [32, 88]> mul_88 = mul(x = tern_2_k, y = mul_88_y_0)[name = string("mul_88")];
            tensor<int32, [3]> reshape_19_shape_0 = const()[name = string("reshape_19_shape_0"), val = tensor<int32, [3]>([32, 2, 44])];
            tensor<fp16, [32, 2, 44]> reshape_19 = reshape(shape = reshape_19_shape_0, x = mul_88)[name = string("reshape_19")];
            tensor<int32, [3]> transpose_9_perm_0 = const()[name = string("transpose_9_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_91_y_0 = const()[name = string("mul_91_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3043776)))];
            tensor<fp16, [32, 352]> mul_91 = mul(x = mul_82, y = mul_91_y_0)[name = string("mul_91")];
            tensor<fp16, [88, 352]> tern_2_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3044544))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_2_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_2_v_bias_0 = const()[name = string("tern_2_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [32, 88]> tern_2_v = linear(bias = tern_2_v_bias_0, weight = tern_2_v_weight_0_palettized, x = mul_91)[name = string("tern_2_v")];
            tensor<fp16, [88]> mul_92_y_0 = const()[name = string("mul_92_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3052352)))];
            tensor<fp16, [32, 88]> mul_92 = mul(x = tern_2_v, y = mul_92_y_0)[name = string("mul_92")];
            tensor<int32, [3]> reshape_20_shape_0 = const()[name = string("reshape_20_shape_0"), val = tensor<int32, [3]>([32, 2, 44])];
            tensor<fp16, [32, 2, 44]> reshape_20 = reshape(shape = reshape_20_shape_0, x = mul_92)[name = string("reshape_20")];
            tensor<int32, [3]> transpose_10_perm_0 = const()[name = string("transpose_10_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 32, 44]> transpose_8 = transpose(perm = transpose_8_perm_0, x = reshape_18)[name = string("transpose_55")];
            tensor<fp16, [8, 32, 44]> mul_93 = mul(x = transpose_8, y = transpose_8)[name = string("mul_93")];
            tensor<int32, [1]> reduce_mean_20_axes_0 = const()[name = string("reduce_mean_20_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_20_keep_dims_0 = const()[name = string("reduce_mean_20_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 32, 1]> reduce_mean_20 = reduce_mean(axes = reduce_mean_20_axes_0, keep_dims = reduce_mean_20_keep_dims_0, x = mul_93)[name = string("reduce_mean_20")];
            fp32 rsqrt_20_epsilon_0 = const()[name = string("rsqrt_20_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 32, 1]> rsqrt_20 = rsqrt(epsilon = rsqrt_20_epsilon_0, x = reduce_mean_20)[name = string("rsqrt_20")];
            tensor<fp16, [8, 32, 44]> mul_94 = mul(x = transpose_8, y = rsqrt_20)[name = string("mul_94")];
            tensor<fp16, [44]> mul_95_y_0 = const()[name = string("mul_95_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3052608)))];
            tensor<fp16, [8, 32, 44]> mul_95 = mul(x = mul_94, y = mul_95_y_0)[name = string("mul_95")];
            tensor<int32, [3]> slice_by_index_8_begin_0 = const()[name = string("slice_by_index_8_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_8_end_0 = const()[name = string("slice_by_index_8_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_8_end_mask_0 = const()[name = string("slice_by_index_8_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 32, 22]> slice_by_index_8 = slice_by_index(begin = slice_by_index_8_begin_0, end = slice_by_index_8_end_0, end_mask = slice_by_index_8_end_mask_0, x = mul_95)[name = string("slice_by_index_8")];
            tensor<int32, [3]> slice_by_index_9_begin_0 = const()[name = string("slice_by_index_9_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_9_end_0 = const()[name = string("slice_by_index_9_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_9_end_mask_0 = const()[name = string("slice_by_index_9_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 32, 22]> slice_by_index_9 = slice_by_index(begin = slice_by_index_9_begin_0, end = slice_by_index_9_end_0, end_mask = slice_by_index_9_end_mask_0, x = mul_95)[name = string("slice_by_index_9")];
            int32 concat_4_axis_0 = const()[name = string("concat_4_axis_0"), val = int32(-1)];
            bool concat_4_interleave_0 = const()[name = string("concat_4_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 32, 44]> concat_4 = concat(axis = concat_4_axis_0, interleave = concat_4_interleave_0, values = (slice_by_index_9, slice_by_index_8))[name = string("concat_4")];
            tensor<fp16, [44]> mul_96_y_0 = const()[name = string("mul_96_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 32, 44]> mul_96 = mul(x = concat_4, y = mul_96_y_0)[name = string("mul_96")];
            tensor<fp16, [8, 32, 44]> mul_97 = mul(x = mul_95, y = mul_11_y_0)[name = string("mul_97")];
            tensor<fp16, [8, 32, 44]> mul_98 = mul(x = mul_96, y = mul_12_y_0)[name = string("mul_98")];
            tensor<fp16, [8, 32, 44]> add_12 = add(x = mul_97, y = mul_98)[name = string("add_12")];
            tensor<fp16, [2, 32, 44]> transpose_9 = transpose(perm = transpose_9_perm_0, x = reshape_19)[name = string("transpose_54")];
            tensor<fp16, [2, 32, 44]> mul_99 = mul(x = transpose_9, y = transpose_9)[name = string("mul_99")];
            tensor<int32, [1]> reduce_mean_21_axes_0 = const()[name = string("reduce_mean_21_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_21_keep_dims_0 = const()[name = string("reduce_mean_21_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 32, 1]> reduce_mean_21 = reduce_mean(axes = reduce_mean_21_axes_0, keep_dims = reduce_mean_21_keep_dims_0, x = mul_99)[name = string("reduce_mean_21")];
            fp32 rsqrt_21_epsilon_0 = const()[name = string("rsqrt_21_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 32, 1]> rsqrt_21 = rsqrt(epsilon = rsqrt_21_epsilon_0, x = reduce_mean_21)[name = string("rsqrt_21")];
            tensor<fp16, [2, 32, 44]> mul_100 = mul(x = transpose_9, y = rsqrt_21)[name = string("mul_100")];
            tensor<fp16, [44]> mul_101_y_0 = const()[name = string("mul_101_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3052800)))];
            tensor<fp16, [2, 32, 44]> mul_101 = mul(x = mul_100, y = mul_101_y_0)[name = string("mul_101")];
            tensor<int32, [3]> slice_by_index_10_begin_0 = const()[name = string("slice_by_index_10_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_10_end_0 = const()[name = string("slice_by_index_10_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_10_end_mask_0 = const()[name = string("slice_by_index_10_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 32, 22]> slice_by_index_10 = slice_by_index(begin = slice_by_index_10_begin_0, end = slice_by_index_10_end_0, end_mask = slice_by_index_10_end_mask_0, x = mul_101)[name = string("slice_by_index_10")];
            tensor<int32, [3]> slice_by_index_11_begin_0 = const()[name = string("slice_by_index_11_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_11_end_0 = const()[name = string("slice_by_index_11_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_11_end_mask_0 = const()[name = string("slice_by_index_11_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 32, 22]> slice_by_index_11 = slice_by_index(begin = slice_by_index_11_begin_0, end = slice_by_index_11_end_0, end_mask = slice_by_index_11_end_mask_0, x = mul_101)[name = string("slice_by_index_11")];
            int32 concat_5_axis_0 = const()[name = string("concat_5_axis_0"), val = int32(-1)];
            bool concat_5_interleave_0 = const()[name = string("concat_5_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 32, 44]> concat_5 = concat(axis = concat_5_axis_0, interleave = concat_5_interleave_0, values = (slice_by_index_11, slice_by_index_10))[name = string("concat_5")];
            tensor<fp16, [44]> mul_102_y_0 = const()[name = string("mul_102_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 32, 44]> mul_102 = mul(x = concat_5, y = mul_102_y_0)[name = string("mul_102")];
            tensor<fp16, [2, 32, 44]> mul_103 = mul(x = mul_101, y = mul_11_y_0)[name = string("mul_103")];
            tensor<fp16, [2, 32, 44]> mul_104 = mul(x = mul_102, y = mul_12_y_0)[name = string("mul_104")];
            tensor<fp16, [2, 32, 44]> add_13 = add(x = mul_103, y = mul_104)[name = string("add_13")];
            tensor<int32, [4]> reshape_21_shape_0 = const()[name = string("reshape_21_shape_0"), val = tensor<int32, [4]>([2, 1, 32, 44])];
            tensor<fp16, [2, 1, 32, 44]> reshape_21 = reshape(shape = reshape_21_shape_0, x = add_13)[name = string("reshape_21")];
            tensor<int32, [4]> tile_4_reps_0 = const()[name = string("tile_4_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 32, 44]> tile_4 = tile(reps = tile_4_reps_0, x = reshape_21)[name = string("tile_4")];
            tensor<int32, [3]> reshape_22_shape_0 = const()[name = string("reshape_22_shape_0"), val = tensor<int32, [3]>([8, 32, 44])];
            tensor<fp16, [8, 32, 44]> reshape_22 = reshape(shape = reshape_22_shape_0, x = tile_4)[name = string("reshape_22")];
            tensor<int32, [4]> reshape_23_shape_0 = const()[name = string("reshape_23_shape_0"), val = tensor<int32, [4]>([2, 1, 32, 44])];
            tensor<fp16, [2, 32, 44]> transpose_10 = transpose(perm = transpose_10_perm_0, x = reshape_20)[name = string("transpose_53")];
            tensor<fp16, [2, 1, 32, 44]> reshape_23 = reshape(shape = reshape_23_shape_0, x = transpose_10)[name = string("reshape_23")];
            tensor<int32, [4]> tile_5_reps_0 = const()[name = string("tile_5_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 32, 44]> tile_5 = tile(reps = tile_5_reps_0, x = reshape_23)[name = string("tile_5")];
            tensor<int32, [3]> reshape_24_shape_0 = const()[name = string("reshape_24_shape_0"), val = tensor<int32, [3]>([8, 32, 44])];
            tensor<fp16, [8, 32, 44]> reshape_24 = reshape(shape = reshape_24_shape_0, x = tile_5)[name = string("reshape_24")];
            fp16 mul_105_y_0 = const()[name = string("mul_105_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 32, 44]> mul_105 = mul(x = add_12, y = mul_105_y_0)[name = string("mul_105")];
            bool matmul_4_transpose_y_0 = const()[name = string("matmul_4_transpose_y_0"), val = bool(true)];
            bool matmul_4_transpose_x_0 = const()[name = string("matmul_4_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 32, 32]> matmul_4 = matmul(transpose_x = matmul_4_transpose_x_0, transpose_y = matmul_4_transpose_y_0, x = mul_105, y = reshape_22)[name = string("matmul_4")];
            tensor<fp16, [8, 32, 32]> add_14 = add(x = matmul_4, y = reshape_1)[name = string("add_14")];
            int32 softmax_2_axis_0 = const()[name = string("softmax_2_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 32, 32]> softmax_2 = softmax(axis = softmax_2_axis_0, x = add_14)[name = string("softmax_2")];
            bool matmul_5_transpose_x_0 = const()[name = string("matmul_5_transpose_x_0"), val = bool(false)];
            bool matmul_5_transpose_y_0 = const()[name = string("matmul_5_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 32, 44]> matmul_5 = matmul(transpose_x = matmul_5_transpose_x_0, transpose_y = matmul_5_transpose_y_0, x = softmax_2, y = reshape_24)[name = string("matmul_5")];
            tensor<int32, [3]> transpose_11_perm_0 = const()[name = string("transpose_11_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_25_shape_0 = const()[name = string("reshape_25_shape_0"), val = tensor<int32, [2]>([32, 352])];
            tensor<fp16, [32, 8, 44]> transpose_11 = transpose(perm = transpose_11_perm_0, x = matmul_5)[name = string("transpose_52")];
            tensor<fp16, [32, 352]> reshape_25 = reshape(shape = reshape_25_shape_0, x = transpose_11)[name = string("reshape_25")];
            tensor<fp16, [32, 352]> mul_106 = mul(x = reshape_25, y = reshape_25)[name = string("mul_106")];
            tensor<int32, [1]> reduce_mean_22_axes_0 = const()[name = string("reduce_mean_22_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_22_keep_dims_0 = const()[name = string("reduce_mean_22_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_22 = reduce_mean(axes = reduce_mean_22_axes_0, keep_dims = reduce_mean_22_keep_dims_0, x = mul_106)[name = string("reduce_mean_22")];
            fp32 rsqrt_22_epsilon_0 = const()[name = string("rsqrt_22_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_22 = rsqrt(epsilon = rsqrt_22_epsilon_0, x = reduce_mean_22)[name = string("rsqrt_22")];
            tensor<fp16, [32, 352]> mul_107 = mul(x = reshape_25, y = rsqrt_22)[name = string("mul_107")];
            tensor<fp16, [352]> mul_108_y_0 = const()[name = string("mul_108_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3052992)))];
            tensor<fp16, [32, 352]> mul_108 = mul(x = mul_107, y = mul_108_y_0)[name = string("mul_108")];
            tensor<fp16, [352, 352]> tern_2_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3053760))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_2_o_weight_0_palettized")];
            tensor<fp16, [32, 352]> tern_2_o = linear(bias = linear_0_bias_0, weight = tern_2_o_weight_0_palettized, x = mul_108)[name = string("tern_2_o")];
            tensor<fp16, [352]> mul_109_y_0 = const()[name = string("mul_109_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3084800)))];
            tensor<fp16, [32, 352]> mul_109 = mul(x = tern_2_o, y = mul_109_y_0)[name = string("mul_109")];
            tensor<fp16, [32, 352]> add_15 = add(x = add_11, y = mul_109)[name = string("add_15")];
            tensor<fp16, [32, 352]> mul_110 = mul(x = add_15, y = add_15)[name = string("mul_110")];
            tensor<int32, [1]> reduce_mean_23_axes_0 = const()[name = string("reduce_mean_23_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_23_keep_dims_0 = const()[name = string("reduce_mean_23_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_23 = reduce_mean(axes = reduce_mean_23_axes_0, keep_dims = reduce_mean_23_keep_dims_0, x = mul_110)[name = string("reduce_mean_23")];
            fp32 rsqrt_23_epsilon_0 = const()[name = string("rsqrt_23_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_23 = rsqrt(epsilon = rsqrt_23_epsilon_0, x = reduce_mean_23)[name = string("rsqrt_23")];
            tensor<fp16, [32, 352]> mul_111 = mul(x = add_15, y = rsqrt_23)[name = string("mul_111")];
            tensor<fp16, [352]> mul_112_y_0 = const()[name = string("mul_112_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3085568)))];
            tensor<fp16, [32, 352]> mul_112 = mul(x = mul_111, y = mul_112_y_0)[name = string("mul_112")];
            tensor<fp16, [32, 352]> mul_113 = mul(x = mul_112, y = mul_112)[name = string("mul_113")];
            tensor<int32, [1]> reduce_mean_24_axes_0 = const()[name = string("reduce_mean_24_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_24_keep_dims_0 = const()[name = string("reduce_mean_24_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_24 = reduce_mean(axes = reduce_mean_24_axes_0, keep_dims = reduce_mean_24_keep_dims_0, x = mul_113)[name = string("reduce_mean_24")];
            fp32 rsqrt_24_epsilon_0 = const()[name = string("rsqrt_24_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_24 = rsqrt(epsilon = rsqrt_24_epsilon_0, x = reduce_mean_24)[name = string("rsqrt_24")];
            tensor<fp16, [32, 352]> mul_114 = mul(x = mul_112, y = rsqrt_24)[name = string("mul_114")];
            tensor<fp16, [352]> mul_115_y_0 = const()[name = string("mul_115_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3086336)))];
            tensor<fp16, [32, 352]> mul_115 = mul(x = mul_114, y = mul_115_y_0)[name = string("mul_115")];
            tensor<fp16, [960, 352]> tern_2_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3087104))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_2_w1_weight_0_palettized")];
            tensor<fp16, [32, 960]> tern_2_w1 = linear(bias = linear_4_bias_0, weight = tern_2_w1_weight_0_palettized, x = mul_115)[name = string("tern_2_w1")];
            tensor<fp16, [960]> mul_116_y_0 = const()[name = string("mul_116_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3171648)))];
            tensor<fp16, [32, 960]> mul_116 = mul(x = tern_2_w1, y = mul_116_y_0)[name = string("mul_116")];
            tensor<fp16, [352]> mul_119_y_0 = const()[name = string("mul_119_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3173632)))];
            tensor<fp16, [32, 352]> mul_119 = mul(x = mul_114, y = mul_119_y_0)[name = string("mul_119")];
            tensor<fp16, [960, 352]> tern_2_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3174400))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_2_w3_weight_0_palettized")];
            tensor<fp16, [32, 960]> tern_2_w3 = linear(bias = linear_4_bias_0, weight = tern_2_w3_weight_0_palettized, x = mul_119)[name = string("tern_2_w3")];
            tensor<fp16, [960]> mul_120_y_0 = const()[name = string("mul_120_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3258944)))];
            tensor<fp16, [32, 960]> mul_120 = mul(x = tern_2_w3, y = mul_120_y_0)[name = string("mul_120")];
            fp16 mul_121_y_0 = const()[name = string("mul_121_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [32, 960]> mul_121 = mul(x = mul_116, y = mul_121_y_0)[name = string("mul_121")];
            tensor<fp16, [32, 960]> tanh_2 = tanh(x = mul_121)[name = string("tanh_2")];
            fp16 mul_122_x_0 = const()[name = string("mul_122_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [32, 960]> mul_122 = mul(x = mul_122_x_0, y = tanh_2)[name = string("mul_122")];
            fp16 add_16_x_0 = const()[name = string("add_16_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [32, 960]> add_16 = add(x = add_16_x_0, y = mul_122)[name = string("add_16")];
            tensor<fp16, [32, 960]> mul_123 = mul(x = mul_116, y = add_16)[name = string("mul_123")];
            tensor<fp16, [32, 960]> mul_124 = mul(x = mul_123, y = mul_120)[name = string("mul_124")];
            tensor<fp16, [32, 960]> mul_125 = mul(x = mul_124, y = mul_124)[name = string("mul_125")];
            tensor<int32, [1]> reduce_mean_26_axes_0 = const()[name = string("reduce_mean_26_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_26_keep_dims_0 = const()[name = string("reduce_mean_26_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_26 = reduce_mean(axes = reduce_mean_26_axes_0, keep_dims = reduce_mean_26_keep_dims_0, x = mul_125)[name = string("reduce_mean_26")];
            fp32 rsqrt_26_epsilon_0 = const()[name = string("rsqrt_26_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_26 = rsqrt(epsilon = rsqrt_26_epsilon_0, x = reduce_mean_26)[name = string("rsqrt_26")];
            tensor<fp16, [32, 960]> mul_126 = mul(x = mul_124, y = rsqrt_26)[name = string("mul_126")];
            tensor<fp16, [960]> mul_127_y_0 = const()[name = string("mul_127_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3260928)))];
            tensor<fp16, [32, 960]> mul_127 = mul(x = mul_126, y = mul_127_y_0)[name = string("mul_127")];
            tensor<fp16, [352, 960]> tern_2_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3262912))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_2_w2_weight_0_palettized")];
            tensor<fp16, [32, 352]> tern_2_w2 = linear(bias = linear_0_bias_0, weight = tern_2_w2_weight_0_palettized, x = mul_127)[name = string("tern_2_w2")];
            tensor<fp16, [352]> mul_128_y_0 = const()[name = string("mul_128_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3347456)))];
            tensor<fp16, [32, 352]> mul_128 = mul(x = tern_2_w2, y = mul_128_y_0)[name = string("mul_128")];
            tensor<fp16, [32, 352]> add_17 = add(x = add_15, y = mul_128)[name = string("add_17")];
            tensor<fp16, [32, 352]> mul_129 = mul(x = add_17, y = add_17)[name = string("mul_129")];
            tensor<int32, [1]> reduce_mean_27_axes_0 = const()[name = string("reduce_mean_27_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_27_keep_dims_0 = const()[name = string("reduce_mean_27_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_27 = reduce_mean(axes = reduce_mean_27_axes_0, keep_dims = reduce_mean_27_keep_dims_0, x = mul_129)[name = string("reduce_mean_27")];
            fp32 rsqrt_27_epsilon_0 = const()[name = string("rsqrt_27_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_27 = rsqrt(epsilon = rsqrt_27_epsilon_0, x = reduce_mean_27)[name = string("rsqrt_27")];
            tensor<fp16, [32, 352]> mul_130 = mul(x = add_17, y = rsqrt_27)[name = string("mul_130")];
            tensor<fp16, [352]> mul_131_y_0 = const()[name = string("mul_131_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3348224)))];
            tensor<fp16, [32, 352]> mul_131 = mul(x = mul_130, y = mul_131_y_0)[name = string("mul_131")];
            tensor<fp16, [32, 352]> mul_132 = mul(x = mul_131, y = mul_131)[name = string("mul_132")];
            tensor<int32, [1]> reduce_mean_28_axes_0 = const()[name = string("reduce_mean_28_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_28_keep_dims_0 = const()[name = string("reduce_mean_28_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_28 = reduce_mean(axes = reduce_mean_28_axes_0, keep_dims = reduce_mean_28_keep_dims_0, x = mul_132)[name = string("reduce_mean_28")];
            fp32 rsqrt_28_epsilon_0 = const()[name = string("rsqrt_28_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_28 = rsqrt(epsilon = rsqrt_28_epsilon_0, x = reduce_mean_28)[name = string("rsqrt_28")];
            tensor<fp16, [32, 352]> mul_133 = mul(x = mul_131, y = rsqrt_28)[name = string("mul_133")];
            tensor<fp16, [352]> mul_134_y_0 = const()[name = string("mul_134_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3348992)))];
            tensor<fp16, [32, 352]> mul_134 = mul(x = mul_133, y = mul_134_y_0)[name = string("mul_134")];
            tensor<fp16, [352, 352]> tern_3_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3349760))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_3_q_weight_0_palettized")];
            tensor<fp16, [32, 352]> tern_3_q = linear(bias = linear_0_bias_0, weight = tern_3_q_weight_0_palettized, x = mul_134)[name = string("tern_3_q")];
            tensor<fp16, [352]> mul_135_y_0 = const()[name = string("mul_135_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3380800)))];
            tensor<fp16, [32, 352]> mul_135 = mul(x = tern_3_q, y = mul_135_y_0)[name = string("mul_135")];
            tensor<int32, [3]> reshape_26_shape_0 = const()[name = string("reshape_26_shape_0"), val = tensor<int32, [3]>([32, 8, 44])];
            tensor<fp16, [32, 8, 44]> reshape_26 = reshape(shape = reshape_26_shape_0, x = mul_135)[name = string("reshape_26")];
            tensor<int32, [3]> transpose_12_perm_0 = const()[name = string("transpose_12_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_138_y_0 = const()[name = string("mul_138_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3381568)))];
            tensor<fp16, [32, 352]> mul_138 = mul(x = mul_133, y = mul_138_y_0)[name = string("mul_138")];
            tensor<fp16, [88, 352]> tern_3_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3382336))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_3_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_3_k_bias_0 = const()[name = string("tern_3_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [32, 88]> tern_3_k = linear(bias = tern_3_k_bias_0, weight = tern_3_k_weight_0_palettized, x = mul_138)[name = string("tern_3_k")];
            tensor<fp16, [88]> mul_139_y_0 = const()[name = string("mul_139_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3390144)))];
            tensor<fp16, [32, 88]> mul_139 = mul(x = tern_3_k, y = mul_139_y_0)[name = string("mul_139")];
            tensor<int32, [3]> reshape_27_shape_0 = const()[name = string("reshape_27_shape_0"), val = tensor<int32, [3]>([32, 2, 44])];
            tensor<fp16, [32, 2, 44]> reshape_27 = reshape(shape = reshape_27_shape_0, x = mul_139)[name = string("reshape_27")];
            tensor<int32, [3]> transpose_13_perm_0 = const()[name = string("transpose_13_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_142_y_0 = const()[name = string("mul_142_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3390400)))];
            tensor<fp16, [32, 352]> mul_142 = mul(x = mul_133, y = mul_142_y_0)[name = string("mul_142")];
            tensor<fp16, [88, 352]> tern_3_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3391168))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_3_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_3_v_bias_0 = const()[name = string("tern_3_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [32, 88]> tern_3_v = linear(bias = tern_3_v_bias_0, weight = tern_3_v_weight_0_palettized, x = mul_142)[name = string("tern_3_v")];
            tensor<fp16, [88]> mul_143_y_0 = const()[name = string("mul_143_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3398976)))];
            tensor<fp16, [32, 88]> mul_143 = mul(x = tern_3_v, y = mul_143_y_0)[name = string("mul_143")];
            tensor<int32, [3]> reshape_28_shape_0 = const()[name = string("reshape_28_shape_0"), val = tensor<int32, [3]>([32, 2, 44])];
            tensor<fp16, [32, 2, 44]> reshape_28 = reshape(shape = reshape_28_shape_0, x = mul_143)[name = string("reshape_28")];
            tensor<int32, [3]> transpose_14_perm_0 = const()[name = string("transpose_14_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 32, 44]> transpose_12 = transpose(perm = transpose_12_perm_0, x = reshape_26)[name = string("transpose_51")];
            tensor<fp16, [8, 32, 44]> mul_144 = mul(x = transpose_12, y = transpose_12)[name = string("mul_144")];
            tensor<int32, [1]> reduce_mean_31_axes_0 = const()[name = string("reduce_mean_31_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_31_keep_dims_0 = const()[name = string("reduce_mean_31_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 32, 1]> reduce_mean_31 = reduce_mean(axes = reduce_mean_31_axes_0, keep_dims = reduce_mean_31_keep_dims_0, x = mul_144)[name = string("reduce_mean_31")];
            fp32 rsqrt_31_epsilon_0 = const()[name = string("rsqrt_31_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 32, 1]> rsqrt_31 = rsqrt(epsilon = rsqrt_31_epsilon_0, x = reduce_mean_31)[name = string("rsqrt_31")];
            tensor<fp16, [8, 32, 44]> mul_145 = mul(x = transpose_12, y = rsqrt_31)[name = string("mul_145")];
            tensor<fp16, [44]> mul_146_y_0 = const()[name = string("mul_146_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3399232)))];
            tensor<fp16, [8, 32, 44]> mul_146 = mul(x = mul_145, y = mul_146_y_0)[name = string("mul_146")];
            tensor<int32, [3]> slice_by_index_12_begin_0 = const()[name = string("slice_by_index_12_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_12_end_0 = const()[name = string("slice_by_index_12_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_12_end_mask_0 = const()[name = string("slice_by_index_12_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 32, 22]> slice_by_index_12 = slice_by_index(begin = slice_by_index_12_begin_0, end = slice_by_index_12_end_0, end_mask = slice_by_index_12_end_mask_0, x = mul_146)[name = string("slice_by_index_12")];
            tensor<int32, [3]> slice_by_index_13_begin_0 = const()[name = string("slice_by_index_13_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_13_end_0 = const()[name = string("slice_by_index_13_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_13_end_mask_0 = const()[name = string("slice_by_index_13_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 32, 22]> slice_by_index_13 = slice_by_index(begin = slice_by_index_13_begin_0, end = slice_by_index_13_end_0, end_mask = slice_by_index_13_end_mask_0, x = mul_146)[name = string("slice_by_index_13")];
            int32 concat_6_axis_0 = const()[name = string("concat_6_axis_0"), val = int32(-1)];
            bool concat_6_interleave_0 = const()[name = string("concat_6_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 32, 44]> concat_6 = concat(axis = concat_6_axis_0, interleave = concat_6_interleave_0, values = (slice_by_index_13, slice_by_index_12))[name = string("concat_6")];
            tensor<fp16, [44]> mul_147_y_0 = const()[name = string("mul_147_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 32, 44]> mul_147 = mul(x = concat_6, y = mul_147_y_0)[name = string("mul_147")];
            tensor<fp16, [8, 32, 44]> mul_148 = mul(x = mul_146, y = mul_11_y_0)[name = string("mul_148")];
            tensor<fp16, [8, 32, 44]> mul_149 = mul(x = mul_147, y = mul_12_y_0)[name = string("mul_149")];
            tensor<fp16, [8, 32, 44]> add_18 = add(x = mul_148, y = mul_149)[name = string("add_18")];
            tensor<fp16, [2, 32, 44]> transpose_13 = transpose(perm = transpose_13_perm_0, x = reshape_27)[name = string("transpose_50")];
            tensor<fp16, [2, 32, 44]> mul_150 = mul(x = transpose_13, y = transpose_13)[name = string("mul_150")];
            tensor<int32, [1]> reduce_mean_32_axes_0 = const()[name = string("reduce_mean_32_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_32_keep_dims_0 = const()[name = string("reduce_mean_32_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 32, 1]> reduce_mean_32 = reduce_mean(axes = reduce_mean_32_axes_0, keep_dims = reduce_mean_32_keep_dims_0, x = mul_150)[name = string("reduce_mean_32")];
            fp32 rsqrt_32_epsilon_0 = const()[name = string("rsqrt_32_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 32, 1]> rsqrt_32 = rsqrt(epsilon = rsqrt_32_epsilon_0, x = reduce_mean_32)[name = string("rsqrt_32")];
            tensor<fp16, [2, 32, 44]> mul_151 = mul(x = transpose_13, y = rsqrt_32)[name = string("mul_151")];
            tensor<fp16, [44]> mul_152_y_0 = const()[name = string("mul_152_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3399424)))];
            tensor<fp16, [2, 32, 44]> mul_152 = mul(x = mul_151, y = mul_152_y_0)[name = string("mul_152")];
            tensor<int32, [3]> slice_by_index_14_begin_0 = const()[name = string("slice_by_index_14_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_14_end_0 = const()[name = string("slice_by_index_14_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_14_end_mask_0 = const()[name = string("slice_by_index_14_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 32, 22]> slice_by_index_14 = slice_by_index(begin = slice_by_index_14_begin_0, end = slice_by_index_14_end_0, end_mask = slice_by_index_14_end_mask_0, x = mul_152)[name = string("slice_by_index_14")];
            tensor<int32, [3]> slice_by_index_15_begin_0 = const()[name = string("slice_by_index_15_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_15_end_0 = const()[name = string("slice_by_index_15_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_15_end_mask_0 = const()[name = string("slice_by_index_15_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 32, 22]> slice_by_index_15 = slice_by_index(begin = slice_by_index_15_begin_0, end = slice_by_index_15_end_0, end_mask = slice_by_index_15_end_mask_0, x = mul_152)[name = string("slice_by_index_15")];
            int32 concat_7_axis_0 = const()[name = string("concat_7_axis_0"), val = int32(-1)];
            bool concat_7_interleave_0 = const()[name = string("concat_7_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 32, 44]> concat_7 = concat(axis = concat_7_axis_0, interleave = concat_7_interleave_0, values = (slice_by_index_15, slice_by_index_14))[name = string("concat_7")];
            tensor<fp16, [44]> mul_153_y_0 = const()[name = string("mul_153_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 32, 44]> mul_153 = mul(x = concat_7, y = mul_153_y_0)[name = string("mul_153")];
            tensor<fp16, [2, 32, 44]> mul_154 = mul(x = mul_152, y = mul_11_y_0)[name = string("mul_154")];
            tensor<fp16, [2, 32, 44]> mul_155 = mul(x = mul_153, y = mul_12_y_0)[name = string("mul_155")];
            tensor<fp16, [2, 32, 44]> add_19 = add(x = mul_154, y = mul_155)[name = string("add_19")];
            tensor<int32, [4]> reshape_29_shape_0 = const()[name = string("reshape_29_shape_0"), val = tensor<int32, [4]>([2, 1, 32, 44])];
            tensor<fp16, [2, 1, 32, 44]> reshape_29 = reshape(shape = reshape_29_shape_0, x = add_19)[name = string("reshape_29")];
            tensor<int32, [4]> tile_6_reps_0 = const()[name = string("tile_6_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 32, 44]> tile_6 = tile(reps = tile_6_reps_0, x = reshape_29)[name = string("tile_6")];
            tensor<int32, [3]> reshape_30_shape_0 = const()[name = string("reshape_30_shape_0"), val = tensor<int32, [3]>([8, 32, 44])];
            tensor<fp16, [8, 32, 44]> reshape_30 = reshape(shape = reshape_30_shape_0, x = tile_6)[name = string("reshape_30")];
            tensor<int32, [4]> reshape_31_shape_0 = const()[name = string("reshape_31_shape_0"), val = tensor<int32, [4]>([2, 1, 32, 44])];
            tensor<fp16, [2, 32, 44]> transpose_14 = transpose(perm = transpose_14_perm_0, x = reshape_28)[name = string("transpose_49")];
            tensor<fp16, [2, 1, 32, 44]> reshape_31 = reshape(shape = reshape_31_shape_0, x = transpose_14)[name = string("reshape_31")];
            tensor<int32, [4]> tile_7_reps_0 = const()[name = string("tile_7_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 32, 44]> tile_7 = tile(reps = tile_7_reps_0, x = reshape_31)[name = string("tile_7")];
            tensor<int32, [3]> reshape_32_shape_0 = const()[name = string("reshape_32_shape_0"), val = tensor<int32, [3]>([8, 32, 44])];
            tensor<fp16, [8, 32, 44]> reshape_32 = reshape(shape = reshape_32_shape_0, x = tile_7)[name = string("reshape_32")];
            fp16 mul_156_y_0 = const()[name = string("mul_156_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 32, 44]> mul_156 = mul(x = add_18, y = mul_156_y_0)[name = string("mul_156")];
            bool matmul_6_transpose_y_0 = const()[name = string("matmul_6_transpose_y_0"), val = bool(true)];
            bool matmul_6_transpose_x_0 = const()[name = string("matmul_6_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 32, 32]> matmul_6 = matmul(transpose_x = matmul_6_transpose_x_0, transpose_y = matmul_6_transpose_y_0, x = mul_156, y = reshape_30)[name = string("matmul_6")];
            tensor<fp16, [8, 32, 32]> add_20 = add(x = matmul_6, y = reshape_1)[name = string("add_20")];
            int32 softmax_3_axis_0 = const()[name = string("softmax_3_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 32, 32]> softmax_3 = softmax(axis = softmax_3_axis_0, x = add_20)[name = string("softmax_3")];
            bool matmul_7_transpose_x_0 = const()[name = string("matmul_7_transpose_x_0"), val = bool(false)];
            bool matmul_7_transpose_y_0 = const()[name = string("matmul_7_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 32, 44]> matmul_7 = matmul(transpose_x = matmul_7_transpose_x_0, transpose_y = matmul_7_transpose_y_0, x = softmax_3, y = reshape_32)[name = string("matmul_7")];
            tensor<int32, [3]> transpose_15_perm_0 = const()[name = string("transpose_15_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_33_shape_0 = const()[name = string("reshape_33_shape_0"), val = tensor<int32, [2]>([32, 352])];
            tensor<fp16, [32, 8, 44]> transpose_15 = transpose(perm = transpose_15_perm_0, x = matmul_7)[name = string("transpose_48")];
            tensor<fp16, [32, 352]> reshape_33 = reshape(shape = reshape_33_shape_0, x = transpose_15)[name = string("reshape_33")];
            tensor<fp16, [32, 352]> mul_157 = mul(x = reshape_33, y = reshape_33)[name = string("mul_157")];
            tensor<int32, [1]> reduce_mean_33_axes_0 = const()[name = string("reduce_mean_33_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_33_keep_dims_0 = const()[name = string("reduce_mean_33_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_33 = reduce_mean(axes = reduce_mean_33_axes_0, keep_dims = reduce_mean_33_keep_dims_0, x = mul_157)[name = string("reduce_mean_33")];
            fp32 rsqrt_33_epsilon_0 = const()[name = string("rsqrt_33_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_33 = rsqrt(epsilon = rsqrt_33_epsilon_0, x = reduce_mean_33)[name = string("rsqrt_33")];
            tensor<fp16, [32, 352]> mul_158 = mul(x = reshape_33, y = rsqrt_33)[name = string("mul_158")];
            tensor<fp16, [352]> mul_159_y_0 = const()[name = string("mul_159_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3399616)))];
            tensor<fp16, [32, 352]> mul_159 = mul(x = mul_158, y = mul_159_y_0)[name = string("mul_159")];
            tensor<fp16, [352, 352]> tern_3_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3400384))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_3_o_weight_0_palettized")];
            tensor<fp16, [32, 352]> tern_3_o = linear(bias = linear_0_bias_0, weight = tern_3_o_weight_0_palettized, x = mul_159)[name = string("tern_3_o")];
            tensor<fp16, [352]> mul_160_y_0 = const()[name = string("mul_160_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3431424)))];
            tensor<fp16, [32, 352]> mul_160 = mul(x = tern_3_o, y = mul_160_y_0)[name = string("mul_160")];
            tensor<fp16, [32, 352]> add_21 = add(x = add_17, y = mul_160)[name = string("add_21")];
            tensor<fp16, [32, 352]> mul_161 = mul(x = add_21, y = add_21)[name = string("mul_161")];
            tensor<int32, [1]> reduce_mean_34_axes_0 = const()[name = string("reduce_mean_34_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_34_keep_dims_0 = const()[name = string("reduce_mean_34_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_34 = reduce_mean(axes = reduce_mean_34_axes_0, keep_dims = reduce_mean_34_keep_dims_0, x = mul_161)[name = string("reduce_mean_34")];
            fp32 rsqrt_34_epsilon_0 = const()[name = string("rsqrt_34_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_34 = rsqrt(epsilon = rsqrt_34_epsilon_0, x = reduce_mean_34)[name = string("rsqrt_34")];
            tensor<fp16, [32, 352]> mul_162 = mul(x = add_21, y = rsqrt_34)[name = string("mul_162")];
            tensor<fp16, [352]> mul_163_y_0 = const()[name = string("mul_163_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3432192)))];
            tensor<fp16, [32, 352]> mul_163 = mul(x = mul_162, y = mul_163_y_0)[name = string("mul_163")];
            tensor<fp16, [32, 352]> mul_164 = mul(x = mul_163, y = mul_163)[name = string("mul_164")];
            tensor<int32, [1]> reduce_mean_35_axes_0 = const()[name = string("reduce_mean_35_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_35_keep_dims_0 = const()[name = string("reduce_mean_35_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_35 = reduce_mean(axes = reduce_mean_35_axes_0, keep_dims = reduce_mean_35_keep_dims_0, x = mul_164)[name = string("reduce_mean_35")];
            fp32 rsqrt_35_epsilon_0 = const()[name = string("rsqrt_35_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_35 = rsqrt(epsilon = rsqrt_35_epsilon_0, x = reduce_mean_35)[name = string("rsqrt_35")];
            tensor<fp16, [32, 352]> mul_165 = mul(x = mul_163, y = rsqrt_35)[name = string("mul_165")];
            tensor<fp16, [352]> mul_166_y_0 = const()[name = string("mul_166_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3432960)))];
            tensor<fp16, [32, 352]> mul_166 = mul(x = mul_165, y = mul_166_y_0)[name = string("mul_166")];
            tensor<fp16, [960, 352]> tern_3_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3433728))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_3_w1_weight_0_palettized")];
            tensor<fp16, [32, 960]> tern_3_w1 = linear(bias = linear_4_bias_0, weight = tern_3_w1_weight_0_palettized, x = mul_166)[name = string("tern_3_w1")];
            tensor<fp16, [960]> mul_167_y_0 = const()[name = string("mul_167_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3518272)))];
            tensor<fp16, [32, 960]> mul_167 = mul(x = tern_3_w1, y = mul_167_y_0)[name = string("mul_167")];
            tensor<fp16, [352]> mul_170_y_0 = const()[name = string("mul_170_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3520256)))];
            tensor<fp16, [32, 352]> mul_170 = mul(x = mul_165, y = mul_170_y_0)[name = string("mul_170")];
            tensor<fp16, [960, 352]> tern_3_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3521024))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_3_w3_weight_0_palettized")];
            tensor<fp16, [32, 960]> tern_3_w3 = linear(bias = linear_4_bias_0, weight = tern_3_w3_weight_0_palettized, x = mul_170)[name = string("tern_3_w3")];
            tensor<fp16, [960]> mul_171_y_0 = const()[name = string("mul_171_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3605568)))];
            tensor<fp16, [32, 960]> mul_171 = mul(x = tern_3_w3, y = mul_171_y_0)[name = string("mul_171")];
            fp16 mul_172_y_0 = const()[name = string("mul_172_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [32, 960]> mul_172 = mul(x = mul_167, y = mul_172_y_0)[name = string("mul_172")];
            tensor<fp16, [32, 960]> tanh_3 = tanh(x = mul_172)[name = string("tanh_3")];
            fp16 mul_173_x_0 = const()[name = string("mul_173_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [32, 960]> mul_173 = mul(x = mul_173_x_0, y = tanh_3)[name = string("mul_173")];
            fp16 add_22_x_0 = const()[name = string("add_22_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [32, 960]> add_22 = add(x = add_22_x_0, y = mul_173)[name = string("add_22")];
            tensor<fp16, [32, 960]> mul_174 = mul(x = mul_167, y = add_22)[name = string("mul_174")];
            tensor<fp16, [32, 960]> mul_175 = mul(x = mul_174, y = mul_171)[name = string("mul_175")];
            tensor<fp16, [32, 960]> mul_176 = mul(x = mul_175, y = mul_175)[name = string("mul_176")];
            tensor<int32, [1]> reduce_mean_37_axes_0 = const()[name = string("reduce_mean_37_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_37_keep_dims_0 = const()[name = string("reduce_mean_37_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_37 = reduce_mean(axes = reduce_mean_37_axes_0, keep_dims = reduce_mean_37_keep_dims_0, x = mul_176)[name = string("reduce_mean_37")];
            fp32 rsqrt_37_epsilon_0 = const()[name = string("rsqrt_37_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_37 = rsqrt(epsilon = rsqrt_37_epsilon_0, x = reduce_mean_37)[name = string("rsqrt_37")];
            tensor<fp16, [32, 960]> mul_177 = mul(x = mul_175, y = rsqrt_37)[name = string("mul_177")];
            tensor<fp16, [960]> mul_178_y_0 = const()[name = string("mul_178_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3607552)))];
            tensor<fp16, [32, 960]> mul_178 = mul(x = mul_177, y = mul_178_y_0)[name = string("mul_178")];
            tensor<fp16, [352, 960]> tern_3_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3609536))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_3_w2_weight_0_palettized")];
            tensor<fp16, [32, 352]> tern_3_w2 = linear(bias = linear_0_bias_0, weight = tern_3_w2_weight_0_palettized, x = mul_178)[name = string("tern_3_w2")];
            tensor<fp16, [352]> mul_179_y_0 = const()[name = string("mul_179_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3694080)))];
            tensor<fp16, [32, 352]> mul_179 = mul(x = tern_3_w2, y = mul_179_y_0)[name = string("mul_179")];
            tensor<fp16, [32, 352]> add_23 = add(x = add_21, y = mul_179)[name = string("add_23")];
            tensor<fp16, [32, 352]> mul_180 = mul(x = add_23, y = add_23)[name = string("mul_180")];
            tensor<int32, [1]> reduce_mean_38_axes_0 = const()[name = string("reduce_mean_38_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_38_keep_dims_0 = const()[name = string("reduce_mean_38_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_38 = reduce_mean(axes = reduce_mean_38_axes_0, keep_dims = reduce_mean_38_keep_dims_0, x = mul_180)[name = string("reduce_mean_38")];
            fp32 rsqrt_38_epsilon_0 = const()[name = string("rsqrt_38_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_38 = rsqrt(epsilon = rsqrt_38_epsilon_0, x = reduce_mean_38)[name = string("rsqrt_38")];
            tensor<fp16, [32, 352]> mul_181 = mul(x = add_23, y = rsqrt_38)[name = string("mul_181")];
            tensor<fp16, [352]> mul_182_y_0 = const()[name = string("mul_182_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3694848)))];
            tensor<fp16, [32, 352]> mul_182 = mul(x = mul_181, y = mul_182_y_0)[name = string("mul_182")];
            tensor<fp16, [32, 352]> mul_183 = mul(x = mul_182, y = mul_182)[name = string("mul_183")];
            tensor<int32, [1]> reduce_mean_39_axes_0 = const()[name = string("reduce_mean_39_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_39_keep_dims_0 = const()[name = string("reduce_mean_39_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_39 = reduce_mean(axes = reduce_mean_39_axes_0, keep_dims = reduce_mean_39_keep_dims_0, x = mul_183)[name = string("reduce_mean_39")];
            fp32 rsqrt_39_epsilon_0 = const()[name = string("rsqrt_39_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_39 = rsqrt(epsilon = rsqrt_39_epsilon_0, x = reduce_mean_39)[name = string("rsqrt_39")];
            tensor<fp16, [32, 352]> mul_184 = mul(x = mul_182, y = rsqrt_39)[name = string("mul_184")];
            tensor<fp16, [352]> mul_185_y_0 = const()[name = string("mul_185_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3695616)))];
            tensor<fp16, [32, 352]> mul_185 = mul(x = mul_184, y = mul_185_y_0)[name = string("mul_185")];
            tensor<fp16, [352, 352]> tern_4_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3696384))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_4_q_weight_0_palettized")];
            tensor<fp16, [32, 352]> tern_4_q = linear(bias = linear_0_bias_0, weight = tern_4_q_weight_0_palettized, x = mul_185)[name = string("tern_4_q")];
            tensor<fp16, [352]> mul_186_y_0 = const()[name = string("mul_186_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3727424)))];
            tensor<fp16, [32, 352]> mul_186 = mul(x = tern_4_q, y = mul_186_y_0)[name = string("mul_186")];
            tensor<int32, [3]> reshape_34_shape_0 = const()[name = string("reshape_34_shape_0"), val = tensor<int32, [3]>([32, 8, 44])];
            tensor<fp16, [32, 8, 44]> reshape_34 = reshape(shape = reshape_34_shape_0, x = mul_186)[name = string("reshape_34")];
            tensor<int32, [3]> transpose_16_perm_0 = const()[name = string("transpose_16_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_189_y_0 = const()[name = string("mul_189_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3728192)))];
            tensor<fp16, [32, 352]> mul_189 = mul(x = mul_184, y = mul_189_y_0)[name = string("mul_189")];
            tensor<fp16, [88, 352]> tern_4_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3728960))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_4_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_4_k_bias_0 = const()[name = string("tern_4_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [32, 88]> tern_4_k = linear(bias = tern_4_k_bias_0, weight = tern_4_k_weight_0_palettized, x = mul_189)[name = string("tern_4_k")];
            tensor<fp16, [88]> mul_190_y_0 = const()[name = string("mul_190_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3736768)))];
            tensor<fp16, [32, 88]> mul_190 = mul(x = tern_4_k, y = mul_190_y_0)[name = string("mul_190")];
            tensor<int32, [3]> reshape_35_shape_0 = const()[name = string("reshape_35_shape_0"), val = tensor<int32, [3]>([32, 2, 44])];
            tensor<fp16, [32, 2, 44]> reshape_35 = reshape(shape = reshape_35_shape_0, x = mul_190)[name = string("reshape_35")];
            tensor<int32, [3]> transpose_17_perm_0 = const()[name = string("transpose_17_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_193_y_0 = const()[name = string("mul_193_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3737024)))];
            tensor<fp16, [32, 352]> mul_193 = mul(x = mul_184, y = mul_193_y_0)[name = string("mul_193")];
            tensor<fp16, [88, 352]> tern_4_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3737792))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_4_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_4_v_bias_0 = const()[name = string("tern_4_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [32, 88]> tern_4_v = linear(bias = tern_4_v_bias_0, weight = tern_4_v_weight_0_palettized, x = mul_193)[name = string("tern_4_v")];
            tensor<fp16, [88]> mul_194_y_0 = const()[name = string("mul_194_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3745600)))];
            tensor<fp16, [32, 88]> mul_194 = mul(x = tern_4_v, y = mul_194_y_0)[name = string("mul_194")];
            tensor<int32, [3]> reshape_36_shape_0 = const()[name = string("reshape_36_shape_0"), val = tensor<int32, [3]>([32, 2, 44])];
            tensor<fp16, [32, 2, 44]> reshape_36 = reshape(shape = reshape_36_shape_0, x = mul_194)[name = string("reshape_36")];
            tensor<int32, [3]> transpose_18_perm_0 = const()[name = string("transpose_18_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 32, 44]> transpose_16 = transpose(perm = transpose_16_perm_0, x = reshape_34)[name = string("transpose_47")];
            tensor<fp16, [8, 32, 44]> mul_195 = mul(x = transpose_16, y = transpose_16)[name = string("mul_195")];
            tensor<int32, [1]> reduce_mean_42_axes_0 = const()[name = string("reduce_mean_42_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_42_keep_dims_0 = const()[name = string("reduce_mean_42_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 32, 1]> reduce_mean_42 = reduce_mean(axes = reduce_mean_42_axes_0, keep_dims = reduce_mean_42_keep_dims_0, x = mul_195)[name = string("reduce_mean_42")];
            fp32 rsqrt_42_epsilon_0 = const()[name = string("rsqrt_42_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 32, 1]> rsqrt_42 = rsqrt(epsilon = rsqrt_42_epsilon_0, x = reduce_mean_42)[name = string("rsqrt_42")];
            tensor<fp16, [8, 32, 44]> mul_196 = mul(x = transpose_16, y = rsqrt_42)[name = string("mul_196")];
            tensor<fp16, [44]> mul_197_y_0 = const()[name = string("mul_197_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3745856)))];
            tensor<fp16, [8, 32, 44]> mul_197 = mul(x = mul_196, y = mul_197_y_0)[name = string("mul_197")];
            tensor<int32, [3]> slice_by_index_16_begin_0 = const()[name = string("slice_by_index_16_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_16_end_0 = const()[name = string("slice_by_index_16_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_16_end_mask_0 = const()[name = string("slice_by_index_16_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 32, 22]> slice_by_index_16 = slice_by_index(begin = slice_by_index_16_begin_0, end = slice_by_index_16_end_0, end_mask = slice_by_index_16_end_mask_0, x = mul_197)[name = string("slice_by_index_16")];
            tensor<int32, [3]> slice_by_index_17_begin_0 = const()[name = string("slice_by_index_17_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_17_end_0 = const()[name = string("slice_by_index_17_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_17_end_mask_0 = const()[name = string("slice_by_index_17_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 32, 22]> slice_by_index_17 = slice_by_index(begin = slice_by_index_17_begin_0, end = slice_by_index_17_end_0, end_mask = slice_by_index_17_end_mask_0, x = mul_197)[name = string("slice_by_index_17")];
            int32 concat_8_axis_0 = const()[name = string("concat_8_axis_0"), val = int32(-1)];
            bool concat_8_interleave_0 = const()[name = string("concat_8_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 32, 44]> concat_8 = concat(axis = concat_8_axis_0, interleave = concat_8_interleave_0, values = (slice_by_index_17, slice_by_index_16))[name = string("concat_8")];
            tensor<fp16, [44]> mul_198_y_0 = const()[name = string("mul_198_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 32, 44]> mul_198 = mul(x = concat_8, y = mul_198_y_0)[name = string("mul_198")];
            tensor<fp16, [8, 32, 44]> mul_199 = mul(x = mul_197, y = mul_11_y_0)[name = string("mul_199")];
            tensor<fp16, [8, 32, 44]> mul_200 = mul(x = mul_198, y = mul_12_y_0)[name = string("mul_200")];
            tensor<fp16, [8, 32, 44]> add_24 = add(x = mul_199, y = mul_200)[name = string("add_24")];
            tensor<fp16, [2, 32, 44]> transpose_17 = transpose(perm = transpose_17_perm_0, x = reshape_35)[name = string("transpose_46")];
            tensor<fp16, [2, 32, 44]> mul_201 = mul(x = transpose_17, y = transpose_17)[name = string("mul_201")];
            tensor<int32, [1]> reduce_mean_43_axes_0 = const()[name = string("reduce_mean_43_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_43_keep_dims_0 = const()[name = string("reduce_mean_43_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 32, 1]> reduce_mean_43 = reduce_mean(axes = reduce_mean_43_axes_0, keep_dims = reduce_mean_43_keep_dims_0, x = mul_201)[name = string("reduce_mean_43")];
            fp32 rsqrt_43_epsilon_0 = const()[name = string("rsqrt_43_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 32, 1]> rsqrt_43 = rsqrt(epsilon = rsqrt_43_epsilon_0, x = reduce_mean_43)[name = string("rsqrt_43")];
            tensor<fp16, [2, 32, 44]> mul_202 = mul(x = transpose_17, y = rsqrt_43)[name = string("mul_202")];
            tensor<fp16, [44]> mul_203_y_0 = const()[name = string("mul_203_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3746048)))];
            tensor<fp16, [2, 32, 44]> mul_203 = mul(x = mul_202, y = mul_203_y_0)[name = string("mul_203")];
            tensor<int32, [3]> slice_by_index_18_begin_0 = const()[name = string("slice_by_index_18_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_18_end_0 = const()[name = string("slice_by_index_18_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_18_end_mask_0 = const()[name = string("slice_by_index_18_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 32, 22]> slice_by_index_18 = slice_by_index(begin = slice_by_index_18_begin_0, end = slice_by_index_18_end_0, end_mask = slice_by_index_18_end_mask_0, x = mul_203)[name = string("slice_by_index_18")];
            tensor<int32, [3]> slice_by_index_19_begin_0 = const()[name = string("slice_by_index_19_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_19_end_0 = const()[name = string("slice_by_index_19_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_19_end_mask_0 = const()[name = string("slice_by_index_19_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 32, 22]> slice_by_index_19 = slice_by_index(begin = slice_by_index_19_begin_0, end = slice_by_index_19_end_0, end_mask = slice_by_index_19_end_mask_0, x = mul_203)[name = string("slice_by_index_19")];
            int32 concat_9_axis_0 = const()[name = string("concat_9_axis_0"), val = int32(-1)];
            bool concat_9_interleave_0 = const()[name = string("concat_9_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 32, 44]> concat_9 = concat(axis = concat_9_axis_0, interleave = concat_9_interleave_0, values = (slice_by_index_19, slice_by_index_18))[name = string("concat_9")];
            tensor<fp16, [44]> mul_204_y_0 = const()[name = string("mul_204_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 32, 44]> mul_204 = mul(x = concat_9, y = mul_204_y_0)[name = string("mul_204")];
            tensor<fp16, [2, 32, 44]> mul_205 = mul(x = mul_203, y = mul_11_y_0)[name = string("mul_205")];
            tensor<fp16, [2, 32, 44]> mul_206 = mul(x = mul_204, y = mul_12_y_0)[name = string("mul_206")];
            tensor<fp16, [2, 32, 44]> add_25 = add(x = mul_205, y = mul_206)[name = string("add_25")];
            tensor<int32, [4]> reshape_37_shape_0 = const()[name = string("reshape_37_shape_0"), val = tensor<int32, [4]>([2, 1, 32, 44])];
            tensor<fp16, [2, 1, 32, 44]> reshape_37 = reshape(shape = reshape_37_shape_0, x = add_25)[name = string("reshape_37")];
            tensor<int32, [4]> tile_8_reps_0 = const()[name = string("tile_8_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 32, 44]> tile_8 = tile(reps = tile_8_reps_0, x = reshape_37)[name = string("tile_8")];
            tensor<int32, [3]> reshape_38_shape_0 = const()[name = string("reshape_38_shape_0"), val = tensor<int32, [3]>([8, 32, 44])];
            tensor<fp16, [8, 32, 44]> reshape_38 = reshape(shape = reshape_38_shape_0, x = tile_8)[name = string("reshape_38")];
            tensor<int32, [4]> reshape_39_shape_0 = const()[name = string("reshape_39_shape_0"), val = tensor<int32, [4]>([2, 1, 32, 44])];
            tensor<fp16, [2, 32, 44]> transpose_18 = transpose(perm = transpose_18_perm_0, x = reshape_36)[name = string("transpose_45")];
            tensor<fp16, [2, 1, 32, 44]> reshape_39 = reshape(shape = reshape_39_shape_0, x = transpose_18)[name = string("reshape_39")];
            tensor<int32, [4]> tile_9_reps_0 = const()[name = string("tile_9_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 32, 44]> tile_9 = tile(reps = tile_9_reps_0, x = reshape_39)[name = string("tile_9")];
            tensor<int32, [3]> reshape_40_shape_0 = const()[name = string("reshape_40_shape_0"), val = tensor<int32, [3]>([8, 32, 44])];
            tensor<fp16, [8, 32, 44]> reshape_40 = reshape(shape = reshape_40_shape_0, x = tile_9)[name = string("reshape_40")];
            fp16 mul_207_y_0 = const()[name = string("mul_207_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 32, 44]> mul_207 = mul(x = add_24, y = mul_207_y_0)[name = string("mul_207")];
            bool matmul_8_transpose_y_0 = const()[name = string("matmul_8_transpose_y_0"), val = bool(true)];
            bool matmul_8_transpose_x_0 = const()[name = string("matmul_8_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 32, 32]> matmul_8 = matmul(transpose_x = matmul_8_transpose_x_0, transpose_y = matmul_8_transpose_y_0, x = mul_207, y = reshape_38)[name = string("matmul_8")];
            tensor<fp16, [8, 32, 32]> add_26 = add(x = matmul_8, y = reshape_1)[name = string("add_26")];
            int32 softmax_4_axis_0 = const()[name = string("softmax_4_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 32, 32]> softmax_4 = softmax(axis = softmax_4_axis_0, x = add_26)[name = string("softmax_4")];
            bool matmul_9_transpose_x_0 = const()[name = string("matmul_9_transpose_x_0"), val = bool(false)];
            bool matmul_9_transpose_y_0 = const()[name = string("matmul_9_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 32, 44]> matmul_9 = matmul(transpose_x = matmul_9_transpose_x_0, transpose_y = matmul_9_transpose_y_0, x = softmax_4, y = reshape_40)[name = string("matmul_9")];
            tensor<int32, [3]> transpose_19_perm_0 = const()[name = string("transpose_19_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_41_shape_0 = const()[name = string("reshape_41_shape_0"), val = tensor<int32, [2]>([32, 352])];
            tensor<fp16, [32, 8, 44]> transpose_19 = transpose(perm = transpose_19_perm_0, x = matmul_9)[name = string("transpose_44")];
            tensor<fp16, [32, 352]> reshape_41 = reshape(shape = reshape_41_shape_0, x = transpose_19)[name = string("reshape_41")];
            tensor<fp16, [32, 352]> mul_208 = mul(x = reshape_41, y = reshape_41)[name = string("mul_208")];
            tensor<int32, [1]> reduce_mean_44_axes_0 = const()[name = string("reduce_mean_44_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_44_keep_dims_0 = const()[name = string("reduce_mean_44_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_44 = reduce_mean(axes = reduce_mean_44_axes_0, keep_dims = reduce_mean_44_keep_dims_0, x = mul_208)[name = string("reduce_mean_44")];
            fp32 rsqrt_44_epsilon_0 = const()[name = string("rsqrt_44_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_44 = rsqrt(epsilon = rsqrt_44_epsilon_0, x = reduce_mean_44)[name = string("rsqrt_44")];
            tensor<fp16, [32, 352]> mul_209 = mul(x = reshape_41, y = rsqrt_44)[name = string("mul_209")];
            tensor<fp16, [352]> mul_210_y_0 = const()[name = string("mul_210_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3746240)))];
            tensor<fp16, [32, 352]> mul_210 = mul(x = mul_209, y = mul_210_y_0)[name = string("mul_210")];
            tensor<fp16, [352, 352]> tern_4_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3747008))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_4_o_weight_0_palettized")];
            tensor<fp16, [32, 352]> tern_4_o = linear(bias = linear_0_bias_0, weight = tern_4_o_weight_0_palettized, x = mul_210)[name = string("tern_4_o")];
            tensor<fp16, [352]> mul_211_y_0 = const()[name = string("mul_211_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3778048)))];
            tensor<fp16, [32, 352]> mul_211 = mul(x = tern_4_o, y = mul_211_y_0)[name = string("mul_211")];
            tensor<fp16, [32, 352]> add_27 = add(x = add_23, y = mul_211)[name = string("add_27")];
            tensor<fp16, [32, 352]> mul_212 = mul(x = add_27, y = add_27)[name = string("mul_212")];
            tensor<int32, [1]> reduce_mean_45_axes_0 = const()[name = string("reduce_mean_45_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_45_keep_dims_0 = const()[name = string("reduce_mean_45_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_45 = reduce_mean(axes = reduce_mean_45_axes_0, keep_dims = reduce_mean_45_keep_dims_0, x = mul_212)[name = string("reduce_mean_45")];
            fp32 rsqrt_45_epsilon_0 = const()[name = string("rsqrt_45_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_45 = rsqrt(epsilon = rsqrt_45_epsilon_0, x = reduce_mean_45)[name = string("rsqrt_45")];
            tensor<fp16, [32, 352]> mul_213 = mul(x = add_27, y = rsqrt_45)[name = string("mul_213")];
            tensor<fp16, [352]> mul_214_y_0 = const()[name = string("mul_214_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3778816)))];
            tensor<fp16, [32, 352]> mul_214 = mul(x = mul_213, y = mul_214_y_0)[name = string("mul_214")];
            tensor<fp16, [32, 352]> mul_215 = mul(x = mul_214, y = mul_214)[name = string("mul_215")];
            tensor<int32, [1]> reduce_mean_46_axes_0 = const()[name = string("reduce_mean_46_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_46_keep_dims_0 = const()[name = string("reduce_mean_46_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_46 = reduce_mean(axes = reduce_mean_46_axes_0, keep_dims = reduce_mean_46_keep_dims_0, x = mul_215)[name = string("reduce_mean_46")];
            fp32 rsqrt_46_epsilon_0 = const()[name = string("rsqrt_46_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_46 = rsqrt(epsilon = rsqrt_46_epsilon_0, x = reduce_mean_46)[name = string("rsqrt_46")];
            tensor<fp16, [32, 352]> mul_216 = mul(x = mul_214, y = rsqrt_46)[name = string("mul_216")];
            tensor<fp16, [352]> mul_217_y_0 = const()[name = string("mul_217_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3779584)))];
            tensor<fp16, [32, 352]> mul_217 = mul(x = mul_216, y = mul_217_y_0)[name = string("mul_217")];
            tensor<fp16, [960, 352]> tern_4_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3780352))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_4_w1_weight_0_palettized")];
            tensor<fp16, [32, 960]> tern_4_w1 = linear(bias = linear_4_bias_0, weight = tern_4_w1_weight_0_palettized, x = mul_217)[name = string("tern_4_w1")];
            tensor<fp16, [960]> mul_218_y_0 = const()[name = string("mul_218_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3864896)))];
            tensor<fp16, [32, 960]> mul_218 = mul(x = tern_4_w1, y = mul_218_y_0)[name = string("mul_218")];
            tensor<fp16, [352]> mul_221_y_0 = const()[name = string("mul_221_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3866880)))];
            tensor<fp16, [32, 352]> mul_221 = mul(x = mul_216, y = mul_221_y_0)[name = string("mul_221")];
            tensor<fp16, [960, 352]> tern_4_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3867648))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_4_w3_weight_0_palettized")];
            tensor<fp16, [32, 960]> tern_4_w3 = linear(bias = linear_4_bias_0, weight = tern_4_w3_weight_0_palettized, x = mul_221)[name = string("tern_4_w3")];
            tensor<fp16, [960]> mul_222_y_0 = const()[name = string("mul_222_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3952192)))];
            tensor<fp16, [32, 960]> mul_222 = mul(x = tern_4_w3, y = mul_222_y_0)[name = string("mul_222")];
            fp16 mul_223_y_0 = const()[name = string("mul_223_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [32, 960]> mul_223 = mul(x = mul_218, y = mul_223_y_0)[name = string("mul_223")];
            tensor<fp16, [32, 960]> tanh_4 = tanh(x = mul_223)[name = string("tanh_4")];
            fp16 mul_224_x_0 = const()[name = string("mul_224_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [32, 960]> mul_224 = mul(x = mul_224_x_0, y = tanh_4)[name = string("mul_224")];
            fp16 add_28_x_0 = const()[name = string("add_28_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [32, 960]> add_28 = add(x = add_28_x_0, y = mul_224)[name = string("add_28")];
            tensor<fp16, [32, 960]> mul_225 = mul(x = mul_218, y = add_28)[name = string("mul_225")];
            tensor<fp16, [32, 960]> mul_226 = mul(x = mul_225, y = mul_222)[name = string("mul_226")];
            tensor<fp16, [32, 960]> mul_227 = mul(x = mul_226, y = mul_226)[name = string("mul_227")];
            tensor<int32, [1]> reduce_mean_48_axes_0 = const()[name = string("reduce_mean_48_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_48_keep_dims_0 = const()[name = string("reduce_mean_48_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_48 = reduce_mean(axes = reduce_mean_48_axes_0, keep_dims = reduce_mean_48_keep_dims_0, x = mul_227)[name = string("reduce_mean_48")];
            fp32 rsqrt_48_epsilon_0 = const()[name = string("rsqrt_48_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_48 = rsqrt(epsilon = rsqrt_48_epsilon_0, x = reduce_mean_48)[name = string("rsqrt_48")];
            tensor<fp16, [32, 960]> mul_228 = mul(x = mul_226, y = rsqrt_48)[name = string("mul_228")];
            tensor<fp16, [960]> mul_229_y_0 = const()[name = string("mul_229_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3954176)))];
            tensor<fp16, [32, 960]> mul_229 = mul(x = mul_228, y = mul_229_y_0)[name = string("mul_229")];
            tensor<fp16, [352, 960]> tern_4_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3956160))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_4_w2_weight_0_palettized")];
            tensor<fp16, [32, 352]> tern_4_w2 = linear(bias = linear_0_bias_0, weight = tern_4_w2_weight_0_palettized, x = mul_229)[name = string("tern_4_w2")];
            tensor<fp16, [352]> mul_230_y_0 = const()[name = string("mul_230_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4040704)))];
            tensor<fp16, [32, 352]> mul_230 = mul(x = tern_4_w2, y = mul_230_y_0)[name = string("mul_230")];
            tensor<fp16, [32, 352]> add_29 = add(x = add_27, y = mul_230)[name = string("add_29")];
            tensor<fp16, [32, 352]> mul_231 = mul(x = add_29, y = add_29)[name = string("mul_231")];
            tensor<int32, [1]> reduce_mean_49_axes_0 = const()[name = string("reduce_mean_49_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_49_keep_dims_0 = const()[name = string("reduce_mean_49_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_49 = reduce_mean(axes = reduce_mean_49_axes_0, keep_dims = reduce_mean_49_keep_dims_0, x = mul_231)[name = string("reduce_mean_49")];
            fp32 rsqrt_49_epsilon_0 = const()[name = string("rsqrt_49_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_49 = rsqrt(epsilon = rsqrt_49_epsilon_0, x = reduce_mean_49)[name = string("rsqrt_49")];
            tensor<fp16, [32, 352]> mul_232 = mul(x = add_29, y = rsqrt_49)[name = string("mul_232")];
            tensor<fp16, [352]> mul_233_y_0 = const()[name = string("mul_233_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4041472)))];
            tensor<fp16, [32, 352]> mul_233 = mul(x = mul_232, y = mul_233_y_0)[name = string("mul_233")];
            tensor<fp16, [32, 352]> mul_234 = mul(x = mul_233, y = mul_233)[name = string("mul_234")];
            tensor<int32, [1]> reduce_mean_50_axes_0 = const()[name = string("reduce_mean_50_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_50_keep_dims_0 = const()[name = string("reduce_mean_50_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_50 = reduce_mean(axes = reduce_mean_50_axes_0, keep_dims = reduce_mean_50_keep_dims_0, x = mul_234)[name = string("reduce_mean_50")];
            fp32 rsqrt_50_epsilon_0 = const()[name = string("rsqrt_50_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_50 = rsqrt(epsilon = rsqrt_50_epsilon_0, x = reduce_mean_50)[name = string("rsqrt_50")];
            tensor<fp16, [32, 352]> mul_235 = mul(x = mul_233, y = rsqrt_50)[name = string("mul_235")];
            tensor<fp16, [352]> mul_236_y_0 = const()[name = string("mul_236_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4042240)))];
            tensor<fp16, [32, 352]> mul_236 = mul(x = mul_235, y = mul_236_y_0)[name = string("mul_236")];
            tensor<fp16, [352, 352]> tern_5_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4043008))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_5_q_weight_0_palettized")];
            tensor<fp16, [32, 352]> tern_5_q = linear(bias = linear_0_bias_0, weight = tern_5_q_weight_0_palettized, x = mul_236)[name = string("tern_5_q")];
            tensor<fp16, [352]> mul_237_y_0 = const()[name = string("mul_237_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4074048)))];
            tensor<fp16, [32, 352]> mul_237 = mul(x = tern_5_q, y = mul_237_y_0)[name = string("mul_237")];
            tensor<int32, [3]> reshape_42_shape_0 = const()[name = string("reshape_42_shape_0"), val = tensor<int32, [3]>([32, 8, 44])];
            tensor<fp16, [32, 8, 44]> reshape_42 = reshape(shape = reshape_42_shape_0, x = mul_237)[name = string("reshape_42")];
            tensor<int32, [3]> transpose_20_perm_0 = const()[name = string("transpose_20_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_240_y_0 = const()[name = string("mul_240_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4074816)))];
            tensor<fp16, [32, 352]> mul_240 = mul(x = mul_235, y = mul_240_y_0)[name = string("mul_240")];
            tensor<fp16, [88, 352]> tern_5_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4075584))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_5_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_5_k_bias_0 = const()[name = string("tern_5_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [32, 88]> tern_5_k = linear(bias = tern_5_k_bias_0, weight = tern_5_k_weight_0_palettized, x = mul_240)[name = string("tern_5_k")];
            tensor<fp16, [88]> mul_241_y_0 = const()[name = string("mul_241_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4083392)))];
            tensor<fp16, [32, 88]> mul_241 = mul(x = tern_5_k, y = mul_241_y_0)[name = string("mul_241")];
            tensor<int32, [3]> reshape_43_shape_0 = const()[name = string("reshape_43_shape_0"), val = tensor<int32, [3]>([32, 2, 44])];
            tensor<fp16, [32, 2, 44]> reshape_43 = reshape(shape = reshape_43_shape_0, x = mul_241)[name = string("reshape_43")];
            tensor<int32, [3]> transpose_21_perm_0 = const()[name = string("transpose_21_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_244_y_0 = const()[name = string("mul_244_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4083648)))];
            tensor<fp16, [32, 352]> mul_244 = mul(x = mul_235, y = mul_244_y_0)[name = string("mul_244")];
            tensor<fp16, [88, 352]> tern_5_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4084416))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_5_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_5_v_bias_0 = const()[name = string("tern_5_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [32, 88]> tern_5_v = linear(bias = tern_5_v_bias_0, weight = tern_5_v_weight_0_palettized, x = mul_244)[name = string("tern_5_v")];
            tensor<fp16, [88]> mul_245_y_0 = const()[name = string("mul_245_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4092224)))];
            tensor<fp16, [32, 88]> mul_245 = mul(x = tern_5_v, y = mul_245_y_0)[name = string("mul_245")];
            tensor<int32, [3]> reshape_44_shape_0 = const()[name = string("reshape_44_shape_0"), val = tensor<int32, [3]>([32, 2, 44])];
            tensor<fp16, [32, 2, 44]> reshape_44 = reshape(shape = reshape_44_shape_0, x = mul_245)[name = string("reshape_44")];
            tensor<int32, [3]> transpose_22_perm_0 = const()[name = string("transpose_22_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 32, 44]> transpose_20 = transpose(perm = transpose_20_perm_0, x = reshape_42)[name = string("transpose_43")];
            tensor<fp16, [8, 32, 44]> mul_246 = mul(x = transpose_20, y = transpose_20)[name = string("mul_246")];
            tensor<int32, [1]> reduce_mean_53_axes_0 = const()[name = string("reduce_mean_53_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_53_keep_dims_0 = const()[name = string("reduce_mean_53_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 32, 1]> reduce_mean_53 = reduce_mean(axes = reduce_mean_53_axes_0, keep_dims = reduce_mean_53_keep_dims_0, x = mul_246)[name = string("reduce_mean_53")];
            fp32 rsqrt_53_epsilon_0 = const()[name = string("rsqrt_53_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 32, 1]> rsqrt_53 = rsqrt(epsilon = rsqrt_53_epsilon_0, x = reduce_mean_53)[name = string("rsqrt_53")];
            tensor<fp16, [8, 32, 44]> mul_247 = mul(x = transpose_20, y = rsqrt_53)[name = string("mul_247")];
            tensor<fp16, [44]> mul_248_y_0 = const()[name = string("mul_248_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4092480)))];
            tensor<fp16, [8, 32, 44]> mul_248 = mul(x = mul_247, y = mul_248_y_0)[name = string("mul_248")];
            tensor<int32, [3]> slice_by_index_20_begin_0 = const()[name = string("slice_by_index_20_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_20_end_0 = const()[name = string("slice_by_index_20_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_20_end_mask_0 = const()[name = string("slice_by_index_20_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 32, 22]> slice_by_index_20 = slice_by_index(begin = slice_by_index_20_begin_0, end = slice_by_index_20_end_0, end_mask = slice_by_index_20_end_mask_0, x = mul_248)[name = string("slice_by_index_20")];
            tensor<int32, [3]> slice_by_index_21_begin_0 = const()[name = string("slice_by_index_21_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_21_end_0 = const()[name = string("slice_by_index_21_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_21_end_mask_0 = const()[name = string("slice_by_index_21_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 32, 22]> slice_by_index_21 = slice_by_index(begin = slice_by_index_21_begin_0, end = slice_by_index_21_end_0, end_mask = slice_by_index_21_end_mask_0, x = mul_248)[name = string("slice_by_index_21")];
            int32 concat_10_axis_0 = const()[name = string("concat_10_axis_0"), val = int32(-1)];
            bool concat_10_interleave_0 = const()[name = string("concat_10_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 32, 44]> concat_10 = concat(axis = concat_10_axis_0, interleave = concat_10_interleave_0, values = (slice_by_index_21, slice_by_index_20))[name = string("concat_10")];
            tensor<fp16, [44]> mul_249_y_0 = const()[name = string("mul_249_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 32, 44]> mul_249 = mul(x = concat_10, y = mul_249_y_0)[name = string("mul_249")];
            tensor<fp16, [8, 32, 44]> mul_250 = mul(x = mul_248, y = mul_11_y_0)[name = string("mul_250")];
            tensor<fp16, [8, 32, 44]> mul_251 = mul(x = mul_249, y = mul_12_y_0)[name = string("mul_251")];
            tensor<fp16, [8, 32, 44]> add_30 = add(x = mul_250, y = mul_251)[name = string("add_30")];
            tensor<fp16, [2, 32, 44]> transpose_21 = transpose(perm = transpose_21_perm_0, x = reshape_43)[name = string("transpose_42")];
            tensor<fp16, [2, 32, 44]> mul_252 = mul(x = transpose_21, y = transpose_21)[name = string("mul_252")];
            tensor<int32, [1]> reduce_mean_54_axes_0 = const()[name = string("reduce_mean_54_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_54_keep_dims_0 = const()[name = string("reduce_mean_54_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 32, 1]> reduce_mean_54 = reduce_mean(axes = reduce_mean_54_axes_0, keep_dims = reduce_mean_54_keep_dims_0, x = mul_252)[name = string("reduce_mean_54")];
            fp32 rsqrt_54_epsilon_0 = const()[name = string("rsqrt_54_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 32, 1]> rsqrt_54 = rsqrt(epsilon = rsqrt_54_epsilon_0, x = reduce_mean_54)[name = string("rsqrt_54")];
            tensor<fp16, [2, 32, 44]> mul_253 = mul(x = transpose_21, y = rsqrt_54)[name = string("mul_253")];
            tensor<fp16, [44]> mul_254_y_0 = const()[name = string("mul_254_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4092672)))];
            tensor<fp16, [2, 32, 44]> mul_254 = mul(x = mul_253, y = mul_254_y_0)[name = string("mul_254")];
            tensor<int32, [3]> slice_by_index_22_begin_0 = const()[name = string("slice_by_index_22_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_22_end_0 = const()[name = string("slice_by_index_22_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_22_end_mask_0 = const()[name = string("slice_by_index_22_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 32, 22]> slice_by_index_22 = slice_by_index(begin = slice_by_index_22_begin_0, end = slice_by_index_22_end_0, end_mask = slice_by_index_22_end_mask_0, x = mul_254)[name = string("slice_by_index_22")];
            tensor<int32, [3]> slice_by_index_23_begin_0 = const()[name = string("slice_by_index_23_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_23_end_0 = const()[name = string("slice_by_index_23_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_23_end_mask_0 = const()[name = string("slice_by_index_23_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 32, 22]> slice_by_index_23 = slice_by_index(begin = slice_by_index_23_begin_0, end = slice_by_index_23_end_0, end_mask = slice_by_index_23_end_mask_0, x = mul_254)[name = string("slice_by_index_23")];
            int32 concat_11_axis_0 = const()[name = string("concat_11_axis_0"), val = int32(-1)];
            bool concat_11_interleave_0 = const()[name = string("concat_11_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 32, 44]> concat_11 = concat(axis = concat_11_axis_0, interleave = concat_11_interleave_0, values = (slice_by_index_23, slice_by_index_22))[name = string("concat_11")];
            tensor<fp16, [44]> mul_255_y_0 = const()[name = string("mul_255_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 32, 44]> mul_255 = mul(x = concat_11, y = mul_255_y_0)[name = string("mul_255")];
            tensor<fp16, [2, 32, 44]> mul_256 = mul(x = mul_254, y = mul_11_y_0)[name = string("mul_256")];
            tensor<fp16, [2, 32, 44]> mul_257 = mul(x = mul_255, y = mul_12_y_0)[name = string("mul_257")];
            tensor<fp16, [2, 32, 44]> add_31 = add(x = mul_256, y = mul_257)[name = string("add_31")];
            tensor<int32, [4]> reshape_45_shape_0 = const()[name = string("reshape_45_shape_0"), val = tensor<int32, [4]>([2, 1, 32, 44])];
            tensor<fp16, [2, 1, 32, 44]> reshape_45 = reshape(shape = reshape_45_shape_0, x = add_31)[name = string("reshape_45")];
            tensor<int32, [4]> tile_10_reps_0 = const()[name = string("tile_10_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 32, 44]> tile_10 = tile(reps = tile_10_reps_0, x = reshape_45)[name = string("tile_10")];
            tensor<int32, [3]> reshape_46_shape_0 = const()[name = string("reshape_46_shape_0"), val = tensor<int32, [3]>([8, 32, 44])];
            tensor<fp16, [8, 32, 44]> reshape_46 = reshape(shape = reshape_46_shape_0, x = tile_10)[name = string("reshape_46")];
            tensor<int32, [4]> reshape_47_shape_0 = const()[name = string("reshape_47_shape_0"), val = tensor<int32, [4]>([2, 1, 32, 44])];
            tensor<fp16, [2, 32, 44]> transpose_22 = transpose(perm = transpose_22_perm_0, x = reshape_44)[name = string("transpose_41")];
            tensor<fp16, [2, 1, 32, 44]> reshape_47 = reshape(shape = reshape_47_shape_0, x = transpose_22)[name = string("reshape_47")];
            tensor<int32, [4]> tile_11_reps_0 = const()[name = string("tile_11_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 32, 44]> tile_11 = tile(reps = tile_11_reps_0, x = reshape_47)[name = string("tile_11")];
            tensor<int32, [3]> reshape_48_shape_0 = const()[name = string("reshape_48_shape_0"), val = tensor<int32, [3]>([8, 32, 44])];
            tensor<fp16, [8, 32, 44]> reshape_48 = reshape(shape = reshape_48_shape_0, x = tile_11)[name = string("reshape_48")];
            fp16 mul_258_y_0 = const()[name = string("mul_258_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 32, 44]> mul_258 = mul(x = add_30, y = mul_258_y_0)[name = string("mul_258")];
            bool matmul_10_transpose_y_0 = const()[name = string("matmul_10_transpose_y_0"), val = bool(true)];
            bool matmul_10_transpose_x_0 = const()[name = string("matmul_10_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 32, 32]> matmul_10 = matmul(transpose_x = matmul_10_transpose_x_0, transpose_y = matmul_10_transpose_y_0, x = mul_258, y = reshape_46)[name = string("matmul_10")];
            tensor<fp16, [8, 32, 32]> add_32 = add(x = matmul_10, y = reshape_1)[name = string("add_32")];
            int32 softmax_5_axis_0 = const()[name = string("softmax_5_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 32, 32]> softmax_5 = softmax(axis = softmax_5_axis_0, x = add_32)[name = string("softmax_5")];
            bool matmul_11_transpose_x_0 = const()[name = string("matmul_11_transpose_x_0"), val = bool(false)];
            bool matmul_11_transpose_y_0 = const()[name = string("matmul_11_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 32, 44]> matmul_11 = matmul(transpose_x = matmul_11_transpose_x_0, transpose_y = matmul_11_transpose_y_0, x = softmax_5, y = reshape_48)[name = string("matmul_11")];
            tensor<int32, [3]> transpose_23_perm_0 = const()[name = string("transpose_23_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_49_shape_0 = const()[name = string("reshape_49_shape_0"), val = tensor<int32, [2]>([32, 352])];
            tensor<fp16, [32, 8, 44]> transpose_23 = transpose(perm = transpose_23_perm_0, x = matmul_11)[name = string("transpose_40")];
            tensor<fp16, [32, 352]> reshape_49 = reshape(shape = reshape_49_shape_0, x = transpose_23)[name = string("reshape_49")];
            tensor<fp16, [32, 352]> mul_259 = mul(x = reshape_49, y = reshape_49)[name = string("mul_259")];
            tensor<int32, [1]> reduce_mean_55_axes_0 = const()[name = string("reduce_mean_55_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_55_keep_dims_0 = const()[name = string("reduce_mean_55_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_55 = reduce_mean(axes = reduce_mean_55_axes_0, keep_dims = reduce_mean_55_keep_dims_0, x = mul_259)[name = string("reduce_mean_55")];
            fp32 rsqrt_55_epsilon_0 = const()[name = string("rsqrt_55_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_55 = rsqrt(epsilon = rsqrt_55_epsilon_0, x = reduce_mean_55)[name = string("rsqrt_55")];
            tensor<fp16, [32, 352]> mul_260 = mul(x = reshape_49, y = rsqrt_55)[name = string("mul_260")];
            tensor<fp16, [352]> mul_261_y_0 = const()[name = string("mul_261_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4092864)))];
            tensor<fp16, [32, 352]> mul_261 = mul(x = mul_260, y = mul_261_y_0)[name = string("mul_261")];
            tensor<fp16, [352, 352]> tern_5_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4093632))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_5_o_weight_0_palettized")];
            tensor<fp16, [32, 352]> tern_5_o = linear(bias = linear_0_bias_0, weight = tern_5_o_weight_0_palettized, x = mul_261)[name = string("tern_5_o")];
            tensor<fp16, [352]> mul_262_y_0 = const()[name = string("mul_262_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4124672)))];
            tensor<fp16, [32, 352]> mul_262 = mul(x = tern_5_o, y = mul_262_y_0)[name = string("mul_262")];
            tensor<fp16, [32, 352]> add_33 = add(x = add_29, y = mul_262)[name = string("add_33")];
            tensor<fp16, [32, 352]> mul_263 = mul(x = add_33, y = add_33)[name = string("mul_263")];
            tensor<int32, [1]> reduce_mean_56_axes_0 = const()[name = string("reduce_mean_56_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_56_keep_dims_0 = const()[name = string("reduce_mean_56_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_56 = reduce_mean(axes = reduce_mean_56_axes_0, keep_dims = reduce_mean_56_keep_dims_0, x = mul_263)[name = string("reduce_mean_56")];
            fp32 rsqrt_56_epsilon_0 = const()[name = string("rsqrt_56_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_56 = rsqrt(epsilon = rsqrt_56_epsilon_0, x = reduce_mean_56)[name = string("rsqrt_56")];
            tensor<fp16, [32, 352]> mul_264 = mul(x = add_33, y = rsqrt_56)[name = string("mul_264")];
            tensor<fp16, [352]> mul_265_y_0 = const()[name = string("mul_265_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4125440)))];
            tensor<fp16, [32, 352]> mul_265 = mul(x = mul_264, y = mul_265_y_0)[name = string("mul_265")];
            tensor<fp16, [32, 352]> mul_266 = mul(x = mul_265, y = mul_265)[name = string("mul_266")];
            tensor<int32, [1]> reduce_mean_57_axes_0 = const()[name = string("reduce_mean_57_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_57_keep_dims_0 = const()[name = string("reduce_mean_57_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_57 = reduce_mean(axes = reduce_mean_57_axes_0, keep_dims = reduce_mean_57_keep_dims_0, x = mul_266)[name = string("reduce_mean_57")];
            fp32 rsqrt_57_epsilon_0 = const()[name = string("rsqrt_57_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_57 = rsqrt(epsilon = rsqrt_57_epsilon_0, x = reduce_mean_57)[name = string("rsqrt_57")];
            tensor<fp16, [32, 352]> mul_267 = mul(x = mul_265, y = rsqrt_57)[name = string("mul_267")];
            tensor<fp16, [352]> mul_268_y_0 = const()[name = string("mul_268_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4126208)))];
            tensor<fp16, [32, 352]> mul_268 = mul(x = mul_267, y = mul_268_y_0)[name = string("mul_268")];
            tensor<fp16, [960, 352]> tern_5_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4126976))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_5_w1_weight_0_palettized")];
            tensor<fp16, [32, 960]> tern_5_w1 = linear(bias = linear_4_bias_0, weight = tern_5_w1_weight_0_palettized, x = mul_268)[name = string("tern_5_w1")];
            tensor<fp16, [960]> mul_269_y_0 = const()[name = string("mul_269_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4211520)))];
            tensor<fp16, [32, 960]> mul_269 = mul(x = tern_5_w1, y = mul_269_y_0)[name = string("mul_269")];
            tensor<fp16, [352]> mul_272_y_0 = const()[name = string("mul_272_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4213504)))];
            tensor<fp16, [32, 352]> mul_272 = mul(x = mul_267, y = mul_272_y_0)[name = string("mul_272")];
            tensor<fp16, [960, 352]> tern_5_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4214272))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_5_w3_weight_0_palettized")];
            tensor<fp16, [32, 960]> tern_5_w3 = linear(bias = linear_4_bias_0, weight = tern_5_w3_weight_0_palettized, x = mul_272)[name = string("tern_5_w3")];
            tensor<fp16, [960]> mul_273_y_0 = const()[name = string("mul_273_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4298816)))];
            tensor<fp16, [32, 960]> mul_273 = mul(x = tern_5_w3, y = mul_273_y_0)[name = string("mul_273")];
            fp16 mul_274_y_0 = const()[name = string("mul_274_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [32, 960]> mul_274 = mul(x = mul_269, y = mul_274_y_0)[name = string("mul_274")];
            tensor<fp16, [32, 960]> tanh_5 = tanh(x = mul_274)[name = string("tanh_5")];
            fp16 mul_275_x_0 = const()[name = string("mul_275_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [32, 960]> mul_275 = mul(x = mul_275_x_0, y = tanh_5)[name = string("mul_275")];
            fp16 add_34_x_0 = const()[name = string("add_34_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [32, 960]> add_34 = add(x = add_34_x_0, y = mul_275)[name = string("add_34")];
            tensor<fp16, [32, 960]> mul_276 = mul(x = mul_269, y = add_34)[name = string("mul_276")];
            tensor<fp16, [32, 960]> mul_277 = mul(x = mul_276, y = mul_273)[name = string("mul_277")];
            tensor<fp16, [32, 960]> mul_278 = mul(x = mul_277, y = mul_277)[name = string("mul_278")];
            tensor<int32, [1]> reduce_mean_59_axes_0 = const()[name = string("reduce_mean_59_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_59_keep_dims_0 = const()[name = string("reduce_mean_59_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_59 = reduce_mean(axes = reduce_mean_59_axes_0, keep_dims = reduce_mean_59_keep_dims_0, x = mul_278)[name = string("reduce_mean_59")];
            fp32 rsqrt_59_epsilon_0 = const()[name = string("rsqrt_59_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_59 = rsqrt(epsilon = rsqrt_59_epsilon_0, x = reduce_mean_59)[name = string("rsqrt_59")];
            tensor<fp16, [32, 960]> mul_279 = mul(x = mul_277, y = rsqrt_59)[name = string("mul_279")];
            tensor<fp16, [960]> mul_280_y_0 = const()[name = string("mul_280_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4300800)))];
            tensor<fp16, [32, 960]> mul_280 = mul(x = mul_279, y = mul_280_y_0)[name = string("mul_280")];
            tensor<fp16, [352, 960]> tern_5_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4302784))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_5_w2_weight_0_palettized")];
            tensor<fp16, [32, 352]> tern_5_w2 = linear(bias = linear_0_bias_0, weight = tern_5_w2_weight_0_palettized, x = mul_280)[name = string("tern_5_w2")];
            tensor<fp16, [352]> mul_281_y_0 = const()[name = string("mul_281_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4387328)))];
            tensor<fp16, [32, 352]> mul_281 = mul(x = tern_5_w2, y = mul_281_y_0)[name = string("mul_281")];
            tensor<fp16, [32, 352]> add_35 = add(x = add_33, y = mul_281)[name = string("add_35")];
            tensor<fp16, [32, 352]> mul_282 = mul(x = add_35, y = add_35)[name = string("mul_282")];
            tensor<int32, [1]> reduce_mean_60_axes_0 = const()[name = string("reduce_mean_60_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_60_keep_dims_0 = const()[name = string("reduce_mean_60_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_60 = reduce_mean(axes = reduce_mean_60_axes_0, keep_dims = reduce_mean_60_keep_dims_0, x = mul_282)[name = string("reduce_mean_60")];
            fp32 rsqrt_60_epsilon_0 = const()[name = string("rsqrt_60_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_60 = rsqrt(epsilon = rsqrt_60_epsilon_0, x = reduce_mean_60)[name = string("rsqrt_60")];
            tensor<fp16, [32, 352]> mul_283 = mul(x = add_35, y = rsqrt_60)[name = string("mul_283")];
            tensor<fp16, [352]> mul_284_y_0 = const()[name = string("mul_284_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4388096)))];
            tensor<fp16, [32, 352]> mul_284 = mul(x = mul_283, y = mul_284_y_0)[name = string("mul_284")];
            tensor<fp16, [32, 352]> mul_285 = mul(x = mul_284, y = mul_284)[name = string("mul_285")];
            tensor<int32, [1]> reduce_mean_61_axes_0 = const()[name = string("reduce_mean_61_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_61_keep_dims_0 = const()[name = string("reduce_mean_61_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_61 = reduce_mean(axes = reduce_mean_61_axes_0, keep_dims = reduce_mean_61_keep_dims_0, x = mul_285)[name = string("reduce_mean_61")];
            fp32 rsqrt_61_epsilon_0 = const()[name = string("rsqrt_61_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_61 = rsqrt(epsilon = rsqrt_61_epsilon_0, x = reduce_mean_61)[name = string("rsqrt_61")];
            tensor<fp16, [32, 352]> mul_286 = mul(x = mul_284, y = rsqrt_61)[name = string("mul_286")];
            tensor<fp16, [352]> mul_287_y_0 = const()[name = string("mul_287_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4388864)))];
            tensor<fp16, [32, 352]> mul_287 = mul(x = mul_286, y = mul_287_y_0)[name = string("mul_287")];
            tensor<fp16, [352, 352]> tern_6_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4389632))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_6_q_weight_0_palettized")];
            tensor<fp16, [32, 352]> tern_6_q = linear(bias = linear_0_bias_0, weight = tern_6_q_weight_0_palettized, x = mul_287)[name = string("tern_6_q")];
            tensor<fp16, [352]> mul_288_y_0 = const()[name = string("mul_288_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4420672)))];
            tensor<fp16, [32, 352]> mul_288 = mul(x = tern_6_q, y = mul_288_y_0)[name = string("mul_288")];
            tensor<int32, [3]> reshape_50_shape_0 = const()[name = string("reshape_50_shape_0"), val = tensor<int32, [3]>([32, 8, 44])];
            tensor<fp16, [32, 8, 44]> reshape_50 = reshape(shape = reshape_50_shape_0, x = mul_288)[name = string("reshape_50")];
            tensor<int32, [3]> transpose_24_perm_0 = const()[name = string("transpose_24_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_291_y_0 = const()[name = string("mul_291_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4421440)))];
            tensor<fp16, [32, 352]> mul_291 = mul(x = mul_286, y = mul_291_y_0)[name = string("mul_291")];
            tensor<fp16, [88, 352]> tern_6_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4422208))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_6_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_6_k_bias_0 = const()[name = string("tern_6_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [32, 88]> tern_6_k = linear(bias = tern_6_k_bias_0, weight = tern_6_k_weight_0_palettized, x = mul_291)[name = string("tern_6_k")];
            tensor<fp16, [88]> mul_292_y_0 = const()[name = string("mul_292_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4430016)))];
            tensor<fp16, [32, 88]> mul_292 = mul(x = tern_6_k, y = mul_292_y_0)[name = string("mul_292")];
            tensor<int32, [3]> reshape_51_shape_0 = const()[name = string("reshape_51_shape_0"), val = tensor<int32, [3]>([32, 2, 44])];
            tensor<fp16, [32, 2, 44]> reshape_51 = reshape(shape = reshape_51_shape_0, x = mul_292)[name = string("reshape_51")];
            tensor<int32, [3]> transpose_25_perm_0 = const()[name = string("transpose_25_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_295_y_0 = const()[name = string("mul_295_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4430272)))];
            tensor<fp16, [32, 352]> mul_295 = mul(x = mul_286, y = mul_295_y_0)[name = string("mul_295")];
            tensor<fp16, [88, 352]> tern_6_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4431040))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_6_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_6_v_bias_0 = const()[name = string("tern_6_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [32, 88]> tern_6_v = linear(bias = tern_6_v_bias_0, weight = tern_6_v_weight_0_palettized, x = mul_295)[name = string("tern_6_v")];
            tensor<fp16, [88]> mul_296_y_0 = const()[name = string("mul_296_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4438848)))];
            tensor<fp16, [32, 88]> mul_296 = mul(x = tern_6_v, y = mul_296_y_0)[name = string("mul_296")];
            tensor<int32, [3]> reshape_52_shape_0 = const()[name = string("reshape_52_shape_0"), val = tensor<int32, [3]>([32, 2, 44])];
            tensor<fp16, [32, 2, 44]> reshape_52 = reshape(shape = reshape_52_shape_0, x = mul_296)[name = string("reshape_52")];
            tensor<int32, [3]> transpose_26_perm_0 = const()[name = string("transpose_26_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 32, 44]> transpose_24 = transpose(perm = transpose_24_perm_0, x = reshape_50)[name = string("transpose_39")];
            tensor<fp16, [8, 32, 44]> mul_297 = mul(x = transpose_24, y = transpose_24)[name = string("mul_297")];
            tensor<int32, [1]> reduce_mean_64_axes_0 = const()[name = string("reduce_mean_64_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_64_keep_dims_0 = const()[name = string("reduce_mean_64_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 32, 1]> reduce_mean_64 = reduce_mean(axes = reduce_mean_64_axes_0, keep_dims = reduce_mean_64_keep_dims_0, x = mul_297)[name = string("reduce_mean_64")];
            fp32 rsqrt_64_epsilon_0 = const()[name = string("rsqrt_64_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 32, 1]> rsqrt_64 = rsqrt(epsilon = rsqrt_64_epsilon_0, x = reduce_mean_64)[name = string("rsqrt_64")];
            tensor<fp16, [8, 32, 44]> mul_298 = mul(x = transpose_24, y = rsqrt_64)[name = string("mul_298")];
            tensor<fp16, [44]> mul_299_y_0 = const()[name = string("mul_299_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4439104)))];
            tensor<fp16, [8, 32, 44]> mul_299 = mul(x = mul_298, y = mul_299_y_0)[name = string("mul_299")];
            tensor<int32, [3]> slice_by_index_24_begin_0 = const()[name = string("slice_by_index_24_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_24_end_0 = const()[name = string("slice_by_index_24_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_24_end_mask_0 = const()[name = string("slice_by_index_24_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 32, 22]> slice_by_index_24 = slice_by_index(begin = slice_by_index_24_begin_0, end = slice_by_index_24_end_0, end_mask = slice_by_index_24_end_mask_0, x = mul_299)[name = string("slice_by_index_24")];
            tensor<int32, [3]> slice_by_index_25_begin_0 = const()[name = string("slice_by_index_25_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_25_end_0 = const()[name = string("slice_by_index_25_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_25_end_mask_0 = const()[name = string("slice_by_index_25_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 32, 22]> slice_by_index_25 = slice_by_index(begin = slice_by_index_25_begin_0, end = slice_by_index_25_end_0, end_mask = slice_by_index_25_end_mask_0, x = mul_299)[name = string("slice_by_index_25")];
            int32 concat_12_axis_0 = const()[name = string("concat_12_axis_0"), val = int32(-1)];
            bool concat_12_interleave_0 = const()[name = string("concat_12_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 32, 44]> concat_12 = concat(axis = concat_12_axis_0, interleave = concat_12_interleave_0, values = (slice_by_index_25, slice_by_index_24))[name = string("concat_12")];
            tensor<fp16, [44]> mul_300_y_0 = const()[name = string("mul_300_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 32, 44]> mul_300 = mul(x = concat_12, y = mul_300_y_0)[name = string("mul_300")];
            tensor<fp16, [8, 32, 44]> mul_301 = mul(x = mul_299, y = mul_11_y_0)[name = string("mul_301")];
            tensor<fp16, [8, 32, 44]> mul_302 = mul(x = mul_300, y = mul_12_y_0)[name = string("mul_302")];
            tensor<fp16, [8, 32, 44]> add_36 = add(x = mul_301, y = mul_302)[name = string("add_36")];
            tensor<fp16, [2, 32, 44]> transpose_25 = transpose(perm = transpose_25_perm_0, x = reshape_51)[name = string("transpose_38")];
            tensor<fp16, [2, 32, 44]> mul_303 = mul(x = transpose_25, y = transpose_25)[name = string("mul_303")];
            tensor<int32, [1]> reduce_mean_65_axes_0 = const()[name = string("reduce_mean_65_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_65_keep_dims_0 = const()[name = string("reduce_mean_65_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 32, 1]> reduce_mean_65 = reduce_mean(axes = reduce_mean_65_axes_0, keep_dims = reduce_mean_65_keep_dims_0, x = mul_303)[name = string("reduce_mean_65")];
            fp32 rsqrt_65_epsilon_0 = const()[name = string("rsqrt_65_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 32, 1]> rsqrt_65 = rsqrt(epsilon = rsqrt_65_epsilon_0, x = reduce_mean_65)[name = string("rsqrt_65")];
            tensor<fp16, [2, 32, 44]> mul_304 = mul(x = transpose_25, y = rsqrt_65)[name = string("mul_304")];
            tensor<fp16, [44]> mul_305_y_0 = const()[name = string("mul_305_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4439296)))];
            tensor<fp16, [2, 32, 44]> mul_305 = mul(x = mul_304, y = mul_305_y_0)[name = string("mul_305")];
            tensor<int32, [3]> slice_by_index_26_begin_0 = const()[name = string("slice_by_index_26_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_26_end_0 = const()[name = string("slice_by_index_26_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_26_end_mask_0 = const()[name = string("slice_by_index_26_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 32, 22]> slice_by_index_26 = slice_by_index(begin = slice_by_index_26_begin_0, end = slice_by_index_26_end_0, end_mask = slice_by_index_26_end_mask_0, x = mul_305)[name = string("slice_by_index_26")];
            tensor<int32, [3]> slice_by_index_27_begin_0 = const()[name = string("slice_by_index_27_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_27_end_0 = const()[name = string("slice_by_index_27_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_27_end_mask_0 = const()[name = string("slice_by_index_27_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 32, 22]> slice_by_index_27 = slice_by_index(begin = slice_by_index_27_begin_0, end = slice_by_index_27_end_0, end_mask = slice_by_index_27_end_mask_0, x = mul_305)[name = string("slice_by_index_27")];
            int32 concat_13_axis_0 = const()[name = string("concat_13_axis_0"), val = int32(-1)];
            bool concat_13_interleave_0 = const()[name = string("concat_13_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 32, 44]> concat_13 = concat(axis = concat_13_axis_0, interleave = concat_13_interleave_0, values = (slice_by_index_27, slice_by_index_26))[name = string("concat_13")];
            tensor<fp16, [44]> mul_306_y_0 = const()[name = string("mul_306_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 32, 44]> mul_306 = mul(x = concat_13, y = mul_306_y_0)[name = string("mul_306")];
            tensor<fp16, [2, 32, 44]> mul_307 = mul(x = mul_305, y = mul_11_y_0)[name = string("mul_307")];
            tensor<fp16, [2, 32, 44]> mul_308 = mul(x = mul_306, y = mul_12_y_0)[name = string("mul_308")];
            tensor<fp16, [2, 32, 44]> add_37 = add(x = mul_307, y = mul_308)[name = string("add_37")];
            tensor<int32, [4]> reshape_53_shape_0 = const()[name = string("reshape_53_shape_0"), val = tensor<int32, [4]>([2, 1, 32, 44])];
            tensor<fp16, [2, 1, 32, 44]> reshape_53 = reshape(shape = reshape_53_shape_0, x = add_37)[name = string("reshape_53")];
            tensor<int32, [4]> tile_12_reps_0 = const()[name = string("tile_12_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 32, 44]> tile_12 = tile(reps = tile_12_reps_0, x = reshape_53)[name = string("tile_12")];
            tensor<int32, [3]> reshape_54_shape_0 = const()[name = string("reshape_54_shape_0"), val = tensor<int32, [3]>([8, 32, 44])];
            tensor<fp16, [8, 32, 44]> reshape_54 = reshape(shape = reshape_54_shape_0, x = tile_12)[name = string("reshape_54")];
            tensor<int32, [4]> reshape_55_shape_0 = const()[name = string("reshape_55_shape_0"), val = tensor<int32, [4]>([2, 1, 32, 44])];
            tensor<fp16, [2, 32, 44]> transpose_26 = transpose(perm = transpose_26_perm_0, x = reshape_52)[name = string("transpose_37")];
            tensor<fp16, [2, 1, 32, 44]> reshape_55 = reshape(shape = reshape_55_shape_0, x = transpose_26)[name = string("reshape_55")];
            tensor<int32, [4]> tile_13_reps_0 = const()[name = string("tile_13_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 32, 44]> tile_13 = tile(reps = tile_13_reps_0, x = reshape_55)[name = string("tile_13")];
            tensor<int32, [3]> reshape_56_shape_0 = const()[name = string("reshape_56_shape_0"), val = tensor<int32, [3]>([8, 32, 44])];
            tensor<fp16, [8, 32, 44]> reshape_56 = reshape(shape = reshape_56_shape_0, x = tile_13)[name = string("reshape_56")];
            fp16 mul_309_y_0 = const()[name = string("mul_309_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 32, 44]> mul_309 = mul(x = add_36, y = mul_309_y_0)[name = string("mul_309")];
            bool matmul_12_transpose_y_0 = const()[name = string("matmul_12_transpose_y_0"), val = bool(true)];
            bool matmul_12_transpose_x_0 = const()[name = string("matmul_12_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 32, 32]> matmul_12 = matmul(transpose_x = matmul_12_transpose_x_0, transpose_y = matmul_12_transpose_y_0, x = mul_309, y = reshape_54)[name = string("matmul_12")];
            tensor<fp16, [8, 32, 32]> add_38 = add(x = matmul_12, y = reshape_1)[name = string("add_38")];
            int32 softmax_6_axis_0 = const()[name = string("softmax_6_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 32, 32]> softmax_6 = softmax(axis = softmax_6_axis_0, x = add_38)[name = string("softmax_6")];
            bool matmul_13_transpose_x_0 = const()[name = string("matmul_13_transpose_x_0"), val = bool(false)];
            bool matmul_13_transpose_y_0 = const()[name = string("matmul_13_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 32, 44]> matmul_13 = matmul(transpose_x = matmul_13_transpose_x_0, transpose_y = matmul_13_transpose_y_0, x = softmax_6, y = reshape_56)[name = string("matmul_13")];
            tensor<int32, [3]> transpose_27_perm_0 = const()[name = string("transpose_27_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_57_shape_0 = const()[name = string("reshape_57_shape_0"), val = tensor<int32, [2]>([32, 352])];
            tensor<fp16, [32, 8, 44]> transpose_27 = transpose(perm = transpose_27_perm_0, x = matmul_13)[name = string("transpose_36")];
            tensor<fp16, [32, 352]> reshape_57 = reshape(shape = reshape_57_shape_0, x = transpose_27)[name = string("reshape_57")];
            tensor<fp16, [32, 352]> mul_310 = mul(x = reshape_57, y = reshape_57)[name = string("mul_310")];
            tensor<int32, [1]> reduce_mean_66_axes_0 = const()[name = string("reduce_mean_66_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_66_keep_dims_0 = const()[name = string("reduce_mean_66_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_66 = reduce_mean(axes = reduce_mean_66_axes_0, keep_dims = reduce_mean_66_keep_dims_0, x = mul_310)[name = string("reduce_mean_66")];
            fp32 rsqrt_66_epsilon_0 = const()[name = string("rsqrt_66_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_66 = rsqrt(epsilon = rsqrt_66_epsilon_0, x = reduce_mean_66)[name = string("rsqrt_66")];
            tensor<fp16, [32, 352]> mul_311 = mul(x = reshape_57, y = rsqrt_66)[name = string("mul_311")];
            tensor<fp16, [352]> mul_312_y_0 = const()[name = string("mul_312_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4439488)))];
            tensor<fp16, [32, 352]> mul_312 = mul(x = mul_311, y = mul_312_y_0)[name = string("mul_312")];
            tensor<fp16, [352, 352]> tern_6_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4440256))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_6_o_weight_0_palettized")];
            tensor<fp16, [32, 352]> tern_6_o = linear(bias = linear_0_bias_0, weight = tern_6_o_weight_0_palettized, x = mul_312)[name = string("tern_6_o")];
            tensor<fp16, [352]> mul_313_y_0 = const()[name = string("mul_313_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4471296)))];
            tensor<fp16, [32, 352]> mul_313 = mul(x = tern_6_o, y = mul_313_y_0)[name = string("mul_313")];
            tensor<fp16, [32, 352]> add_39 = add(x = add_35, y = mul_313)[name = string("add_39")];
            tensor<fp16, [32, 352]> mul_314 = mul(x = add_39, y = add_39)[name = string("mul_314")];
            tensor<int32, [1]> reduce_mean_67_axes_0 = const()[name = string("reduce_mean_67_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_67_keep_dims_0 = const()[name = string("reduce_mean_67_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_67 = reduce_mean(axes = reduce_mean_67_axes_0, keep_dims = reduce_mean_67_keep_dims_0, x = mul_314)[name = string("reduce_mean_67")];
            fp32 rsqrt_67_epsilon_0 = const()[name = string("rsqrt_67_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_67 = rsqrt(epsilon = rsqrt_67_epsilon_0, x = reduce_mean_67)[name = string("rsqrt_67")];
            tensor<fp16, [32, 352]> mul_315 = mul(x = add_39, y = rsqrt_67)[name = string("mul_315")];
            tensor<fp16, [352]> mul_316_y_0 = const()[name = string("mul_316_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4472064)))];
            tensor<fp16, [32, 352]> mul_316 = mul(x = mul_315, y = mul_316_y_0)[name = string("mul_316")];
            tensor<fp16, [32, 352]> mul_317 = mul(x = mul_316, y = mul_316)[name = string("mul_317")];
            tensor<int32, [1]> reduce_mean_68_axes_0 = const()[name = string("reduce_mean_68_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_68_keep_dims_0 = const()[name = string("reduce_mean_68_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_68 = reduce_mean(axes = reduce_mean_68_axes_0, keep_dims = reduce_mean_68_keep_dims_0, x = mul_317)[name = string("reduce_mean_68")];
            fp32 rsqrt_68_epsilon_0 = const()[name = string("rsqrt_68_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_68 = rsqrt(epsilon = rsqrt_68_epsilon_0, x = reduce_mean_68)[name = string("rsqrt_68")];
            tensor<fp16, [32, 352]> mul_318 = mul(x = mul_316, y = rsqrt_68)[name = string("mul_318")];
            tensor<fp16, [352]> mul_319_y_0 = const()[name = string("mul_319_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4472832)))];
            tensor<fp16, [32, 352]> mul_319 = mul(x = mul_318, y = mul_319_y_0)[name = string("mul_319")];
            tensor<fp16, [960, 352]> tern_6_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4473600))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_6_w1_weight_0_palettized")];
            tensor<fp16, [32, 960]> tern_6_w1 = linear(bias = linear_4_bias_0, weight = tern_6_w1_weight_0_palettized, x = mul_319)[name = string("tern_6_w1")];
            tensor<fp16, [960]> mul_320_y_0 = const()[name = string("mul_320_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4558144)))];
            tensor<fp16, [32, 960]> mul_320 = mul(x = tern_6_w1, y = mul_320_y_0)[name = string("mul_320")];
            tensor<fp16, [352]> mul_323_y_0 = const()[name = string("mul_323_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4560128)))];
            tensor<fp16, [32, 352]> mul_323 = mul(x = mul_318, y = mul_323_y_0)[name = string("mul_323")];
            tensor<fp16, [960, 352]> tern_6_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4560896))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_6_w3_weight_0_palettized")];
            tensor<fp16, [32, 960]> tern_6_w3 = linear(bias = linear_4_bias_0, weight = tern_6_w3_weight_0_palettized, x = mul_323)[name = string("tern_6_w3")];
            tensor<fp16, [960]> mul_324_y_0 = const()[name = string("mul_324_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4645440)))];
            tensor<fp16, [32, 960]> mul_324 = mul(x = tern_6_w3, y = mul_324_y_0)[name = string("mul_324")];
            fp16 mul_325_y_0 = const()[name = string("mul_325_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [32, 960]> mul_325 = mul(x = mul_320, y = mul_325_y_0)[name = string("mul_325")];
            tensor<fp16, [32, 960]> tanh_6 = tanh(x = mul_325)[name = string("tanh_6")];
            fp16 mul_326_x_0 = const()[name = string("mul_326_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [32, 960]> mul_326 = mul(x = mul_326_x_0, y = tanh_6)[name = string("mul_326")];
            fp16 add_40_x_0 = const()[name = string("add_40_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [32, 960]> add_40 = add(x = add_40_x_0, y = mul_326)[name = string("add_40")];
            tensor<fp16, [32, 960]> mul_327 = mul(x = mul_320, y = add_40)[name = string("mul_327")];
            tensor<fp16, [32, 960]> mul_328 = mul(x = mul_327, y = mul_324)[name = string("mul_328")];
            tensor<fp16, [32, 960]> mul_329 = mul(x = mul_328, y = mul_328)[name = string("mul_329")];
            tensor<int32, [1]> reduce_mean_70_axes_0 = const()[name = string("reduce_mean_70_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_70_keep_dims_0 = const()[name = string("reduce_mean_70_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_70 = reduce_mean(axes = reduce_mean_70_axes_0, keep_dims = reduce_mean_70_keep_dims_0, x = mul_329)[name = string("reduce_mean_70")];
            fp32 rsqrt_70_epsilon_0 = const()[name = string("rsqrt_70_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_70 = rsqrt(epsilon = rsqrt_70_epsilon_0, x = reduce_mean_70)[name = string("rsqrt_70")];
            tensor<fp16, [32, 960]> mul_330 = mul(x = mul_328, y = rsqrt_70)[name = string("mul_330")];
            tensor<fp16, [960]> mul_331_y_0 = const()[name = string("mul_331_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4647424)))];
            tensor<fp16, [32, 960]> mul_331 = mul(x = mul_330, y = mul_331_y_0)[name = string("mul_331")];
            tensor<fp16, [352, 960]> tern_6_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4649408))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_6_w2_weight_0_palettized")];
            tensor<fp16, [32, 352]> tern_6_w2 = linear(bias = linear_0_bias_0, weight = tern_6_w2_weight_0_palettized, x = mul_331)[name = string("tern_6_w2")];
            tensor<fp16, [352]> mul_332_y_0 = const()[name = string("mul_332_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4733952)))];
            tensor<fp16, [32, 352]> mul_332 = mul(x = tern_6_w2, y = mul_332_y_0)[name = string("mul_332")];
            tensor<fp16, [32, 352]> add_41 = add(x = add_39, y = mul_332)[name = string("add_41")];
            tensor<fp16, [32, 352]> mul_333 = mul(x = add_41, y = add_41)[name = string("mul_333")];
            tensor<int32, [1]> reduce_mean_71_axes_0 = const()[name = string("reduce_mean_71_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_71_keep_dims_0 = const()[name = string("reduce_mean_71_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_71 = reduce_mean(axes = reduce_mean_71_axes_0, keep_dims = reduce_mean_71_keep_dims_0, x = mul_333)[name = string("reduce_mean_71")];
            fp32 rsqrt_71_epsilon_0 = const()[name = string("rsqrt_71_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_71 = rsqrt(epsilon = rsqrt_71_epsilon_0, x = reduce_mean_71)[name = string("rsqrt_71")];
            tensor<fp16, [32, 352]> mul_334 = mul(x = add_41, y = rsqrt_71)[name = string("mul_334")];
            tensor<fp16, [352]> mul_335_y_0 = const()[name = string("mul_335_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4734720)))];
            tensor<fp16, [32, 352]> mul_335 = mul(x = mul_334, y = mul_335_y_0)[name = string("mul_335")];
            tensor<fp16, [32, 352]> mul_336 = mul(x = mul_335, y = mul_335)[name = string("mul_336")];
            tensor<int32, [1]> reduce_mean_72_axes_0 = const()[name = string("reduce_mean_72_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_72_keep_dims_0 = const()[name = string("reduce_mean_72_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_72 = reduce_mean(axes = reduce_mean_72_axes_0, keep_dims = reduce_mean_72_keep_dims_0, x = mul_336)[name = string("reduce_mean_72")];
            fp32 rsqrt_72_epsilon_0 = const()[name = string("rsqrt_72_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_72 = rsqrt(epsilon = rsqrt_72_epsilon_0, x = reduce_mean_72)[name = string("rsqrt_72")];
            tensor<fp16, [32, 352]> mul_337 = mul(x = mul_335, y = rsqrt_72)[name = string("mul_337")];
            tensor<fp16, [352]> mul_338_y_0 = const()[name = string("mul_338_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4735488)))];
            tensor<fp16, [32, 352]> mul_338 = mul(x = mul_337, y = mul_338_y_0)[name = string("mul_338")];
            tensor<fp16, [352, 352]> tern_7_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4736256))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_7_q_weight_0_palettized")];
            tensor<fp16, [32, 352]> tern_7_q = linear(bias = linear_0_bias_0, weight = tern_7_q_weight_0_palettized, x = mul_338)[name = string("tern_7_q")];
            tensor<fp16, [352]> mul_339_y_0 = const()[name = string("mul_339_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4767296)))];
            tensor<fp16, [32, 352]> mul_339 = mul(x = tern_7_q, y = mul_339_y_0)[name = string("mul_339")];
            tensor<int32, [3]> reshape_58_shape_0 = const()[name = string("reshape_58_shape_0"), val = tensor<int32, [3]>([32, 8, 44])];
            tensor<fp16, [32, 8, 44]> reshape_58 = reshape(shape = reshape_58_shape_0, x = mul_339)[name = string("reshape_58")];
            tensor<int32, [3]> transpose_28_perm_0 = const()[name = string("transpose_28_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_342_y_0 = const()[name = string("mul_342_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4768064)))];
            tensor<fp16, [32, 352]> mul_342 = mul(x = mul_337, y = mul_342_y_0)[name = string("mul_342")];
            tensor<fp16, [88, 352]> tern_7_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4768832))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_7_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_7_k_bias_0 = const()[name = string("tern_7_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [32, 88]> tern_7_k = linear(bias = tern_7_k_bias_0, weight = tern_7_k_weight_0_palettized, x = mul_342)[name = string("tern_7_k")];
            tensor<fp16, [88]> mul_343_y_0 = const()[name = string("mul_343_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4776640)))];
            tensor<fp16, [32, 88]> mul_343 = mul(x = tern_7_k, y = mul_343_y_0)[name = string("mul_343")];
            tensor<int32, [3]> reshape_59_shape_0 = const()[name = string("reshape_59_shape_0"), val = tensor<int32, [3]>([32, 2, 44])];
            tensor<fp16, [32, 2, 44]> reshape_59 = reshape(shape = reshape_59_shape_0, x = mul_343)[name = string("reshape_59")];
            tensor<int32, [3]> transpose_29_perm_0 = const()[name = string("transpose_29_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_346_y_0 = const()[name = string("mul_346_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4776896)))];
            tensor<fp16, [32, 352]> mul_346 = mul(x = mul_337, y = mul_346_y_0)[name = string("mul_346")];
            tensor<fp16, [88, 352]> tern_7_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4777664))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_7_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_7_v_bias_0 = const()[name = string("tern_7_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [32, 88]> tern_7_v = linear(bias = tern_7_v_bias_0, weight = tern_7_v_weight_0_palettized, x = mul_346)[name = string("tern_7_v")];
            tensor<fp16, [88]> mul_347_y_0 = const()[name = string("mul_347_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4785472)))];
            tensor<fp16, [32, 88]> mul_347 = mul(x = tern_7_v, y = mul_347_y_0)[name = string("mul_347")];
            tensor<int32, [3]> reshape_60_shape_0 = const()[name = string("reshape_60_shape_0"), val = tensor<int32, [3]>([32, 2, 44])];
            tensor<fp16, [32, 2, 44]> reshape_60 = reshape(shape = reshape_60_shape_0, x = mul_347)[name = string("reshape_60")];
            tensor<int32, [3]> transpose_30_perm_0 = const()[name = string("transpose_30_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 32, 44]> transpose_28 = transpose(perm = transpose_28_perm_0, x = reshape_58)[name = string("transpose_35")];
            tensor<fp16, [8, 32, 44]> mul_348 = mul(x = transpose_28, y = transpose_28)[name = string("mul_348")];
            tensor<int32, [1]> reduce_mean_75_axes_0 = const()[name = string("reduce_mean_75_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_75_keep_dims_0 = const()[name = string("reduce_mean_75_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 32, 1]> reduce_mean_75 = reduce_mean(axes = reduce_mean_75_axes_0, keep_dims = reduce_mean_75_keep_dims_0, x = mul_348)[name = string("reduce_mean_75")];
            fp32 rsqrt_75_epsilon_0 = const()[name = string("rsqrt_75_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 32, 1]> rsqrt_75 = rsqrt(epsilon = rsqrt_75_epsilon_0, x = reduce_mean_75)[name = string("rsqrt_75")];
            tensor<fp16, [8, 32, 44]> mul_349 = mul(x = transpose_28, y = rsqrt_75)[name = string("mul_349")];
            tensor<fp16, [44]> mul_350_y_0 = const()[name = string("mul_350_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4785728)))];
            tensor<fp16, [8, 32, 44]> mul_350 = mul(x = mul_349, y = mul_350_y_0)[name = string("mul_350")];
            tensor<int32, [3]> slice_by_index_28_begin_0 = const()[name = string("slice_by_index_28_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_28_end_0 = const()[name = string("slice_by_index_28_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_28_end_mask_0 = const()[name = string("slice_by_index_28_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 32, 22]> slice_by_index_28 = slice_by_index(begin = slice_by_index_28_begin_0, end = slice_by_index_28_end_0, end_mask = slice_by_index_28_end_mask_0, x = mul_350)[name = string("slice_by_index_28")];
            tensor<int32, [3]> slice_by_index_29_begin_0 = const()[name = string("slice_by_index_29_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_29_end_0 = const()[name = string("slice_by_index_29_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_29_end_mask_0 = const()[name = string("slice_by_index_29_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 32, 22]> slice_by_index_29 = slice_by_index(begin = slice_by_index_29_begin_0, end = slice_by_index_29_end_0, end_mask = slice_by_index_29_end_mask_0, x = mul_350)[name = string("slice_by_index_29")];
            int32 concat_14_axis_0 = const()[name = string("concat_14_axis_0"), val = int32(-1)];
            bool concat_14_interleave_0 = const()[name = string("concat_14_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 32, 44]> concat_14 = concat(axis = concat_14_axis_0, interleave = concat_14_interleave_0, values = (slice_by_index_29, slice_by_index_28))[name = string("concat_14")];
            tensor<fp16, [44]> mul_351_y_0 = const()[name = string("mul_351_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 32, 44]> mul_351 = mul(x = concat_14, y = mul_351_y_0)[name = string("mul_351")];
            tensor<fp16, [8, 32, 44]> mul_352 = mul(x = mul_350, y = mul_11_y_0)[name = string("mul_352")];
            tensor<fp16, [8, 32, 44]> mul_353 = mul(x = mul_351, y = mul_12_y_0)[name = string("mul_353")];
            tensor<fp16, [8, 32, 44]> add_42 = add(x = mul_352, y = mul_353)[name = string("add_42")];
            tensor<fp16, [2, 32, 44]> transpose_29 = transpose(perm = transpose_29_perm_0, x = reshape_59)[name = string("transpose_34")];
            tensor<fp16, [2, 32, 44]> mul_354 = mul(x = transpose_29, y = transpose_29)[name = string("mul_354")];
            tensor<int32, [1]> reduce_mean_76_axes_0 = const()[name = string("reduce_mean_76_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_76_keep_dims_0 = const()[name = string("reduce_mean_76_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 32, 1]> reduce_mean_76 = reduce_mean(axes = reduce_mean_76_axes_0, keep_dims = reduce_mean_76_keep_dims_0, x = mul_354)[name = string("reduce_mean_76")];
            fp32 rsqrt_76_epsilon_0 = const()[name = string("rsqrt_76_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 32, 1]> rsqrt_76 = rsqrt(epsilon = rsqrt_76_epsilon_0, x = reduce_mean_76)[name = string("rsqrt_76")];
            tensor<fp16, [2, 32, 44]> mul_355 = mul(x = transpose_29, y = rsqrt_76)[name = string("mul_355")];
            tensor<fp16, [44]> mul_356_y_0 = const()[name = string("mul_356_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4785920)))];
            tensor<fp16, [2, 32, 44]> mul_356 = mul(x = mul_355, y = mul_356_y_0)[name = string("mul_356")];
            tensor<int32, [3]> slice_by_index_30_begin_0 = const()[name = string("slice_by_index_30_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_30_end_0 = const()[name = string("slice_by_index_30_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_30_end_mask_0 = const()[name = string("slice_by_index_30_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 32, 22]> slice_by_index_30 = slice_by_index(begin = slice_by_index_30_begin_0, end = slice_by_index_30_end_0, end_mask = slice_by_index_30_end_mask_0, x = mul_356)[name = string("slice_by_index_30")];
            tensor<int32, [3]> slice_by_index_31_begin_0 = const()[name = string("slice_by_index_31_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_31_end_0 = const()[name = string("slice_by_index_31_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_31_end_mask_0 = const()[name = string("slice_by_index_31_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 32, 22]> slice_by_index_31 = slice_by_index(begin = slice_by_index_31_begin_0, end = slice_by_index_31_end_0, end_mask = slice_by_index_31_end_mask_0, x = mul_356)[name = string("slice_by_index_31")];
            int32 concat_15_axis_0 = const()[name = string("concat_15_axis_0"), val = int32(-1)];
            bool concat_15_interleave_0 = const()[name = string("concat_15_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 32, 44]> concat_15 = concat(axis = concat_15_axis_0, interleave = concat_15_interleave_0, values = (slice_by_index_31, slice_by_index_30))[name = string("concat_15")];
            tensor<fp16, [44]> mul_357_y_0 = const()[name = string("mul_357_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 32, 44]> mul_357 = mul(x = concat_15, y = mul_357_y_0)[name = string("mul_357")];
            tensor<fp16, [2, 32, 44]> mul_358 = mul(x = mul_356, y = mul_11_y_0)[name = string("mul_358")];
            tensor<fp16, [2, 32, 44]> mul_359 = mul(x = mul_357, y = mul_12_y_0)[name = string("mul_359")];
            tensor<fp16, [2, 32, 44]> add_43 = add(x = mul_358, y = mul_359)[name = string("add_43")];
            tensor<int32, [4]> reshape_61_shape_0 = const()[name = string("reshape_61_shape_0"), val = tensor<int32, [4]>([2, 1, 32, 44])];
            tensor<fp16, [2, 1, 32, 44]> reshape_61 = reshape(shape = reshape_61_shape_0, x = add_43)[name = string("reshape_61")];
            tensor<int32, [4]> tile_14_reps_0 = const()[name = string("tile_14_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 32, 44]> tile_14 = tile(reps = tile_14_reps_0, x = reshape_61)[name = string("tile_14")];
            tensor<int32, [3]> reshape_62_shape_0 = const()[name = string("reshape_62_shape_0"), val = tensor<int32, [3]>([8, 32, 44])];
            tensor<fp16, [8, 32, 44]> reshape_62 = reshape(shape = reshape_62_shape_0, x = tile_14)[name = string("reshape_62")];
            tensor<int32, [4]> reshape_63_shape_0 = const()[name = string("reshape_63_shape_0"), val = tensor<int32, [4]>([2, 1, 32, 44])];
            tensor<fp16, [2, 32, 44]> transpose_30 = transpose(perm = transpose_30_perm_0, x = reshape_60)[name = string("transpose_33")];
            tensor<fp16, [2, 1, 32, 44]> reshape_63 = reshape(shape = reshape_63_shape_0, x = transpose_30)[name = string("reshape_63")];
            tensor<int32, [4]> tile_15_reps_0 = const()[name = string("tile_15_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 32, 44]> tile_15 = tile(reps = tile_15_reps_0, x = reshape_63)[name = string("tile_15")];
            tensor<int32, [3]> reshape_64_shape_0 = const()[name = string("reshape_64_shape_0"), val = tensor<int32, [3]>([8, 32, 44])];
            tensor<fp16, [8, 32, 44]> reshape_64 = reshape(shape = reshape_64_shape_0, x = tile_15)[name = string("reshape_64")];
            fp16 mul_360_y_0 = const()[name = string("mul_360_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 32, 44]> mul_360 = mul(x = add_42, y = mul_360_y_0)[name = string("mul_360")];
            bool matmul_14_transpose_y_0 = const()[name = string("matmul_14_transpose_y_0"), val = bool(true)];
            bool matmul_14_transpose_x_0 = const()[name = string("matmul_14_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 32, 32]> matmul_14 = matmul(transpose_x = matmul_14_transpose_x_0, transpose_y = matmul_14_transpose_y_0, x = mul_360, y = reshape_62)[name = string("matmul_14")];
            tensor<fp16, [8, 32, 32]> add_44 = add(x = matmul_14, y = reshape_1)[name = string("add_44")];
            int32 softmax_7_axis_0 = const()[name = string("softmax_7_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 32, 32]> softmax_7 = softmax(axis = softmax_7_axis_0, x = add_44)[name = string("softmax_7")];
            bool matmul_15_transpose_x_0 = const()[name = string("matmul_15_transpose_x_0"), val = bool(false)];
            bool matmul_15_transpose_y_0 = const()[name = string("matmul_15_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 32, 44]> matmul_15 = matmul(transpose_x = matmul_15_transpose_x_0, transpose_y = matmul_15_transpose_y_0, x = softmax_7, y = reshape_64)[name = string("matmul_15")];
            tensor<int32, [3]> transpose_31_perm_0 = const()[name = string("transpose_31_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_65_shape_0 = const()[name = string("reshape_65_shape_0"), val = tensor<int32, [2]>([32, 352])];
            tensor<fp16, [32, 8, 44]> transpose_31 = transpose(perm = transpose_31_perm_0, x = matmul_15)[name = string("transpose_32")];
            tensor<fp16, [32, 352]> reshape_65 = reshape(shape = reshape_65_shape_0, x = transpose_31)[name = string("reshape_65")];
            tensor<fp16, [32, 352]> mul_361 = mul(x = reshape_65, y = reshape_65)[name = string("mul_361")];
            tensor<int32, [1]> reduce_mean_77_axes_0 = const()[name = string("reduce_mean_77_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_77_keep_dims_0 = const()[name = string("reduce_mean_77_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_77 = reduce_mean(axes = reduce_mean_77_axes_0, keep_dims = reduce_mean_77_keep_dims_0, x = mul_361)[name = string("reduce_mean_77")];
            fp32 rsqrt_77_epsilon_0 = const()[name = string("rsqrt_77_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_77 = rsqrt(epsilon = rsqrt_77_epsilon_0, x = reduce_mean_77)[name = string("rsqrt_77")];
            tensor<fp16, [32, 352]> mul_362 = mul(x = reshape_65, y = rsqrt_77)[name = string("mul_362")];
            tensor<fp16, [352]> mul_363_y_0 = const()[name = string("mul_363_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4786112)))];
            tensor<fp16, [32, 352]> mul_363 = mul(x = mul_362, y = mul_363_y_0)[name = string("mul_363")];
            tensor<fp16, [352, 352]> tern_7_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4786880))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_7_o_weight_0_palettized")];
            tensor<fp16, [32, 352]> tern_7_o = linear(bias = linear_0_bias_0, weight = tern_7_o_weight_0_palettized, x = mul_363)[name = string("tern_7_o")];
            tensor<fp16, [352]> mul_364_y_0 = const()[name = string("mul_364_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4817920)))];
            tensor<fp16, [32, 352]> mul_364 = mul(x = tern_7_o, y = mul_364_y_0)[name = string("mul_364")];
            tensor<fp16, [32, 352]> add_45 = add(x = add_41, y = mul_364)[name = string("add_45")];
            tensor<fp16, [32, 352]> mul_365 = mul(x = add_45, y = add_45)[name = string("mul_365")];
            tensor<int32, [1]> reduce_mean_78_axes_0 = const()[name = string("reduce_mean_78_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_78_keep_dims_0 = const()[name = string("reduce_mean_78_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_78 = reduce_mean(axes = reduce_mean_78_axes_0, keep_dims = reduce_mean_78_keep_dims_0, x = mul_365)[name = string("reduce_mean_78")];
            fp32 rsqrt_78_epsilon_0 = const()[name = string("rsqrt_78_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_78 = rsqrt(epsilon = rsqrt_78_epsilon_0, x = reduce_mean_78)[name = string("rsqrt_78")];
            tensor<fp16, [32, 352]> mul_366 = mul(x = add_45, y = rsqrt_78)[name = string("mul_366")];
            tensor<fp16, [352]> mul_367_y_0 = const()[name = string("mul_367_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4818688)))];
            tensor<fp16, [32, 352]> mul_367 = mul(x = mul_366, y = mul_367_y_0)[name = string("mul_367")];
            tensor<fp16, [32, 352]> mul_368 = mul(x = mul_367, y = mul_367)[name = string("mul_368")];
            tensor<int32, [1]> reduce_mean_79_axes_0 = const()[name = string("reduce_mean_79_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_79_keep_dims_0 = const()[name = string("reduce_mean_79_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_79 = reduce_mean(axes = reduce_mean_79_axes_0, keep_dims = reduce_mean_79_keep_dims_0, x = mul_368)[name = string("reduce_mean_79")];
            fp32 rsqrt_79_epsilon_0 = const()[name = string("rsqrt_79_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_79 = rsqrt(epsilon = rsqrt_79_epsilon_0, x = reduce_mean_79)[name = string("rsqrt_79")];
            tensor<fp16, [32, 352]> mul_369 = mul(x = mul_367, y = rsqrt_79)[name = string("mul_369")];
            tensor<fp16, [352]> mul_370_y_0 = const()[name = string("mul_370_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4819456)))];
            tensor<fp16, [32, 352]> mul_370 = mul(x = mul_369, y = mul_370_y_0)[name = string("mul_370")];
            tensor<fp16, [960, 352]> tern_7_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4820224))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_7_w1_weight_0_palettized")];
            tensor<fp16, [32, 960]> tern_7_w1 = linear(bias = linear_4_bias_0, weight = tern_7_w1_weight_0_palettized, x = mul_370)[name = string("tern_7_w1")];
            tensor<fp16, [960]> mul_371_y_0 = const()[name = string("mul_371_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4904768)))];
            tensor<fp16, [32, 960]> mul_371 = mul(x = tern_7_w1, y = mul_371_y_0)[name = string("mul_371")];
            tensor<fp16, [352]> mul_374_y_0 = const()[name = string("mul_374_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4906752)))];
            tensor<fp16, [32, 352]> mul_374 = mul(x = mul_369, y = mul_374_y_0)[name = string("mul_374")];
            tensor<fp16, [960, 352]> tern_7_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4907520))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_7_w3_weight_0_palettized")];
            tensor<fp16, [32, 960]> tern_7_w3 = linear(bias = linear_4_bias_0, weight = tern_7_w3_weight_0_palettized, x = mul_374)[name = string("tern_7_w3")];
            tensor<fp16, [960]> mul_375_y_0 = const()[name = string("mul_375_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4992064)))];
            tensor<fp16, [32, 960]> mul_375 = mul(x = tern_7_w3, y = mul_375_y_0)[name = string("mul_375")];
            fp16 mul_376_y_0 = const()[name = string("mul_376_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [32, 960]> mul_376 = mul(x = mul_371, y = mul_376_y_0)[name = string("mul_376")];
            tensor<fp16, [32, 960]> tanh_7 = tanh(x = mul_376)[name = string("tanh_7")];
            fp16 mul_377_x_0 = const()[name = string("mul_377_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [32, 960]> mul_377 = mul(x = mul_377_x_0, y = tanh_7)[name = string("mul_377")];
            fp16 add_46_x_0 = const()[name = string("add_46_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [32, 960]> add_46 = add(x = add_46_x_0, y = mul_377)[name = string("add_46")];
            tensor<fp16, [32, 960]> mul_378 = mul(x = mul_371, y = add_46)[name = string("mul_378")];
            tensor<fp16, [32, 960]> mul_379 = mul(x = mul_378, y = mul_375)[name = string("mul_379")];
            tensor<fp16, [32, 960]> mul_380 = mul(x = mul_379, y = mul_379)[name = string("mul_380")];
            tensor<int32, [1]> reduce_mean_81_axes_0 = const()[name = string("reduce_mean_81_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_81_keep_dims_0 = const()[name = string("reduce_mean_81_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_81 = reduce_mean(axes = reduce_mean_81_axes_0, keep_dims = reduce_mean_81_keep_dims_0, x = mul_380)[name = string("reduce_mean_81")];
            fp32 rsqrt_81_epsilon_0 = const()[name = string("rsqrt_81_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_81 = rsqrt(epsilon = rsqrt_81_epsilon_0, x = reduce_mean_81)[name = string("rsqrt_81")];
            tensor<fp16, [32, 960]> mul_381 = mul(x = mul_379, y = rsqrt_81)[name = string("mul_381")];
            tensor<fp16, [960]> mul_382_y_0 = const()[name = string("mul_382_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4994048)))];
            tensor<fp16, [32, 960]> mul_382 = mul(x = mul_381, y = mul_382_y_0)[name = string("mul_382")];
            tensor<fp16, [352, 960]> tern_7_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4996032))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_7_w2_weight_0_palettized")];
            tensor<fp16, [32, 352]> tern_7_w2 = linear(bias = linear_0_bias_0, weight = tern_7_w2_weight_0_palettized, x = mul_382)[name = string("tern_7_w2")];
            tensor<fp16, [352]> mul_383_y_0 = const()[name = string("mul_383_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5080576)))];
            tensor<fp16, [32, 352]> mul_383 = mul(x = tern_7_w2, y = mul_383_y_0)[name = string("mul_383")];
            tensor<fp16, [32, 352]> add_47 = add(x = add_45, y = mul_383)[name = string("add_47")];
            tensor<fp16, [32, 352]> mul_384 = mul(x = add_47, y = add_47)[name = string("mul_384")];
            tensor<int32, [1]> reduce_mean_82_axes_0 = const()[name = string("reduce_mean_82_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_82_keep_dims_0 = const()[name = string("reduce_mean_82_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_82 = reduce_mean(axes = reduce_mean_82_axes_0, keep_dims = reduce_mean_82_keep_dims_0, x = mul_384)[name = string("reduce_mean_82")];
            fp32 rsqrt_82_epsilon_0 = const()[name = string("rsqrt_82_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_82 = rsqrt(epsilon = rsqrt_82_epsilon_0, x = reduce_mean_82)[name = string("rsqrt_82")];
            tensor<fp16, [32, 352]> mul_385 = mul(x = add_47, y = rsqrt_82)[name = string("mul_385")];
            tensor<fp16, [352]> mul_386_y_0 = const()[name = string("mul_386_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5081344)))];
            tensor<fp16, [32, 352]> mul_386 = mul(x = mul_385, y = mul_386_y_0)[name = string("mul_386")];
            tensor<fp16, [32, 352]> mul_387 = mul(x = mul_386, y = mul_386)[name = string("mul_387")];
            tensor<int32, [1]> reduce_mean_83_axes_0 = const()[name = string("reduce_mean_83_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_83_keep_dims_0 = const()[name = string("reduce_mean_83_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_83 = reduce_mean(axes = reduce_mean_83_axes_0, keep_dims = reduce_mean_83_keep_dims_0, x = mul_387)[name = string("reduce_mean_83")];
            fp32 rsqrt_83_epsilon_0 = const()[name = string("rsqrt_83_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_83 = rsqrt(epsilon = rsqrt_83_epsilon_0, x = reduce_mean_83)[name = string("rsqrt_83")];
            tensor<fp16, [32, 352]> mul_388 = mul(x = mul_386, y = rsqrt_83)[name = string("mul_388")];
            tensor<fp16, [352]> mul_389_y_0 = const()[name = string("mul_389_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5082112)))];
            tensor<fp16, [32, 352]> mul_389 = mul(x = mul_388, y = mul_389_y_0)[name = string("mul_389")];
            tensor<fp16, [352, 352]> tern_8_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5082880))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_8_q_weight_0_palettized")];
            tensor<fp16, [32, 352]> tern_8_q = linear(bias = linear_0_bias_0, weight = tern_8_q_weight_0_palettized, x = mul_389)[name = string("tern_8_q")];
            tensor<fp16, [352]> mul_390_y_0 = const()[name = string("mul_390_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5113920)))];
            tensor<fp16, [32, 352]> mul_390 = mul(x = tern_8_q, y = mul_390_y_0)[name = string("mul_390")];
            tensor<int32, [3]> reshape_66_shape_0 = const()[name = string("reshape_66_shape_0"), val = tensor<int32, [3]>([32, 8, 44])];
            tensor<fp16, [32, 8, 44]> reshape_66 = reshape(shape = reshape_66_shape_0, x = mul_390)[name = string("reshape_66")];
            tensor<int32, [3]> transpose_32_perm_0 = const()[name = string("transpose_32_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_393_y_0 = const()[name = string("mul_393_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5114688)))];
            tensor<fp16, [32, 352]> mul_393 = mul(x = mul_388, y = mul_393_y_0)[name = string("mul_393")];
            tensor<fp16, [88, 352]> tern_8_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5115456))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_8_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_8_k_bias_0 = const()[name = string("tern_8_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [32, 88]> tern_8_k = linear(bias = tern_8_k_bias_0, weight = tern_8_k_weight_0_palettized, x = mul_393)[name = string("tern_8_k")];
            tensor<fp16, [88]> mul_394_y_0 = const()[name = string("mul_394_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5123264)))];
            tensor<fp16, [32, 88]> mul_394 = mul(x = tern_8_k, y = mul_394_y_0)[name = string("mul_394")];
            tensor<int32, [3]> reshape_67_shape_0 = const()[name = string("reshape_67_shape_0"), val = tensor<int32, [3]>([32, 2, 44])];
            tensor<fp16, [32, 2, 44]> reshape_67 = reshape(shape = reshape_67_shape_0, x = mul_394)[name = string("reshape_67")];
            tensor<int32, [3]> transpose_33_perm_0 = const()[name = string("transpose_33_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_397_y_0 = const()[name = string("mul_397_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5123520)))];
            tensor<fp16, [32, 352]> mul_397 = mul(x = mul_388, y = mul_397_y_0)[name = string("mul_397")];
            tensor<fp16, [88, 352]> tern_8_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5124288))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_8_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_8_v_bias_0 = const()[name = string("tern_8_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [32, 88]> tern_8_v = linear(bias = tern_8_v_bias_0, weight = tern_8_v_weight_0_palettized, x = mul_397)[name = string("tern_8_v")];
            tensor<fp16, [88]> mul_398_y_0 = const()[name = string("mul_398_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5132096)))];
            tensor<fp16, [32, 88]> mul_398 = mul(x = tern_8_v, y = mul_398_y_0)[name = string("mul_398")];
            tensor<int32, [3]> reshape_68_shape_0 = const()[name = string("reshape_68_shape_0"), val = tensor<int32, [3]>([32, 2, 44])];
            tensor<fp16, [32, 2, 44]> reshape_68 = reshape(shape = reshape_68_shape_0, x = mul_398)[name = string("reshape_68")];
            tensor<int32, [3]> transpose_34_perm_0 = const()[name = string("transpose_34_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 32, 44]> transpose_32 = transpose(perm = transpose_32_perm_0, x = reshape_66)[name = string("transpose_31")];
            tensor<fp16, [8, 32, 44]> mul_399 = mul(x = transpose_32, y = transpose_32)[name = string("mul_399")];
            tensor<int32, [1]> reduce_mean_86_axes_0 = const()[name = string("reduce_mean_86_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_86_keep_dims_0 = const()[name = string("reduce_mean_86_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 32, 1]> reduce_mean_86 = reduce_mean(axes = reduce_mean_86_axes_0, keep_dims = reduce_mean_86_keep_dims_0, x = mul_399)[name = string("reduce_mean_86")];
            fp32 rsqrt_86_epsilon_0 = const()[name = string("rsqrt_86_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 32, 1]> rsqrt_86 = rsqrt(epsilon = rsqrt_86_epsilon_0, x = reduce_mean_86)[name = string("rsqrt_86")];
            tensor<fp16, [8, 32, 44]> mul_400 = mul(x = transpose_32, y = rsqrt_86)[name = string("mul_400")];
            tensor<fp16, [44]> mul_401_y_0 = const()[name = string("mul_401_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5132352)))];
            tensor<fp16, [8, 32, 44]> mul_401 = mul(x = mul_400, y = mul_401_y_0)[name = string("mul_401")];
            tensor<int32, [3]> slice_by_index_32_begin_0 = const()[name = string("slice_by_index_32_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_32_end_0 = const()[name = string("slice_by_index_32_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_32_end_mask_0 = const()[name = string("slice_by_index_32_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 32, 22]> slice_by_index_32 = slice_by_index(begin = slice_by_index_32_begin_0, end = slice_by_index_32_end_0, end_mask = slice_by_index_32_end_mask_0, x = mul_401)[name = string("slice_by_index_32")];
            tensor<int32, [3]> slice_by_index_33_begin_0 = const()[name = string("slice_by_index_33_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_33_end_0 = const()[name = string("slice_by_index_33_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_33_end_mask_0 = const()[name = string("slice_by_index_33_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 32, 22]> slice_by_index_33 = slice_by_index(begin = slice_by_index_33_begin_0, end = slice_by_index_33_end_0, end_mask = slice_by_index_33_end_mask_0, x = mul_401)[name = string("slice_by_index_33")];
            int32 concat_16_axis_0 = const()[name = string("concat_16_axis_0"), val = int32(-1)];
            bool concat_16_interleave_0 = const()[name = string("concat_16_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 32, 44]> concat_16 = concat(axis = concat_16_axis_0, interleave = concat_16_interleave_0, values = (slice_by_index_33, slice_by_index_32))[name = string("concat_16")];
            tensor<fp16, [44]> mul_402_y_0 = const()[name = string("mul_402_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 32, 44]> mul_402 = mul(x = concat_16, y = mul_402_y_0)[name = string("mul_402")];
            tensor<fp16, [8, 32, 44]> mul_403 = mul(x = mul_401, y = mul_11_y_0)[name = string("mul_403")];
            tensor<fp16, [8, 32, 44]> mul_404 = mul(x = mul_402, y = mul_12_y_0)[name = string("mul_404")];
            tensor<fp16, [8, 32, 44]> add_48 = add(x = mul_403, y = mul_404)[name = string("add_48")];
            tensor<fp16, [2, 32, 44]> transpose_33 = transpose(perm = transpose_33_perm_0, x = reshape_67)[name = string("transpose_30")];
            tensor<fp16, [2, 32, 44]> mul_405 = mul(x = transpose_33, y = transpose_33)[name = string("mul_405")];
            tensor<int32, [1]> reduce_mean_87_axes_0 = const()[name = string("reduce_mean_87_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_87_keep_dims_0 = const()[name = string("reduce_mean_87_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 32, 1]> reduce_mean_87 = reduce_mean(axes = reduce_mean_87_axes_0, keep_dims = reduce_mean_87_keep_dims_0, x = mul_405)[name = string("reduce_mean_87")];
            fp32 rsqrt_87_epsilon_0 = const()[name = string("rsqrt_87_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 32, 1]> rsqrt_87 = rsqrt(epsilon = rsqrt_87_epsilon_0, x = reduce_mean_87)[name = string("rsqrt_87")];
            tensor<fp16, [2, 32, 44]> mul_406 = mul(x = transpose_33, y = rsqrt_87)[name = string("mul_406")];
            tensor<fp16, [44]> mul_407_y_0 = const()[name = string("mul_407_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5132544)))];
            tensor<fp16, [2, 32, 44]> mul_407 = mul(x = mul_406, y = mul_407_y_0)[name = string("mul_407")];
            tensor<int32, [3]> slice_by_index_34_begin_0 = const()[name = string("slice_by_index_34_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_34_end_0 = const()[name = string("slice_by_index_34_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_34_end_mask_0 = const()[name = string("slice_by_index_34_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 32, 22]> slice_by_index_34 = slice_by_index(begin = slice_by_index_34_begin_0, end = slice_by_index_34_end_0, end_mask = slice_by_index_34_end_mask_0, x = mul_407)[name = string("slice_by_index_34")];
            tensor<int32, [3]> slice_by_index_35_begin_0 = const()[name = string("slice_by_index_35_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_35_end_0 = const()[name = string("slice_by_index_35_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_35_end_mask_0 = const()[name = string("slice_by_index_35_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 32, 22]> slice_by_index_35 = slice_by_index(begin = slice_by_index_35_begin_0, end = slice_by_index_35_end_0, end_mask = slice_by_index_35_end_mask_0, x = mul_407)[name = string("slice_by_index_35")];
            int32 concat_17_axis_0 = const()[name = string("concat_17_axis_0"), val = int32(-1)];
            bool concat_17_interleave_0 = const()[name = string("concat_17_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 32, 44]> concat_17 = concat(axis = concat_17_axis_0, interleave = concat_17_interleave_0, values = (slice_by_index_35, slice_by_index_34))[name = string("concat_17")];
            tensor<fp16, [44]> mul_408_y_0 = const()[name = string("mul_408_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 32, 44]> mul_408 = mul(x = concat_17, y = mul_408_y_0)[name = string("mul_408")];
            tensor<fp16, [2, 32, 44]> mul_409 = mul(x = mul_407, y = mul_11_y_0)[name = string("mul_409")];
            tensor<fp16, [2, 32, 44]> mul_410 = mul(x = mul_408, y = mul_12_y_0)[name = string("mul_410")];
            tensor<fp16, [2, 32, 44]> add_49 = add(x = mul_409, y = mul_410)[name = string("add_49")];
            tensor<int32, [4]> reshape_69_shape_0 = const()[name = string("reshape_69_shape_0"), val = tensor<int32, [4]>([2, 1, 32, 44])];
            tensor<fp16, [2, 1, 32, 44]> reshape_69 = reshape(shape = reshape_69_shape_0, x = add_49)[name = string("reshape_69")];
            tensor<int32, [4]> tile_16_reps_0 = const()[name = string("tile_16_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 32, 44]> tile_16 = tile(reps = tile_16_reps_0, x = reshape_69)[name = string("tile_16")];
            tensor<int32, [3]> reshape_70_shape_0 = const()[name = string("reshape_70_shape_0"), val = tensor<int32, [3]>([8, 32, 44])];
            tensor<fp16, [8, 32, 44]> reshape_70 = reshape(shape = reshape_70_shape_0, x = tile_16)[name = string("reshape_70")];
            tensor<int32, [4]> reshape_71_shape_0 = const()[name = string("reshape_71_shape_0"), val = tensor<int32, [4]>([2, 1, 32, 44])];
            tensor<fp16, [2, 32, 44]> transpose_34 = transpose(perm = transpose_34_perm_0, x = reshape_68)[name = string("transpose_29")];
            tensor<fp16, [2, 1, 32, 44]> reshape_71 = reshape(shape = reshape_71_shape_0, x = transpose_34)[name = string("reshape_71")];
            tensor<int32, [4]> tile_17_reps_0 = const()[name = string("tile_17_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 32, 44]> tile_17 = tile(reps = tile_17_reps_0, x = reshape_71)[name = string("tile_17")];
            tensor<int32, [3]> reshape_72_shape_0 = const()[name = string("reshape_72_shape_0"), val = tensor<int32, [3]>([8, 32, 44])];
            tensor<fp16, [8, 32, 44]> reshape_72 = reshape(shape = reshape_72_shape_0, x = tile_17)[name = string("reshape_72")];
            fp16 mul_411_y_0 = const()[name = string("mul_411_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 32, 44]> mul_411 = mul(x = add_48, y = mul_411_y_0)[name = string("mul_411")];
            bool matmul_16_transpose_y_0 = const()[name = string("matmul_16_transpose_y_0"), val = bool(true)];
            bool matmul_16_transpose_x_0 = const()[name = string("matmul_16_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 32, 32]> matmul_16 = matmul(transpose_x = matmul_16_transpose_x_0, transpose_y = matmul_16_transpose_y_0, x = mul_411, y = reshape_70)[name = string("matmul_16")];
            tensor<fp16, [8, 32, 32]> add_50 = add(x = matmul_16, y = reshape_1)[name = string("add_50")];
            int32 softmax_8_axis_0 = const()[name = string("softmax_8_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 32, 32]> softmax_8 = softmax(axis = softmax_8_axis_0, x = add_50)[name = string("softmax_8")];
            bool matmul_17_transpose_x_0 = const()[name = string("matmul_17_transpose_x_0"), val = bool(false)];
            bool matmul_17_transpose_y_0 = const()[name = string("matmul_17_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 32, 44]> matmul_17 = matmul(transpose_x = matmul_17_transpose_x_0, transpose_y = matmul_17_transpose_y_0, x = softmax_8, y = reshape_72)[name = string("matmul_17")];
            tensor<int32, [3]> transpose_35_perm_0 = const()[name = string("transpose_35_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_73_shape_0 = const()[name = string("reshape_73_shape_0"), val = tensor<int32, [2]>([32, 352])];
            tensor<fp16, [32, 8, 44]> transpose_35 = transpose(perm = transpose_35_perm_0, x = matmul_17)[name = string("transpose_28")];
            tensor<fp16, [32, 352]> reshape_73 = reshape(shape = reshape_73_shape_0, x = transpose_35)[name = string("reshape_73")];
            tensor<fp16, [32, 352]> mul_412 = mul(x = reshape_73, y = reshape_73)[name = string("mul_412")];
            tensor<int32, [1]> reduce_mean_88_axes_0 = const()[name = string("reduce_mean_88_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_88_keep_dims_0 = const()[name = string("reduce_mean_88_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_88 = reduce_mean(axes = reduce_mean_88_axes_0, keep_dims = reduce_mean_88_keep_dims_0, x = mul_412)[name = string("reduce_mean_88")];
            fp32 rsqrt_88_epsilon_0 = const()[name = string("rsqrt_88_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_88 = rsqrt(epsilon = rsqrt_88_epsilon_0, x = reduce_mean_88)[name = string("rsqrt_88")];
            tensor<fp16, [32, 352]> mul_413 = mul(x = reshape_73, y = rsqrt_88)[name = string("mul_413")];
            tensor<fp16, [352]> mul_414_y_0 = const()[name = string("mul_414_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5132736)))];
            tensor<fp16, [32, 352]> mul_414 = mul(x = mul_413, y = mul_414_y_0)[name = string("mul_414")];
            tensor<fp16, [352, 352]> tern_8_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5133504))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_8_o_weight_0_palettized")];
            tensor<fp16, [32, 352]> tern_8_o = linear(bias = linear_0_bias_0, weight = tern_8_o_weight_0_palettized, x = mul_414)[name = string("tern_8_o")];
            tensor<fp16, [352]> mul_415_y_0 = const()[name = string("mul_415_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5164544)))];
            tensor<fp16, [32, 352]> mul_415 = mul(x = tern_8_o, y = mul_415_y_0)[name = string("mul_415")];
            tensor<fp16, [32, 352]> add_51 = add(x = add_47, y = mul_415)[name = string("add_51")];
            tensor<fp16, [32, 352]> mul_416 = mul(x = add_51, y = add_51)[name = string("mul_416")];
            tensor<int32, [1]> reduce_mean_89_axes_0 = const()[name = string("reduce_mean_89_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_89_keep_dims_0 = const()[name = string("reduce_mean_89_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_89 = reduce_mean(axes = reduce_mean_89_axes_0, keep_dims = reduce_mean_89_keep_dims_0, x = mul_416)[name = string("reduce_mean_89")];
            fp32 rsqrt_89_epsilon_0 = const()[name = string("rsqrt_89_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_89 = rsqrt(epsilon = rsqrt_89_epsilon_0, x = reduce_mean_89)[name = string("rsqrt_89")];
            tensor<fp16, [32, 352]> mul_417 = mul(x = add_51, y = rsqrt_89)[name = string("mul_417")];
            tensor<fp16, [352]> mul_418_y_0 = const()[name = string("mul_418_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5165312)))];
            tensor<fp16, [32, 352]> mul_418 = mul(x = mul_417, y = mul_418_y_0)[name = string("mul_418")];
            tensor<fp16, [32, 352]> mul_419 = mul(x = mul_418, y = mul_418)[name = string("mul_419")];
            tensor<int32, [1]> reduce_mean_90_axes_0 = const()[name = string("reduce_mean_90_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_90_keep_dims_0 = const()[name = string("reduce_mean_90_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_90 = reduce_mean(axes = reduce_mean_90_axes_0, keep_dims = reduce_mean_90_keep_dims_0, x = mul_419)[name = string("reduce_mean_90")];
            fp32 rsqrt_90_epsilon_0 = const()[name = string("rsqrt_90_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_90 = rsqrt(epsilon = rsqrt_90_epsilon_0, x = reduce_mean_90)[name = string("rsqrt_90")];
            tensor<fp16, [32, 352]> mul_420 = mul(x = mul_418, y = rsqrt_90)[name = string("mul_420")];
            tensor<fp16, [352]> mul_421_y_0 = const()[name = string("mul_421_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5166080)))];
            tensor<fp16, [32, 352]> mul_421 = mul(x = mul_420, y = mul_421_y_0)[name = string("mul_421")];
            tensor<fp16, [960, 352]> tern_8_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5166848))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_8_w1_weight_0_palettized")];
            tensor<fp16, [32, 960]> tern_8_w1 = linear(bias = linear_4_bias_0, weight = tern_8_w1_weight_0_palettized, x = mul_421)[name = string("tern_8_w1")];
            tensor<fp16, [960]> mul_422_y_0 = const()[name = string("mul_422_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5251392)))];
            tensor<fp16, [32, 960]> mul_422 = mul(x = tern_8_w1, y = mul_422_y_0)[name = string("mul_422")];
            tensor<fp16, [352]> mul_425_y_0 = const()[name = string("mul_425_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5253376)))];
            tensor<fp16, [32, 352]> mul_425 = mul(x = mul_420, y = mul_425_y_0)[name = string("mul_425")];
            tensor<fp16, [960, 352]> tern_8_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5254144))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_8_w3_weight_0_palettized")];
            tensor<fp16, [32, 960]> tern_8_w3 = linear(bias = linear_4_bias_0, weight = tern_8_w3_weight_0_palettized, x = mul_425)[name = string("tern_8_w3")];
            tensor<fp16, [960]> mul_426_y_0 = const()[name = string("mul_426_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5338688)))];
            tensor<fp16, [32, 960]> mul_426 = mul(x = tern_8_w3, y = mul_426_y_0)[name = string("mul_426")];
            fp16 mul_427_y_0 = const()[name = string("mul_427_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [32, 960]> mul_427 = mul(x = mul_422, y = mul_427_y_0)[name = string("mul_427")];
            tensor<fp16, [32, 960]> tanh_8 = tanh(x = mul_427)[name = string("tanh_8")];
            fp16 mul_428_x_0 = const()[name = string("mul_428_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [32, 960]> mul_428 = mul(x = mul_428_x_0, y = tanh_8)[name = string("mul_428")];
            fp16 add_52_x_0 = const()[name = string("add_52_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [32, 960]> add_52 = add(x = add_52_x_0, y = mul_428)[name = string("add_52")];
            tensor<fp16, [32, 960]> mul_429 = mul(x = mul_422, y = add_52)[name = string("mul_429")];
            tensor<fp16, [32, 960]> mul_430 = mul(x = mul_429, y = mul_426)[name = string("mul_430")];
            tensor<fp16, [32, 960]> mul_431 = mul(x = mul_430, y = mul_430)[name = string("mul_431")];
            tensor<int32, [1]> reduce_mean_92_axes_0 = const()[name = string("reduce_mean_92_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_92_keep_dims_0 = const()[name = string("reduce_mean_92_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_92 = reduce_mean(axes = reduce_mean_92_axes_0, keep_dims = reduce_mean_92_keep_dims_0, x = mul_431)[name = string("reduce_mean_92")];
            fp32 rsqrt_92_epsilon_0 = const()[name = string("rsqrt_92_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_92 = rsqrt(epsilon = rsqrt_92_epsilon_0, x = reduce_mean_92)[name = string("rsqrt_92")];
            tensor<fp16, [32, 960]> mul_432 = mul(x = mul_430, y = rsqrt_92)[name = string("mul_432")];
            tensor<fp16, [960]> mul_433_y_0 = const()[name = string("mul_433_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5340672)))];
            tensor<fp16, [32, 960]> mul_433 = mul(x = mul_432, y = mul_433_y_0)[name = string("mul_433")];
            tensor<fp16, [352, 960]> tern_8_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5342656))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_8_w2_weight_0_palettized")];
            tensor<fp16, [32, 352]> tern_8_w2 = linear(bias = linear_0_bias_0, weight = tern_8_w2_weight_0_palettized, x = mul_433)[name = string("tern_8_w2")];
            tensor<fp16, [352]> mul_434_y_0 = const()[name = string("mul_434_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5427200)))];
            tensor<fp16, [32, 352]> mul_434 = mul(x = tern_8_w2, y = mul_434_y_0)[name = string("mul_434")];
            tensor<fp16, [32, 352]> add_53 = add(x = add_51, y = mul_434)[name = string("add_53")];
            tensor<fp16, [32, 352]> mul_435 = mul(x = add_53, y = add_53)[name = string("mul_435")];
            tensor<int32, [1]> reduce_mean_93_axes_0 = const()[name = string("reduce_mean_93_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_93_keep_dims_0 = const()[name = string("reduce_mean_93_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_93 = reduce_mean(axes = reduce_mean_93_axes_0, keep_dims = reduce_mean_93_keep_dims_0, x = mul_435)[name = string("reduce_mean_93")];
            fp32 rsqrt_93_epsilon_0 = const()[name = string("rsqrt_93_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_93 = rsqrt(epsilon = rsqrt_93_epsilon_0, x = reduce_mean_93)[name = string("rsqrt_93")];
            tensor<fp16, [32, 352]> mul_436 = mul(x = add_53, y = rsqrt_93)[name = string("mul_436")];
            tensor<fp16, [352]> mul_437_y_0 = const()[name = string("mul_437_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5427968)))];
            tensor<fp16, [32, 352]> mul_437 = mul(x = mul_436, y = mul_437_y_0)[name = string("mul_437")];
            tensor<fp16, [32, 352]> mul_438 = mul(x = mul_437, y = mul_437)[name = string("mul_438")];
            tensor<int32, [1]> reduce_mean_94_axes_0 = const()[name = string("reduce_mean_94_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_94_keep_dims_0 = const()[name = string("reduce_mean_94_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_94 = reduce_mean(axes = reduce_mean_94_axes_0, keep_dims = reduce_mean_94_keep_dims_0, x = mul_438)[name = string("reduce_mean_94")];
            fp32 rsqrt_94_epsilon_0 = const()[name = string("rsqrt_94_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_94 = rsqrt(epsilon = rsqrt_94_epsilon_0, x = reduce_mean_94)[name = string("rsqrt_94")];
            tensor<fp16, [32, 352]> mul_439 = mul(x = mul_437, y = rsqrt_94)[name = string("mul_439")];
            tensor<fp16, [352]> mul_440_y_0 = const()[name = string("mul_440_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5428736)))];
            tensor<fp16, [32, 352]> mul_440 = mul(x = mul_439, y = mul_440_y_0)[name = string("mul_440")];
            tensor<fp16, [352, 352]> tern_9_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5429504))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_9_q_weight_0_palettized")];
            tensor<fp16, [32, 352]> tern_9_q = linear(bias = linear_0_bias_0, weight = tern_9_q_weight_0_palettized, x = mul_440)[name = string("tern_9_q")];
            tensor<fp16, [352]> mul_441_y_0 = const()[name = string("mul_441_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5460544)))];
            tensor<fp16, [32, 352]> mul_441 = mul(x = tern_9_q, y = mul_441_y_0)[name = string("mul_441")];
            tensor<int32, [3]> reshape_74_shape_0 = const()[name = string("reshape_74_shape_0"), val = tensor<int32, [3]>([32, 8, 44])];
            tensor<fp16, [32, 8, 44]> reshape_74 = reshape(shape = reshape_74_shape_0, x = mul_441)[name = string("reshape_74")];
            tensor<int32, [3]> transpose_36_perm_0 = const()[name = string("transpose_36_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_444_y_0 = const()[name = string("mul_444_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5461312)))];
            tensor<fp16, [32, 352]> mul_444 = mul(x = mul_439, y = mul_444_y_0)[name = string("mul_444")];
            tensor<fp16, [88, 352]> tern_9_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5462080))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_9_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_9_k_bias_0 = const()[name = string("tern_9_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [32, 88]> tern_9_k = linear(bias = tern_9_k_bias_0, weight = tern_9_k_weight_0_palettized, x = mul_444)[name = string("tern_9_k")];
            tensor<fp16, [88]> mul_445_y_0 = const()[name = string("mul_445_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5469888)))];
            tensor<fp16, [32, 88]> mul_445 = mul(x = tern_9_k, y = mul_445_y_0)[name = string("mul_445")];
            tensor<int32, [3]> reshape_75_shape_0 = const()[name = string("reshape_75_shape_0"), val = tensor<int32, [3]>([32, 2, 44])];
            tensor<fp16, [32, 2, 44]> reshape_75 = reshape(shape = reshape_75_shape_0, x = mul_445)[name = string("reshape_75")];
            tensor<int32, [3]> transpose_37_perm_0 = const()[name = string("transpose_37_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_448_y_0 = const()[name = string("mul_448_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5470144)))];
            tensor<fp16, [32, 352]> mul_448 = mul(x = mul_439, y = mul_448_y_0)[name = string("mul_448")];
            tensor<fp16, [88, 352]> tern_9_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5470912))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_9_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_9_v_bias_0 = const()[name = string("tern_9_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [32, 88]> tern_9_v = linear(bias = tern_9_v_bias_0, weight = tern_9_v_weight_0_palettized, x = mul_448)[name = string("tern_9_v")];
            tensor<fp16, [88]> mul_449_y_0 = const()[name = string("mul_449_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5478720)))];
            tensor<fp16, [32, 88]> mul_449 = mul(x = tern_9_v, y = mul_449_y_0)[name = string("mul_449")];
            tensor<int32, [3]> reshape_76_shape_0 = const()[name = string("reshape_76_shape_0"), val = tensor<int32, [3]>([32, 2, 44])];
            tensor<fp16, [32, 2, 44]> reshape_76 = reshape(shape = reshape_76_shape_0, x = mul_449)[name = string("reshape_76")];
            tensor<int32, [3]> transpose_38_perm_0 = const()[name = string("transpose_38_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 32, 44]> transpose_36 = transpose(perm = transpose_36_perm_0, x = reshape_74)[name = string("transpose_27")];
            tensor<fp16, [8, 32, 44]> mul_450 = mul(x = transpose_36, y = transpose_36)[name = string("mul_450")];
            tensor<int32, [1]> reduce_mean_97_axes_0 = const()[name = string("reduce_mean_97_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_97_keep_dims_0 = const()[name = string("reduce_mean_97_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 32, 1]> reduce_mean_97 = reduce_mean(axes = reduce_mean_97_axes_0, keep_dims = reduce_mean_97_keep_dims_0, x = mul_450)[name = string("reduce_mean_97")];
            fp32 rsqrt_97_epsilon_0 = const()[name = string("rsqrt_97_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 32, 1]> rsqrt_97 = rsqrt(epsilon = rsqrt_97_epsilon_0, x = reduce_mean_97)[name = string("rsqrt_97")];
            tensor<fp16, [8, 32, 44]> mul_451 = mul(x = transpose_36, y = rsqrt_97)[name = string("mul_451")];
            tensor<fp16, [44]> mul_452_y_0 = const()[name = string("mul_452_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5478976)))];
            tensor<fp16, [8, 32, 44]> mul_452 = mul(x = mul_451, y = mul_452_y_0)[name = string("mul_452")];
            tensor<int32, [3]> slice_by_index_36_begin_0 = const()[name = string("slice_by_index_36_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_36_end_0 = const()[name = string("slice_by_index_36_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_36_end_mask_0 = const()[name = string("slice_by_index_36_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 32, 22]> slice_by_index_36 = slice_by_index(begin = slice_by_index_36_begin_0, end = slice_by_index_36_end_0, end_mask = slice_by_index_36_end_mask_0, x = mul_452)[name = string("slice_by_index_36")];
            tensor<int32, [3]> slice_by_index_37_begin_0 = const()[name = string("slice_by_index_37_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_37_end_0 = const()[name = string("slice_by_index_37_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_37_end_mask_0 = const()[name = string("slice_by_index_37_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 32, 22]> slice_by_index_37 = slice_by_index(begin = slice_by_index_37_begin_0, end = slice_by_index_37_end_0, end_mask = slice_by_index_37_end_mask_0, x = mul_452)[name = string("slice_by_index_37")];
            int32 concat_18_axis_0 = const()[name = string("concat_18_axis_0"), val = int32(-1)];
            bool concat_18_interleave_0 = const()[name = string("concat_18_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 32, 44]> concat_18 = concat(axis = concat_18_axis_0, interleave = concat_18_interleave_0, values = (slice_by_index_37, slice_by_index_36))[name = string("concat_18")];
            tensor<fp16, [44]> mul_453_y_0 = const()[name = string("mul_453_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 32, 44]> mul_453 = mul(x = concat_18, y = mul_453_y_0)[name = string("mul_453")];
            tensor<fp16, [8, 32, 44]> mul_454 = mul(x = mul_452, y = mul_11_y_0)[name = string("mul_454")];
            tensor<fp16, [8, 32, 44]> mul_455 = mul(x = mul_453, y = mul_12_y_0)[name = string("mul_455")];
            tensor<fp16, [8, 32, 44]> add_54 = add(x = mul_454, y = mul_455)[name = string("add_54")];
            tensor<fp16, [2, 32, 44]> transpose_37 = transpose(perm = transpose_37_perm_0, x = reshape_75)[name = string("transpose_26")];
            tensor<fp16, [2, 32, 44]> mul_456 = mul(x = transpose_37, y = transpose_37)[name = string("mul_456")];
            tensor<int32, [1]> reduce_mean_98_axes_0 = const()[name = string("reduce_mean_98_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_98_keep_dims_0 = const()[name = string("reduce_mean_98_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 32, 1]> reduce_mean_98 = reduce_mean(axes = reduce_mean_98_axes_0, keep_dims = reduce_mean_98_keep_dims_0, x = mul_456)[name = string("reduce_mean_98")];
            fp32 rsqrt_98_epsilon_0 = const()[name = string("rsqrt_98_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 32, 1]> rsqrt_98 = rsqrt(epsilon = rsqrt_98_epsilon_0, x = reduce_mean_98)[name = string("rsqrt_98")];
            tensor<fp16, [2, 32, 44]> mul_457 = mul(x = transpose_37, y = rsqrt_98)[name = string("mul_457")];
            tensor<fp16, [44]> mul_458_y_0 = const()[name = string("mul_458_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5479168)))];
            tensor<fp16, [2, 32, 44]> mul_458 = mul(x = mul_457, y = mul_458_y_0)[name = string("mul_458")];
            tensor<int32, [3]> slice_by_index_38_begin_0 = const()[name = string("slice_by_index_38_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_38_end_0 = const()[name = string("slice_by_index_38_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_38_end_mask_0 = const()[name = string("slice_by_index_38_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 32, 22]> slice_by_index_38 = slice_by_index(begin = slice_by_index_38_begin_0, end = slice_by_index_38_end_0, end_mask = slice_by_index_38_end_mask_0, x = mul_458)[name = string("slice_by_index_38")];
            tensor<int32, [3]> slice_by_index_39_begin_0 = const()[name = string("slice_by_index_39_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_39_end_0 = const()[name = string("slice_by_index_39_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_39_end_mask_0 = const()[name = string("slice_by_index_39_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 32, 22]> slice_by_index_39 = slice_by_index(begin = slice_by_index_39_begin_0, end = slice_by_index_39_end_0, end_mask = slice_by_index_39_end_mask_0, x = mul_458)[name = string("slice_by_index_39")];
            int32 concat_19_axis_0 = const()[name = string("concat_19_axis_0"), val = int32(-1)];
            bool concat_19_interleave_0 = const()[name = string("concat_19_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 32, 44]> concat_19 = concat(axis = concat_19_axis_0, interleave = concat_19_interleave_0, values = (slice_by_index_39, slice_by_index_38))[name = string("concat_19")];
            tensor<fp16, [44]> mul_459_y_0 = const()[name = string("mul_459_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 32, 44]> mul_459 = mul(x = concat_19, y = mul_459_y_0)[name = string("mul_459")];
            tensor<fp16, [2, 32, 44]> mul_460 = mul(x = mul_458, y = mul_11_y_0)[name = string("mul_460")];
            tensor<fp16, [2, 32, 44]> mul_461 = mul(x = mul_459, y = mul_12_y_0)[name = string("mul_461")];
            tensor<fp16, [2, 32, 44]> add_55 = add(x = mul_460, y = mul_461)[name = string("add_55")];
            tensor<int32, [4]> reshape_77_shape_0 = const()[name = string("reshape_77_shape_0"), val = tensor<int32, [4]>([2, 1, 32, 44])];
            tensor<fp16, [2, 1, 32, 44]> reshape_77 = reshape(shape = reshape_77_shape_0, x = add_55)[name = string("reshape_77")];
            tensor<int32, [4]> tile_18_reps_0 = const()[name = string("tile_18_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 32, 44]> tile_18 = tile(reps = tile_18_reps_0, x = reshape_77)[name = string("tile_18")];
            tensor<int32, [3]> reshape_78_shape_0 = const()[name = string("reshape_78_shape_0"), val = tensor<int32, [3]>([8, 32, 44])];
            tensor<fp16, [8, 32, 44]> reshape_78 = reshape(shape = reshape_78_shape_0, x = tile_18)[name = string("reshape_78")];
            tensor<int32, [4]> reshape_79_shape_0 = const()[name = string("reshape_79_shape_0"), val = tensor<int32, [4]>([2, 1, 32, 44])];
            tensor<fp16, [2, 32, 44]> transpose_38 = transpose(perm = transpose_38_perm_0, x = reshape_76)[name = string("transpose_25")];
            tensor<fp16, [2, 1, 32, 44]> reshape_79 = reshape(shape = reshape_79_shape_0, x = transpose_38)[name = string("reshape_79")];
            tensor<int32, [4]> tile_19_reps_0 = const()[name = string("tile_19_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 32, 44]> tile_19 = tile(reps = tile_19_reps_0, x = reshape_79)[name = string("tile_19")];
            tensor<int32, [3]> reshape_80_shape_0 = const()[name = string("reshape_80_shape_0"), val = tensor<int32, [3]>([8, 32, 44])];
            tensor<fp16, [8, 32, 44]> reshape_80 = reshape(shape = reshape_80_shape_0, x = tile_19)[name = string("reshape_80")];
            fp16 mul_462_y_0 = const()[name = string("mul_462_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 32, 44]> mul_462 = mul(x = add_54, y = mul_462_y_0)[name = string("mul_462")];
            bool matmul_18_transpose_y_0 = const()[name = string("matmul_18_transpose_y_0"), val = bool(true)];
            bool matmul_18_transpose_x_0 = const()[name = string("matmul_18_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 32, 32]> matmul_18 = matmul(transpose_x = matmul_18_transpose_x_0, transpose_y = matmul_18_transpose_y_0, x = mul_462, y = reshape_78)[name = string("matmul_18")];
            tensor<fp16, [8, 32, 32]> add_56 = add(x = matmul_18, y = reshape_1)[name = string("add_56")];
            int32 softmax_9_axis_0 = const()[name = string("softmax_9_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 32, 32]> softmax_9 = softmax(axis = softmax_9_axis_0, x = add_56)[name = string("softmax_9")];
            bool matmul_19_transpose_x_0 = const()[name = string("matmul_19_transpose_x_0"), val = bool(false)];
            bool matmul_19_transpose_y_0 = const()[name = string("matmul_19_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 32, 44]> matmul_19 = matmul(transpose_x = matmul_19_transpose_x_0, transpose_y = matmul_19_transpose_y_0, x = softmax_9, y = reshape_80)[name = string("matmul_19")];
            tensor<int32, [3]> transpose_39_perm_0 = const()[name = string("transpose_39_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_81_shape_0 = const()[name = string("reshape_81_shape_0"), val = tensor<int32, [2]>([32, 352])];
            tensor<fp16, [32, 8, 44]> transpose_39 = transpose(perm = transpose_39_perm_0, x = matmul_19)[name = string("transpose_24")];
            tensor<fp16, [32, 352]> reshape_81 = reshape(shape = reshape_81_shape_0, x = transpose_39)[name = string("reshape_81")];
            tensor<fp16, [32, 352]> mul_463 = mul(x = reshape_81, y = reshape_81)[name = string("mul_463")];
            tensor<int32, [1]> reduce_mean_99_axes_0 = const()[name = string("reduce_mean_99_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_99_keep_dims_0 = const()[name = string("reduce_mean_99_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_99 = reduce_mean(axes = reduce_mean_99_axes_0, keep_dims = reduce_mean_99_keep_dims_0, x = mul_463)[name = string("reduce_mean_99")];
            fp32 rsqrt_99_epsilon_0 = const()[name = string("rsqrt_99_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_99 = rsqrt(epsilon = rsqrt_99_epsilon_0, x = reduce_mean_99)[name = string("rsqrt_99")];
            tensor<fp16, [32, 352]> mul_464 = mul(x = reshape_81, y = rsqrt_99)[name = string("mul_464")];
            tensor<fp16, [352]> mul_465_y_0 = const()[name = string("mul_465_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5479360)))];
            tensor<fp16, [32, 352]> mul_465 = mul(x = mul_464, y = mul_465_y_0)[name = string("mul_465")];
            tensor<fp16, [352, 352]> tern_9_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5480128))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_9_o_weight_0_palettized")];
            tensor<fp16, [32, 352]> tern_9_o = linear(bias = linear_0_bias_0, weight = tern_9_o_weight_0_palettized, x = mul_465)[name = string("tern_9_o")];
            tensor<fp16, [352]> mul_466_y_0 = const()[name = string("mul_466_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5511168)))];
            tensor<fp16, [32, 352]> mul_466 = mul(x = tern_9_o, y = mul_466_y_0)[name = string("mul_466")];
            tensor<fp16, [32, 352]> add_57 = add(x = add_53, y = mul_466)[name = string("add_57")];
            tensor<fp16, [32, 352]> mul_467 = mul(x = add_57, y = add_57)[name = string("mul_467")];
            tensor<int32, [1]> reduce_mean_100_axes_0 = const()[name = string("reduce_mean_100_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_100_keep_dims_0 = const()[name = string("reduce_mean_100_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_100 = reduce_mean(axes = reduce_mean_100_axes_0, keep_dims = reduce_mean_100_keep_dims_0, x = mul_467)[name = string("reduce_mean_100")];
            fp32 rsqrt_100_epsilon_0 = const()[name = string("rsqrt_100_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_100 = rsqrt(epsilon = rsqrt_100_epsilon_0, x = reduce_mean_100)[name = string("rsqrt_100")];
            tensor<fp16, [32, 352]> mul_468 = mul(x = add_57, y = rsqrt_100)[name = string("mul_468")];
            tensor<fp16, [352]> mul_469_y_0 = const()[name = string("mul_469_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5511936)))];
            tensor<fp16, [32, 352]> mul_469 = mul(x = mul_468, y = mul_469_y_0)[name = string("mul_469")];
            tensor<fp16, [32, 352]> mul_470 = mul(x = mul_469, y = mul_469)[name = string("mul_470")];
            tensor<int32, [1]> reduce_mean_101_axes_0 = const()[name = string("reduce_mean_101_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_101_keep_dims_0 = const()[name = string("reduce_mean_101_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_101 = reduce_mean(axes = reduce_mean_101_axes_0, keep_dims = reduce_mean_101_keep_dims_0, x = mul_470)[name = string("reduce_mean_101")];
            fp32 rsqrt_101_epsilon_0 = const()[name = string("rsqrt_101_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_101 = rsqrt(epsilon = rsqrt_101_epsilon_0, x = reduce_mean_101)[name = string("rsqrt_101")];
            tensor<fp16, [32, 352]> mul_471 = mul(x = mul_469, y = rsqrt_101)[name = string("mul_471")];
            tensor<fp16, [352]> mul_472_y_0 = const()[name = string("mul_472_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5512704)))];
            tensor<fp16, [32, 352]> mul_472 = mul(x = mul_471, y = mul_472_y_0)[name = string("mul_472")];
            tensor<fp16, [960, 352]> tern_9_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5513472))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_9_w1_weight_0_palettized")];
            tensor<fp16, [32, 960]> tern_9_w1 = linear(bias = linear_4_bias_0, weight = tern_9_w1_weight_0_palettized, x = mul_472)[name = string("tern_9_w1")];
            tensor<fp16, [960]> mul_473_y_0 = const()[name = string("mul_473_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5598016)))];
            tensor<fp16, [32, 960]> mul_473 = mul(x = tern_9_w1, y = mul_473_y_0)[name = string("mul_473")];
            tensor<fp16, [352]> mul_476_y_0 = const()[name = string("mul_476_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5600000)))];
            tensor<fp16, [32, 352]> mul_476 = mul(x = mul_471, y = mul_476_y_0)[name = string("mul_476")];
            tensor<fp16, [960, 352]> tern_9_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5600768))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_9_w3_weight_0_palettized")];
            tensor<fp16, [32, 960]> tern_9_w3 = linear(bias = linear_4_bias_0, weight = tern_9_w3_weight_0_palettized, x = mul_476)[name = string("tern_9_w3")];
            tensor<fp16, [960]> mul_477_y_0 = const()[name = string("mul_477_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5685312)))];
            tensor<fp16, [32, 960]> mul_477 = mul(x = tern_9_w3, y = mul_477_y_0)[name = string("mul_477")];
            fp16 mul_478_y_0 = const()[name = string("mul_478_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [32, 960]> mul_478 = mul(x = mul_473, y = mul_478_y_0)[name = string("mul_478")];
            tensor<fp16, [32, 960]> tanh_9 = tanh(x = mul_478)[name = string("tanh_9")];
            fp16 mul_479_x_0 = const()[name = string("mul_479_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [32, 960]> mul_479 = mul(x = mul_479_x_0, y = tanh_9)[name = string("mul_479")];
            fp16 add_58_x_0 = const()[name = string("add_58_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [32, 960]> add_58 = add(x = add_58_x_0, y = mul_479)[name = string("add_58")];
            tensor<fp16, [32, 960]> mul_480 = mul(x = mul_473, y = add_58)[name = string("mul_480")];
            tensor<fp16, [32, 960]> mul_481 = mul(x = mul_480, y = mul_477)[name = string("mul_481")];
            tensor<fp16, [32, 960]> mul_482 = mul(x = mul_481, y = mul_481)[name = string("mul_482")];
            tensor<int32, [1]> reduce_mean_103_axes_0 = const()[name = string("reduce_mean_103_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_103_keep_dims_0 = const()[name = string("reduce_mean_103_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_103 = reduce_mean(axes = reduce_mean_103_axes_0, keep_dims = reduce_mean_103_keep_dims_0, x = mul_482)[name = string("reduce_mean_103")];
            fp32 rsqrt_103_epsilon_0 = const()[name = string("rsqrt_103_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_103 = rsqrt(epsilon = rsqrt_103_epsilon_0, x = reduce_mean_103)[name = string("rsqrt_103")];
            tensor<fp16, [32, 960]> mul_483 = mul(x = mul_481, y = rsqrt_103)[name = string("mul_483")];
            tensor<fp16, [960]> mul_484_y_0 = const()[name = string("mul_484_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5687296)))];
            tensor<fp16, [32, 960]> mul_484 = mul(x = mul_483, y = mul_484_y_0)[name = string("mul_484")];
            tensor<fp16, [352, 960]> tern_9_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5689280))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_9_w2_weight_0_palettized")];
            tensor<fp16, [32, 352]> tern_9_w2 = linear(bias = linear_0_bias_0, weight = tern_9_w2_weight_0_palettized, x = mul_484)[name = string("tern_9_w2")];
            tensor<fp16, [352]> mul_485_y_0 = const()[name = string("mul_485_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5773824)))];
            tensor<fp16, [32, 352]> mul_485 = mul(x = tern_9_w2, y = mul_485_y_0)[name = string("mul_485")];
            tensor<fp16, [32, 352]> add_59 = add(x = add_57, y = mul_485)[name = string("add_59")];
            tensor<fp16, [32, 352]> mul_486 = mul(x = add_59, y = add_59)[name = string("mul_486")];
            tensor<int32, [1]> reduce_mean_104_axes_0 = const()[name = string("reduce_mean_104_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_104_keep_dims_0 = const()[name = string("reduce_mean_104_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_104 = reduce_mean(axes = reduce_mean_104_axes_0, keep_dims = reduce_mean_104_keep_dims_0, x = mul_486)[name = string("reduce_mean_104")];
            fp32 rsqrt_104_epsilon_0 = const()[name = string("rsqrt_104_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_104 = rsqrt(epsilon = rsqrt_104_epsilon_0, x = reduce_mean_104)[name = string("rsqrt_104")];
            tensor<fp16, [32, 352]> mul_487 = mul(x = add_59, y = rsqrt_104)[name = string("mul_487")];
            tensor<fp16, [352]> mul_488_y_0 = const()[name = string("mul_488_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5774592)))];
            tensor<fp16, [32, 352]> mul_488 = mul(x = mul_487, y = mul_488_y_0)[name = string("mul_488")];
            tensor<fp16, [32, 352]> mul_489 = mul(x = mul_488, y = mul_488)[name = string("mul_489")];
            tensor<int32, [1]> reduce_mean_105_axes_0 = const()[name = string("reduce_mean_105_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_105_keep_dims_0 = const()[name = string("reduce_mean_105_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_105 = reduce_mean(axes = reduce_mean_105_axes_0, keep_dims = reduce_mean_105_keep_dims_0, x = mul_489)[name = string("reduce_mean_105")];
            fp32 rsqrt_105_epsilon_0 = const()[name = string("rsqrt_105_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_105 = rsqrt(epsilon = rsqrt_105_epsilon_0, x = reduce_mean_105)[name = string("rsqrt_105")];
            tensor<fp16, [32, 352]> mul_490 = mul(x = mul_488, y = rsqrt_105)[name = string("mul_490")];
            tensor<fp16, [352]> mul_491_y_0 = const()[name = string("mul_491_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5775360)))];
            tensor<fp16, [32, 352]> mul_491 = mul(x = mul_490, y = mul_491_y_0)[name = string("mul_491")];
            tensor<fp16, [352, 352]> tern_10_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5776128))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_10_q_weight_0_palettized")];
            tensor<fp16, [32, 352]> tern_10_q = linear(bias = linear_0_bias_0, weight = tern_10_q_weight_0_palettized, x = mul_491)[name = string("tern_10_q")];
            tensor<fp16, [352]> mul_492_y_0 = const()[name = string("mul_492_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5807168)))];
            tensor<fp16, [32, 352]> mul_492 = mul(x = tern_10_q, y = mul_492_y_0)[name = string("mul_492")];
            tensor<int32, [3]> reshape_82_shape_0 = const()[name = string("reshape_82_shape_0"), val = tensor<int32, [3]>([32, 8, 44])];
            tensor<fp16, [32, 8, 44]> reshape_82 = reshape(shape = reshape_82_shape_0, x = mul_492)[name = string("reshape_82")];
            tensor<int32, [3]> transpose_40_perm_0 = const()[name = string("transpose_40_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_495_y_0 = const()[name = string("mul_495_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5807936)))];
            tensor<fp16, [32, 352]> mul_495 = mul(x = mul_490, y = mul_495_y_0)[name = string("mul_495")];
            tensor<fp16, [88, 352]> tern_10_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5808704))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_10_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_10_k_bias_0 = const()[name = string("tern_10_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [32, 88]> tern_10_k = linear(bias = tern_10_k_bias_0, weight = tern_10_k_weight_0_palettized, x = mul_495)[name = string("tern_10_k")];
            tensor<fp16, [88]> mul_496_y_0 = const()[name = string("mul_496_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5816512)))];
            tensor<fp16, [32, 88]> mul_496 = mul(x = tern_10_k, y = mul_496_y_0)[name = string("mul_496")];
            tensor<int32, [3]> reshape_83_shape_0 = const()[name = string("reshape_83_shape_0"), val = tensor<int32, [3]>([32, 2, 44])];
            tensor<fp16, [32, 2, 44]> reshape_83 = reshape(shape = reshape_83_shape_0, x = mul_496)[name = string("reshape_83")];
            tensor<int32, [3]> transpose_41_perm_0 = const()[name = string("transpose_41_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_499_y_0 = const()[name = string("mul_499_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5816768)))];
            tensor<fp16, [32, 352]> mul_499 = mul(x = mul_490, y = mul_499_y_0)[name = string("mul_499")];
            tensor<fp16, [88, 352]> tern_10_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5817536))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_10_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_10_v_bias_0 = const()[name = string("tern_10_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [32, 88]> tern_10_v = linear(bias = tern_10_v_bias_0, weight = tern_10_v_weight_0_palettized, x = mul_499)[name = string("tern_10_v")];
            tensor<fp16, [88]> mul_500_y_0 = const()[name = string("mul_500_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5825344)))];
            tensor<fp16, [32, 88]> mul_500 = mul(x = tern_10_v, y = mul_500_y_0)[name = string("mul_500")];
            tensor<int32, [3]> reshape_84_shape_0 = const()[name = string("reshape_84_shape_0"), val = tensor<int32, [3]>([32, 2, 44])];
            tensor<fp16, [32, 2, 44]> reshape_84 = reshape(shape = reshape_84_shape_0, x = mul_500)[name = string("reshape_84")];
            tensor<int32, [3]> transpose_42_perm_0 = const()[name = string("transpose_42_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 32, 44]> transpose_40 = transpose(perm = transpose_40_perm_0, x = reshape_82)[name = string("transpose_23")];
            tensor<fp16, [8, 32, 44]> mul_501 = mul(x = transpose_40, y = transpose_40)[name = string("mul_501")];
            tensor<int32, [1]> reduce_mean_108_axes_0 = const()[name = string("reduce_mean_108_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_108_keep_dims_0 = const()[name = string("reduce_mean_108_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 32, 1]> reduce_mean_108 = reduce_mean(axes = reduce_mean_108_axes_0, keep_dims = reduce_mean_108_keep_dims_0, x = mul_501)[name = string("reduce_mean_108")];
            fp32 rsqrt_108_epsilon_0 = const()[name = string("rsqrt_108_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 32, 1]> rsqrt_108 = rsqrt(epsilon = rsqrt_108_epsilon_0, x = reduce_mean_108)[name = string("rsqrt_108")];
            tensor<fp16, [8, 32, 44]> mul_502 = mul(x = transpose_40, y = rsqrt_108)[name = string("mul_502")];
            tensor<fp16, [44]> mul_503_y_0 = const()[name = string("mul_503_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5825600)))];
            tensor<fp16, [8, 32, 44]> mul_503 = mul(x = mul_502, y = mul_503_y_0)[name = string("mul_503")];
            tensor<int32, [3]> slice_by_index_40_begin_0 = const()[name = string("slice_by_index_40_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_40_end_0 = const()[name = string("slice_by_index_40_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_40_end_mask_0 = const()[name = string("slice_by_index_40_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 32, 22]> slice_by_index_40 = slice_by_index(begin = slice_by_index_40_begin_0, end = slice_by_index_40_end_0, end_mask = slice_by_index_40_end_mask_0, x = mul_503)[name = string("slice_by_index_40")];
            tensor<int32, [3]> slice_by_index_41_begin_0 = const()[name = string("slice_by_index_41_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_41_end_0 = const()[name = string("slice_by_index_41_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_41_end_mask_0 = const()[name = string("slice_by_index_41_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 32, 22]> slice_by_index_41 = slice_by_index(begin = slice_by_index_41_begin_0, end = slice_by_index_41_end_0, end_mask = slice_by_index_41_end_mask_0, x = mul_503)[name = string("slice_by_index_41")];
            int32 concat_20_axis_0 = const()[name = string("concat_20_axis_0"), val = int32(-1)];
            bool concat_20_interleave_0 = const()[name = string("concat_20_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 32, 44]> concat_20 = concat(axis = concat_20_axis_0, interleave = concat_20_interleave_0, values = (slice_by_index_41, slice_by_index_40))[name = string("concat_20")];
            tensor<fp16, [44]> mul_504_y_0 = const()[name = string("mul_504_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 32, 44]> mul_504 = mul(x = concat_20, y = mul_504_y_0)[name = string("mul_504")];
            tensor<fp16, [8, 32, 44]> mul_505 = mul(x = mul_503, y = mul_11_y_0)[name = string("mul_505")];
            tensor<fp16, [8, 32, 44]> mul_506 = mul(x = mul_504, y = mul_12_y_0)[name = string("mul_506")];
            tensor<fp16, [8, 32, 44]> add_60 = add(x = mul_505, y = mul_506)[name = string("add_60")];
            tensor<fp16, [2, 32, 44]> transpose_41 = transpose(perm = transpose_41_perm_0, x = reshape_83)[name = string("transpose_22")];
            tensor<fp16, [2, 32, 44]> mul_507 = mul(x = transpose_41, y = transpose_41)[name = string("mul_507")];
            tensor<int32, [1]> reduce_mean_109_axes_0 = const()[name = string("reduce_mean_109_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_109_keep_dims_0 = const()[name = string("reduce_mean_109_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 32, 1]> reduce_mean_109 = reduce_mean(axes = reduce_mean_109_axes_0, keep_dims = reduce_mean_109_keep_dims_0, x = mul_507)[name = string("reduce_mean_109")];
            fp32 rsqrt_109_epsilon_0 = const()[name = string("rsqrt_109_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 32, 1]> rsqrt_109 = rsqrt(epsilon = rsqrt_109_epsilon_0, x = reduce_mean_109)[name = string("rsqrt_109")];
            tensor<fp16, [2, 32, 44]> mul_508 = mul(x = transpose_41, y = rsqrt_109)[name = string("mul_508")];
            tensor<fp16, [44]> mul_509_y_0 = const()[name = string("mul_509_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5825792)))];
            tensor<fp16, [2, 32, 44]> mul_509 = mul(x = mul_508, y = mul_509_y_0)[name = string("mul_509")];
            tensor<int32, [3]> slice_by_index_42_begin_0 = const()[name = string("slice_by_index_42_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_42_end_0 = const()[name = string("slice_by_index_42_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_42_end_mask_0 = const()[name = string("slice_by_index_42_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 32, 22]> slice_by_index_42 = slice_by_index(begin = slice_by_index_42_begin_0, end = slice_by_index_42_end_0, end_mask = slice_by_index_42_end_mask_0, x = mul_509)[name = string("slice_by_index_42")];
            tensor<int32, [3]> slice_by_index_43_begin_0 = const()[name = string("slice_by_index_43_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_43_end_0 = const()[name = string("slice_by_index_43_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_43_end_mask_0 = const()[name = string("slice_by_index_43_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 32, 22]> slice_by_index_43 = slice_by_index(begin = slice_by_index_43_begin_0, end = slice_by_index_43_end_0, end_mask = slice_by_index_43_end_mask_0, x = mul_509)[name = string("slice_by_index_43")];
            int32 concat_21_axis_0 = const()[name = string("concat_21_axis_0"), val = int32(-1)];
            bool concat_21_interleave_0 = const()[name = string("concat_21_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 32, 44]> concat_21 = concat(axis = concat_21_axis_0, interleave = concat_21_interleave_0, values = (slice_by_index_43, slice_by_index_42))[name = string("concat_21")];
            tensor<fp16, [44]> mul_510_y_0 = const()[name = string("mul_510_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 32, 44]> mul_510 = mul(x = concat_21, y = mul_510_y_0)[name = string("mul_510")];
            tensor<fp16, [2, 32, 44]> mul_511 = mul(x = mul_509, y = mul_11_y_0)[name = string("mul_511")];
            tensor<fp16, [2, 32, 44]> mul_512 = mul(x = mul_510, y = mul_12_y_0)[name = string("mul_512")];
            tensor<fp16, [2, 32, 44]> add_61 = add(x = mul_511, y = mul_512)[name = string("add_61")];
            tensor<int32, [4]> reshape_85_shape_0 = const()[name = string("reshape_85_shape_0"), val = tensor<int32, [4]>([2, 1, 32, 44])];
            tensor<fp16, [2, 1, 32, 44]> reshape_85 = reshape(shape = reshape_85_shape_0, x = add_61)[name = string("reshape_85")];
            tensor<int32, [4]> tile_20_reps_0 = const()[name = string("tile_20_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 32, 44]> tile_20 = tile(reps = tile_20_reps_0, x = reshape_85)[name = string("tile_20")];
            tensor<int32, [3]> reshape_86_shape_0 = const()[name = string("reshape_86_shape_0"), val = tensor<int32, [3]>([8, 32, 44])];
            tensor<fp16, [8, 32, 44]> reshape_86 = reshape(shape = reshape_86_shape_0, x = tile_20)[name = string("reshape_86")];
            tensor<int32, [4]> reshape_87_shape_0 = const()[name = string("reshape_87_shape_0"), val = tensor<int32, [4]>([2, 1, 32, 44])];
            tensor<fp16, [2, 32, 44]> transpose_42 = transpose(perm = transpose_42_perm_0, x = reshape_84)[name = string("transpose_21")];
            tensor<fp16, [2, 1, 32, 44]> reshape_87 = reshape(shape = reshape_87_shape_0, x = transpose_42)[name = string("reshape_87")];
            tensor<int32, [4]> tile_21_reps_0 = const()[name = string("tile_21_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 32, 44]> tile_21 = tile(reps = tile_21_reps_0, x = reshape_87)[name = string("tile_21")];
            tensor<int32, [3]> reshape_88_shape_0 = const()[name = string("reshape_88_shape_0"), val = tensor<int32, [3]>([8, 32, 44])];
            tensor<fp16, [8, 32, 44]> reshape_88 = reshape(shape = reshape_88_shape_0, x = tile_21)[name = string("reshape_88")];
            fp16 mul_513_y_0 = const()[name = string("mul_513_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 32, 44]> mul_513 = mul(x = add_60, y = mul_513_y_0)[name = string("mul_513")];
            bool matmul_20_transpose_y_0 = const()[name = string("matmul_20_transpose_y_0"), val = bool(true)];
            bool matmul_20_transpose_x_0 = const()[name = string("matmul_20_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 32, 32]> matmul_20 = matmul(transpose_x = matmul_20_transpose_x_0, transpose_y = matmul_20_transpose_y_0, x = mul_513, y = reshape_86)[name = string("matmul_20")];
            tensor<fp16, [8, 32, 32]> add_62 = add(x = matmul_20, y = reshape_1)[name = string("add_62")];
            int32 softmax_10_axis_0 = const()[name = string("softmax_10_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 32, 32]> softmax_10 = softmax(axis = softmax_10_axis_0, x = add_62)[name = string("softmax_10")];
            bool matmul_21_transpose_x_0 = const()[name = string("matmul_21_transpose_x_0"), val = bool(false)];
            bool matmul_21_transpose_y_0 = const()[name = string("matmul_21_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 32, 44]> matmul_21 = matmul(transpose_x = matmul_21_transpose_x_0, transpose_y = matmul_21_transpose_y_0, x = softmax_10, y = reshape_88)[name = string("matmul_21")];
            tensor<int32, [3]> transpose_43_perm_0 = const()[name = string("transpose_43_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_89_shape_0 = const()[name = string("reshape_89_shape_0"), val = tensor<int32, [2]>([32, 352])];
            tensor<fp16, [32, 8, 44]> transpose_43 = transpose(perm = transpose_43_perm_0, x = matmul_21)[name = string("transpose_20")];
            tensor<fp16, [32, 352]> reshape_89 = reshape(shape = reshape_89_shape_0, x = transpose_43)[name = string("reshape_89")];
            tensor<fp16, [32, 352]> mul_514 = mul(x = reshape_89, y = reshape_89)[name = string("mul_514")];
            tensor<int32, [1]> reduce_mean_110_axes_0 = const()[name = string("reduce_mean_110_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_110_keep_dims_0 = const()[name = string("reduce_mean_110_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_110 = reduce_mean(axes = reduce_mean_110_axes_0, keep_dims = reduce_mean_110_keep_dims_0, x = mul_514)[name = string("reduce_mean_110")];
            fp32 rsqrt_110_epsilon_0 = const()[name = string("rsqrt_110_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_110 = rsqrt(epsilon = rsqrt_110_epsilon_0, x = reduce_mean_110)[name = string("rsqrt_110")];
            tensor<fp16, [32, 352]> mul_515 = mul(x = reshape_89, y = rsqrt_110)[name = string("mul_515")];
            tensor<fp16, [352]> mul_516_y_0 = const()[name = string("mul_516_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5825984)))];
            tensor<fp16, [32, 352]> mul_516 = mul(x = mul_515, y = mul_516_y_0)[name = string("mul_516")];
            tensor<fp16, [352, 352]> tern_10_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5826752))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_10_o_weight_0_palettized")];
            tensor<fp16, [32, 352]> tern_10_o = linear(bias = linear_0_bias_0, weight = tern_10_o_weight_0_palettized, x = mul_516)[name = string("tern_10_o")];
            tensor<fp16, [352]> mul_517_y_0 = const()[name = string("mul_517_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5857792)))];
            tensor<fp16, [32, 352]> mul_517 = mul(x = tern_10_o, y = mul_517_y_0)[name = string("mul_517")];
            tensor<fp16, [32, 352]> add_63 = add(x = add_59, y = mul_517)[name = string("add_63")];
            tensor<fp16, [32, 352]> mul_518 = mul(x = add_63, y = add_63)[name = string("mul_518")];
            tensor<int32, [1]> reduce_mean_111_axes_0 = const()[name = string("reduce_mean_111_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_111_keep_dims_0 = const()[name = string("reduce_mean_111_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_111 = reduce_mean(axes = reduce_mean_111_axes_0, keep_dims = reduce_mean_111_keep_dims_0, x = mul_518)[name = string("reduce_mean_111")];
            fp32 rsqrt_111_epsilon_0 = const()[name = string("rsqrt_111_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_111 = rsqrt(epsilon = rsqrt_111_epsilon_0, x = reduce_mean_111)[name = string("rsqrt_111")];
            tensor<fp16, [32, 352]> mul_519 = mul(x = add_63, y = rsqrt_111)[name = string("mul_519")];
            tensor<fp16, [352]> mul_520_y_0 = const()[name = string("mul_520_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5858560)))];
            tensor<fp16, [32, 352]> mul_520 = mul(x = mul_519, y = mul_520_y_0)[name = string("mul_520")];
            tensor<fp16, [32, 352]> mul_521 = mul(x = mul_520, y = mul_520)[name = string("mul_521")];
            tensor<int32, [1]> reduce_mean_112_axes_0 = const()[name = string("reduce_mean_112_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_112_keep_dims_0 = const()[name = string("reduce_mean_112_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_112 = reduce_mean(axes = reduce_mean_112_axes_0, keep_dims = reduce_mean_112_keep_dims_0, x = mul_521)[name = string("reduce_mean_112")];
            fp32 rsqrt_112_epsilon_0 = const()[name = string("rsqrt_112_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_112 = rsqrt(epsilon = rsqrt_112_epsilon_0, x = reduce_mean_112)[name = string("rsqrt_112")];
            tensor<fp16, [32, 352]> mul_522 = mul(x = mul_520, y = rsqrt_112)[name = string("mul_522")];
            tensor<fp16, [352]> mul_523_y_0 = const()[name = string("mul_523_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5859328)))];
            tensor<fp16, [32, 352]> mul_523 = mul(x = mul_522, y = mul_523_y_0)[name = string("mul_523")];
            tensor<fp16, [960, 352]> tern_10_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5860096))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_10_w1_weight_0_palettized")];
            tensor<fp16, [32, 960]> tern_10_w1 = linear(bias = linear_4_bias_0, weight = tern_10_w1_weight_0_palettized, x = mul_523)[name = string("tern_10_w1")];
            tensor<fp16, [960]> mul_524_y_0 = const()[name = string("mul_524_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5944640)))];
            tensor<fp16, [32, 960]> mul_524 = mul(x = tern_10_w1, y = mul_524_y_0)[name = string("mul_524")];
            tensor<fp16, [352]> mul_527_y_0 = const()[name = string("mul_527_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5946624)))];
            tensor<fp16, [32, 352]> mul_527 = mul(x = mul_522, y = mul_527_y_0)[name = string("mul_527")];
            tensor<fp16, [960, 352]> tern_10_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5947392))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_10_w3_weight_0_palettized")];
            tensor<fp16, [32, 960]> tern_10_w3 = linear(bias = linear_4_bias_0, weight = tern_10_w3_weight_0_palettized, x = mul_527)[name = string("tern_10_w3")];
            tensor<fp16, [960]> mul_528_y_0 = const()[name = string("mul_528_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6031936)))];
            tensor<fp16, [32, 960]> mul_528 = mul(x = tern_10_w3, y = mul_528_y_0)[name = string("mul_528")];
            fp16 mul_529_y_0 = const()[name = string("mul_529_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [32, 960]> mul_529 = mul(x = mul_524, y = mul_529_y_0)[name = string("mul_529")];
            tensor<fp16, [32, 960]> tanh_10 = tanh(x = mul_529)[name = string("tanh_10")];
            fp16 mul_530_x_0 = const()[name = string("mul_530_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [32, 960]> mul_530 = mul(x = mul_530_x_0, y = tanh_10)[name = string("mul_530")];
            fp16 add_64_x_0 = const()[name = string("add_64_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [32, 960]> add_64 = add(x = add_64_x_0, y = mul_530)[name = string("add_64")];
            tensor<fp16, [32, 960]> mul_531 = mul(x = mul_524, y = add_64)[name = string("mul_531")];
            tensor<fp16, [32, 960]> mul_532 = mul(x = mul_531, y = mul_528)[name = string("mul_532")];
            tensor<fp16, [32, 960]> mul_533 = mul(x = mul_532, y = mul_532)[name = string("mul_533")];
            tensor<int32, [1]> reduce_mean_114_axes_0 = const()[name = string("reduce_mean_114_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_114_keep_dims_0 = const()[name = string("reduce_mean_114_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_114 = reduce_mean(axes = reduce_mean_114_axes_0, keep_dims = reduce_mean_114_keep_dims_0, x = mul_533)[name = string("reduce_mean_114")];
            fp32 rsqrt_114_epsilon_0 = const()[name = string("rsqrt_114_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_114 = rsqrt(epsilon = rsqrt_114_epsilon_0, x = reduce_mean_114)[name = string("rsqrt_114")];
            tensor<fp16, [32, 960]> mul_534 = mul(x = mul_532, y = rsqrt_114)[name = string("mul_534")];
            tensor<fp16, [960]> mul_535_y_0 = const()[name = string("mul_535_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6033920)))];
            tensor<fp16, [32, 960]> mul_535 = mul(x = mul_534, y = mul_535_y_0)[name = string("mul_535")];
            tensor<fp16, [352, 960]> tern_10_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6035904))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_10_w2_weight_0_palettized")];
            tensor<fp16, [32, 352]> tern_10_w2 = linear(bias = linear_0_bias_0, weight = tern_10_w2_weight_0_palettized, x = mul_535)[name = string("tern_10_w2")];
            tensor<fp16, [352]> mul_536_y_0 = const()[name = string("mul_536_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6120448)))];
            tensor<fp16, [32, 352]> mul_536 = mul(x = tern_10_w2, y = mul_536_y_0)[name = string("mul_536")];
            tensor<fp16, [32, 352]> add_65 = add(x = add_63, y = mul_536)[name = string("add_65")];
            tensor<fp16, [32, 352]> mul_537 = mul(x = add_65, y = add_65)[name = string("mul_537")];
            tensor<int32, [1]> reduce_mean_115_axes_0 = const()[name = string("reduce_mean_115_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_115_keep_dims_0 = const()[name = string("reduce_mean_115_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_115 = reduce_mean(axes = reduce_mean_115_axes_0, keep_dims = reduce_mean_115_keep_dims_0, x = mul_537)[name = string("reduce_mean_115")];
            fp32 rsqrt_115_epsilon_0 = const()[name = string("rsqrt_115_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_115 = rsqrt(epsilon = rsqrt_115_epsilon_0, x = reduce_mean_115)[name = string("rsqrt_115")];
            tensor<fp16, [32, 352]> mul_538 = mul(x = add_65, y = rsqrt_115)[name = string("mul_538")];
            tensor<fp16, [352]> mul_539_y_0 = const()[name = string("mul_539_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6121216)))];
            tensor<fp16, [32, 352]> mul_539 = mul(x = mul_538, y = mul_539_y_0)[name = string("mul_539")];
            tensor<fp16, [32, 352]> mul_540 = mul(x = mul_539, y = mul_539)[name = string("mul_540")];
            tensor<int32, [1]> reduce_mean_116_axes_0 = const()[name = string("reduce_mean_116_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_116_keep_dims_0 = const()[name = string("reduce_mean_116_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_116 = reduce_mean(axes = reduce_mean_116_axes_0, keep_dims = reduce_mean_116_keep_dims_0, x = mul_540)[name = string("reduce_mean_116")];
            fp32 rsqrt_116_epsilon_0 = const()[name = string("rsqrt_116_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_116 = rsqrt(epsilon = rsqrt_116_epsilon_0, x = reduce_mean_116)[name = string("rsqrt_116")];
            tensor<fp16, [32, 352]> mul_541 = mul(x = mul_539, y = rsqrt_116)[name = string("mul_541")];
            tensor<fp16, [352]> mul_542_y_0 = const()[name = string("mul_542_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6121984)))];
            tensor<fp16, [32, 352]> mul_542 = mul(x = mul_541, y = mul_542_y_0)[name = string("mul_542")];
            tensor<fp16, [352, 352]> tern_11_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6122752))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_11_q_weight_0_palettized")];
            tensor<fp16, [32, 352]> tern_11_q = linear(bias = linear_0_bias_0, weight = tern_11_q_weight_0_palettized, x = mul_542)[name = string("tern_11_q")];
            tensor<fp16, [352]> mul_543_y_0 = const()[name = string("mul_543_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6153792)))];
            tensor<fp16, [32, 352]> mul_543 = mul(x = tern_11_q, y = mul_543_y_0)[name = string("mul_543")];
            tensor<int32, [3]> reshape_90_shape_0 = const()[name = string("reshape_90_shape_0"), val = tensor<int32, [3]>([32, 8, 44])];
            tensor<fp16, [32, 8, 44]> reshape_90 = reshape(shape = reshape_90_shape_0, x = mul_543)[name = string("reshape_90")];
            tensor<int32, [3]> transpose_44_perm_0 = const()[name = string("transpose_44_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_546_y_0 = const()[name = string("mul_546_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6154560)))];
            tensor<fp16, [32, 352]> mul_546 = mul(x = mul_541, y = mul_546_y_0)[name = string("mul_546")];
            tensor<fp16, [88, 352]> tern_11_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6155328))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_11_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_11_k_bias_0 = const()[name = string("tern_11_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [32, 88]> tern_11_k = linear(bias = tern_11_k_bias_0, weight = tern_11_k_weight_0_palettized, x = mul_546)[name = string("tern_11_k")];
            tensor<fp16, [88]> mul_547_y_0 = const()[name = string("mul_547_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6163136)))];
            tensor<fp16, [32, 88]> mul_547 = mul(x = tern_11_k, y = mul_547_y_0)[name = string("mul_547")];
            tensor<int32, [3]> reshape_91_shape_0 = const()[name = string("reshape_91_shape_0"), val = tensor<int32, [3]>([32, 2, 44])];
            tensor<fp16, [32, 2, 44]> reshape_91 = reshape(shape = reshape_91_shape_0, x = mul_547)[name = string("reshape_91")];
            tensor<int32, [3]> transpose_45_perm_0 = const()[name = string("transpose_45_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_550_y_0 = const()[name = string("mul_550_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6163392)))];
            tensor<fp16, [32, 352]> mul_550 = mul(x = mul_541, y = mul_550_y_0)[name = string("mul_550")];
            tensor<fp16, [88, 352]> tern_11_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6164160))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_11_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_11_v_bias_0 = const()[name = string("tern_11_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [32, 88]> tern_11_v = linear(bias = tern_11_v_bias_0, weight = tern_11_v_weight_0_palettized, x = mul_550)[name = string("tern_11_v")];
            tensor<fp16, [88]> mul_551_y_0 = const()[name = string("mul_551_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6171968)))];
            tensor<fp16, [32, 88]> mul_551 = mul(x = tern_11_v, y = mul_551_y_0)[name = string("mul_551")];
            tensor<int32, [3]> reshape_92_shape_0 = const()[name = string("reshape_92_shape_0"), val = tensor<int32, [3]>([32, 2, 44])];
            tensor<fp16, [32, 2, 44]> reshape_92 = reshape(shape = reshape_92_shape_0, x = mul_551)[name = string("reshape_92")];
            tensor<int32, [3]> transpose_46_perm_0 = const()[name = string("transpose_46_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 32, 44]> transpose_44 = transpose(perm = transpose_44_perm_0, x = reshape_90)[name = string("transpose_19")];
            tensor<fp16, [8, 32, 44]> mul_552 = mul(x = transpose_44, y = transpose_44)[name = string("mul_552")];
            tensor<int32, [1]> reduce_mean_119_axes_0 = const()[name = string("reduce_mean_119_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_119_keep_dims_0 = const()[name = string("reduce_mean_119_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 32, 1]> reduce_mean_119 = reduce_mean(axes = reduce_mean_119_axes_0, keep_dims = reduce_mean_119_keep_dims_0, x = mul_552)[name = string("reduce_mean_119")];
            fp32 rsqrt_119_epsilon_0 = const()[name = string("rsqrt_119_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 32, 1]> rsqrt_119 = rsqrt(epsilon = rsqrt_119_epsilon_0, x = reduce_mean_119)[name = string("rsqrt_119")];
            tensor<fp16, [8, 32, 44]> mul_553 = mul(x = transpose_44, y = rsqrt_119)[name = string("mul_553")];
            tensor<fp16, [44]> mul_554_y_0 = const()[name = string("mul_554_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6172224)))];
            tensor<fp16, [8, 32, 44]> mul_554 = mul(x = mul_553, y = mul_554_y_0)[name = string("mul_554")];
            tensor<int32, [3]> slice_by_index_44_begin_0 = const()[name = string("slice_by_index_44_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_44_end_0 = const()[name = string("slice_by_index_44_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_44_end_mask_0 = const()[name = string("slice_by_index_44_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 32, 22]> slice_by_index_44 = slice_by_index(begin = slice_by_index_44_begin_0, end = slice_by_index_44_end_0, end_mask = slice_by_index_44_end_mask_0, x = mul_554)[name = string("slice_by_index_44")];
            tensor<int32, [3]> slice_by_index_45_begin_0 = const()[name = string("slice_by_index_45_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_45_end_0 = const()[name = string("slice_by_index_45_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_45_end_mask_0 = const()[name = string("slice_by_index_45_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 32, 22]> slice_by_index_45 = slice_by_index(begin = slice_by_index_45_begin_0, end = slice_by_index_45_end_0, end_mask = slice_by_index_45_end_mask_0, x = mul_554)[name = string("slice_by_index_45")];
            int32 concat_22_axis_0 = const()[name = string("concat_22_axis_0"), val = int32(-1)];
            bool concat_22_interleave_0 = const()[name = string("concat_22_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 32, 44]> concat_22 = concat(axis = concat_22_axis_0, interleave = concat_22_interleave_0, values = (slice_by_index_45, slice_by_index_44))[name = string("concat_22")];
            tensor<fp16, [44]> mul_555_y_0 = const()[name = string("mul_555_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 32, 44]> mul_555 = mul(x = concat_22, y = mul_555_y_0)[name = string("mul_555")];
            tensor<fp16, [8, 32, 44]> mul_556 = mul(x = mul_554, y = mul_11_y_0)[name = string("mul_556")];
            tensor<fp16, [8, 32, 44]> mul_557 = mul(x = mul_555, y = mul_12_y_0)[name = string("mul_557")];
            tensor<fp16, [8, 32, 44]> add_66 = add(x = mul_556, y = mul_557)[name = string("add_66")];
            tensor<fp16, [2, 32, 44]> transpose_45 = transpose(perm = transpose_45_perm_0, x = reshape_91)[name = string("transpose_18")];
            tensor<fp16, [2, 32, 44]> mul_558 = mul(x = transpose_45, y = transpose_45)[name = string("mul_558")];
            tensor<int32, [1]> reduce_mean_120_axes_0 = const()[name = string("reduce_mean_120_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_120_keep_dims_0 = const()[name = string("reduce_mean_120_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 32, 1]> reduce_mean_120 = reduce_mean(axes = reduce_mean_120_axes_0, keep_dims = reduce_mean_120_keep_dims_0, x = mul_558)[name = string("reduce_mean_120")];
            fp32 rsqrt_120_epsilon_0 = const()[name = string("rsqrt_120_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 32, 1]> rsqrt_120 = rsqrt(epsilon = rsqrt_120_epsilon_0, x = reduce_mean_120)[name = string("rsqrt_120")];
            tensor<fp16, [2, 32, 44]> mul_559 = mul(x = transpose_45, y = rsqrt_120)[name = string("mul_559")];
            tensor<fp16, [44]> mul_560_y_0 = const()[name = string("mul_560_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6172416)))];
            tensor<fp16, [2, 32, 44]> mul_560 = mul(x = mul_559, y = mul_560_y_0)[name = string("mul_560")];
            tensor<int32, [3]> slice_by_index_46_begin_0 = const()[name = string("slice_by_index_46_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_46_end_0 = const()[name = string("slice_by_index_46_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_46_end_mask_0 = const()[name = string("slice_by_index_46_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 32, 22]> slice_by_index_46 = slice_by_index(begin = slice_by_index_46_begin_0, end = slice_by_index_46_end_0, end_mask = slice_by_index_46_end_mask_0, x = mul_560)[name = string("slice_by_index_46")];
            tensor<int32, [3]> slice_by_index_47_begin_0 = const()[name = string("slice_by_index_47_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_47_end_0 = const()[name = string("slice_by_index_47_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_47_end_mask_0 = const()[name = string("slice_by_index_47_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 32, 22]> slice_by_index_47 = slice_by_index(begin = slice_by_index_47_begin_0, end = slice_by_index_47_end_0, end_mask = slice_by_index_47_end_mask_0, x = mul_560)[name = string("slice_by_index_47")];
            int32 concat_23_axis_0 = const()[name = string("concat_23_axis_0"), val = int32(-1)];
            bool concat_23_interleave_0 = const()[name = string("concat_23_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 32, 44]> concat_23 = concat(axis = concat_23_axis_0, interleave = concat_23_interleave_0, values = (slice_by_index_47, slice_by_index_46))[name = string("concat_23")];
            tensor<fp16, [44]> mul_561_y_0 = const()[name = string("mul_561_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 32, 44]> mul_561 = mul(x = concat_23, y = mul_561_y_0)[name = string("mul_561")];
            tensor<fp16, [2, 32, 44]> mul_562 = mul(x = mul_560, y = mul_11_y_0)[name = string("mul_562")];
            tensor<fp16, [2, 32, 44]> mul_563 = mul(x = mul_561, y = mul_12_y_0)[name = string("mul_563")];
            tensor<fp16, [2, 32, 44]> add_67 = add(x = mul_562, y = mul_563)[name = string("add_67")];
            tensor<int32, [4]> reshape_93_shape_0 = const()[name = string("reshape_93_shape_0"), val = tensor<int32, [4]>([2, 1, 32, 44])];
            tensor<fp16, [2, 1, 32, 44]> reshape_93 = reshape(shape = reshape_93_shape_0, x = add_67)[name = string("reshape_93")];
            tensor<int32, [4]> tile_22_reps_0 = const()[name = string("tile_22_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 32, 44]> tile_22 = tile(reps = tile_22_reps_0, x = reshape_93)[name = string("tile_22")];
            tensor<int32, [3]> reshape_94_shape_0 = const()[name = string("reshape_94_shape_0"), val = tensor<int32, [3]>([8, 32, 44])];
            tensor<fp16, [8, 32, 44]> reshape_94 = reshape(shape = reshape_94_shape_0, x = tile_22)[name = string("reshape_94")];
            tensor<int32, [4]> reshape_95_shape_0 = const()[name = string("reshape_95_shape_0"), val = tensor<int32, [4]>([2, 1, 32, 44])];
            tensor<fp16, [2, 32, 44]> transpose_46 = transpose(perm = transpose_46_perm_0, x = reshape_92)[name = string("transpose_17")];
            tensor<fp16, [2, 1, 32, 44]> reshape_95 = reshape(shape = reshape_95_shape_0, x = transpose_46)[name = string("reshape_95")];
            tensor<int32, [4]> tile_23_reps_0 = const()[name = string("tile_23_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 32, 44]> tile_23 = tile(reps = tile_23_reps_0, x = reshape_95)[name = string("tile_23")];
            tensor<int32, [3]> reshape_96_shape_0 = const()[name = string("reshape_96_shape_0"), val = tensor<int32, [3]>([8, 32, 44])];
            tensor<fp16, [8, 32, 44]> reshape_96 = reshape(shape = reshape_96_shape_0, x = tile_23)[name = string("reshape_96")];
            fp16 mul_564_y_0 = const()[name = string("mul_564_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 32, 44]> mul_564 = mul(x = add_66, y = mul_564_y_0)[name = string("mul_564")];
            bool matmul_22_transpose_y_0 = const()[name = string("matmul_22_transpose_y_0"), val = bool(true)];
            bool matmul_22_transpose_x_0 = const()[name = string("matmul_22_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 32, 32]> matmul_22 = matmul(transpose_x = matmul_22_transpose_x_0, transpose_y = matmul_22_transpose_y_0, x = mul_564, y = reshape_94)[name = string("matmul_22")];
            tensor<fp16, [8, 32, 32]> add_68 = add(x = matmul_22, y = reshape_1)[name = string("add_68")];
            int32 softmax_11_axis_0 = const()[name = string("softmax_11_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 32, 32]> softmax_11 = softmax(axis = softmax_11_axis_0, x = add_68)[name = string("softmax_11")];
            bool matmul_23_transpose_x_0 = const()[name = string("matmul_23_transpose_x_0"), val = bool(false)];
            bool matmul_23_transpose_y_0 = const()[name = string("matmul_23_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 32, 44]> matmul_23 = matmul(transpose_x = matmul_23_transpose_x_0, transpose_y = matmul_23_transpose_y_0, x = softmax_11, y = reshape_96)[name = string("matmul_23")];
            tensor<int32, [3]> transpose_47_perm_0 = const()[name = string("transpose_47_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_97_shape_0 = const()[name = string("reshape_97_shape_0"), val = tensor<int32, [2]>([32, 352])];
            tensor<fp16, [32, 8, 44]> transpose_47 = transpose(perm = transpose_47_perm_0, x = matmul_23)[name = string("transpose_16")];
            tensor<fp16, [32, 352]> reshape_97 = reshape(shape = reshape_97_shape_0, x = transpose_47)[name = string("reshape_97")];
            tensor<fp16, [32, 352]> mul_565 = mul(x = reshape_97, y = reshape_97)[name = string("mul_565")];
            tensor<int32, [1]> reduce_mean_121_axes_0 = const()[name = string("reduce_mean_121_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_121_keep_dims_0 = const()[name = string("reduce_mean_121_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_121 = reduce_mean(axes = reduce_mean_121_axes_0, keep_dims = reduce_mean_121_keep_dims_0, x = mul_565)[name = string("reduce_mean_121")];
            fp32 rsqrt_121_epsilon_0 = const()[name = string("rsqrt_121_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_121 = rsqrt(epsilon = rsqrt_121_epsilon_0, x = reduce_mean_121)[name = string("rsqrt_121")];
            tensor<fp16, [32, 352]> mul_566 = mul(x = reshape_97, y = rsqrt_121)[name = string("mul_566")];
            tensor<fp16, [352]> mul_567_y_0 = const()[name = string("mul_567_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6172608)))];
            tensor<fp16, [32, 352]> mul_567 = mul(x = mul_566, y = mul_567_y_0)[name = string("mul_567")];
            tensor<fp16, [352, 352]> tern_11_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6173376))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_11_o_weight_0_palettized")];
            tensor<fp16, [32, 352]> tern_11_o = linear(bias = linear_0_bias_0, weight = tern_11_o_weight_0_palettized, x = mul_567)[name = string("tern_11_o")];
            tensor<fp16, [352]> mul_568_y_0 = const()[name = string("mul_568_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6204416)))];
            tensor<fp16, [32, 352]> mul_568 = mul(x = tern_11_o, y = mul_568_y_0)[name = string("mul_568")];
            tensor<fp16, [32, 352]> add_69 = add(x = add_65, y = mul_568)[name = string("add_69")];
            tensor<fp16, [32, 352]> mul_569 = mul(x = add_69, y = add_69)[name = string("mul_569")];
            tensor<int32, [1]> reduce_mean_122_axes_0 = const()[name = string("reduce_mean_122_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_122_keep_dims_0 = const()[name = string("reduce_mean_122_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_122 = reduce_mean(axes = reduce_mean_122_axes_0, keep_dims = reduce_mean_122_keep_dims_0, x = mul_569)[name = string("reduce_mean_122")];
            fp32 rsqrt_122_epsilon_0 = const()[name = string("rsqrt_122_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_122 = rsqrt(epsilon = rsqrt_122_epsilon_0, x = reduce_mean_122)[name = string("rsqrt_122")];
            tensor<fp16, [32, 352]> mul_570 = mul(x = add_69, y = rsqrt_122)[name = string("mul_570")];
            tensor<fp16, [352]> mul_571_y_0 = const()[name = string("mul_571_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6205184)))];
            tensor<fp16, [32, 352]> mul_571 = mul(x = mul_570, y = mul_571_y_0)[name = string("mul_571")];
            tensor<fp16, [32, 352]> mul_572 = mul(x = mul_571, y = mul_571)[name = string("mul_572")];
            tensor<int32, [1]> reduce_mean_123_axes_0 = const()[name = string("reduce_mean_123_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_123_keep_dims_0 = const()[name = string("reduce_mean_123_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_123 = reduce_mean(axes = reduce_mean_123_axes_0, keep_dims = reduce_mean_123_keep_dims_0, x = mul_572)[name = string("reduce_mean_123")];
            fp32 rsqrt_123_epsilon_0 = const()[name = string("rsqrt_123_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_123 = rsqrt(epsilon = rsqrt_123_epsilon_0, x = reduce_mean_123)[name = string("rsqrt_123")];
            tensor<fp16, [32, 352]> mul_573 = mul(x = mul_571, y = rsqrt_123)[name = string("mul_573")];
            tensor<fp16, [352]> mul_574_y_0 = const()[name = string("mul_574_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6205952)))];
            tensor<fp16, [32, 352]> mul_574 = mul(x = mul_573, y = mul_574_y_0)[name = string("mul_574")];
            tensor<fp16, [960, 352]> tern_11_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6206720))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_11_w1_weight_0_palettized")];
            tensor<fp16, [32, 960]> tern_11_w1 = linear(bias = linear_4_bias_0, weight = tern_11_w1_weight_0_palettized, x = mul_574)[name = string("tern_11_w1")];
            tensor<fp16, [960]> mul_575_y_0 = const()[name = string("mul_575_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6291264)))];
            tensor<fp16, [32, 960]> mul_575 = mul(x = tern_11_w1, y = mul_575_y_0)[name = string("mul_575")];
            tensor<fp16, [352]> mul_578_y_0 = const()[name = string("mul_578_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6293248)))];
            tensor<fp16, [32, 352]> mul_578 = mul(x = mul_573, y = mul_578_y_0)[name = string("mul_578")];
            tensor<fp16, [960, 352]> tern_11_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6294016))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_11_w3_weight_0_palettized")];
            tensor<fp16, [32, 960]> tern_11_w3 = linear(bias = linear_4_bias_0, weight = tern_11_w3_weight_0_palettized, x = mul_578)[name = string("tern_11_w3")];
            tensor<fp16, [960]> mul_579_y_0 = const()[name = string("mul_579_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6378560)))];
            tensor<fp16, [32, 960]> mul_579 = mul(x = tern_11_w3, y = mul_579_y_0)[name = string("mul_579")];
            fp16 mul_580_y_0 = const()[name = string("mul_580_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [32, 960]> mul_580 = mul(x = mul_575, y = mul_580_y_0)[name = string("mul_580")];
            tensor<fp16, [32, 960]> tanh_11 = tanh(x = mul_580)[name = string("tanh_11")];
            fp16 mul_581_x_0 = const()[name = string("mul_581_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [32, 960]> mul_581 = mul(x = mul_581_x_0, y = tanh_11)[name = string("mul_581")];
            fp16 add_70_x_0 = const()[name = string("add_70_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [32, 960]> add_70 = add(x = add_70_x_0, y = mul_581)[name = string("add_70")];
            tensor<fp16, [32, 960]> mul_582 = mul(x = mul_575, y = add_70)[name = string("mul_582")];
            tensor<fp16, [32, 960]> mul_583 = mul(x = mul_582, y = mul_579)[name = string("mul_583")];
            tensor<fp16, [32, 960]> mul_584 = mul(x = mul_583, y = mul_583)[name = string("mul_584")];
            tensor<int32, [1]> reduce_mean_125_axes_0 = const()[name = string("reduce_mean_125_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_125_keep_dims_0 = const()[name = string("reduce_mean_125_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_125 = reduce_mean(axes = reduce_mean_125_axes_0, keep_dims = reduce_mean_125_keep_dims_0, x = mul_584)[name = string("reduce_mean_125")];
            fp32 rsqrt_125_epsilon_0 = const()[name = string("rsqrt_125_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_125 = rsqrt(epsilon = rsqrt_125_epsilon_0, x = reduce_mean_125)[name = string("rsqrt_125")];
            tensor<fp16, [32, 960]> mul_585 = mul(x = mul_583, y = rsqrt_125)[name = string("mul_585")];
            tensor<fp16, [960]> mul_586_y_0 = const()[name = string("mul_586_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6380544)))];
            tensor<fp16, [32, 960]> mul_586 = mul(x = mul_585, y = mul_586_y_0)[name = string("mul_586")];
            tensor<fp16, [352, 960]> tern_11_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6382528))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_11_w2_weight_0_palettized")];
            tensor<fp16, [32, 352]> tern_11_w2 = linear(bias = linear_0_bias_0, weight = tern_11_w2_weight_0_palettized, x = mul_586)[name = string("tern_11_w2")];
            tensor<fp16, [352]> mul_587_y_0 = const()[name = string("mul_587_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6467072)))];
            tensor<fp16, [32, 352]> mul_587 = mul(x = tern_11_w2, y = mul_587_y_0)[name = string("mul_587")];
            tensor<fp16, [32, 352]> add_71 = add(x = add_69, y = mul_587)[name = string("add_71")];
            tensor<fp16, [32, 352]> mul_588 = mul(x = add_71, y = add_71)[name = string("mul_588")];
            tensor<int32, [1]> reduce_mean_126_axes_0 = const()[name = string("reduce_mean_126_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_126_keep_dims_0 = const()[name = string("reduce_mean_126_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_126 = reduce_mean(axes = reduce_mean_126_axes_0, keep_dims = reduce_mean_126_keep_dims_0, x = mul_588)[name = string("reduce_mean_126")];
            fp32 rsqrt_126_epsilon_0 = const()[name = string("rsqrt_126_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_126 = rsqrt(epsilon = rsqrt_126_epsilon_0, x = reduce_mean_126)[name = string("rsqrt_126")];
            tensor<fp16, [32, 352]> mul_589 = mul(x = add_71, y = rsqrt_126)[name = string("mul_589")];
            tensor<fp16, [352]> mul_590_y_0 = const()[name = string("mul_590_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6467840)))];
            tensor<fp16, [32, 352]> mul_590 = mul(x = mul_589, y = mul_590_y_0)[name = string("mul_590")];
            tensor<fp16, [32, 352]> mul_591 = mul(x = mul_590, y = mul_590)[name = string("mul_591")];
            tensor<int32, [1]> reduce_mean_127_axes_0 = const()[name = string("reduce_mean_127_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_127_keep_dims_0 = const()[name = string("reduce_mean_127_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_127 = reduce_mean(axes = reduce_mean_127_axes_0, keep_dims = reduce_mean_127_keep_dims_0, x = mul_591)[name = string("reduce_mean_127")];
            fp32 rsqrt_127_epsilon_0 = const()[name = string("rsqrt_127_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_127 = rsqrt(epsilon = rsqrt_127_epsilon_0, x = reduce_mean_127)[name = string("rsqrt_127")];
            tensor<fp16, [32, 352]> mul_592 = mul(x = mul_590, y = rsqrt_127)[name = string("mul_592")];
            tensor<fp16, [352]> mul_593_y_0 = const()[name = string("mul_593_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6468608)))];
            tensor<fp16, [32, 352]> mul_593 = mul(x = mul_592, y = mul_593_y_0)[name = string("mul_593")];
            tensor<fp16, [352, 352]> tern_12_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6469376))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_12_q_weight_0_palettized")];
            tensor<fp16, [32, 352]> tern_12_q = linear(bias = linear_0_bias_0, weight = tern_12_q_weight_0_palettized, x = mul_593)[name = string("tern_12_q")];
            tensor<fp16, [352]> mul_594_y_0 = const()[name = string("mul_594_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6500416)))];
            tensor<fp16, [32, 352]> mul_594 = mul(x = tern_12_q, y = mul_594_y_0)[name = string("mul_594")];
            tensor<int32, [3]> reshape_98_shape_0 = const()[name = string("reshape_98_shape_0"), val = tensor<int32, [3]>([32, 8, 44])];
            tensor<fp16, [32, 8, 44]> reshape_98 = reshape(shape = reshape_98_shape_0, x = mul_594)[name = string("reshape_98")];
            tensor<int32, [3]> transpose_48_perm_0 = const()[name = string("transpose_48_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_597_y_0 = const()[name = string("mul_597_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6501184)))];
            tensor<fp16, [32, 352]> mul_597 = mul(x = mul_592, y = mul_597_y_0)[name = string("mul_597")];
            tensor<fp16, [88, 352]> tern_12_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6501952))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_12_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_12_k_bias_0 = const()[name = string("tern_12_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [32, 88]> tern_12_k = linear(bias = tern_12_k_bias_0, weight = tern_12_k_weight_0_palettized, x = mul_597)[name = string("tern_12_k")];
            tensor<fp16, [88]> mul_598_y_0 = const()[name = string("mul_598_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6509760)))];
            tensor<fp16, [32, 88]> mul_598 = mul(x = tern_12_k, y = mul_598_y_0)[name = string("mul_598")];
            tensor<int32, [3]> reshape_99_shape_0 = const()[name = string("reshape_99_shape_0"), val = tensor<int32, [3]>([32, 2, 44])];
            tensor<fp16, [32, 2, 44]> reshape_99 = reshape(shape = reshape_99_shape_0, x = mul_598)[name = string("reshape_99")];
            tensor<int32, [3]> transpose_49_perm_0 = const()[name = string("transpose_49_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_601_y_0 = const()[name = string("mul_601_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6510016)))];
            tensor<fp16, [32, 352]> mul_601 = mul(x = mul_592, y = mul_601_y_0)[name = string("mul_601")];
            tensor<fp16, [88, 352]> tern_12_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6510784))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_12_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_12_v_bias_0 = const()[name = string("tern_12_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [32, 88]> tern_12_v = linear(bias = tern_12_v_bias_0, weight = tern_12_v_weight_0_palettized, x = mul_601)[name = string("tern_12_v")];
            tensor<fp16, [88]> mul_602_y_0 = const()[name = string("mul_602_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6518592)))];
            tensor<fp16, [32, 88]> mul_602 = mul(x = tern_12_v, y = mul_602_y_0)[name = string("mul_602")];
            tensor<int32, [3]> reshape_100_shape_0 = const()[name = string("reshape_100_shape_0"), val = tensor<int32, [3]>([32, 2, 44])];
            tensor<fp16, [32, 2, 44]> reshape_100 = reshape(shape = reshape_100_shape_0, x = mul_602)[name = string("reshape_100")];
            tensor<int32, [3]> transpose_50_perm_0 = const()[name = string("transpose_50_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 32, 44]> transpose_48 = transpose(perm = transpose_48_perm_0, x = reshape_98)[name = string("transpose_15")];
            tensor<fp16, [8, 32, 44]> mul_603 = mul(x = transpose_48, y = transpose_48)[name = string("mul_603")];
            tensor<int32, [1]> reduce_mean_130_axes_0 = const()[name = string("reduce_mean_130_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_130_keep_dims_0 = const()[name = string("reduce_mean_130_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 32, 1]> reduce_mean_130 = reduce_mean(axes = reduce_mean_130_axes_0, keep_dims = reduce_mean_130_keep_dims_0, x = mul_603)[name = string("reduce_mean_130")];
            fp32 rsqrt_130_epsilon_0 = const()[name = string("rsqrt_130_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 32, 1]> rsqrt_130 = rsqrt(epsilon = rsqrt_130_epsilon_0, x = reduce_mean_130)[name = string("rsqrt_130")];
            tensor<fp16, [8, 32, 44]> mul_604 = mul(x = transpose_48, y = rsqrt_130)[name = string("mul_604")];
            tensor<fp16, [44]> mul_605_y_0 = const()[name = string("mul_605_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6518848)))];
            tensor<fp16, [8, 32, 44]> mul_605 = mul(x = mul_604, y = mul_605_y_0)[name = string("mul_605")];
            tensor<int32, [3]> slice_by_index_48_begin_0 = const()[name = string("slice_by_index_48_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_48_end_0 = const()[name = string("slice_by_index_48_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_48_end_mask_0 = const()[name = string("slice_by_index_48_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 32, 22]> slice_by_index_48 = slice_by_index(begin = slice_by_index_48_begin_0, end = slice_by_index_48_end_0, end_mask = slice_by_index_48_end_mask_0, x = mul_605)[name = string("slice_by_index_48")];
            tensor<int32, [3]> slice_by_index_49_begin_0 = const()[name = string("slice_by_index_49_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_49_end_0 = const()[name = string("slice_by_index_49_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_49_end_mask_0 = const()[name = string("slice_by_index_49_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 32, 22]> slice_by_index_49 = slice_by_index(begin = slice_by_index_49_begin_0, end = slice_by_index_49_end_0, end_mask = slice_by_index_49_end_mask_0, x = mul_605)[name = string("slice_by_index_49")];
            int32 concat_24_axis_0 = const()[name = string("concat_24_axis_0"), val = int32(-1)];
            bool concat_24_interleave_0 = const()[name = string("concat_24_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 32, 44]> concat_24 = concat(axis = concat_24_axis_0, interleave = concat_24_interleave_0, values = (slice_by_index_49, slice_by_index_48))[name = string("concat_24")];
            tensor<fp16, [44]> mul_606_y_0 = const()[name = string("mul_606_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 32, 44]> mul_606 = mul(x = concat_24, y = mul_606_y_0)[name = string("mul_606")];
            tensor<fp16, [8, 32, 44]> mul_607 = mul(x = mul_605, y = mul_11_y_0)[name = string("mul_607")];
            tensor<fp16, [8, 32, 44]> mul_608 = mul(x = mul_606, y = mul_12_y_0)[name = string("mul_608")];
            tensor<fp16, [8, 32, 44]> add_72 = add(x = mul_607, y = mul_608)[name = string("add_72")];
            tensor<fp16, [2, 32, 44]> transpose_49 = transpose(perm = transpose_49_perm_0, x = reshape_99)[name = string("transpose_14")];
            tensor<fp16, [2, 32, 44]> mul_609 = mul(x = transpose_49, y = transpose_49)[name = string("mul_609")];
            tensor<int32, [1]> reduce_mean_131_axes_0 = const()[name = string("reduce_mean_131_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_131_keep_dims_0 = const()[name = string("reduce_mean_131_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 32, 1]> reduce_mean_131 = reduce_mean(axes = reduce_mean_131_axes_0, keep_dims = reduce_mean_131_keep_dims_0, x = mul_609)[name = string("reduce_mean_131")];
            fp32 rsqrt_131_epsilon_0 = const()[name = string("rsqrt_131_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 32, 1]> rsqrt_131 = rsqrt(epsilon = rsqrt_131_epsilon_0, x = reduce_mean_131)[name = string("rsqrt_131")];
            tensor<fp16, [2, 32, 44]> mul_610 = mul(x = transpose_49, y = rsqrt_131)[name = string("mul_610")];
            tensor<fp16, [44]> mul_611_y_0 = const()[name = string("mul_611_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6519040)))];
            tensor<fp16, [2, 32, 44]> mul_611 = mul(x = mul_610, y = mul_611_y_0)[name = string("mul_611")];
            tensor<int32, [3]> slice_by_index_50_begin_0 = const()[name = string("slice_by_index_50_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_50_end_0 = const()[name = string("slice_by_index_50_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_50_end_mask_0 = const()[name = string("slice_by_index_50_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 32, 22]> slice_by_index_50 = slice_by_index(begin = slice_by_index_50_begin_0, end = slice_by_index_50_end_0, end_mask = slice_by_index_50_end_mask_0, x = mul_611)[name = string("slice_by_index_50")];
            tensor<int32, [3]> slice_by_index_51_begin_0 = const()[name = string("slice_by_index_51_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_51_end_0 = const()[name = string("slice_by_index_51_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_51_end_mask_0 = const()[name = string("slice_by_index_51_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 32, 22]> slice_by_index_51 = slice_by_index(begin = slice_by_index_51_begin_0, end = slice_by_index_51_end_0, end_mask = slice_by_index_51_end_mask_0, x = mul_611)[name = string("slice_by_index_51")];
            int32 concat_25_axis_0 = const()[name = string("concat_25_axis_0"), val = int32(-1)];
            bool concat_25_interleave_0 = const()[name = string("concat_25_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 32, 44]> concat_25 = concat(axis = concat_25_axis_0, interleave = concat_25_interleave_0, values = (slice_by_index_51, slice_by_index_50))[name = string("concat_25")];
            tensor<fp16, [44]> mul_612_y_0 = const()[name = string("mul_612_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 32, 44]> mul_612 = mul(x = concat_25, y = mul_612_y_0)[name = string("mul_612")];
            tensor<fp16, [2, 32, 44]> mul_613 = mul(x = mul_611, y = mul_11_y_0)[name = string("mul_613")];
            tensor<fp16, [2, 32, 44]> mul_614 = mul(x = mul_612, y = mul_12_y_0)[name = string("mul_614")];
            tensor<fp16, [2, 32, 44]> add_73 = add(x = mul_613, y = mul_614)[name = string("add_73")];
            tensor<int32, [4]> reshape_101_shape_0 = const()[name = string("reshape_101_shape_0"), val = tensor<int32, [4]>([2, 1, 32, 44])];
            tensor<fp16, [2, 1, 32, 44]> reshape_101 = reshape(shape = reshape_101_shape_0, x = add_73)[name = string("reshape_101")];
            tensor<int32, [4]> tile_24_reps_0 = const()[name = string("tile_24_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 32, 44]> tile_24 = tile(reps = tile_24_reps_0, x = reshape_101)[name = string("tile_24")];
            tensor<int32, [3]> reshape_102_shape_0 = const()[name = string("reshape_102_shape_0"), val = tensor<int32, [3]>([8, 32, 44])];
            tensor<fp16, [8, 32, 44]> reshape_102 = reshape(shape = reshape_102_shape_0, x = tile_24)[name = string("reshape_102")];
            tensor<int32, [4]> reshape_103_shape_0 = const()[name = string("reshape_103_shape_0"), val = tensor<int32, [4]>([2, 1, 32, 44])];
            tensor<fp16, [2, 32, 44]> transpose_50 = transpose(perm = transpose_50_perm_0, x = reshape_100)[name = string("transpose_13")];
            tensor<fp16, [2, 1, 32, 44]> reshape_103 = reshape(shape = reshape_103_shape_0, x = transpose_50)[name = string("reshape_103")];
            tensor<int32, [4]> tile_25_reps_0 = const()[name = string("tile_25_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 32, 44]> tile_25 = tile(reps = tile_25_reps_0, x = reshape_103)[name = string("tile_25")];
            tensor<int32, [3]> reshape_104_shape_0 = const()[name = string("reshape_104_shape_0"), val = tensor<int32, [3]>([8, 32, 44])];
            tensor<fp16, [8, 32, 44]> reshape_104 = reshape(shape = reshape_104_shape_0, x = tile_25)[name = string("reshape_104")];
            fp16 mul_615_y_0 = const()[name = string("mul_615_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 32, 44]> mul_615 = mul(x = add_72, y = mul_615_y_0)[name = string("mul_615")];
            bool matmul_24_transpose_y_0 = const()[name = string("matmul_24_transpose_y_0"), val = bool(true)];
            bool matmul_24_transpose_x_0 = const()[name = string("matmul_24_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 32, 32]> matmul_24 = matmul(transpose_x = matmul_24_transpose_x_0, transpose_y = matmul_24_transpose_y_0, x = mul_615, y = reshape_102)[name = string("matmul_24")];
            tensor<fp16, [8, 32, 32]> add_74 = add(x = matmul_24, y = reshape_1)[name = string("add_74")];
            int32 softmax_12_axis_0 = const()[name = string("softmax_12_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 32, 32]> softmax_12 = softmax(axis = softmax_12_axis_0, x = add_74)[name = string("softmax_12")];
            bool matmul_25_transpose_x_0 = const()[name = string("matmul_25_transpose_x_0"), val = bool(false)];
            bool matmul_25_transpose_y_0 = const()[name = string("matmul_25_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 32, 44]> matmul_25 = matmul(transpose_x = matmul_25_transpose_x_0, transpose_y = matmul_25_transpose_y_0, x = softmax_12, y = reshape_104)[name = string("matmul_25")];
            tensor<int32, [3]> transpose_51_perm_0 = const()[name = string("transpose_51_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_105_shape_0 = const()[name = string("reshape_105_shape_0"), val = tensor<int32, [2]>([32, 352])];
            tensor<fp16, [32, 8, 44]> transpose_51 = transpose(perm = transpose_51_perm_0, x = matmul_25)[name = string("transpose_12")];
            tensor<fp16, [32, 352]> reshape_105 = reshape(shape = reshape_105_shape_0, x = transpose_51)[name = string("reshape_105")];
            tensor<fp16, [32, 352]> mul_616 = mul(x = reshape_105, y = reshape_105)[name = string("mul_616")];
            tensor<int32, [1]> reduce_mean_132_axes_0 = const()[name = string("reduce_mean_132_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_132_keep_dims_0 = const()[name = string("reduce_mean_132_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_132 = reduce_mean(axes = reduce_mean_132_axes_0, keep_dims = reduce_mean_132_keep_dims_0, x = mul_616)[name = string("reduce_mean_132")];
            fp32 rsqrt_132_epsilon_0 = const()[name = string("rsqrt_132_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_132 = rsqrt(epsilon = rsqrt_132_epsilon_0, x = reduce_mean_132)[name = string("rsqrt_132")];
            tensor<fp16, [32, 352]> mul_617 = mul(x = reshape_105, y = rsqrt_132)[name = string("mul_617")];
            tensor<fp16, [352]> mul_618_y_0 = const()[name = string("mul_618_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6519232)))];
            tensor<fp16, [32, 352]> mul_618 = mul(x = mul_617, y = mul_618_y_0)[name = string("mul_618")];
            tensor<fp16, [352, 352]> tern_12_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6520000))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_12_o_weight_0_palettized")];
            tensor<fp16, [32, 352]> tern_12_o = linear(bias = linear_0_bias_0, weight = tern_12_o_weight_0_palettized, x = mul_618)[name = string("tern_12_o")];
            tensor<fp16, [352]> mul_619_y_0 = const()[name = string("mul_619_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6551040)))];
            tensor<fp16, [32, 352]> mul_619 = mul(x = tern_12_o, y = mul_619_y_0)[name = string("mul_619")];
            tensor<fp16, [32, 352]> add_75 = add(x = add_71, y = mul_619)[name = string("add_75")];
            tensor<fp16, [32, 352]> mul_620 = mul(x = add_75, y = add_75)[name = string("mul_620")];
            tensor<int32, [1]> reduce_mean_133_axes_0 = const()[name = string("reduce_mean_133_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_133_keep_dims_0 = const()[name = string("reduce_mean_133_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_133 = reduce_mean(axes = reduce_mean_133_axes_0, keep_dims = reduce_mean_133_keep_dims_0, x = mul_620)[name = string("reduce_mean_133")];
            fp32 rsqrt_133_epsilon_0 = const()[name = string("rsqrt_133_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_133 = rsqrt(epsilon = rsqrt_133_epsilon_0, x = reduce_mean_133)[name = string("rsqrt_133")];
            tensor<fp16, [32, 352]> mul_621 = mul(x = add_75, y = rsqrt_133)[name = string("mul_621")];
            tensor<fp16, [352]> mul_622_y_0 = const()[name = string("mul_622_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6551808)))];
            tensor<fp16, [32, 352]> mul_622 = mul(x = mul_621, y = mul_622_y_0)[name = string("mul_622")];
            tensor<fp16, [32, 352]> mul_623 = mul(x = mul_622, y = mul_622)[name = string("mul_623")];
            tensor<int32, [1]> reduce_mean_134_axes_0 = const()[name = string("reduce_mean_134_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_134_keep_dims_0 = const()[name = string("reduce_mean_134_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_134 = reduce_mean(axes = reduce_mean_134_axes_0, keep_dims = reduce_mean_134_keep_dims_0, x = mul_623)[name = string("reduce_mean_134")];
            fp32 rsqrt_134_epsilon_0 = const()[name = string("rsqrt_134_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_134 = rsqrt(epsilon = rsqrt_134_epsilon_0, x = reduce_mean_134)[name = string("rsqrt_134")];
            tensor<fp16, [32, 352]> mul_624 = mul(x = mul_622, y = rsqrt_134)[name = string("mul_624")];
            tensor<fp16, [352]> mul_625_y_0 = const()[name = string("mul_625_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6552576)))];
            tensor<fp16, [32, 352]> mul_625 = mul(x = mul_624, y = mul_625_y_0)[name = string("mul_625")];
            tensor<fp16, [960, 352]> tern_12_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6553344))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_12_w1_weight_0_palettized")];
            tensor<fp16, [32, 960]> tern_12_w1 = linear(bias = linear_4_bias_0, weight = tern_12_w1_weight_0_palettized, x = mul_625)[name = string("tern_12_w1")];
            tensor<fp16, [960]> mul_626_y_0 = const()[name = string("mul_626_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6637888)))];
            tensor<fp16, [32, 960]> mul_626 = mul(x = tern_12_w1, y = mul_626_y_0)[name = string("mul_626")];
            tensor<fp16, [352]> mul_629_y_0 = const()[name = string("mul_629_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6639872)))];
            tensor<fp16, [32, 352]> mul_629 = mul(x = mul_624, y = mul_629_y_0)[name = string("mul_629")];
            tensor<fp16, [960, 352]> tern_12_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6640640))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_12_w3_weight_0_palettized")];
            tensor<fp16, [32, 960]> tern_12_w3 = linear(bias = linear_4_bias_0, weight = tern_12_w3_weight_0_palettized, x = mul_629)[name = string("tern_12_w3")];
            tensor<fp16, [960]> mul_630_y_0 = const()[name = string("mul_630_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6725184)))];
            tensor<fp16, [32, 960]> mul_630 = mul(x = tern_12_w3, y = mul_630_y_0)[name = string("mul_630")];
            fp16 mul_631_y_0 = const()[name = string("mul_631_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [32, 960]> mul_631 = mul(x = mul_626, y = mul_631_y_0)[name = string("mul_631")];
            tensor<fp16, [32, 960]> tanh_12 = tanh(x = mul_631)[name = string("tanh_12")];
            fp16 mul_632_x_0 = const()[name = string("mul_632_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [32, 960]> mul_632 = mul(x = mul_632_x_0, y = tanh_12)[name = string("mul_632")];
            fp16 add_76_x_0 = const()[name = string("add_76_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [32, 960]> add_76 = add(x = add_76_x_0, y = mul_632)[name = string("add_76")];
            tensor<fp16, [32, 960]> mul_633 = mul(x = mul_626, y = add_76)[name = string("mul_633")];
            tensor<fp16, [32, 960]> mul_634 = mul(x = mul_633, y = mul_630)[name = string("mul_634")];
            tensor<fp16, [32, 960]> mul_635 = mul(x = mul_634, y = mul_634)[name = string("mul_635")];
            tensor<int32, [1]> reduce_mean_136_axes_0 = const()[name = string("reduce_mean_136_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_136_keep_dims_0 = const()[name = string("reduce_mean_136_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_136 = reduce_mean(axes = reduce_mean_136_axes_0, keep_dims = reduce_mean_136_keep_dims_0, x = mul_635)[name = string("reduce_mean_136")];
            fp32 rsqrt_136_epsilon_0 = const()[name = string("rsqrt_136_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_136 = rsqrt(epsilon = rsqrt_136_epsilon_0, x = reduce_mean_136)[name = string("rsqrt_136")];
            tensor<fp16, [32, 960]> mul_636 = mul(x = mul_634, y = rsqrt_136)[name = string("mul_636")];
            tensor<fp16, [960]> mul_637_y_0 = const()[name = string("mul_637_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6727168)))];
            tensor<fp16, [32, 960]> mul_637 = mul(x = mul_636, y = mul_637_y_0)[name = string("mul_637")];
            tensor<fp16, [352, 960]> tern_12_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6729152))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_12_w2_weight_0_palettized")];
            tensor<fp16, [32, 352]> tern_12_w2 = linear(bias = linear_0_bias_0, weight = tern_12_w2_weight_0_palettized, x = mul_637)[name = string("tern_12_w2")];
            tensor<fp16, [352]> mul_638_y_0 = const()[name = string("mul_638_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6813696)))];
            tensor<fp16, [32, 352]> mul_638 = mul(x = tern_12_w2, y = mul_638_y_0)[name = string("mul_638")];
            tensor<fp16, [32, 352]> add_77 = add(x = add_75, y = mul_638)[name = string("add_77")];
            tensor<fp16, [32, 352]> mul_639 = mul(x = add_77, y = add_77)[name = string("mul_639")];
            tensor<int32, [1]> reduce_mean_137_axes_0 = const()[name = string("reduce_mean_137_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_137_keep_dims_0 = const()[name = string("reduce_mean_137_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_137 = reduce_mean(axes = reduce_mean_137_axes_0, keep_dims = reduce_mean_137_keep_dims_0, x = mul_639)[name = string("reduce_mean_137")];
            fp32 rsqrt_137_epsilon_0 = const()[name = string("rsqrt_137_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_137 = rsqrt(epsilon = rsqrt_137_epsilon_0, x = reduce_mean_137)[name = string("rsqrt_137")];
            tensor<fp16, [32, 352]> mul_640 = mul(x = add_77, y = rsqrt_137)[name = string("mul_640")];
            tensor<fp16, [352]> mul_641_y_0 = const()[name = string("mul_641_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6814464)))];
            tensor<fp16, [32, 352]> mul_641 = mul(x = mul_640, y = mul_641_y_0)[name = string("mul_641")];
            tensor<fp16, [32, 352]> mul_642 = mul(x = mul_641, y = mul_641)[name = string("mul_642")];
            tensor<int32, [1]> reduce_mean_138_axes_0 = const()[name = string("reduce_mean_138_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_138_keep_dims_0 = const()[name = string("reduce_mean_138_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_138 = reduce_mean(axes = reduce_mean_138_axes_0, keep_dims = reduce_mean_138_keep_dims_0, x = mul_642)[name = string("reduce_mean_138")];
            fp32 rsqrt_138_epsilon_0 = const()[name = string("rsqrt_138_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_138 = rsqrt(epsilon = rsqrt_138_epsilon_0, x = reduce_mean_138)[name = string("rsqrt_138")];
            tensor<fp16, [32, 352]> mul_643 = mul(x = mul_641, y = rsqrt_138)[name = string("mul_643")];
            tensor<fp16, [352]> mul_644_y_0 = const()[name = string("mul_644_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6815232)))];
            tensor<fp16, [32, 352]> mul_644 = mul(x = mul_643, y = mul_644_y_0)[name = string("mul_644")];
            tensor<fp16, [352, 352]> tern_13_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6816000))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_13_q_weight_0_palettized")];
            tensor<fp16, [32, 352]> tern_13_q = linear(bias = linear_0_bias_0, weight = tern_13_q_weight_0_palettized, x = mul_644)[name = string("tern_13_q")];
            tensor<fp16, [352]> mul_645_y_0 = const()[name = string("mul_645_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6847040)))];
            tensor<fp16, [32, 352]> mul_645 = mul(x = tern_13_q, y = mul_645_y_0)[name = string("mul_645")];
            tensor<int32, [3]> reshape_106_shape_0 = const()[name = string("reshape_106_shape_0"), val = tensor<int32, [3]>([32, 8, 44])];
            tensor<fp16, [32, 8, 44]> reshape_106 = reshape(shape = reshape_106_shape_0, x = mul_645)[name = string("reshape_106")];
            tensor<int32, [3]> transpose_52_perm_0 = const()[name = string("transpose_52_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_648_y_0 = const()[name = string("mul_648_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6847808)))];
            tensor<fp16, [32, 352]> mul_648 = mul(x = mul_643, y = mul_648_y_0)[name = string("mul_648")];
            tensor<fp16, [88, 352]> tern_13_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6848576))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_13_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_13_k_bias_0 = const()[name = string("tern_13_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [32, 88]> tern_13_k = linear(bias = tern_13_k_bias_0, weight = tern_13_k_weight_0_palettized, x = mul_648)[name = string("tern_13_k")];
            tensor<fp16, [88]> mul_649_y_0 = const()[name = string("mul_649_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6856384)))];
            tensor<fp16, [32, 88]> mul_649 = mul(x = tern_13_k, y = mul_649_y_0)[name = string("mul_649")];
            tensor<int32, [3]> reshape_107_shape_0 = const()[name = string("reshape_107_shape_0"), val = tensor<int32, [3]>([32, 2, 44])];
            tensor<fp16, [32, 2, 44]> reshape_107 = reshape(shape = reshape_107_shape_0, x = mul_649)[name = string("reshape_107")];
            tensor<int32, [3]> transpose_53_perm_0 = const()[name = string("transpose_53_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_652_y_0 = const()[name = string("mul_652_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6856640)))];
            tensor<fp16, [32, 352]> mul_652 = mul(x = mul_643, y = mul_652_y_0)[name = string("mul_652")];
            tensor<fp16, [88, 352]> tern_13_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6857408))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_13_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_13_v_bias_0 = const()[name = string("tern_13_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [32, 88]> tern_13_v = linear(bias = tern_13_v_bias_0, weight = tern_13_v_weight_0_palettized, x = mul_652)[name = string("tern_13_v")];
            tensor<fp16, [88]> mul_653_y_0 = const()[name = string("mul_653_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6865216)))];
            tensor<fp16, [32, 88]> mul_653 = mul(x = tern_13_v, y = mul_653_y_0)[name = string("mul_653")];
            tensor<int32, [3]> reshape_108_shape_0 = const()[name = string("reshape_108_shape_0"), val = tensor<int32, [3]>([32, 2, 44])];
            tensor<fp16, [32, 2, 44]> reshape_108 = reshape(shape = reshape_108_shape_0, x = mul_653)[name = string("reshape_108")];
            tensor<int32, [3]> transpose_54_perm_0 = const()[name = string("transpose_54_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 32, 44]> transpose_52 = transpose(perm = transpose_52_perm_0, x = reshape_106)[name = string("transpose_11")];
            tensor<fp16, [8, 32, 44]> mul_654 = mul(x = transpose_52, y = transpose_52)[name = string("mul_654")];
            tensor<int32, [1]> reduce_mean_141_axes_0 = const()[name = string("reduce_mean_141_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_141_keep_dims_0 = const()[name = string("reduce_mean_141_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 32, 1]> reduce_mean_141 = reduce_mean(axes = reduce_mean_141_axes_0, keep_dims = reduce_mean_141_keep_dims_0, x = mul_654)[name = string("reduce_mean_141")];
            fp32 rsqrt_141_epsilon_0 = const()[name = string("rsqrt_141_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 32, 1]> rsqrt_141 = rsqrt(epsilon = rsqrt_141_epsilon_0, x = reduce_mean_141)[name = string("rsqrt_141")];
            tensor<fp16, [8, 32, 44]> mul_655 = mul(x = transpose_52, y = rsqrt_141)[name = string("mul_655")];
            tensor<fp16, [44]> mul_656_y_0 = const()[name = string("mul_656_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6865472)))];
            tensor<fp16, [8, 32, 44]> mul_656 = mul(x = mul_655, y = mul_656_y_0)[name = string("mul_656")];
            tensor<int32, [3]> slice_by_index_52_begin_0 = const()[name = string("slice_by_index_52_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_52_end_0 = const()[name = string("slice_by_index_52_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_52_end_mask_0 = const()[name = string("slice_by_index_52_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 32, 22]> slice_by_index_52 = slice_by_index(begin = slice_by_index_52_begin_0, end = slice_by_index_52_end_0, end_mask = slice_by_index_52_end_mask_0, x = mul_656)[name = string("slice_by_index_52")];
            tensor<int32, [3]> slice_by_index_53_begin_0 = const()[name = string("slice_by_index_53_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_53_end_0 = const()[name = string("slice_by_index_53_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_53_end_mask_0 = const()[name = string("slice_by_index_53_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 32, 22]> slice_by_index_53 = slice_by_index(begin = slice_by_index_53_begin_0, end = slice_by_index_53_end_0, end_mask = slice_by_index_53_end_mask_0, x = mul_656)[name = string("slice_by_index_53")];
            int32 concat_26_axis_0 = const()[name = string("concat_26_axis_0"), val = int32(-1)];
            bool concat_26_interleave_0 = const()[name = string("concat_26_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 32, 44]> concat_26 = concat(axis = concat_26_axis_0, interleave = concat_26_interleave_0, values = (slice_by_index_53, slice_by_index_52))[name = string("concat_26")];
            tensor<fp16, [44]> mul_657_y_0 = const()[name = string("mul_657_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 32, 44]> mul_657 = mul(x = concat_26, y = mul_657_y_0)[name = string("mul_657")];
            tensor<fp16, [8, 32, 44]> mul_658 = mul(x = mul_656, y = mul_11_y_0)[name = string("mul_658")];
            tensor<fp16, [8, 32, 44]> mul_659 = mul(x = mul_657, y = mul_12_y_0)[name = string("mul_659")];
            tensor<fp16, [8, 32, 44]> add_78 = add(x = mul_658, y = mul_659)[name = string("add_78")];
            tensor<fp16, [2, 32, 44]> transpose_53 = transpose(perm = transpose_53_perm_0, x = reshape_107)[name = string("transpose_10")];
            tensor<fp16, [2, 32, 44]> mul_660 = mul(x = transpose_53, y = transpose_53)[name = string("mul_660")];
            tensor<int32, [1]> reduce_mean_142_axes_0 = const()[name = string("reduce_mean_142_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_142_keep_dims_0 = const()[name = string("reduce_mean_142_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 32, 1]> reduce_mean_142 = reduce_mean(axes = reduce_mean_142_axes_0, keep_dims = reduce_mean_142_keep_dims_0, x = mul_660)[name = string("reduce_mean_142")];
            fp32 rsqrt_142_epsilon_0 = const()[name = string("rsqrt_142_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 32, 1]> rsqrt_142 = rsqrt(epsilon = rsqrt_142_epsilon_0, x = reduce_mean_142)[name = string("rsqrt_142")];
            tensor<fp16, [2, 32, 44]> mul_661 = mul(x = transpose_53, y = rsqrt_142)[name = string("mul_661")];
            tensor<fp16, [44]> mul_662_y_0 = const()[name = string("mul_662_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6865664)))];
            tensor<fp16, [2, 32, 44]> mul_662 = mul(x = mul_661, y = mul_662_y_0)[name = string("mul_662")];
            tensor<int32, [3]> slice_by_index_54_begin_0 = const()[name = string("slice_by_index_54_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_54_end_0 = const()[name = string("slice_by_index_54_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_54_end_mask_0 = const()[name = string("slice_by_index_54_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 32, 22]> slice_by_index_54 = slice_by_index(begin = slice_by_index_54_begin_0, end = slice_by_index_54_end_0, end_mask = slice_by_index_54_end_mask_0, x = mul_662)[name = string("slice_by_index_54")];
            tensor<int32, [3]> slice_by_index_55_begin_0 = const()[name = string("slice_by_index_55_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_55_end_0 = const()[name = string("slice_by_index_55_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_55_end_mask_0 = const()[name = string("slice_by_index_55_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 32, 22]> slice_by_index_55 = slice_by_index(begin = slice_by_index_55_begin_0, end = slice_by_index_55_end_0, end_mask = slice_by_index_55_end_mask_0, x = mul_662)[name = string("slice_by_index_55")];
            int32 concat_27_axis_0 = const()[name = string("concat_27_axis_0"), val = int32(-1)];
            bool concat_27_interleave_0 = const()[name = string("concat_27_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 32, 44]> concat_27 = concat(axis = concat_27_axis_0, interleave = concat_27_interleave_0, values = (slice_by_index_55, slice_by_index_54))[name = string("concat_27")];
            tensor<fp16, [44]> mul_663_y_0 = const()[name = string("mul_663_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 32, 44]> mul_663 = mul(x = concat_27, y = mul_663_y_0)[name = string("mul_663")];
            tensor<fp16, [2, 32, 44]> mul_664 = mul(x = mul_662, y = mul_11_y_0)[name = string("mul_664")];
            tensor<fp16, [2, 32, 44]> mul_665 = mul(x = mul_663, y = mul_12_y_0)[name = string("mul_665")];
            tensor<fp16, [2, 32, 44]> add_79 = add(x = mul_664, y = mul_665)[name = string("add_79")];
            tensor<int32, [4]> reshape_109_shape_0 = const()[name = string("reshape_109_shape_0"), val = tensor<int32, [4]>([2, 1, 32, 44])];
            tensor<fp16, [2, 1, 32, 44]> reshape_109 = reshape(shape = reshape_109_shape_0, x = add_79)[name = string("reshape_109")];
            tensor<int32, [4]> tile_26_reps_0 = const()[name = string("tile_26_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 32, 44]> tile_26 = tile(reps = tile_26_reps_0, x = reshape_109)[name = string("tile_26")];
            tensor<int32, [3]> reshape_110_shape_0 = const()[name = string("reshape_110_shape_0"), val = tensor<int32, [3]>([8, 32, 44])];
            tensor<fp16, [8, 32, 44]> reshape_110 = reshape(shape = reshape_110_shape_0, x = tile_26)[name = string("reshape_110")];
            tensor<int32, [4]> reshape_111_shape_0 = const()[name = string("reshape_111_shape_0"), val = tensor<int32, [4]>([2, 1, 32, 44])];
            tensor<fp16, [2, 32, 44]> transpose_54 = transpose(perm = transpose_54_perm_0, x = reshape_108)[name = string("transpose_9")];
            tensor<fp16, [2, 1, 32, 44]> reshape_111 = reshape(shape = reshape_111_shape_0, x = transpose_54)[name = string("reshape_111")];
            tensor<int32, [4]> tile_27_reps_0 = const()[name = string("tile_27_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 32, 44]> tile_27 = tile(reps = tile_27_reps_0, x = reshape_111)[name = string("tile_27")];
            tensor<int32, [3]> reshape_112_shape_0 = const()[name = string("reshape_112_shape_0"), val = tensor<int32, [3]>([8, 32, 44])];
            tensor<fp16, [8, 32, 44]> reshape_112 = reshape(shape = reshape_112_shape_0, x = tile_27)[name = string("reshape_112")];
            fp16 mul_666_y_0 = const()[name = string("mul_666_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 32, 44]> mul_666 = mul(x = add_78, y = mul_666_y_0)[name = string("mul_666")];
            bool matmul_26_transpose_y_0 = const()[name = string("matmul_26_transpose_y_0"), val = bool(true)];
            bool matmul_26_transpose_x_0 = const()[name = string("matmul_26_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 32, 32]> matmul_26 = matmul(transpose_x = matmul_26_transpose_x_0, transpose_y = matmul_26_transpose_y_0, x = mul_666, y = reshape_110)[name = string("matmul_26")];
            tensor<fp16, [8, 32, 32]> add_80 = add(x = matmul_26, y = reshape_1)[name = string("add_80")];
            int32 softmax_13_axis_0 = const()[name = string("softmax_13_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 32, 32]> softmax_13 = softmax(axis = softmax_13_axis_0, x = add_80)[name = string("softmax_13")];
            bool matmul_27_transpose_x_0 = const()[name = string("matmul_27_transpose_x_0"), val = bool(false)];
            bool matmul_27_transpose_y_0 = const()[name = string("matmul_27_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 32, 44]> matmul_27 = matmul(transpose_x = matmul_27_transpose_x_0, transpose_y = matmul_27_transpose_y_0, x = softmax_13, y = reshape_112)[name = string("matmul_27")];
            tensor<int32, [3]> transpose_55_perm_0 = const()[name = string("transpose_55_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_113_shape_0 = const()[name = string("reshape_113_shape_0"), val = tensor<int32, [2]>([32, 352])];
            tensor<fp16, [32, 8, 44]> transpose_55 = transpose(perm = transpose_55_perm_0, x = matmul_27)[name = string("transpose_8")];
            tensor<fp16, [32, 352]> reshape_113 = reshape(shape = reshape_113_shape_0, x = transpose_55)[name = string("reshape_113")];
            tensor<fp16, [32, 352]> mul_667 = mul(x = reshape_113, y = reshape_113)[name = string("mul_667")];
            tensor<int32, [1]> reduce_mean_143_axes_0 = const()[name = string("reduce_mean_143_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_143_keep_dims_0 = const()[name = string("reduce_mean_143_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_143 = reduce_mean(axes = reduce_mean_143_axes_0, keep_dims = reduce_mean_143_keep_dims_0, x = mul_667)[name = string("reduce_mean_143")];
            fp32 rsqrt_143_epsilon_0 = const()[name = string("rsqrt_143_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_143 = rsqrt(epsilon = rsqrt_143_epsilon_0, x = reduce_mean_143)[name = string("rsqrt_143")];
            tensor<fp16, [32, 352]> mul_668 = mul(x = reshape_113, y = rsqrt_143)[name = string("mul_668")];
            tensor<fp16, [352]> mul_669_y_0 = const()[name = string("mul_669_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6865856)))];
            tensor<fp16, [32, 352]> mul_669 = mul(x = mul_668, y = mul_669_y_0)[name = string("mul_669")];
            tensor<fp16, [352, 352]> tern_13_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6866624))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_13_o_weight_0_palettized")];
            tensor<fp16, [32, 352]> tern_13_o = linear(bias = linear_0_bias_0, weight = tern_13_o_weight_0_palettized, x = mul_669)[name = string("tern_13_o")];
            tensor<fp16, [352]> mul_670_y_0 = const()[name = string("mul_670_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6897664)))];
            tensor<fp16, [32, 352]> mul_670 = mul(x = tern_13_o, y = mul_670_y_0)[name = string("mul_670")];
            tensor<fp16, [32, 352]> add_81 = add(x = add_77, y = mul_670)[name = string("add_81")];
            tensor<fp16, [32, 352]> mul_671 = mul(x = add_81, y = add_81)[name = string("mul_671")];
            tensor<int32, [1]> reduce_mean_144_axes_0 = const()[name = string("reduce_mean_144_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_144_keep_dims_0 = const()[name = string("reduce_mean_144_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_144 = reduce_mean(axes = reduce_mean_144_axes_0, keep_dims = reduce_mean_144_keep_dims_0, x = mul_671)[name = string("reduce_mean_144")];
            fp32 rsqrt_144_epsilon_0 = const()[name = string("rsqrt_144_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_144 = rsqrt(epsilon = rsqrt_144_epsilon_0, x = reduce_mean_144)[name = string("rsqrt_144")];
            tensor<fp16, [32, 352]> mul_672 = mul(x = add_81, y = rsqrt_144)[name = string("mul_672")];
            tensor<fp16, [352]> mul_673_y_0 = const()[name = string("mul_673_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6898432)))];
            tensor<fp16, [32, 352]> mul_673 = mul(x = mul_672, y = mul_673_y_0)[name = string("mul_673")];
            tensor<fp16, [32, 352]> mul_674 = mul(x = mul_673, y = mul_673)[name = string("mul_674")];
            tensor<int32, [1]> reduce_mean_145_axes_0 = const()[name = string("reduce_mean_145_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_145_keep_dims_0 = const()[name = string("reduce_mean_145_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_145 = reduce_mean(axes = reduce_mean_145_axes_0, keep_dims = reduce_mean_145_keep_dims_0, x = mul_674)[name = string("reduce_mean_145")];
            fp32 rsqrt_145_epsilon_0 = const()[name = string("rsqrt_145_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_145 = rsqrt(epsilon = rsqrt_145_epsilon_0, x = reduce_mean_145)[name = string("rsqrt_145")];
            tensor<fp16, [32, 352]> mul_675 = mul(x = mul_673, y = rsqrt_145)[name = string("mul_675")];
            tensor<fp16, [352]> mul_676_y_0 = const()[name = string("mul_676_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6899200)))];
            tensor<fp16, [32, 352]> mul_676 = mul(x = mul_675, y = mul_676_y_0)[name = string("mul_676")];
            tensor<fp16, [960, 352]> tern_13_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6899968))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_13_w1_weight_0_palettized")];
            tensor<fp16, [32, 960]> tern_13_w1 = linear(bias = linear_4_bias_0, weight = tern_13_w1_weight_0_palettized, x = mul_676)[name = string("tern_13_w1")];
            tensor<fp16, [960]> mul_677_y_0 = const()[name = string("mul_677_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6984512)))];
            tensor<fp16, [32, 960]> mul_677 = mul(x = tern_13_w1, y = mul_677_y_0)[name = string("mul_677")];
            tensor<fp16, [352]> mul_680_y_0 = const()[name = string("mul_680_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6986496)))];
            tensor<fp16, [32, 352]> mul_680 = mul(x = mul_675, y = mul_680_y_0)[name = string("mul_680")];
            tensor<fp16, [960, 352]> tern_13_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6987264))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_13_w3_weight_0_palettized")];
            tensor<fp16, [32, 960]> tern_13_w3 = linear(bias = linear_4_bias_0, weight = tern_13_w3_weight_0_palettized, x = mul_680)[name = string("tern_13_w3")];
            tensor<fp16, [960]> mul_681_y_0 = const()[name = string("mul_681_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7071808)))];
            tensor<fp16, [32, 960]> mul_681 = mul(x = tern_13_w3, y = mul_681_y_0)[name = string("mul_681")];
            fp16 mul_682_y_0 = const()[name = string("mul_682_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [32, 960]> mul_682 = mul(x = mul_677, y = mul_682_y_0)[name = string("mul_682")];
            tensor<fp16, [32, 960]> tanh_13 = tanh(x = mul_682)[name = string("tanh_13")];
            fp16 mul_683_x_0 = const()[name = string("mul_683_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [32, 960]> mul_683 = mul(x = mul_683_x_0, y = tanh_13)[name = string("mul_683")];
            fp16 add_82_x_0 = const()[name = string("add_82_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [32, 960]> add_82 = add(x = add_82_x_0, y = mul_683)[name = string("add_82")];
            tensor<fp16, [32, 960]> mul_684 = mul(x = mul_677, y = add_82)[name = string("mul_684")];
            tensor<fp16, [32, 960]> mul_685 = mul(x = mul_684, y = mul_681)[name = string("mul_685")];
            tensor<fp16, [32, 960]> mul_686 = mul(x = mul_685, y = mul_685)[name = string("mul_686")];
            tensor<int32, [1]> reduce_mean_147_axes_0 = const()[name = string("reduce_mean_147_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_147_keep_dims_0 = const()[name = string("reduce_mean_147_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_147 = reduce_mean(axes = reduce_mean_147_axes_0, keep_dims = reduce_mean_147_keep_dims_0, x = mul_686)[name = string("reduce_mean_147")];
            fp32 rsqrt_147_epsilon_0 = const()[name = string("rsqrt_147_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_147 = rsqrt(epsilon = rsqrt_147_epsilon_0, x = reduce_mean_147)[name = string("rsqrt_147")];
            tensor<fp16, [32, 960]> mul_687 = mul(x = mul_685, y = rsqrt_147)[name = string("mul_687")];
            tensor<fp16, [960]> mul_688_y_0 = const()[name = string("mul_688_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7073792)))];
            tensor<fp16, [32, 960]> mul_688 = mul(x = mul_687, y = mul_688_y_0)[name = string("mul_688")];
            tensor<fp16, [352, 960]> tern_13_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7075776))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_13_w2_weight_0_palettized")];
            tensor<fp16, [32, 352]> tern_13_w2 = linear(bias = linear_0_bias_0, weight = tern_13_w2_weight_0_palettized, x = mul_688)[name = string("tern_13_w2")];
            tensor<fp16, [352]> mul_689_y_0 = const()[name = string("mul_689_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7160320)))];
            tensor<fp16, [32, 352]> mul_689 = mul(x = tern_13_w2, y = mul_689_y_0)[name = string("mul_689")];
            tensor<fp16, [32, 352]> add_83 = add(x = add_81, y = mul_689)[name = string("add_83")];
            tensor<fp16, [32, 352]> mul_690 = mul(x = add_83, y = add_83)[name = string("mul_690")];
            tensor<int32, [1]> reduce_mean_148_axes_0 = const()[name = string("reduce_mean_148_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_148_keep_dims_0 = const()[name = string("reduce_mean_148_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_148 = reduce_mean(axes = reduce_mean_148_axes_0, keep_dims = reduce_mean_148_keep_dims_0, x = mul_690)[name = string("reduce_mean_148")];
            fp32 rsqrt_148_epsilon_0 = const()[name = string("rsqrt_148_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_148 = rsqrt(epsilon = rsqrt_148_epsilon_0, x = reduce_mean_148)[name = string("rsqrt_148")];
            tensor<fp16, [32, 352]> mul_691 = mul(x = add_83, y = rsqrt_148)[name = string("mul_691")];
            tensor<fp16, [352]> mul_692_y_0 = const()[name = string("mul_692_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7161088)))];
            tensor<fp16, [32, 352]> mul_692 = mul(x = mul_691, y = mul_692_y_0)[name = string("mul_692")];
            tensor<fp16, [32, 352]> mul_693 = mul(x = mul_692, y = mul_692)[name = string("mul_693")];
            tensor<int32, [1]> reduce_mean_149_axes_0 = const()[name = string("reduce_mean_149_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_149_keep_dims_0 = const()[name = string("reduce_mean_149_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_149 = reduce_mean(axes = reduce_mean_149_axes_0, keep_dims = reduce_mean_149_keep_dims_0, x = mul_693)[name = string("reduce_mean_149")];
            fp32 rsqrt_149_epsilon_0 = const()[name = string("rsqrt_149_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_149 = rsqrt(epsilon = rsqrt_149_epsilon_0, x = reduce_mean_149)[name = string("rsqrt_149")];
            tensor<fp16, [32, 352]> mul_694 = mul(x = mul_692, y = rsqrt_149)[name = string("mul_694")];
            tensor<fp16, [352]> mul_695_y_0 = const()[name = string("mul_695_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7161856)))];
            tensor<fp16, [32, 352]> mul_695 = mul(x = mul_694, y = mul_695_y_0)[name = string("mul_695")];
            tensor<fp16, [352, 352]> tern_14_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7162624))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_14_q_weight_0_palettized")];
            tensor<fp16, [32, 352]> tern_14_q = linear(bias = linear_0_bias_0, weight = tern_14_q_weight_0_palettized, x = mul_695)[name = string("tern_14_q")];
            tensor<fp16, [352]> mul_696_y_0 = const()[name = string("mul_696_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7193664)))];
            tensor<fp16, [32, 352]> mul_696 = mul(x = tern_14_q, y = mul_696_y_0)[name = string("mul_696")];
            tensor<int32, [3]> reshape_114_shape_0 = const()[name = string("reshape_114_shape_0"), val = tensor<int32, [3]>([32, 8, 44])];
            tensor<fp16, [32, 8, 44]> reshape_114 = reshape(shape = reshape_114_shape_0, x = mul_696)[name = string("reshape_114")];
            tensor<int32, [3]> transpose_56_perm_0 = const()[name = string("transpose_56_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_699_y_0 = const()[name = string("mul_699_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7194432)))];
            tensor<fp16, [32, 352]> mul_699 = mul(x = mul_694, y = mul_699_y_0)[name = string("mul_699")];
            tensor<fp16, [88, 352]> tern_14_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7195200))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_14_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_14_k_bias_0 = const()[name = string("tern_14_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [32, 88]> tern_14_k = linear(bias = tern_14_k_bias_0, weight = tern_14_k_weight_0_palettized, x = mul_699)[name = string("tern_14_k")];
            tensor<fp16, [88]> mul_700_y_0 = const()[name = string("mul_700_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7203008)))];
            tensor<fp16, [32, 88]> mul_700 = mul(x = tern_14_k, y = mul_700_y_0)[name = string("mul_700")];
            tensor<int32, [3]> reshape_115_shape_0 = const()[name = string("reshape_115_shape_0"), val = tensor<int32, [3]>([32, 2, 44])];
            tensor<fp16, [32, 2, 44]> reshape_115 = reshape(shape = reshape_115_shape_0, x = mul_700)[name = string("reshape_115")];
            tensor<int32, [3]> transpose_57_perm_0 = const()[name = string("transpose_57_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_703_y_0 = const()[name = string("mul_703_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7203264)))];
            tensor<fp16, [32, 352]> mul_703 = mul(x = mul_694, y = mul_703_y_0)[name = string("mul_703")];
            tensor<fp16, [88, 352]> tern_14_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7204032))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_14_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_14_v_bias_0 = const()[name = string("tern_14_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [32, 88]> tern_14_v = linear(bias = tern_14_v_bias_0, weight = tern_14_v_weight_0_palettized, x = mul_703)[name = string("tern_14_v")];
            tensor<fp16, [88]> mul_704_y_0 = const()[name = string("mul_704_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7211840)))];
            tensor<fp16, [32, 88]> mul_704 = mul(x = tern_14_v, y = mul_704_y_0)[name = string("mul_704")];
            tensor<int32, [3]> reshape_116_shape_0 = const()[name = string("reshape_116_shape_0"), val = tensor<int32, [3]>([32, 2, 44])];
            tensor<fp16, [32, 2, 44]> reshape_116 = reshape(shape = reshape_116_shape_0, x = mul_704)[name = string("reshape_116")];
            tensor<int32, [3]> transpose_58_perm_0 = const()[name = string("transpose_58_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 32, 44]> transpose_56 = transpose(perm = transpose_56_perm_0, x = reshape_114)[name = string("transpose_7")];
            tensor<fp16, [8, 32, 44]> mul_705 = mul(x = transpose_56, y = transpose_56)[name = string("mul_705")];
            tensor<int32, [1]> reduce_mean_152_axes_0 = const()[name = string("reduce_mean_152_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_152_keep_dims_0 = const()[name = string("reduce_mean_152_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 32, 1]> reduce_mean_152 = reduce_mean(axes = reduce_mean_152_axes_0, keep_dims = reduce_mean_152_keep_dims_0, x = mul_705)[name = string("reduce_mean_152")];
            fp32 rsqrt_152_epsilon_0 = const()[name = string("rsqrt_152_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 32, 1]> rsqrt_152 = rsqrt(epsilon = rsqrt_152_epsilon_0, x = reduce_mean_152)[name = string("rsqrt_152")];
            tensor<fp16, [8, 32, 44]> mul_706 = mul(x = transpose_56, y = rsqrt_152)[name = string("mul_706")];
            tensor<fp16, [44]> mul_707_y_0 = const()[name = string("mul_707_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7212096)))];
            tensor<fp16, [8, 32, 44]> mul_707 = mul(x = mul_706, y = mul_707_y_0)[name = string("mul_707")];
            tensor<int32, [3]> slice_by_index_56_begin_0 = const()[name = string("slice_by_index_56_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_56_end_0 = const()[name = string("slice_by_index_56_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_56_end_mask_0 = const()[name = string("slice_by_index_56_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 32, 22]> slice_by_index_56 = slice_by_index(begin = slice_by_index_56_begin_0, end = slice_by_index_56_end_0, end_mask = slice_by_index_56_end_mask_0, x = mul_707)[name = string("slice_by_index_56")];
            tensor<int32, [3]> slice_by_index_57_begin_0 = const()[name = string("slice_by_index_57_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_57_end_0 = const()[name = string("slice_by_index_57_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_57_end_mask_0 = const()[name = string("slice_by_index_57_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 32, 22]> slice_by_index_57 = slice_by_index(begin = slice_by_index_57_begin_0, end = slice_by_index_57_end_0, end_mask = slice_by_index_57_end_mask_0, x = mul_707)[name = string("slice_by_index_57")];
            int32 concat_28_axis_0 = const()[name = string("concat_28_axis_0"), val = int32(-1)];
            bool concat_28_interleave_0 = const()[name = string("concat_28_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 32, 44]> concat_28 = concat(axis = concat_28_axis_0, interleave = concat_28_interleave_0, values = (slice_by_index_57, slice_by_index_56))[name = string("concat_28")];
            tensor<fp16, [44]> mul_708_y_0 = const()[name = string("mul_708_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 32, 44]> mul_708 = mul(x = concat_28, y = mul_708_y_0)[name = string("mul_708")];
            tensor<fp16, [8, 32, 44]> mul_709 = mul(x = mul_707, y = mul_11_y_0)[name = string("mul_709")];
            tensor<fp16, [8, 32, 44]> mul_710 = mul(x = mul_708, y = mul_12_y_0)[name = string("mul_710")];
            tensor<fp16, [8, 32, 44]> add_84 = add(x = mul_709, y = mul_710)[name = string("add_84")];
            tensor<fp16, [2, 32, 44]> transpose_57 = transpose(perm = transpose_57_perm_0, x = reshape_115)[name = string("transpose_6")];
            tensor<fp16, [2, 32, 44]> mul_711 = mul(x = transpose_57, y = transpose_57)[name = string("mul_711")];
            tensor<int32, [1]> reduce_mean_153_axes_0 = const()[name = string("reduce_mean_153_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_153_keep_dims_0 = const()[name = string("reduce_mean_153_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 32, 1]> reduce_mean_153 = reduce_mean(axes = reduce_mean_153_axes_0, keep_dims = reduce_mean_153_keep_dims_0, x = mul_711)[name = string("reduce_mean_153")];
            fp32 rsqrt_153_epsilon_0 = const()[name = string("rsqrt_153_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 32, 1]> rsqrt_153 = rsqrt(epsilon = rsqrt_153_epsilon_0, x = reduce_mean_153)[name = string("rsqrt_153")];
            tensor<fp16, [2, 32, 44]> mul_712 = mul(x = transpose_57, y = rsqrt_153)[name = string("mul_712")];
            tensor<fp16, [44]> mul_713_y_0 = const()[name = string("mul_713_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7212288)))];
            tensor<fp16, [2, 32, 44]> mul_713 = mul(x = mul_712, y = mul_713_y_0)[name = string("mul_713")];
            tensor<int32, [3]> slice_by_index_58_begin_0 = const()[name = string("slice_by_index_58_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_58_end_0 = const()[name = string("slice_by_index_58_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_58_end_mask_0 = const()[name = string("slice_by_index_58_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 32, 22]> slice_by_index_58 = slice_by_index(begin = slice_by_index_58_begin_0, end = slice_by_index_58_end_0, end_mask = slice_by_index_58_end_mask_0, x = mul_713)[name = string("slice_by_index_58")];
            tensor<int32, [3]> slice_by_index_59_begin_0 = const()[name = string("slice_by_index_59_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_59_end_0 = const()[name = string("slice_by_index_59_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_59_end_mask_0 = const()[name = string("slice_by_index_59_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 32, 22]> slice_by_index_59 = slice_by_index(begin = slice_by_index_59_begin_0, end = slice_by_index_59_end_0, end_mask = slice_by_index_59_end_mask_0, x = mul_713)[name = string("slice_by_index_59")];
            int32 concat_29_axis_0 = const()[name = string("concat_29_axis_0"), val = int32(-1)];
            bool concat_29_interleave_0 = const()[name = string("concat_29_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 32, 44]> concat_29 = concat(axis = concat_29_axis_0, interleave = concat_29_interleave_0, values = (slice_by_index_59, slice_by_index_58))[name = string("concat_29")];
            tensor<fp16, [44]> mul_714_y_0 = const()[name = string("mul_714_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 32, 44]> mul_714 = mul(x = concat_29, y = mul_714_y_0)[name = string("mul_714")];
            tensor<fp16, [2, 32, 44]> mul_715 = mul(x = mul_713, y = mul_11_y_0)[name = string("mul_715")];
            tensor<fp16, [2, 32, 44]> mul_716 = mul(x = mul_714, y = mul_12_y_0)[name = string("mul_716")];
            tensor<fp16, [2, 32, 44]> add_85 = add(x = mul_715, y = mul_716)[name = string("add_85")];
            tensor<int32, [4]> reshape_117_shape_0 = const()[name = string("reshape_117_shape_0"), val = tensor<int32, [4]>([2, 1, 32, 44])];
            tensor<fp16, [2, 1, 32, 44]> reshape_117 = reshape(shape = reshape_117_shape_0, x = add_85)[name = string("reshape_117")];
            tensor<int32, [4]> tile_28_reps_0 = const()[name = string("tile_28_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 32, 44]> tile_28 = tile(reps = tile_28_reps_0, x = reshape_117)[name = string("tile_28")];
            tensor<int32, [3]> reshape_118_shape_0 = const()[name = string("reshape_118_shape_0"), val = tensor<int32, [3]>([8, 32, 44])];
            tensor<fp16, [8, 32, 44]> reshape_118 = reshape(shape = reshape_118_shape_0, x = tile_28)[name = string("reshape_118")];
            tensor<int32, [4]> reshape_119_shape_0 = const()[name = string("reshape_119_shape_0"), val = tensor<int32, [4]>([2, 1, 32, 44])];
            tensor<fp16, [2, 32, 44]> transpose_58 = transpose(perm = transpose_58_perm_0, x = reshape_116)[name = string("transpose_5")];
            tensor<fp16, [2, 1, 32, 44]> reshape_119 = reshape(shape = reshape_119_shape_0, x = transpose_58)[name = string("reshape_119")];
            tensor<int32, [4]> tile_29_reps_0 = const()[name = string("tile_29_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 32, 44]> tile_29 = tile(reps = tile_29_reps_0, x = reshape_119)[name = string("tile_29")];
            tensor<int32, [3]> reshape_120_shape_0 = const()[name = string("reshape_120_shape_0"), val = tensor<int32, [3]>([8, 32, 44])];
            tensor<fp16, [8, 32, 44]> reshape_120 = reshape(shape = reshape_120_shape_0, x = tile_29)[name = string("reshape_120")];
            fp16 mul_717_y_0 = const()[name = string("mul_717_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 32, 44]> mul_717 = mul(x = add_84, y = mul_717_y_0)[name = string("mul_717")];
            bool matmul_28_transpose_y_0 = const()[name = string("matmul_28_transpose_y_0"), val = bool(true)];
            bool matmul_28_transpose_x_0 = const()[name = string("matmul_28_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 32, 32]> matmul_28 = matmul(transpose_x = matmul_28_transpose_x_0, transpose_y = matmul_28_transpose_y_0, x = mul_717, y = reshape_118)[name = string("matmul_28")];
            tensor<fp16, [8, 32, 32]> add_86 = add(x = matmul_28, y = reshape_1)[name = string("add_86")];
            int32 softmax_14_axis_0 = const()[name = string("softmax_14_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 32, 32]> softmax_14 = softmax(axis = softmax_14_axis_0, x = add_86)[name = string("softmax_14")];
            bool matmul_29_transpose_x_0 = const()[name = string("matmul_29_transpose_x_0"), val = bool(false)];
            bool matmul_29_transpose_y_0 = const()[name = string("matmul_29_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 32, 44]> matmul_29 = matmul(transpose_x = matmul_29_transpose_x_0, transpose_y = matmul_29_transpose_y_0, x = softmax_14, y = reshape_120)[name = string("matmul_29")];
            tensor<int32, [3]> transpose_59_perm_0 = const()[name = string("transpose_59_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_121_shape_0 = const()[name = string("reshape_121_shape_0"), val = tensor<int32, [2]>([32, 352])];
            tensor<fp16, [32, 8, 44]> transpose_59 = transpose(perm = transpose_59_perm_0, x = matmul_29)[name = string("transpose_4")];
            tensor<fp16, [32, 352]> reshape_121 = reshape(shape = reshape_121_shape_0, x = transpose_59)[name = string("reshape_121")];
            tensor<fp16, [32, 352]> mul_718 = mul(x = reshape_121, y = reshape_121)[name = string("mul_718")];
            tensor<int32, [1]> reduce_mean_154_axes_0 = const()[name = string("reduce_mean_154_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_154_keep_dims_0 = const()[name = string("reduce_mean_154_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_154 = reduce_mean(axes = reduce_mean_154_axes_0, keep_dims = reduce_mean_154_keep_dims_0, x = mul_718)[name = string("reduce_mean_154")];
            fp32 rsqrt_154_epsilon_0 = const()[name = string("rsqrt_154_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_154 = rsqrt(epsilon = rsqrt_154_epsilon_0, x = reduce_mean_154)[name = string("rsqrt_154")];
            tensor<fp16, [32, 352]> mul_719 = mul(x = reshape_121, y = rsqrt_154)[name = string("mul_719")];
            tensor<fp16, [352]> mul_720_y_0 = const()[name = string("mul_720_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7212480)))];
            tensor<fp16, [32, 352]> mul_720 = mul(x = mul_719, y = mul_720_y_0)[name = string("mul_720")];
            tensor<fp16, [352, 352]> tern_14_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7213248))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_14_o_weight_0_palettized")];
            tensor<fp16, [32, 352]> tern_14_o = linear(bias = linear_0_bias_0, weight = tern_14_o_weight_0_palettized, x = mul_720)[name = string("tern_14_o")];
            tensor<fp16, [352]> mul_721_y_0 = const()[name = string("mul_721_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7244288)))];
            tensor<fp16, [32, 352]> mul_721 = mul(x = tern_14_o, y = mul_721_y_0)[name = string("mul_721")];
            tensor<fp16, [32, 352]> add_87 = add(x = add_83, y = mul_721)[name = string("add_87")];
            tensor<fp16, [32, 352]> mul_722 = mul(x = add_87, y = add_87)[name = string("mul_722")];
            tensor<int32, [1]> reduce_mean_155_axes_0 = const()[name = string("reduce_mean_155_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_155_keep_dims_0 = const()[name = string("reduce_mean_155_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_155 = reduce_mean(axes = reduce_mean_155_axes_0, keep_dims = reduce_mean_155_keep_dims_0, x = mul_722)[name = string("reduce_mean_155")];
            fp32 rsqrt_155_epsilon_0 = const()[name = string("rsqrt_155_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_155 = rsqrt(epsilon = rsqrt_155_epsilon_0, x = reduce_mean_155)[name = string("rsqrt_155")];
            tensor<fp16, [32, 352]> mul_723 = mul(x = add_87, y = rsqrt_155)[name = string("mul_723")];
            tensor<fp16, [352]> mul_724_y_0 = const()[name = string("mul_724_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7245056)))];
            tensor<fp16, [32, 352]> mul_724 = mul(x = mul_723, y = mul_724_y_0)[name = string("mul_724")];
            tensor<fp16, [32, 352]> mul_725 = mul(x = mul_724, y = mul_724)[name = string("mul_725")];
            tensor<int32, [1]> reduce_mean_156_axes_0 = const()[name = string("reduce_mean_156_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_156_keep_dims_0 = const()[name = string("reduce_mean_156_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_156 = reduce_mean(axes = reduce_mean_156_axes_0, keep_dims = reduce_mean_156_keep_dims_0, x = mul_725)[name = string("reduce_mean_156")];
            fp32 rsqrt_156_epsilon_0 = const()[name = string("rsqrt_156_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_156 = rsqrt(epsilon = rsqrt_156_epsilon_0, x = reduce_mean_156)[name = string("rsqrt_156")];
            tensor<fp16, [32, 352]> mul_726 = mul(x = mul_724, y = rsqrt_156)[name = string("mul_726")];
            tensor<fp16, [352]> mul_727_y_0 = const()[name = string("mul_727_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7245824)))];
            tensor<fp16, [32, 352]> mul_727 = mul(x = mul_726, y = mul_727_y_0)[name = string("mul_727")];
            tensor<fp16, [960, 352]> tern_14_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7246592))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_14_w1_weight_0_palettized")];
            tensor<fp16, [32, 960]> tern_14_w1 = linear(bias = linear_4_bias_0, weight = tern_14_w1_weight_0_palettized, x = mul_727)[name = string("tern_14_w1")];
            tensor<fp16, [960]> mul_728_y_0 = const()[name = string("mul_728_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7331136)))];
            tensor<fp16, [32, 960]> mul_728 = mul(x = tern_14_w1, y = mul_728_y_0)[name = string("mul_728")];
            tensor<fp16, [352]> mul_731_y_0 = const()[name = string("mul_731_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7333120)))];
            tensor<fp16, [32, 352]> mul_731 = mul(x = mul_726, y = mul_731_y_0)[name = string("mul_731")];
            tensor<fp16, [960, 352]> tern_14_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7333888))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_14_w3_weight_0_palettized")];
            tensor<fp16, [32, 960]> tern_14_w3 = linear(bias = linear_4_bias_0, weight = tern_14_w3_weight_0_palettized, x = mul_731)[name = string("tern_14_w3")];
            tensor<fp16, [960]> mul_732_y_0 = const()[name = string("mul_732_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7418432)))];
            tensor<fp16, [32, 960]> mul_732 = mul(x = tern_14_w3, y = mul_732_y_0)[name = string("mul_732")];
            fp16 mul_733_y_0 = const()[name = string("mul_733_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [32, 960]> mul_733 = mul(x = mul_728, y = mul_733_y_0)[name = string("mul_733")];
            tensor<fp16, [32, 960]> tanh_14 = tanh(x = mul_733)[name = string("tanh_14")];
            fp16 mul_734_x_0 = const()[name = string("mul_734_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [32, 960]> mul_734 = mul(x = mul_734_x_0, y = tanh_14)[name = string("mul_734")];
            fp16 add_88_x_0 = const()[name = string("add_88_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [32, 960]> add_88 = add(x = add_88_x_0, y = mul_734)[name = string("add_88")];
            tensor<fp16, [32, 960]> mul_735 = mul(x = mul_728, y = add_88)[name = string("mul_735")];
            tensor<fp16, [32, 960]> mul_736 = mul(x = mul_735, y = mul_732)[name = string("mul_736")];
            tensor<fp16, [32, 960]> mul_737 = mul(x = mul_736, y = mul_736)[name = string("mul_737")];
            tensor<int32, [1]> reduce_mean_158_axes_0 = const()[name = string("reduce_mean_158_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_158_keep_dims_0 = const()[name = string("reduce_mean_158_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_158 = reduce_mean(axes = reduce_mean_158_axes_0, keep_dims = reduce_mean_158_keep_dims_0, x = mul_737)[name = string("reduce_mean_158")];
            fp32 rsqrt_158_epsilon_0 = const()[name = string("rsqrt_158_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_158 = rsqrt(epsilon = rsqrt_158_epsilon_0, x = reduce_mean_158)[name = string("rsqrt_158")];
            tensor<fp16, [32, 960]> mul_738 = mul(x = mul_736, y = rsqrt_158)[name = string("mul_738")];
            tensor<fp16, [960]> mul_739_y_0 = const()[name = string("mul_739_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7420416)))];
            tensor<fp16, [32, 960]> mul_739 = mul(x = mul_738, y = mul_739_y_0)[name = string("mul_739")];
            tensor<fp16, [352, 960]> tern_14_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7422400))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_14_w2_weight_0_palettized")];
            tensor<fp16, [32, 352]> tern_14_w2 = linear(bias = linear_0_bias_0, weight = tern_14_w2_weight_0_palettized, x = mul_739)[name = string("tern_14_w2")];
            tensor<fp16, [352]> mul_740_y_0 = const()[name = string("mul_740_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7506944)))];
            tensor<fp16, [32, 352]> mul_740 = mul(x = tern_14_w2, y = mul_740_y_0)[name = string("mul_740")];
            tensor<fp16, [32, 352]> add_89 = add(x = add_87, y = mul_740)[name = string("add_89")];
            tensor<fp16, [32, 352]> mul_741 = mul(x = add_89, y = add_89)[name = string("mul_741")];
            tensor<int32, [1]> reduce_mean_159_axes_0 = const()[name = string("reduce_mean_159_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_159_keep_dims_0 = const()[name = string("reduce_mean_159_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_159 = reduce_mean(axes = reduce_mean_159_axes_0, keep_dims = reduce_mean_159_keep_dims_0, x = mul_741)[name = string("reduce_mean_159")];
            fp32 rsqrt_159_epsilon_0 = const()[name = string("rsqrt_159_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_159 = rsqrt(epsilon = rsqrt_159_epsilon_0, x = reduce_mean_159)[name = string("rsqrt_159")];
            tensor<fp16, [32, 352]> mul_742 = mul(x = add_89, y = rsqrt_159)[name = string("mul_742")];
            tensor<fp16, [352]> mul_743_y_0 = const()[name = string("mul_743_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7507712)))];
            tensor<fp16, [32, 352]> mul_743 = mul(x = mul_742, y = mul_743_y_0)[name = string("mul_743")];
            tensor<fp16, [352, 352]> linear_7_weight_0 = const()[name = string("linear_7_weight_0"), val = tensor<fp16, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7508480)))];
            tensor<fp16, [32, 352]> linear_7 = linear(bias = linear_0_bias_0, weight = linear_7_weight_0, x = mul_743)[name = string("linear_7")];
            tensor<int32, [3]> reshape_122_shape_0 = const()[name = string("reshape_122_shape_0"), val = tensor<int32, [3]>([32, 8, 44])];
            tensor<fp16, [32, 8, 44]> reshape_122 = reshape(shape = reshape_122_shape_0, x = linear_7)[name = string("reshape_122")];
            tensor<int32, [3]> transpose_60_perm_0 = const()[name = string("transpose_60_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [88, 352]> linear_8_weight_0 = const()[name = string("linear_8_weight_0"), val = tensor<fp16, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7756352)))];
            tensor<fp16, [88]> linear_8_bias_0 = const()[name = string("linear_8_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [32, 88]> linear_8 = linear(bias = linear_8_bias_0, weight = linear_8_weight_0, x = mul_743)[name = string("linear_8")];
            tensor<int32, [3]> reshape_123_shape_0 = const()[name = string("reshape_123_shape_0"), val = tensor<int32, [3]>([32, 2, 44])];
            tensor<fp16, [32, 2, 44]> reshape_123 = reshape(shape = reshape_123_shape_0, x = linear_8)[name = string("reshape_123")];
            tensor<int32, [3]> transpose_61_perm_0 = const()[name = string("transpose_61_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [88, 352]> linear_9_weight_0 = const()[name = string("linear_9_weight_0"), val = tensor<fp16, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7818368)))];
            tensor<fp16, [88]> linear_9_bias_0 = const()[name = string("linear_9_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [32, 88]> linear_9 = linear(bias = linear_9_bias_0, weight = linear_9_weight_0, x = mul_743)[name = string("linear_9")];
            tensor<int32, [3]> reshape_124_shape_0 = const()[name = string("reshape_124_shape_0"), val = tensor<int32, [3]>([32, 2, 44])];
            tensor<fp16, [32, 2, 44]> reshape_124 = reshape(shape = reshape_124_shape_0, x = linear_9)[name = string("reshape_124")];
            tensor<int32, [3]> transpose_62_perm_0 = const()[name = string("transpose_62_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 32, 44]> transpose_60 = transpose(perm = transpose_60_perm_0, x = reshape_122)[name = string("transpose_3")];
            tensor<fp16, [8, 32, 44]> mul_744 = mul(x = transpose_60, y = transpose_60)[name = string("mul_744")];
            tensor<int32, [1]> reduce_mean_160_axes_0 = const()[name = string("reduce_mean_160_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_160_keep_dims_0 = const()[name = string("reduce_mean_160_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 32, 1]> reduce_mean_160 = reduce_mean(axes = reduce_mean_160_axes_0, keep_dims = reduce_mean_160_keep_dims_0, x = mul_744)[name = string("reduce_mean_160")];
            fp32 rsqrt_160_epsilon_0 = const()[name = string("rsqrt_160_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 32, 1]> rsqrt_160 = rsqrt(epsilon = rsqrt_160_epsilon_0, x = reduce_mean_160)[name = string("rsqrt_160")];
            tensor<fp16, [8, 32, 44]> mul_745 = mul(x = transpose_60, y = rsqrt_160)[name = string("mul_745")];
            tensor<fp16, [44]> mul_746_y_0 = const()[name = string("mul_746_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7880384)))];
            tensor<fp16, [8, 32, 44]> mul_746 = mul(x = mul_745, y = mul_746_y_0)[name = string("mul_746")];
            tensor<int32, [3]> slice_by_index_60_begin_0 = const()[name = string("slice_by_index_60_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_60_end_0 = const()[name = string("slice_by_index_60_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_60_end_mask_0 = const()[name = string("slice_by_index_60_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 32, 22]> slice_by_index_60 = slice_by_index(begin = slice_by_index_60_begin_0, end = slice_by_index_60_end_0, end_mask = slice_by_index_60_end_mask_0, x = mul_746)[name = string("slice_by_index_60")];
            tensor<int32, [3]> slice_by_index_61_begin_0 = const()[name = string("slice_by_index_61_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_61_end_0 = const()[name = string("slice_by_index_61_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_61_end_mask_0 = const()[name = string("slice_by_index_61_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 32, 22]> slice_by_index_61 = slice_by_index(begin = slice_by_index_61_begin_0, end = slice_by_index_61_end_0, end_mask = slice_by_index_61_end_mask_0, x = mul_746)[name = string("slice_by_index_61")];
            int32 concat_30_axis_0 = const()[name = string("concat_30_axis_0"), val = int32(-1)];
            bool concat_30_interleave_0 = const()[name = string("concat_30_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 32, 44]> concat_30 = concat(axis = concat_30_axis_0, interleave = concat_30_interleave_0, values = (slice_by_index_61, slice_by_index_60))[name = string("concat_30")];
            tensor<fp16, [44]> mul_747_y_0 = const()[name = string("mul_747_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 32, 44]> mul_747 = mul(x = concat_30, y = mul_747_y_0)[name = string("mul_747")];
            tensor<fp16, [8, 32, 44]> mul_748 = mul(x = mul_746, y = mul_11_y_0)[name = string("mul_748")];
            tensor<fp16, [8, 32, 44]> mul_749 = mul(x = mul_747, y = mul_12_y_0)[name = string("mul_749")];
            tensor<fp16, [8, 32, 44]> add_90 = add(x = mul_748, y = mul_749)[name = string("add_90")];
            tensor<fp16, [2, 32, 44]> transpose_61 = transpose(perm = transpose_61_perm_0, x = reshape_123)[name = string("transpose_2")];
            tensor<fp16, [2, 32, 44]> mul_750 = mul(x = transpose_61, y = transpose_61)[name = string("mul_750")];
            tensor<int32, [1]> reduce_mean_161_axes_0 = const()[name = string("reduce_mean_161_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_161_keep_dims_0 = const()[name = string("reduce_mean_161_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 32, 1]> reduce_mean_161 = reduce_mean(axes = reduce_mean_161_axes_0, keep_dims = reduce_mean_161_keep_dims_0, x = mul_750)[name = string("reduce_mean_161")];
            fp32 rsqrt_161_epsilon_0 = const()[name = string("rsqrt_161_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 32, 1]> rsqrt_161 = rsqrt(epsilon = rsqrt_161_epsilon_0, x = reduce_mean_161)[name = string("rsqrt_161")];
            tensor<fp16, [2, 32, 44]> mul_751 = mul(x = transpose_61, y = rsqrt_161)[name = string("mul_751")];
            tensor<fp16, [44]> mul_752_y_0 = const()[name = string("mul_752_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7880576)))];
            tensor<fp16, [2, 32, 44]> mul_752 = mul(x = mul_751, y = mul_752_y_0)[name = string("mul_752")];
            tensor<int32, [3]> slice_by_index_62_begin_0 = const()[name = string("slice_by_index_62_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_62_end_0 = const()[name = string("slice_by_index_62_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_62_end_mask_0 = const()[name = string("slice_by_index_62_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 32, 22]> slice_by_index_62 = slice_by_index(begin = slice_by_index_62_begin_0, end = slice_by_index_62_end_0, end_mask = slice_by_index_62_end_mask_0, x = mul_752)[name = string("slice_by_index_62")];
            tensor<int32, [3]> slice_by_index_63_begin_0 = const()[name = string("slice_by_index_63_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_63_end_0 = const()[name = string("slice_by_index_63_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_63_end_mask_0 = const()[name = string("slice_by_index_63_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 32, 22]> slice_by_index_63 = slice_by_index(begin = slice_by_index_63_begin_0, end = slice_by_index_63_end_0, end_mask = slice_by_index_63_end_mask_0, x = mul_752)[name = string("slice_by_index_63")];
            int32 concat_31_axis_0 = const()[name = string("concat_31_axis_0"), val = int32(-1)];
            bool concat_31_interleave_0 = const()[name = string("concat_31_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 32, 44]> concat_31 = concat(axis = concat_31_axis_0, interleave = concat_31_interleave_0, values = (slice_by_index_63, slice_by_index_62))[name = string("concat_31")];
            tensor<fp16, [44]> mul_753_y_0 = const()[name = string("mul_753_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 32, 44]> mul_753 = mul(x = concat_31, y = mul_753_y_0)[name = string("mul_753")];
            tensor<fp16, [2, 32, 44]> mul_754 = mul(x = mul_752, y = mul_11_y_0)[name = string("mul_754")];
            tensor<fp16, [2, 32, 44]> mul_755 = mul(x = mul_753, y = mul_12_y_0)[name = string("mul_755")];
            tensor<fp16, [2, 32, 44]> add_91 = add(x = mul_754, y = mul_755)[name = string("add_91")];
            tensor<int32, [4]> reshape_125_shape_0 = const()[name = string("reshape_125_shape_0"), val = tensor<int32, [4]>([2, 1, 32, 44])];
            tensor<fp16, [2, 1, 32, 44]> reshape_125 = reshape(shape = reshape_125_shape_0, x = add_91)[name = string("reshape_125")];
            tensor<int32, [4]> tile_30_reps_0 = const()[name = string("tile_30_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 32, 44]> tile_30 = tile(reps = tile_30_reps_0, x = reshape_125)[name = string("tile_30")];
            tensor<int32, [3]> reshape_126_shape_0 = const()[name = string("reshape_126_shape_0"), val = tensor<int32, [3]>([8, 32, 44])];
            tensor<fp16, [8, 32, 44]> reshape_126 = reshape(shape = reshape_126_shape_0, x = tile_30)[name = string("reshape_126")];
            tensor<int32, [4]> reshape_127_shape_0 = const()[name = string("reshape_127_shape_0"), val = tensor<int32, [4]>([2, 1, 32, 44])];
            tensor<fp16, [2, 32, 44]> transpose_62 = transpose(perm = transpose_62_perm_0, x = reshape_124)[name = string("transpose_1")];
            tensor<fp16, [2, 1, 32, 44]> reshape_127 = reshape(shape = reshape_127_shape_0, x = transpose_62)[name = string("reshape_127")];
            tensor<int32, [4]> tile_31_reps_0 = const()[name = string("tile_31_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 32, 44]> tile_31 = tile(reps = tile_31_reps_0, x = reshape_127)[name = string("tile_31")];
            tensor<int32, [3]> reshape_128_shape_0 = const()[name = string("reshape_128_shape_0"), val = tensor<int32, [3]>([8, 32, 44])];
            tensor<fp16, [8, 32, 44]> reshape_128 = reshape(shape = reshape_128_shape_0, x = tile_31)[name = string("reshape_128")];
            fp16 mul_756_y_0 = const()[name = string("mul_756_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 32, 44]> mul_756 = mul(x = add_90, y = mul_756_y_0)[name = string("mul_756")];
            bool matmul_30_transpose_y_0 = const()[name = string("matmul_30_transpose_y_0"), val = bool(true)];
            bool matmul_30_transpose_x_0 = const()[name = string("matmul_30_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 32, 32]> matmul_30 = matmul(transpose_x = matmul_30_transpose_x_0, transpose_y = matmul_30_transpose_y_0, x = mul_756, y = reshape_126)[name = string("matmul_30")];
            tensor<fp16, [8, 32, 32]> add_92 = add(x = matmul_30, y = reshape_1)[name = string("add_92")];
            int32 softmax_15_axis_0 = const()[name = string("softmax_15_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 32, 32]> softmax_15 = softmax(axis = softmax_15_axis_0, x = add_92)[name = string("softmax_15")];
            bool matmul_31_transpose_x_0 = const()[name = string("matmul_31_transpose_x_0"), val = bool(false)];
            bool matmul_31_transpose_y_0 = const()[name = string("matmul_31_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 32, 44]> matmul_31 = matmul(transpose_x = matmul_31_transpose_x_0, transpose_y = matmul_31_transpose_y_0, x = softmax_15, y = reshape_128)[name = string("matmul_31")];
            tensor<int32, [3]> transpose_63_perm_0 = const()[name = string("transpose_63_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_129_shape_0 = const()[name = string("reshape_129_shape_0"), val = tensor<int32, [2]>([32, 352])];
            tensor<fp16, [32, 8, 44]> transpose_63 = transpose(perm = transpose_63_perm_0, x = matmul_31)[name = string("transpose_0")];
            tensor<fp16, [32, 352]> reshape_129 = reshape(shape = reshape_129_shape_0, x = transpose_63)[name = string("reshape_129")];
            tensor<fp16, [352, 352]> linear_10_weight_0 = const()[name = string("linear_10_weight_0"), val = tensor<fp16, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7880768)))];
            tensor<fp16, [32, 352]> linear_10 = linear(bias = linear_0_bias_0, weight = linear_10_weight_0, x = reshape_129)[name = string("linear_10")];
            tensor<fp16, [32, 352]> add_93 = add(x = add_89, y = linear_10)[name = string("add_93")];
            tensor<fp16, [32, 352]> mul_757 = mul(x = add_93, y = add_93)[name = string("mul_757")];
            tensor<int32, [1]> reduce_mean_162_axes_0 = const()[name = string("reduce_mean_162_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_162_keep_dims_0 = const()[name = string("reduce_mean_162_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_162 = reduce_mean(axes = reduce_mean_162_axes_0, keep_dims = reduce_mean_162_keep_dims_0, x = mul_757)[name = string("reduce_mean_162")];
            fp32 rsqrt_162_epsilon_0 = const()[name = string("rsqrt_162_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_162 = rsqrt(epsilon = rsqrt_162_epsilon_0, x = reduce_mean_162)[name = string("rsqrt_162")];
            tensor<fp16, [32, 352]> mul_758 = mul(x = add_93, y = rsqrt_162)[name = string("mul_758")];
            tensor<fp16, [352]> mul_759_y_0 = const()[name = string("mul_759_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8128640)))];
            tensor<fp16, [32, 352]> mul_759 = mul(x = mul_758, y = mul_759_y_0)[name = string("mul_759")];
            tensor<fp16, [960, 352]> linear_11_weight_0 = const()[name = string("linear_11_weight_0"), val = tensor<fp16, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8129408)))];
            tensor<fp16, [32, 960]> linear_11 = linear(bias = linear_4_bias_0, weight = linear_11_weight_0, x = mul_759)[name = string("linear_11")];
            tensor<fp16, [960, 352]> linear_12_weight_0 = const()[name = string("linear_12_weight_0"), val = tensor<fp16, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8805312)))];
            tensor<fp16, [32, 960]> linear_12 = linear(bias = linear_4_bias_0, weight = linear_12_weight_0, x = mul_759)[name = string("linear_12")];
            fp16 mul_760_y_0 = const()[name = string("mul_760_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [32, 960]> mul_760 = mul(x = linear_11, y = mul_760_y_0)[name = string("mul_760")];
            tensor<fp16, [32, 960]> tanh_15 = tanh(x = mul_760)[name = string("tanh_15")];
            fp16 mul_761_x_0 = const()[name = string("mul_761_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [32, 960]> mul_761 = mul(x = mul_761_x_0, y = tanh_15)[name = string("mul_761")];
            fp16 add_94_x_0 = const()[name = string("add_94_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [32, 960]> add_94 = add(x = add_94_x_0, y = mul_761)[name = string("add_94")];
            tensor<fp16, [32, 960]> mul_762 = mul(x = linear_11, y = add_94)[name = string("mul_762")];
            tensor<fp16, [32, 960]> mul_763 = mul(x = mul_762, y = linear_12)[name = string("mul_763")];
            tensor<fp16, [352, 960]> linear_13_weight_0 = const()[name = string("linear_13_weight_0"), val = tensor<fp16, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9481216)))];
            tensor<fp16, [32, 352]> linear_13 = linear(bias = linear_0_bias_0, weight = linear_13_weight_0, x = mul_763)[name = string("linear_13")];
            tensor<fp16, [32, 352]> add_95 = add(x = add_93, y = linear_13)[name = string("add_95")];
            tensor<fp16, [32, 352]> mul_764 = mul(x = add_95, y = add_95)[name = string("mul_764")];
            tensor<int32, [1]> reduce_mean_163_axes_0 = const()[name = string("reduce_mean_163_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_163_keep_dims_0 = const()[name = string("reduce_mean_163_keep_dims_0"), val = bool(true)];
            tensor<fp16, [32, 1]> reduce_mean_163 = reduce_mean(axes = reduce_mean_163_axes_0, keep_dims = reduce_mean_163_keep_dims_0, x = mul_764)[name = string("reduce_mean_163")];
            fp32 rsqrt_163_epsilon_0 = const()[name = string("rsqrt_163_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [32, 1]> rsqrt_163 = rsqrt(epsilon = rsqrt_163_epsilon_0, x = reduce_mean_163)[name = string("rsqrt_163")];
            tensor<fp16, [32, 352]> mul_765 = mul(x = add_95, y = rsqrt_163)[name = string("mul_765")];
            tensor<fp16, [352]> mul_766_y_0 = const()[name = string("mul_766_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10157120)))];
            tensor<fp16, [32, 352]> mul_766 = mul(x = mul_765, y = mul_766_y_0)[name = string("mul_766")];
            tensor<fp16, [8342, 352]> linear_14_weight_0 = const()[name = string("linear_14_weight_0"), val = tensor<fp16, [8342, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10157888)))];
            tensor<fp16, [8342]> linear_14_bias_0 = const()[name = string("linear_14_bias_0"), val = tensor<fp16, [8342]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16030720)))];
            tensor<fp16, [32, 8342]> linear_14 = linear(bias = linear_14_bias_0, weight = linear_14_weight_0, x = mul_766)[name = string("linear_14")];
            tensor<int32, [3]> logits_shape_0 = const()[name = string("logits_shape_0"), val = tensor<int32, [3]>([1, 32, 8342])];
            tensor<fp16, [1, 32, 8342]> logits = reshape(shape = logits_shape_0, x = linear_14)[name = string("logits")];
        } -> (logits);
    func L64<ios18>(tensor<fp16, [1, 64, 352]> ids, tensor<fp16, [1, 64]> mask) {
            tensor<int32, [2]> reshape_0_shape_0 = const()[name = string("reshape_0_shape_0"), val = tensor<int32, [2]>([64, 352])];
            tensor<fp16, [64, 352]> reshape_0 = reshape(shape = reshape_0_shape_0, x = ids)[name = string("reshape_0")];
            tensor<fp16, [64, 352]> mul_0 = mul(x = reshape_0, y = reshape_0)[name = string("mul_0")];
            tensor<int32, [1]> reduce_mean_0_axes_0 = const()[name = string("reduce_mean_0_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_0_keep_dims_0 = const()[name = string("reduce_mean_0_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_0 = reduce_mean(axes = reduce_mean_0_axes_0, keep_dims = reduce_mean_0_keep_dims_0, x = mul_0)[name = string("reduce_mean_0")];
            fp32 rsqrt_0_epsilon_0 = const()[name = string("rsqrt_0_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_0 = rsqrt(epsilon = rsqrt_0_epsilon_0, x = reduce_mean_0)[name = string("rsqrt_0")];
            tensor<fp16, [64, 352]> mul_1 = mul(x = reshape_0, y = rsqrt_0)[name = string("mul_1")];
            tensor<fp16, [352]> mul_2_y_0 = const()[name = string("mul_2_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(64)))];
            tensor<fp16, [64, 352]> mul_2 = mul(x = mul_1, y = mul_2_y_0)[name = string("mul_2")];
            fp16 sub_0_y_0 = const()[name = string("sub_0_y_0"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 64]> sub_0 = sub(x = mask, y = sub_0_y_0)[name = string("sub_0")];
            fp16 mul_3_y_0 = const()[name = string("mul_3_y_0"), val = fp16(0x1.388p+13)];
            tensor<fp16, [1, 64]> mul_3 = mul(x = sub_0, y = mul_3_y_0)[name = string("mul_3")];
            tensor<int32, [3]> reshape_1_shape_0 = const()[name = string("reshape_1_shape_0"), val = tensor<int32, [3]>([1, 1, 64])];
            tensor<fp16, [1, 1, 64]> reshape_1 = reshape(shape = reshape_1_shape_0, x = mul_3)[name = string("reshape_1")];
            tensor<fp16, [64, 352]> mul_4 = mul(x = mul_2, y = mul_2)[name = string("mul_4")];
            tensor<int32, [1]> reduce_mean_1_axes_0 = const()[name = string("reduce_mean_1_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_1_keep_dims_0 = const()[name = string("reduce_mean_1_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_1 = reduce_mean(axes = reduce_mean_1_axes_0, keep_dims = reduce_mean_1_keep_dims_0, x = mul_4)[name = string("reduce_mean_1")];
            fp32 rsqrt_1_epsilon_0 = const()[name = string("rsqrt_1_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_1 = rsqrt(epsilon = rsqrt_1_epsilon_0, x = reduce_mean_1)[name = string("rsqrt_1")];
            tensor<fp16, [64, 352]> mul_5 = mul(x = mul_2, y = rsqrt_1)[name = string("mul_5")];
            tensor<fp16, [352]> mul_6_y_0 = const()[name = string("mul_6_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(832)))];
            tensor<fp16, [64, 352]> mul_6 = mul(x = mul_5, y = mul_6_y_0)[name = string("mul_6")];
            tensor<fp16, [352, 352]> linear_0_weight_0 = const()[name = string("linear_0_weight_0"), val = tensor<fp16, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1600)))];
            tensor<fp16, [352]> linear_0_bias_0 = const()[name = string("linear_0_bias_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(249472)))];
            tensor<fp16, [64, 352]> linear_0 = linear(bias = linear_0_bias_0, weight = linear_0_weight_0, x = mul_6)[name = string("linear_0")];
            tensor<int32, [3]> reshape_2_shape_0 = const()[name = string("reshape_2_shape_0"), val = tensor<int32, [3]>([64, 8, 44])];
            tensor<fp16, [64, 8, 44]> reshape_2 = reshape(shape = reshape_2_shape_0, x = linear_0)[name = string("reshape_2")];
            tensor<int32, [3]> transpose_0_perm_0 = const()[name = string("transpose_0_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [88, 352]> linear_1_weight_0 = const()[name = string("linear_1_weight_0"), val = tensor<fp16, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(250240)))];
            tensor<fp16, [88]> linear_1_bias_0 = const()[name = string("linear_1_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [64, 88]> linear_1 = linear(bias = linear_1_bias_0, weight = linear_1_weight_0, x = mul_6)[name = string("linear_1")];
            tensor<int32, [3]> reshape_3_shape_0 = const()[name = string("reshape_3_shape_0"), val = tensor<int32, [3]>([64, 2, 44])];
            tensor<fp16, [64, 2, 44]> reshape_3 = reshape(shape = reshape_3_shape_0, x = linear_1)[name = string("reshape_3")];
            tensor<int32, [3]> transpose_1_perm_0 = const()[name = string("transpose_1_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [88, 352]> linear_2_weight_0 = const()[name = string("linear_2_weight_0"), val = tensor<fp16, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312512)))];
            tensor<fp16, [88]> linear_2_bias_0 = const()[name = string("linear_2_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [64, 88]> linear_2 = linear(bias = linear_2_bias_0, weight = linear_2_weight_0, x = mul_6)[name = string("linear_2")];
            tensor<int32, [3]> reshape_4_shape_0 = const()[name = string("reshape_4_shape_0"), val = tensor<int32, [3]>([64, 2, 44])];
            tensor<fp16, [64, 2, 44]> reshape_4 = reshape(shape = reshape_4_shape_0, x = linear_2)[name = string("reshape_4")];
            tensor<int32, [3]> transpose_2_perm_0 = const()[name = string("transpose_2_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 64, 44]> transpose_0 = transpose(perm = transpose_0_perm_0, x = reshape_2)[name = string("transpose_63")];
            tensor<fp16, [8, 64, 44]> mul_7 = mul(x = transpose_0, y = transpose_0)[name = string("mul_7")];
            tensor<int32, [1]> reduce_mean_2_axes_0 = const()[name = string("reduce_mean_2_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_2_keep_dims_0 = const()[name = string("reduce_mean_2_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 64, 1]> reduce_mean_2 = reduce_mean(axes = reduce_mean_2_axes_0, keep_dims = reduce_mean_2_keep_dims_0, x = mul_7)[name = string("reduce_mean_2")];
            fp32 rsqrt_2_epsilon_0 = const()[name = string("rsqrt_2_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 64, 1]> rsqrt_2 = rsqrt(epsilon = rsqrt_2_epsilon_0, x = reduce_mean_2)[name = string("rsqrt_2")];
            tensor<fp16, [8, 64, 44]> mul_8 = mul(x = transpose_0, y = rsqrt_2)[name = string("mul_8")];
            tensor<fp16, [44]> mul_9_y_0 = const()[name = string("mul_9_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374528)))];
            tensor<fp16, [8, 64, 44]> mul_9 = mul(x = mul_8, y = mul_9_y_0)[name = string("mul_9")];
            tensor<int32, [3]> slice_by_index_0_begin_0 = const()[name = string("slice_by_index_0_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_0_end_0 = const()[name = string("slice_by_index_0_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_0_end_mask_0 = const()[name = string("slice_by_index_0_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 64, 22]> slice_by_index_0 = slice_by_index(begin = slice_by_index_0_begin_0, end = slice_by_index_0_end_0, end_mask = slice_by_index_0_end_mask_0, x = mul_9)[name = string("slice_by_index_0")];
            tensor<int32, [3]> slice_by_index_1_begin_0 = const()[name = string("slice_by_index_1_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_1_end_0 = const()[name = string("slice_by_index_1_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_1_end_mask_0 = const()[name = string("slice_by_index_1_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 64, 22]> slice_by_index_1 = slice_by_index(begin = slice_by_index_1_begin_0, end = slice_by_index_1_end_0, end_mask = slice_by_index_1_end_mask_0, x = mul_9)[name = string("slice_by_index_1")];
            int32 concat_0_axis_0 = const()[name = string("concat_0_axis_0"), val = int32(-1)];
            bool concat_0_interleave_0 = const()[name = string("concat_0_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 64, 44]> concat_0 = concat(axis = concat_0_axis_0, interleave = concat_0_interleave_0, values = (slice_by_index_1, slice_by_index_0))[name = string("concat_0")];
            tensor<fp16, [44]> mul_10_y_0 = const()[name = string("mul_10_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 64, 44]> mul_10 = mul(x = concat_0, y = mul_10_y_0)[name = string("mul_10")];
            tensor<fp16, [1, 64, 44]> mul_11_y_0 = const()[name = string("mul_11_y_0"), val = tensor<fp16, [1, 64, 44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16056192)))];
            tensor<fp16, [8, 64, 44]> mul_11 = mul(x = mul_9, y = mul_11_y_0)[name = string("mul_11")];
            tensor<fp16, [1, 64, 44]> mul_12_y_0 = const()[name = string("mul_12_y_0"), val = tensor<fp16, [1, 64, 44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16061888)))];
            tensor<fp16, [8, 64, 44]> mul_12 = mul(x = mul_10, y = mul_12_y_0)[name = string("mul_12")];
            tensor<fp16, [8, 64, 44]> add_0 = add(x = mul_11, y = mul_12)[name = string("add_0")];
            tensor<fp16, [2, 64, 44]> transpose_1 = transpose(perm = transpose_1_perm_0, x = reshape_3)[name = string("transpose_62")];
            tensor<fp16, [2, 64, 44]> mul_13 = mul(x = transpose_1, y = transpose_1)[name = string("mul_13")];
            tensor<int32, [1]> reduce_mean_3_axes_0 = const()[name = string("reduce_mean_3_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_3_keep_dims_0 = const()[name = string("reduce_mean_3_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 64, 1]> reduce_mean_3 = reduce_mean(axes = reduce_mean_3_axes_0, keep_dims = reduce_mean_3_keep_dims_0, x = mul_13)[name = string("reduce_mean_3")];
            fp32 rsqrt_3_epsilon_0 = const()[name = string("rsqrt_3_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 64, 1]> rsqrt_3 = rsqrt(epsilon = rsqrt_3_epsilon_0, x = reduce_mean_3)[name = string("rsqrt_3")];
            tensor<fp16, [2, 64, 44]> mul_14 = mul(x = transpose_1, y = rsqrt_3)[name = string("mul_14")];
            tensor<fp16, [44]> mul_15_y_0 = const()[name = string("mul_15_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(376448)))];
            tensor<fp16, [2, 64, 44]> mul_15 = mul(x = mul_14, y = mul_15_y_0)[name = string("mul_15")];
            tensor<int32, [3]> slice_by_index_2_begin_0 = const()[name = string("slice_by_index_2_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_2_end_0 = const()[name = string("slice_by_index_2_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_2_end_mask_0 = const()[name = string("slice_by_index_2_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 64, 22]> slice_by_index_2 = slice_by_index(begin = slice_by_index_2_begin_0, end = slice_by_index_2_end_0, end_mask = slice_by_index_2_end_mask_0, x = mul_15)[name = string("slice_by_index_2")];
            tensor<int32, [3]> slice_by_index_3_begin_0 = const()[name = string("slice_by_index_3_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_3_end_0 = const()[name = string("slice_by_index_3_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_3_end_mask_0 = const()[name = string("slice_by_index_3_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 64, 22]> slice_by_index_3 = slice_by_index(begin = slice_by_index_3_begin_0, end = slice_by_index_3_end_0, end_mask = slice_by_index_3_end_mask_0, x = mul_15)[name = string("slice_by_index_3")];
            int32 concat_1_axis_0 = const()[name = string("concat_1_axis_0"), val = int32(-1)];
            bool concat_1_interleave_0 = const()[name = string("concat_1_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 64, 44]> concat_1 = concat(axis = concat_1_axis_0, interleave = concat_1_interleave_0, values = (slice_by_index_3, slice_by_index_2))[name = string("concat_1")];
            tensor<fp16, [44]> mul_16_y_0 = const()[name = string("mul_16_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 64, 44]> mul_16 = mul(x = concat_1, y = mul_16_y_0)[name = string("mul_16")];
            tensor<fp16, [2, 64, 44]> mul_17 = mul(x = mul_15, y = mul_11_y_0)[name = string("mul_17")];
            tensor<fp16, [2, 64, 44]> mul_18 = mul(x = mul_16, y = mul_12_y_0)[name = string("mul_18")];
            tensor<fp16, [2, 64, 44]> add_1 = add(x = mul_17, y = mul_18)[name = string("add_1")];
            tensor<int32, [4]> reshape_5_shape_0 = const()[name = string("reshape_5_shape_0"), val = tensor<int32, [4]>([2, 1, 64, 44])];
            tensor<fp16, [2, 1, 64, 44]> reshape_5 = reshape(shape = reshape_5_shape_0, x = add_1)[name = string("reshape_5")];
            tensor<int32, [4]> tile_0_reps_0 = const()[name = string("tile_0_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 64, 44]> tile_0 = tile(reps = tile_0_reps_0, x = reshape_5)[name = string("tile_0")];
            tensor<int32, [3]> reshape_6_shape_0 = const()[name = string("reshape_6_shape_0"), val = tensor<int32, [3]>([8, 64, 44])];
            tensor<fp16, [8, 64, 44]> reshape_6 = reshape(shape = reshape_6_shape_0, x = tile_0)[name = string("reshape_6")];
            tensor<int32, [4]> reshape_7_shape_0 = const()[name = string("reshape_7_shape_0"), val = tensor<int32, [4]>([2, 1, 64, 44])];
            tensor<fp16, [2, 64, 44]> transpose_2 = transpose(perm = transpose_2_perm_0, x = reshape_4)[name = string("transpose_61")];
            tensor<fp16, [2, 1, 64, 44]> reshape_7 = reshape(shape = reshape_7_shape_0, x = transpose_2)[name = string("reshape_7")];
            tensor<int32, [4]> tile_1_reps_0 = const()[name = string("tile_1_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 64, 44]> tile_1 = tile(reps = tile_1_reps_0, x = reshape_7)[name = string("tile_1")];
            tensor<int32, [3]> reshape_8_shape_0 = const()[name = string("reshape_8_shape_0"), val = tensor<int32, [3]>([8, 64, 44])];
            tensor<fp16, [8, 64, 44]> reshape_8 = reshape(shape = reshape_8_shape_0, x = tile_1)[name = string("reshape_8")];
            fp16 mul_19_y_0 = const()[name = string("mul_19_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 64, 44]> mul_19 = mul(x = add_0, y = mul_19_y_0)[name = string("mul_19")];
            bool matmul_0_transpose_y_0 = const()[name = string("matmul_0_transpose_y_0"), val = bool(true)];
            bool matmul_0_transpose_x_0 = const()[name = string("matmul_0_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 64, 64]> matmul_0 = matmul(transpose_x = matmul_0_transpose_x_0, transpose_y = matmul_0_transpose_y_0, x = mul_19, y = reshape_6)[name = string("matmul_0")];
            tensor<fp16, [8, 64, 64]> add_2 = add(x = matmul_0, y = reshape_1)[name = string("add_2")];
            int32 softmax_0_axis_0 = const()[name = string("softmax_0_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 64, 64]> softmax_0 = softmax(axis = softmax_0_axis_0, x = add_2)[name = string("softmax_0")];
            bool matmul_1_transpose_x_0 = const()[name = string("matmul_1_transpose_x_0"), val = bool(false)];
            bool matmul_1_transpose_y_0 = const()[name = string("matmul_1_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 64, 44]> matmul_1 = matmul(transpose_x = matmul_1_transpose_x_0, transpose_y = matmul_1_transpose_y_0, x = softmax_0, y = reshape_8)[name = string("matmul_1")];
            tensor<int32, [3]> transpose_3_perm_0 = const()[name = string("transpose_3_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_9_shape_0 = const()[name = string("reshape_9_shape_0"), val = tensor<int32, [2]>([64, 352])];
            tensor<fp16, [64, 8, 44]> transpose_3 = transpose(perm = transpose_3_perm_0, x = matmul_1)[name = string("transpose_60")];
            tensor<fp16, [64, 352]> reshape_9 = reshape(shape = reshape_9_shape_0, x = transpose_3)[name = string("reshape_9")];
            tensor<fp16, [352, 352]> linear_3_weight_0 = const()[name = string("linear_3_weight_0"), val = tensor<fp16, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(376640)))];
            tensor<fp16, [64, 352]> linear_3 = linear(bias = linear_0_bias_0, weight = linear_3_weight_0, x = reshape_9)[name = string("linear_3")];
            tensor<fp16, [64, 352]> add_3 = add(x = mul_2, y = linear_3)[name = string("add_3")];
            tensor<fp16, [64, 352]> mul_20 = mul(x = add_3, y = add_3)[name = string("mul_20")];
            tensor<int32, [1]> reduce_mean_4_axes_0 = const()[name = string("reduce_mean_4_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_4_keep_dims_0 = const()[name = string("reduce_mean_4_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_4 = reduce_mean(axes = reduce_mean_4_axes_0, keep_dims = reduce_mean_4_keep_dims_0, x = mul_20)[name = string("reduce_mean_4")];
            fp32 rsqrt_4_epsilon_0 = const()[name = string("rsqrt_4_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_4 = rsqrt(epsilon = rsqrt_4_epsilon_0, x = reduce_mean_4)[name = string("rsqrt_4")];
            tensor<fp16, [64, 352]> mul_21 = mul(x = add_3, y = rsqrt_4)[name = string("mul_21")];
            tensor<fp16, [352]> mul_22_y_0 = const()[name = string("mul_22_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(624512)))];
            tensor<fp16, [64, 352]> mul_22 = mul(x = mul_21, y = mul_22_y_0)[name = string("mul_22")];
            tensor<fp16, [960, 352]> linear_4_weight_0 = const()[name = string("linear_4_weight_0"), val = tensor<fp16, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(625280)))];
            tensor<fp16, [960]> linear_4_bias_0 = const()[name = string("linear_4_bias_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1301184)))];
            tensor<fp16, [64, 960]> linear_4 = linear(bias = linear_4_bias_0, weight = linear_4_weight_0, x = mul_22)[name = string("linear_4")];
            tensor<fp16, [960, 352]> linear_5_weight_0 = const()[name = string("linear_5_weight_0"), val = tensor<fp16, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1303168)))];
            tensor<fp16, [64, 960]> linear_5 = linear(bias = linear_4_bias_0, weight = linear_5_weight_0, x = mul_22)[name = string("linear_5")];
            fp16 mul_23_y_0 = const()[name = string("mul_23_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [64, 960]> mul_23 = mul(x = linear_4, y = mul_23_y_0)[name = string("mul_23")];
            tensor<fp16, [64, 960]> tanh_0 = tanh(x = mul_23)[name = string("tanh_0")];
            fp16 mul_24_x_0 = const()[name = string("mul_24_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [64, 960]> mul_24 = mul(x = mul_24_x_0, y = tanh_0)[name = string("mul_24")];
            fp16 add_4_x_0 = const()[name = string("add_4_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [64, 960]> add_4 = add(x = add_4_x_0, y = mul_24)[name = string("add_4")];
            tensor<fp16, [64, 960]> mul_25 = mul(x = linear_4, y = add_4)[name = string("mul_25")];
            tensor<fp16, [64, 960]> mul_26 = mul(x = mul_25, y = linear_5)[name = string("mul_26")];
            tensor<fp16, [352, 960]> linear_6_weight_0 = const()[name = string("linear_6_weight_0"), val = tensor<fp16, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1979072)))];
            tensor<fp16, [64, 352]> linear_6 = linear(bias = linear_0_bias_0, weight = linear_6_weight_0, x = mul_26)[name = string("linear_6")];
            tensor<fp16, [64, 352]> add_5 = add(x = add_3, y = linear_6)[name = string("add_5")];
            tensor<fp16, [64, 352]> mul_27 = mul(x = add_5, y = add_5)[name = string("mul_27")];
            tensor<int32, [1]> reduce_mean_5_axes_0 = const()[name = string("reduce_mean_5_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_5_keep_dims_0 = const()[name = string("reduce_mean_5_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_5 = reduce_mean(axes = reduce_mean_5_axes_0, keep_dims = reduce_mean_5_keep_dims_0, x = mul_27)[name = string("reduce_mean_5")];
            fp32 rsqrt_5_epsilon_0 = const()[name = string("rsqrt_5_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_5 = rsqrt(epsilon = rsqrt_5_epsilon_0, x = reduce_mean_5)[name = string("rsqrt_5")];
            tensor<fp16, [64, 352]> mul_28 = mul(x = add_5, y = rsqrt_5)[name = string("mul_28")];
            tensor<fp16, [352]> mul_29_y_0 = const()[name = string("mul_29_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2654976)))];
            tensor<fp16, [64, 352]> mul_29 = mul(x = mul_28, y = mul_29_y_0)[name = string("mul_29")];
            tensor<fp16, [64, 352]> mul_30 = mul(x = mul_29, y = mul_29)[name = string("mul_30")];
            tensor<int32, [1]> reduce_mean_6_axes_0 = const()[name = string("reduce_mean_6_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_6_keep_dims_0 = const()[name = string("reduce_mean_6_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_6 = reduce_mean(axes = reduce_mean_6_axes_0, keep_dims = reduce_mean_6_keep_dims_0, x = mul_30)[name = string("reduce_mean_6")];
            fp32 rsqrt_6_epsilon_0 = const()[name = string("rsqrt_6_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_6 = rsqrt(epsilon = rsqrt_6_epsilon_0, x = reduce_mean_6)[name = string("rsqrt_6")];
            tensor<fp16, [64, 352]> mul_31 = mul(x = mul_29, y = rsqrt_6)[name = string("mul_31")];
            tensor<fp16, [352]> mul_32_y_0 = const()[name = string("mul_32_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2655744)))];
            tensor<fp16, [64, 352]> mul_32 = mul(x = mul_31, y = mul_32_y_0)[name = string("mul_32")];
            tensor<fp16, [352, 352]> tern_1_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2656512))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_1_q_weight_0_palettized")];
            tensor<fp16, [64, 352]> tern_1_q = linear(bias = linear_0_bias_0, weight = tern_1_q_weight_0_palettized, x = mul_32)[name = string("tern_1_q")];
            tensor<fp16, [352]> mul_33_y_0 = const()[name = string("mul_33_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2687552)))];
            tensor<fp16, [64, 352]> mul_33 = mul(x = tern_1_q, y = mul_33_y_0)[name = string("mul_33")];
            tensor<int32, [3]> reshape_10_shape_0 = const()[name = string("reshape_10_shape_0"), val = tensor<int32, [3]>([64, 8, 44])];
            tensor<fp16, [64, 8, 44]> reshape_10 = reshape(shape = reshape_10_shape_0, x = mul_33)[name = string("reshape_10")];
            tensor<int32, [3]> transpose_4_perm_0 = const()[name = string("transpose_4_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_36_y_0 = const()[name = string("mul_36_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2688320)))];
            tensor<fp16, [64, 352]> mul_36 = mul(x = mul_31, y = mul_36_y_0)[name = string("mul_36")];
            tensor<fp16, [88, 352]> tern_1_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2689088))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_1_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_1_k_bias_0 = const()[name = string("tern_1_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [64, 88]> tern_1_k = linear(bias = tern_1_k_bias_0, weight = tern_1_k_weight_0_palettized, x = mul_36)[name = string("tern_1_k")];
            tensor<fp16, [88]> mul_37_y_0 = const()[name = string("mul_37_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2696896)))];
            tensor<fp16, [64, 88]> mul_37 = mul(x = tern_1_k, y = mul_37_y_0)[name = string("mul_37")];
            tensor<int32, [3]> reshape_11_shape_0 = const()[name = string("reshape_11_shape_0"), val = tensor<int32, [3]>([64, 2, 44])];
            tensor<fp16, [64, 2, 44]> reshape_11 = reshape(shape = reshape_11_shape_0, x = mul_37)[name = string("reshape_11")];
            tensor<int32, [3]> transpose_5_perm_0 = const()[name = string("transpose_5_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_40_y_0 = const()[name = string("mul_40_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2697152)))];
            tensor<fp16, [64, 352]> mul_40 = mul(x = mul_31, y = mul_40_y_0)[name = string("mul_40")];
            tensor<fp16, [88, 352]> tern_1_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2697920))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_1_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_1_v_bias_0 = const()[name = string("tern_1_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [64, 88]> tern_1_v = linear(bias = tern_1_v_bias_0, weight = tern_1_v_weight_0_palettized, x = mul_40)[name = string("tern_1_v")];
            tensor<fp16, [88]> mul_41_y_0 = const()[name = string("mul_41_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2705728)))];
            tensor<fp16, [64, 88]> mul_41 = mul(x = tern_1_v, y = mul_41_y_0)[name = string("mul_41")];
            tensor<int32, [3]> reshape_12_shape_0 = const()[name = string("reshape_12_shape_0"), val = tensor<int32, [3]>([64, 2, 44])];
            tensor<fp16, [64, 2, 44]> reshape_12 = reshape(shape = reshape_12_shape_0, x = mul_41)[name = string("reshape_12")];
            tensor<int32, [3]> transpose_6_perm_0 = const()[name = string("transpose_6_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 64, 44]> transpose_4 = transpose(perm = transpose_4_perm_0, x = reshape_10)[name = string("transpose_59")];
            tensor<fp16, [8, 64, 44]> mul_42 = mul(x = transpose_4, y = transpose_4)[name = string("mul_42")];
            tensor<int32, [1]> reduce_mean_9_axes_0 = const()[name = string("reduce_mean_9_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_9_keep_dims_0 = const()[name = string("reduce_mean_9_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 64, 1]> reduce_mean_9 = reduce_mean(axes = reduce_mean_9_axes_0, keep_dims = reduce_mean_9_keep_dims_0, x = mul_42)[name = string("reduce_mean_9")];
            fp32 rsqrt_9_epsilon_0 = const()[name = string("rsqrt_9_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 64, 1]> rsqrt_9 = rsqrt(epsilon = rsqrt_9_epsilon_0, x = reduce_mean_9)[name = string("rsqrt_9")];
            tensor<fp16, [8, 64, 44]> mul_43 = mul(x = transpose_4, y = rsqrt_9)[name = string("mul_43")];
            tensor<fp16, [44]> mul_44_y_0 = const()[name = string("mul_44_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2705984)))];
            tensor<fp16, [8, 64, 44]> mul_44 = mul(x = mul_43, y = mul_44_y_0)[name = string("mul_44")];
            tensor<int32, [3]> slice_by_index_4_begin_0 = const()[name = string("slice_by_index_4_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_4_end_0 = const()[name = string("slice_by_index_4_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_4_end_mask_0 = const()[name = string("slice_by_index_4_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 64, 22]> slice_by_index_4 = slice_by_index(begin = slice_by_index_4_begin_0, end = slice_by_index_4_end_0, end_mask = slice_by_index_4_end_mask_0, x = mul_44)[name = string("slice_by_index_4")];
            tensor<int32, [3]> slice_by_index_5_begin_0 = const()[name = string("slice_by_index_5_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_5_end_0 = const()[name = string("slice_by_index_5_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_5_end_mask_0 = const()[name = string("slice_by_index_5_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 64, 22]> slice_by_index_5 = slice_by_index(begin = slice_by_index_5_begin_0, end = slice_by_index_5_end_0, end_mask = slice_by_index_5_end_mask_0, x = mul_44)[name = string("slice_by_index_5")];
            int32 concat_2_axis_0 = const()[name = string("concat_2_axis_0"), val = int32(-1)];
            bool concat_2_interleave_0 = const()[name = string("concat_2_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 64, 44]> concat_2 = concat(axis = concat_2_axis_0, interleave = concat_2_interleave_0, values = (slice_by_index_5, slice_by_index_4))[name = string("concat_2")];
            tensor<fp16, [44]> mul_45_y_0 = const()[name = string("mul_45_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 64, 44]> mul_45 = mul(x = concat_2, y = mul_45_y_0)[name = string("mul_45")];
            tensor<fp16, [8, 64, 44]> mul_46 = mul(x = mul_44, y = mul_11_y_0)[name = string("mul_46")];
            tensor<fp16, [8, 64, 44]> mul_47 = mul(x = mul_45, y = mul_12_y_0)[name = string("mul_47")];
            tensor<fp16, [8, 64, 44]> add_6 = add(x = mul_46, y = mul_47)[name = string("add_6")];
            tensor<fp16, [2, 64, 44]> transpose_5 = transpose(perm = transpose_5_perm_0, x = reshape_11)[name = string("transpose_58")];
            tensor<fp16, [2, 64, 44]> mul_48 = mul(x = transpose_5, y = transpose_5)[name = string("mul_48")];
            tensor<int32, [1]> reduce_mean_10_axes_0 = const()[name = string("reduce_mean_10_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_10_keep_dims_0 = const()[name = string("reduce_mean_10_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 64, 1]> reduce_mean_10 = reduce_mean(axes = reduce_mean_10_axes_0, keep_dims = reduce_mean_10_keep_dims_0, x = mul_48)[name = string("reduce_mean_10")];
            fp32 rsqrt_10_epsilon_0 = const()[name = string("rsqrt_10_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 64, 1]> rsqrt_10 = rsqrt(epsilon = rsqrt_10_epsilon_0, x = reduce_mean_10)[name = string("rsqrt_10")];
            tensor<fp16, [2, 64, 44]> mul_49 = mul(x = transpose_5, y = rsqrt_10)[name = string("mul_49")];
            tensor<fp16, [44]> mul_50_y_0 = const()[name = string("mul_50_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2706176)))];
            tensor<fp16, [2, 64, 44]> mul_50 = mul(x = mul_49, y = mul_50_y_0)[name = string("mul_50")];
            tensor<int32, [3]> slice_by_index_6_begin_0 = const()[name = string("slice_by_index_6_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_6_end_0 = const()[name = string("slice_by_index_6_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_6_end_mask_0 = const()[name = string("slice_by_index_6_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 64, 22]> slice_by_index_6 = slice_by_index(begin = slice_by_index_6_begin_0, end = slice_by_index_6_end_0, end_mask = slice_by_index_6_end_mask_0, x = mul_50)[name = string("slice_by_index_6")];
            tensor<int32, [3]> slice_by_index_7_begin_0 = const()[name = string("slice_by_index_7_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_7_end_0 = const()[name = string("slice_by_index_7_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_7_end_mask_0 = const()[name = string("slice_by_index_7_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 64, 22]> slice_by_index_7 = slice_by_index(begin = slice_by_index_7_begin_0, end = slice_by_index_7_end_0, end_mask = slice_by_index_7_end_mask_0, x = mul_50)[name = string("slice_by_index_7")];
            int32 concat_3_axis_0 = const()[name = string("concat_3_axis_0"), val = int32(-1)];
            bool concat_3_interleave_0 = const()[name = string("concat_3_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 64, 44]> concat_3 = concat(axis = concat_3_axis_0, interleave = concat_3_interleave_0, values = (slice_by_index_7, slice_by_index_6))[name = string("concat_3")];
            tensor<fp16, [44]> mul_51_y_0 = const()[name = string("mul_51_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 64, 44]> mul_51 = mul(x = concat_3, y = mul_51_y_0)[name = string("mul_51")];
            tensor<fp16, [2, 64, 44]> mul_52 = mul(x = mul_50, y = mul_11_y_0)[name = string("mul_52")];
            tensor<fp16, [2, 64, 44]> mul_53 = mul(x = mul_51, y = mul_12_y_0)[name = string("mul_53")];
            tensor<fp16, [2, 64, 44]> add_7 = add(x = mul_52, y = mul_53)[name = string("add_7")];
            tensor<int32, [4]> reshape_13_shape_0 = const()[name = string("reshape_13_shape_0"), val = tensor<int32, [4]>([2, 1, 64, 44])];
            tensor<fp16, [2, 1, 64, 44]> reshape_13 = reshape(shape = reshape_13_shape_0, x = add_7)[name = string("reshape_13")];
            tensor<int32, [4]> tile_2_reps_0 = const()[name = string("tile_2_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 64, 44]> tile_2 = tile(reps = tile_2_reps_0, x = reshape_13)[name = string("tile_2")];
            tensor<int32, [3]> reshape_14_shape_0 = const()[name = string("reshape_14_shape_0"), val = tensor<int32, [3]>([8, 64, 44])];
            tensor<fp16, [8, 64, 44]> reshape_14 = reshape(shape = reshape_14_shape_0, x = tile_2)[name = string("reshape_14")];
            tensor<int32, [4]> reshape_15_shape_0 = const()[name = string("reshape_15_shape_0"), val = tensor<int32, [4]>([2, 1, 64, 44])];
            tensor<fp16, [2, 64, 44]> transpose_6 = transpose(perm = transpose_6_perm_0, x = reshape_12)[name = string("transpose_57")];
            tensor<fp16, [2, 1, 64, 44]> reshape_15 = reshape(shape = reshape_15_shape_0, x = transpose_6)[name = string("reshape_15")];
            tensor<int32, [4]> tile_3_reps_0 = const()[name = string("tile_3_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 64, 44]> tile_3 = tile(reps = tile_3_reps_0, x = reshape_15)[name = string("tile_3")];
            tensor<int32, [3]> reshape_16_shape_0 = const()[name = string("reshape_16_shape_0"), val = tensor<int32, [3]>([8, 64, 44])];
            tensor<fp16, [8, 64, 44]> reshape_16 = reshape(shape = reshape_16_shape_0, x = tile_3)[name = string("reshape_16")];
            fp16 mul_54_y_0 = const()[name = string("mul_54_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 64, 44]> mul_54 = mul(x = add_6, y = mul_54_y_0)[name = string("mul_54")];
            bool matmul_2_transpose_y_0 = const()[name = string("matmul_2_transpose_y_0"), val = bool(true)];
            bool matmul_2_transpose_x_0 = const()[name = string("matmul_2_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 64, 64]> matmul_2 = matmul(transpose_x = matmul_2_transpose_x_0, transpose_y = matmul_2_transpose_y_0, x = mul_54, y = reshape_14)[name = string("matmul_2")];
            tensor<fp16, [8, 64, 64]> add_8 = add(x = matmul_2, y = reshape_1)[name = string("add_8")];
            int32 softmax_1_axis_0 = const()[name = string("softmax_1_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 64, 64]> softmax_1 = softmax(axis = softmax_1_axis_0, x = add_8)[name = string("softmax_1")];
            bool matmul_3_transpose_x_0 = const()[name = string("matmul_3_transpose_x_0"), val = bool(false)];
            bool matmul_3_transpose_y_0 = const()[name = string("matmul_3_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 64, 44]> matmul_3 = matmul(transpose_x = matmul_3_transpose_x_0, transpose_y = matmul_3_transpose_y_0, x = softmax_1, y = reshape_16)[name = string("matmul_3")];
            tensor<int32, [3]> transpose_7_perm_0 = const()[name = string("transpose_7_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_17_shape_0 = const()[name = string("reshape_17_shape_0"), val = tensor<int32, [2]>([64, 352])];
            tensor<fp16, [64, 8, 44]> transpose_7 = transpose(perm = transpose_7_perm_0, x = matmul_3)[name = string("transpose_56")];
            tensor<fp16, [64, 352]> reshape_17 = reshape(shape = reshape_17_shape_0, x = transpose_7)[name = string("reshape_17")];
            tensor<fp16, [64, 352]> mul_55 = mul(x = reshape_17, y = reshape_17)[name = string("mul_55")];
            tensor<int32, [1]> reduce_mean_11_axes_0 = const()[name = string("reduce_mean_11_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_11_keep_dims_0 = const()[name = string("reduce_mean_11_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_11 = reduce_mean(axes = reduce_mean_11_axes_0, keep_dims = reduce_mean_11_keep_dims_0, x = mul_55)[name = string("reduce_mean_11")];
            fp32 rsqrt_11_epsilon_0 = const()[name = string("rsqrt_11_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_11 = rsqrt(epsilon = rsqrt_11_epsilon_0, x = reduce_mean_11)[name = string("rsqrt_11")];
            tensor<fp16, [64, 352]> mul_56 = mul(x = reshape_17, y = rsqrt_11)[name = string("mul_56")];
            tensor<fp16, [352]> mul_57_y_0 = const()[name = string("mul_57_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2706368)))];
            tensor<fp16, [64, 352]> mul_57 = mul(x = mul_56, y = mul_57_y_0)[name = string("mul_57")];
            tensor<fp16, [352, 352]> tern_1_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2707136))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_1_o_weight_0_palettized")];
            tensor<fp16, [64, 352]> tern_1_o = linear(bias = linear_0_bias_0, weight = tern_1_o_weight_0_palettized, x = mul_57)[name = string("tern_1_o")];
            tensor<fp16, [352]> mul_58_y_0 = const()[name = string("mul_58_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2738176)))];
            tensor<fp16, [64, 352]> mul_58 = mul(x = tern_1_o, y = mul_58_y_0)[name = string("mul_58")];
            tensor<fp16, [64, 352]> add_9 = add(x = add_5, y = mul_58)[name = string("add_9")];
            tensor<fp16, [64, 352]> mul_59 = mul(x = add_9, y = add_9)[name = string("mul_59")];
            tensor<int32, [1]> reduce_mean_12_axes_0 = const()[name = string("reduce_mean_12_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_12_keep_dims_0 = const()[name = string("reduce_mean_12_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_12 = reduce_mean(axes = reduce_mean_12_axes_0, keep_dims = reduce_mean_12_keep_dims_0, x = mul_59)[name = string("reduce_mean_12")];
            fp32 rsqrt_12_epsilon_0 = const()[name = string("rsqrt_12_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_12 = rsqrt(epsilon = rsqrt_12_epsilon_0, x = reduce_mean_12)[name = string("rsqrt_12")];
            tensor<fp16, [64, 352]> mul_60 = mul(x = add_9, y = rsqrt_12)[name = string("mul_60")];
            tensor<fp16, [352]> mul_61_y_0 = const()[name = string("mul_61_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2738944)))];
            tensor<fp16, [64, 352]> mul_61 = mul(x = mul_60, y = mul_61_y_0)[name = string("mul_61")];
            tensor<fp16, [64, 352]> mul_62 = mul(x = mul_61, y = mul_61)[name = string("mul_62")];
            tensor<int32, [1]> reduce_mean_13_axes_0 = const()[name = string("reduce_mean_13_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_13_keep_dims_0 = const()[name = string("reduce_mean_13_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_13 = reduce_mean(axes = reduce_mean_13_axes_0, keep_dims = reduce_mean_13_keep_dims_0, x = mul_62)[name = string("reduce_mean_13")];
            fp32 rsqrt_13_epsilon_0 = const()[name = string("rsqrt_13_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_13 = rsqrt(epsilon = rsqrt_13_epsilon_0, x = reduce_mean_13)[name = string("rsqrt_13")];
            tensor<fp16, [64, 352]> mul_63 = mul(x = mul_61, y = rsqrt_13)[name = string("mul_63")];
            tensor<fp16, [352]> mul_64_y_0 = const()[name = string("mul_64_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2739712)))];
            tensor<fp16, [64, 352]> mul_64 = mul(x = mul_63, y = mul_64_y_0)[name = string("mul_64")];
            tensor<fp16, [960, 352]> tern_1_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2740480))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_1_w1_weight_0_palettized")];
            tensor<fp16, [64, 960]> tern_1_w1 = linear(bias = linear_4_bias_0, weight = tern_1_w1_weight_0_palettized, x = mul_64)[name = string("tern_1_w1")];
            tensor<fp16, [960]> mul_65_y_0 = const()[name = string("mul_65_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2825024)))];
            tensor<fp16, [64, 960]> mul_65 = mul(x = tern_1_w1, y = mul_65_y_0)[name = string("mul_65")];
            tensor<fp16, [352]> mul_68_y_0 = const()[name = string("mul_68_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2827008)))];
            tensor<fp16, [64, 352]> mul_68 = mul(x = mul_63, y = mul_68_y_0)[name = string("mul_68")];
            tensor<fp16, [960, 352]> tern_1_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2827776))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_1_w3_weight_0_palettized")];
            tensor<fp16, [64, 960]> tern_1_w3 = linear(bias = linear_4_bias_0, weight = tern_1_w3_weight_0_palettized, x = mul_68)[name = string("tern_1_w3")];
            tensor<fp16, [960]> mul_69_y_0 = const()[name = string("mul_69_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2912320)))];
            tensor<fp16, [64, 960]> mul_69 = mul(x = tern_1_w3, y = mul_69_y_0)[name = string("mul_69")];
            fp16 mul_70_y_0 = const()[name = string("mul_70_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [64, 960]> mul_70 = mul(x = mul_65, y = mul_70_y_0)[name = string("mul_70")];
            tensor<fp16, [64, 960]> tanh_1 = tanh(x = mul_70)[name = string("tanh_1")];
            fp16 mul_71_x_0 = const()[name = string("mul_71_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [64, 960]> mul_71 = mul(x = mul_71_x_0, y = tanh_1)[name = string("mul_71")];
            fp16 add_10_x_0 = const()[name = string("add_10_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [64, 960]> add_10 = add(x = add_10_x_0, y = mul_71)[name = string("add_10")];
            tensor<fp16, [64, 960]> mul_72 = mul(x = mul_65, y = add_10)[name = string("mul_72")];
            tensor<fp16, [64, 960]> mul_73 = mul(x = mul_72, y = mul_69)[name = string("mul_73")];
            tensor<fp16, [64, 960]> mul_74 = mul(x = mul_73, y = mul_73)[name = string("mul_74")];
            tensor<int32, [1]> reduce_mean_15_axes_0 = const()[name = string("reduce_mean_15_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_15_keep_dims_0 = const()[name = string("reduce_mean_15_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_15 = reduce_mean(axes = reduce_mean_15_axes_0, keep_dims = reduce_mean_15_keep_dims_0, x = mul_74)[name = string("reduce_mean_15")];
            fp32 rsqrt_15_epsilon_0 = const()[name = string("rsqrt_15_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_15 = rsqrt(epsilon = rsqrt_15_epsilon_0, x = reduce_mean_15)[name = string("rsqrt_15")];
            tensor<fp16, [64, 960]> mul_75 = mul(x = mul_73, y = rsqrt_15)[name = string("mul_75")];
            tensor<fp16, [960]> mul_76_y_0 = const()[name = string("mul_76_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2914304)))];
            tensor<fp16, [64, 960]> mul_76 = mul(x = mul_75, y = mul_76_y_0)[name = string("mul_76")];
            tensor<fp16, [352, 960]> tern_1_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2916288))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_1_w2_weight_0_palettized")];
            tensor<fp16, [64, 352]> tern_1_w2 = linear(bias = linear_0_bias_0, weight = tern_1_w2_weight_0_palettized, x = mul_76)[name = string("tern_1_w2")];
            tensor<fp16, [352]> mul_77_y_0 = const()[name = string("mul_77_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3000832)))];
            tensor<fp16, [64, 352]> mul_77 = mul(x = tern_1_w2, y = mul_77_y_0)[name = string("mul_77")];
            tensor<fp16, [64, 352]> add_11 = add(x = add_9, y = mul_77)[name = string("add_11")];
            tensor<fp16, [64, 352]> mul_78 = mul(x = add_11, y = add_11)[name = string("mul_78")];
            tensor<int32, [1]> reduce_mean_16_axes_0 = const()[name = string("reduce_mean_16_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_16_keep_dims_0 = const()[name = string("reduce_mean_16_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_16 = reduce_mean(axes = reduce_mean_16_axes_0, keep_dims = reduce_mean_16_keep_dims_0, x = mul_78)[name = string("reduce_mean_16")];
            fp32 rsqrt_16_epsilon_0 = const()[name = string("rsqrt_16_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_16 = rsqrt(epsilon = rsqrt_16_epsilon_0, x = reduce_mean_16)[name = string("rsqrt_16")];
            tensor<fp16, [64, 352]> mul_79 = mul(x = add_11, y = rsqrt_16)[name = string("mul_79")];
            tensor<fp16, [352]> mul_80_y_0 = const()[name = string("mul_80_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3001600)))];
            tensor<fp16, [64, 352]> mul_80 = mul(x = mul_79, y = mul_80_y_0)[name = string("mul_80")];
            tensor<fp16, [64, 352]> mul_81 = mul(x = mul_80, y = mul_80)[name = string("mul_81")];
            tensor<int32, [1]> reduce_mean_17_axes_0 = const()[name = string("reduce_mean_17_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_17_keep_dims_0 = const()[name = string("reduce_mean_17_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_17 = reduce_mean(axes = reduce_mean_17_axes_0, keep_dims = reduce_mean_17_keep_dims_0, x = mul_81)[name = string("reduce_mean_17")];
            fp32 rsqrt_17_epsilon_0 = const()[name = string("rsqrt_17_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_17 = rsqrt(epsilon = rsqrt_17_epsilon_0, x = reduce_mean_17)[name = string("rsqrt_17")];
            tensor<fp16, [64, 352]> mul_82 = mul(x = mul_80, y = rsqrt_17)[name = string("mul_82")];
            tensor<fp16, [352]> mul_83_y_0 = const()[name = string("mul_83_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3002368)))];
            tensor<fp16, [64, 352]> mul_83 = mul(x = mul_82, y = mul_83_y_0)[name = string("mul_83")];
            tensor<fp16, [352, 352]> tern_2_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3003136))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_2_q_weight_0_palettized")];
            tensor<fp16, [64, 352]> tern_2_q = linear(bias = linear_0_bias_0, weight = tern_2_q_weight_0_palettized, x = mul_83)[name = string("tern_2_q")];
            tensor<fp16, [352]> mul_84_y_0 = const()[name = string("mul_84_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3034176)))];
            tensor<fp16, [64, 352]> mul_84 = mul(x = tern_2_q, y = mul_84_y_0)[name = string("mul_84")];
            tensor<int32, [3]> reshape_18_shape_0 = const()[name = string("reshape_18_shape_0"), val = tensor<int32, [3]>([64, 8, 44])];
            tensor<fp16, [64, 8, 44]> reshape_18 = reshape(shape = reshape_18_shape_0, x = mul_84)[name = string("reshape_18")];
            tensor<int32, [3]> transpose_8_perm_0 = const()[name = string("transpose_8_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_87_y_0 = const()[name = string("mul_87_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3034944)))];
            tensor<fp16, [64, 352]> mul_87 = mul(x = mul_82, y = mul_87_y_0)[name = string("mul_87")];
            tensor<fp16, [88, 352]> tern_2_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3035712))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_2_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_2_k_bias_0 = const()[name = string("tern_2_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [64, 88]> tern_2_k = linear(bias = tern_2_k_bias_0, weight = tern_2_k_weight_0_palettized, x = mul_87)[name = string("tern_2_k")];
            tensor<fp16, [88]> mul_88_y_0 = const()[name = string("mul_88_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3043520)))];
            tensor<fp16, [64, 88]> mul_88 = mul(x = tern_2_k, y = mul_88_y_0)[name = string("mul_88")];
            tensor<int32, [3]> reshape_19_shape_0 = const()[name = string("reshape_19_shape_0"), val = tensor<int32, [3]>([64, 2, 44])];
            tensor<fp16, [64, 2, 44]> reshape_19 = reshape(shape = reshape_19_shape_0, x = mul_88)[name = string("reshape_19")];
            tensor<int32, [3]> transpose_9_perm_0 = const()[name = string("transpose_9_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_91_y_0 = const()[name = string("mul_91_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3043776)))];
            tensor<fp16, [64, 352]> mul_91 = mul(x = mul_82, y = mul_91_y_0)[name = string("mul_91")];
            tensor<fp16, [88, 352]> tern_2_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3044544))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_2_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_2_v_bias_0 = const()[name = string("tern_2_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [64, 88]> tern_2_v = linear(bias = tern_2_v_bias_0, weight = tern_2_v_weight_0_palettized, x = mul_91)[name = string("tern_2_v")];
            tensor<fp16, [88]> mul_92_y_0 = const()[name = string("mul_92_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3052352)))];
            tensor<fp16, [64, 88]> mul_92 = mul(x = tern_2_v, y = mul_92_y_0)[name = string("mul_92")];
            tensor<int32, [3]> reshape_20_shape_0 = const()[name = string("reshape_20_shape_0"), val = tensor<int32, [3]>([64, 2, 44])];
            tensor<fp16, [64, 2, 44]> reshape_20 = reshape(shape = reshape_20_shape_0, x = mul_92)[name = string("reshape_20")];
            tensor<int32, [3]> transpose_10_perm_0 = const()[name = string("transpose_10_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 64, 44]> transpose_8 = transpose(perm = transpose_8_perm_0, x = reshape_18)[name = string("transpose_55")];
            tensor<fp16, [8, 64, 44]> mul_93 = mul(x = transpose_8, y = transpose_8)[name = string("mul_93")];
            tensor<int32, [1]> reduce_mean_20_axes_0 = const()[name = string("reduce_mean_20_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_20_keep_dims_0 = const()[name = string("reduce_mean_20_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 64, 1]> reduce_mean_20 = reduce_mean(axes = reduce_mean_20_axes_0, keep_dims = reduce_mean_20_keep_dims_0, x = mul_93)[name = string("reduce_mean_20")];
            fp32 rsqrt_20_epsilon_0 = const()[name = string("rsqrt_20_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 64, 1]> rsqrt_20 = rsqrt(epsilon = rsqrt_20_epsilon_0, x = reduce_mean_20)[name = string("rsqrt_20")];
            tensor<fp16, [8, 64, 44]> mul_94 = mul(x = transpose_8, y = rsqrt_20)[name = string("mul_94")];
            tensor<fp16, [44]> mul_95_y_0 = const()[name = string("mul_95_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3052608)))];
            tensor<fp16, [8, 64, 44]> mul_95 = mul(x = mul_94, y = mul_95_y_0)[name = string("mul_95")];
            tensor<int32, [3]> slice_by_index_8_begin_0 = const()[name = string("slice_by_index_8_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_8_end_0 = const()[name = string("slice_by_index_8_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_8_end_mask_0 = const()[name = string("slice_by_index_8_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 64, 22]> slice_by_index_8 = slice_by_index(begin = slice_by_index_8_begin_0, end = slice_by_index_8_end_0, end_mask = slice_by_index_8_end_mask_0, x = mul_95)[name = string("slice_by_index_8")];
            tensor<int32, [3]> slice_by_index_9_begin_0 = const()[name = string("slice_by_index_9_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_9_end_0 = const()[name = string("slice_by_index_9_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_9_end_mask_0 = const()[name = string("slice_by_index_9_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 64, 22]> slice_by_index_9 = slice_by_index(begin = slice_by_index_9_begin_0, end = slice_by_index_9_end_0, end_mask = slice_by_index_9_end_mask_0, x = mul_95)[name = string("slice_by_index_9")];
            int32 concat_4_axis_0 = const()[name = string("concat_4_axis_0"), val = int32(-1)];
            bool concat_4_interleave_0 = const()[name = string("concat_4_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 64, 44]> concat_4 = concat(axis = concat_4_axis_0, interleave = concat_4_interleave_0, values = (slice_by_index_9, slice_by_index_8))[name = string("concat_4")];
            tensor<fp16, [44]> mul_96_y_0 = const()[name = string("mul_96_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 64, 44]> mul_96 = mul(x = concat_4, y = mul_96_y_0)[name = string("mul_96")];
            tensor<fp16, [8, 64, 44]> mul_97 = mul(x = mul_95, y = mul_11_y_0)[name = string("mul_97")];
            tensor<fp16, [8, 64, 44]> mul_98 = mul(x = mul_96, y = mul_12_y_0)[name = string("mul_98")];
            tensor<fp16, [8, 64, 44]> add_12 = add(x = mul_97, y = mul_98)[name = string("add_12")];
            tensor<fp16, [2, 64, 44]> transpose_9 = transpose(perm = transpose_9_perm_0, x = reshape_19)[name = string("transpose_54")];
            tensor<fp16, [2, 64, 44]> mul_99 = mul(x = transpose_9, y = transpose_9)[name = string("mul_99")];
            tensor<int32, [1]> reduce_mean_21_axes_0 = const()[name = string("reduce_mean_21_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_21_keep_dims_0 = const()[name = string("reduce_mean_21_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 64, 1]> reduce_mean_21 = reduce_mean(axes = reduce_mean_21_axes_0, keep_dims = reduce_mean_21_keep_dims_0, x = mul_99)[name = string("reduce_mean_21")];
            fp32 rsqrt_21_epsilon_0 = const()[name = string("rsqrt_21_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 64, 1]> rsqrt_21 = rsqrt(epsilon = rsqrt_21_epsilon_0, x = reduce_mean_21)[name = string("rsqrt_21")];
            tensor<fp16, [2, 64, 44]> mul_100 = mul(x = transpose_9, y = rsqrt_21)[name = string("mul_100")];
            tensor<fp16, [44]> mul_101_y_0 = const()[name = string("mul_101_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3052800)))];
            tensor<fp16, [2, 64, 44]> mul_101 = mul(x = mul_100, y = mul_101_y_0)[name = string("mul_101")];
            tensor<int32, [3]> slice_by_index_10_begin_0 = const()[name = string("slice_by_index_10_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_10_end_0 = const()[name = string("slice_by_index_10_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_10_end_mask_0 = const()[name = string("slice_by_index_10_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 64, 22]> slice_by_index_10 = slice_by_index(begin = slice_by_index_10_begin_0, end = slice_by_index_10_end_0, end_mask = slice_by_index_10_end_mask_0, x = mul_101)[name = string("slice_by_index_10")];
            tensor<int32, [3]> slice_by_index_11_begin_0 = const()[name = string("slice_by_index_11_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_11_end_0 = const()[name = string("slice_by_index_11_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_11_end_mask_0 = const()[name = string("slice_by_index_11_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 64, 22]> slice_by_index_11 = slice_by_index(begin = slice_by_index_11_begin_0, end = slice_by_index_11_end_0, end_mask = slice_by_index_11_end_mask_0, x = mul_101)[name = string("slice_by_index_11")];
            int32 concat_5_axis_0 = const()[name = string("concat_5_axis_0"), val = int32(-1)];
            bool concat_5_interleave_0 = const()[name = string("concat_5_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 64, 44]> concat_5 = concat(axis = concat_5_axis_0, interleave = concat_5_interleave_0, values = (slice_by_index_11, slice_by_index_10))[name = string("concat_5")];
            tensor<fp16, [44]> mul_102_y_0 = const()[name = string("mul_102_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 64, 44]> mul_102 = mul(x = concat_5, y = mul_102_y_0)[name = string("mul_102")];
            tensor<fp16, [2, 64, 44]> mul_103 = mul(x = mul_101, y = mul_11_y_0)[name = string("mul_103")];
            tensor<fp16, [2, 64, 44]> mul_104 = mul(x = mul_102, y = mul_12_y_0)[name = string("mul_104")];
            tensor<fp16, [2, 64, 44]> add_13 = add(x = mul_103, y = mul_104)[name = string("add_13")];
            tensor<int32, [4]> reshape_21_shape_0 = const()[name = string("reshape_21_shape_0"), val = tensor<int32, [4]>([2, 1, 64, 44])];
            tensor<fp16, [2, 1, 64, 44]> reshape_21 = reshape(shape = reshape_21_shape_0, x = add_13)[name = string("reshape_21")];
            tensor<int32, [4]> tile_4_reps_0 = const()[name = string("tile_4_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 64, 44]> tile_4 = tile(reps = tile_4_reps_0, x = reshape_21)[name = string("tile_4")];
            tensor<int32, [3]> reshape_22_shape_0 = const()[name = string("reshape_22_shape_0"), val = tensor<int32, [3]>([8, 64, 44])];
            tensor<fp16, [8, 64, 44]> reshape_22 = reshape(shape = reshape_22_shape_0, x = tile_4)[name = string("reshape_22")];
            tensor<int32, [4]> reshape_23_shape_0 = const()[name = string("reshape_23_shape_0"), val = tensor<int32, [4]>([2, 1, 64, 44])];
            tensor<fp16, [2, 64, 44]> transpose_10 = transpose(perm = transpose_10_perm_0, x = reshape_20)[name = string("transpose_53")];
            tensor<fp16, [2, 1, 64, 44]> reshape_23 = reshape(shape = reshape_23_shape_0, x = transpose_10)[name = string("reshape_23")];
            tensor<int32, [4]> tile_5_reps_0 = const()[name = string("tile_5_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 64, 44]> tile_5 = tile(reps = tile_5_reps_0, x = reshape_23)[name = string("tile_5")];
            tensor<int32, [3]> reshape_24_shape_0 = const()[name = string("reshape_24_shape_0"), val = tensor<int32, [3]>([8, 64, 44])];
            tensor<fp16, [8, 64, 44]> reshape_24 = reshape(shape = reshape_24_shape_0, x = tile_5)[name = string("reshape_24")];
            fp16 mul_105_y_0 = const()[name = string("mul_105_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 64, 44]> mul_105 = mul(x = add_12, y = mul_105_y_0)[name = string("mul_105")];
            bool matmul_4_transpose_y_0 = const()[name = string("matmul_4_transpose_y_0"), val = bool(true)];
            bool matmul_4_transpose_x_0 = const()[name = string("matmul_4_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 64, 64]> matmul_4 = matmul(transpose_x = matmul_4_transpose_x_0, transpose_y = matmul_4_transpose_y_0, x = mul_105, y = reshape_22)[name = string("matmul_4")];
            tensor<fp16, [8, 64, 64]> add_14 = add(x = matmul_4, y = reshape_1)[name = string("add_14")];
            int32 softmax_2_axis_0 = const()[name = string("softmax_2_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 64, 64]> softmax_2 = softmax(axis = softmax_2_axis_0, x = add_14)[name = string("softmax_2")];
            bool matmul_5_transpose_x_0 = const()[name = string("matmul_5_transpose_x_0"), val = bool(false)];
            bool matmul_5_transpose_y_0 = const()[name = string("matmul_5_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 64, 44]> matmul_5 = matmul(transpose_x = matmul_5_transpose_x_0, transpose_y = matmul_5_transpose_y_0, x = softmax_2, y = reshape_24)[name = string("matmul_5")];
            tensor<int32, [3]> transpose_11_perm_0 = const()[name = string("transpose_11_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_25_shape_0 = const()[name = string("reshape_25_shape_0"), val = tensor<int32, [2]>([64, 352])];
            tensor<fp16, [64, 8, 44]> transpose_11 = transpose(perm = transpose_11_perm_0, x = matmul_5)[name = string("transpose_52")];
            tensor<fp16, [64, 352]> reshape_25 = reshape(shape = reshape_25_shape_0, x = transpose_11)[name = string("reshape_25")];
            tensor<fp16, [64, 352]> mul_106 = mul(x = reshape_25, y = reshape_25)[name = string("mul_106")];
            tensor<int32, [1]> reduce_mean_22_axes_0 = const()[name = string("reduce_mean_22_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_22_keep_dims_0 = const()[name = string("reduce_mean_22_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_22 = reduce_mean(axes = reduce_mean_22_axes_0, keep_dims = reduce_mean_22_keep_dims_0, x = mul_106)[name = string("reduce_mean_22")];
            fp32 rsqrt_22_epsilon_0 = const()[name = string("rsqrt_22_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_22 = rsqrt(epsilon = rsqrt_22_epsilon_0, x = reduce_mean_22)[name = string("rsqrt_22")];
            tensor<fp16, [64, 352]> mul_107 = mul(x = reshape_25, y = rsqrt_22)[name = string("mul_107")];
            tensor<fp16, [352]> mul_108_y_0 = const()[name = string("mul_108_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3052992)))];
            tensor<fp16, [64, 352]> mul_108 = mul(x = mul_107, y = mul_108_y_0)[name = string("mul_108")];
            tensor<fp16, [352, 352]> tern_2_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3053760))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_2_o_weight_0_palettized")];
            tensor<fp16, [64, 352]> tern_2_o = linear(bias = linear_0_bias_0, weight = tern_2_o_weight_0_palettized, x = mul_108)[name = string("tern_2_o")];
            tensor<fp16, [352]> mul_109_y_0 = const()[name = string("mul_109_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3084800)))];
            tensor<fp16, [64, 352]> mul_109 = mul(x = tern_2_o, y = mul_109_y_0)[name = string("mul_109")];
            tensor<fp16, [64, 352]> add_15 = add(x = add_11, y = mul_109)[name = string("add_15")];
            tensor<fp16, [64, 352]> mul_110 = mul(x = add_15, y = add_15)[name = string("mul_110")];
            tensor<int32, [1]> reduce_mean_23_axes_0 = const()[name = string("reduce_mean_23_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_23_keep_dims_0 = const()[name = string("reduce_mean_23_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_23 = reduce_mean(axes = reduce_mean_23_axes_0, keep_dims = reduce_mean_23_keep_dims_0, x = mul_110)[name = string("reduce_mean_23")];
            fp32 rsqrt_23_epsilon_0 = const()[name = string("rsqrt_23_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_23 = rsqrt(epsilon = rsqrt_23_epsilon_0, x = reduce_mean_23)[name = string("rsqrt_23")];
            tensor<fp16, [64, 352]> mul_111 = mul(x = add_15, y = rsqrt_23)[name = string("mul_111")];
            tensor<fp16, [352]> mul_112_y_0 = const()[name = string("mul_112_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3085568)))];
            tensor<fp16, [64, 352]> mul_112 = mul(x = mul_111, y = mul_112_y_0)[name = string("mul_112")];
            tensor<fp16, [64, 352]> mul_113 = mul(x = mul_112, y = mul_112)[name = string("mul_113")];
            tensor<int32, [1]> reduce_mean_24_axes_0 = const()[name = string("reduce_mean_24_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_24_keep_dims_0 = const()[name = string("reduce_mean_24_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_24 = reduce_mean(axes = reduce_mean_24_axes_0, keep_dims = reduce_mean_24_keep_dims_0, x = mul_113)[name = string("reduce_mean_24")];
            fp32 rsqrt_24_epsilon_0 = const()[name = string("rsqrt_24_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_24 = rsqrt(epsilon = rsqrt_24_epsilon_0, x = reduce_mean_24)[name = string("rsqrt_24")];
            tensor<fp16, [64, 352]> mul_114 = mul(x = mul_112, y = rsqrt_24)[name = string("mul_114")];
            tensor<fp16, [352]> mul_115_y_0 = const()[name = string("mul_115_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3086336)))];
            tensor<fp16, [64, 352]> mul_115 = mul(x = mul_114, y = mul_115_y_0)[name = string("mul_115")];
            tensor<fp16, [960, 352]> tern_2_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3087104))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_2_w1_weight_0_palettized")];
            tensor<fp16, [64, 960]> tern_2_w1 = linear(bias = linear_4_bias_0, weight = tern_2_w1_weight_0_palettized, x = mul_115)[name = string("tern_2_w1")];
            tensor<fp16, [960]> mul_116_y_0 = const()[name = string("mul_116_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3171648)))];
            tensor<fp16, [64, 960]> mul_116 = mul(x = tern_2_w1, y = mul_116_y_0)[name = string("mul_116")];
            tensor<fp16, [352]> mul_119_y_0 = const()[name = string("mul_119_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3173632)))];
            tensor<fp16, [64, 352]> mul_119 = mul(x = mul_114, y = mul_119_y_0)[name = string("mul_119")];
            tensor<fp16, [960, 352]> tern_2_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3174400))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_2_w3_weight_0_palettized")];
            tensor<fp16, [64, 960]> tern_2_w3 = linear(bias = linear_4_bias_0, weight = tern_2_w3_weight_0_palettized, x = mul_119)[name = string("tern_2_w3")];
            tensor<fp16, [960]> mul_120_y_0 = const()[name = string("mul_120_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3258944)))];
            tensor<fp16, [64, 960]> mul_120 = mul(x = tern_2_w3, y = mul_120_y_0)[name = string("mul_120")];
            fp16 mul_121_y_0 = const()[name = string("mul_121_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [64, 960]> mul_121 = mul(x = mul_116, y = mul_121_y_0)[name = string("mul_121")];
            tensor<fp16, [64, 960]> tanh_2 = tanh(x = mul_121)[name = string("tanh_2")];
            fp16 mul_122_x_0 = const()[name = string("mul_122_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [64, 960]> mul_122 = mul(x = mul_122_x_0, y = tanh_2)[name = string("mul_122")];
            fp16 add_16_x_0 = const()[name = string("add_16_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [64, 960]> add_16 = add(x = add_16_x_0, y = mul_122)[name = string("add_16")];
            tensor<fp16, [64, 960]> mul_123 = mul(x = mul_116, y = add_16)[name = string("mul_123")];
            tensor<fp16, [64, 960]> mul_124 = mul(x = mul_123, y = mul_120)[name = string("mul_124")];
            tensor<fp16, [64, 960]> mul_125 = mul(x = mul_124, y = mul_124)[name = string("mul_125")];
            tensor<int32, [1]> reduce_mean_26_axes_0 = const()[name = string("reduce_mean_26_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_26_keep_dims_0 = const()[name = string("reduce_mean_26_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_26 = reduce_mean(axes = reduce_mean_26_axes_0, keep_dims = reduce_mean_26_keep_dims_0, x = mul_125)[name = string("reduce_mean_26")];
            fp32 rsqrt_26_epsilon_0 = const()[name = string("rsqrt_26_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_26 = rsqrt(epsilon = rsqrt_26_epsilon_0, x = reduce_mean_26)[name = string("rsqrt_26")];
            tensor<fp16, [64, 960]> mul_126 = mul(x = mul_124, y = rsqrt_26)[name = string("mul_126")];
            tensor<fp16, [960]> mul_127_y_0 = const()[name = string("mul_127_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3260928)))];
            tensor<fp16, [64, 960]> mul_127 = mul(x = mul_126, y = mul_127_y_0)[name = string("mul_127")];
            tensor<fp16, [352, 960]> tern_2_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3262912))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_2_w2_weight_0_palettized")];
            tensor<fp16, [64, 352]> tern_2_w2 = linear(bias = linear_0_bias_0, weight = tern_2_w2_weight_0_palettized, x = mul_127)[name = string("tern_2_w2")];
            tensor<fp16, [352]> mul_128_y_0 = const()[name = string("mul_128_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3347456)))];
            tensor<fp16, [64, 352]> mul_128 = mul(x = tern_2_w2, y = mul_128_y_0)[name = string("mul_128")];
            tensor<fp16, [64, 352]> add_17 = add(x = add_15, y = mul_128)[name = string("add_17")];
            tensor<fp16, [64, 352]> mul_129 = mul(x = add_17, y = add_17)[name = string("mul_129")];
            tensor<int32, [1]> reduce_mean_27_axes_0 = const()[name = string("reduce_mean_27_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_27_keep_dims_0 = const()[name = string("reduce_mean_27_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_27 = reduce_mean(axes = reduce_mean_27_axes_0, keep_dims = reduce_mean_27_keep_dims_0, x = mul_129)[name = string("reduce_mean_27")];
            fp32 rsqrt_27_epsilon_0 = const()[name = string("rsqrt_27_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_27 = rsqrt(epsilon = rsqrt_27_epsilon_0, x = reduce_mean_27)[name = string("rsqrt_27")];
            tensor<fp16, [64, 352]> mul_130 = mul(x = add_17, y = rsqrt_27)[name = string("mul_130")];
            tensor<fp16, [352]> mul_131_y_0 = const()[name = string("mul_131_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3348224)))];
            tensor<fp16, [64, 352]> mul_131 = mul(x = mul_130, y = mul_131_y_0)[name = string("mul_131")];
            tensor<fp16, [64, 352]> mul_132 = mul(x = mul_131, y = mul_131)[name = string("mul_132")];
            tensor<int32, [1]> reduce_mean_28_axes_0 = const()[name = string("reduce_mean_28_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_28_keep_dims_0 = const()[name = string("reduce_mean_28_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_28 = reduce_mean(axes = reduce_mean_28_axes_0, keep_dims = reduce_mean_28_keep_dims_0, x = mul_132)[name = string("reduce_mean_28")];
            fp32 rsqrt_28_epsilon_0 = const()[name = string("rsqrt_28_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_28 = rsqrt(epsilon = rsqrt_28_epsilon_0, x = reduce_mean_28)[name = string("rsqrt_28")];
            tensor<fp16, [64, 352]> mul_133 = mul(x = mul_131, y = rsqrt_28)[name = string("mul_133")];
            tensor<fp16, [352]> mul_134_y_0 = const()[name = string("mul_134_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3348992)))];
            tensor<fp16, [64, 352]> mul_134 = mul(x = mul_133, y = mul_134_y_0)[name = string("mul_134")];
            tensor<fp16, [352, 352]> tern_3_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3349760))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_3_q_weight_0_palettized")];
            tensor<fp16, [64, 352]> tern_3_q = linear(bias = linear_0_bias_0, weight = tern_3_q_weight_0_palettized, x = mul_134)[name = string("tern_3_q")];
            tensor<fp16, [352]> mul_135_y_0 = const()[name = string("mul_135_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3380800)))];
            tensor<fp16, [64, 352]> mul_135 = mul(x = tern_3_q, y = mul_135_y_0)[name = string("mul_135")];
            tensor<int32, [3]> reshape_26_shape_0 = const()[name = string("reshape_26_shape_0"), val = tensor<int32, [3]>([64, 8, 44])];
            tensor<fp16, [64, 8, 44]> reshape_26 = reshape(shape = reshape_26_shape_0, x = mul_135)[name = string("reshape_26")];
            tensor<int32, [3]> transpose_12_perm_0 = const()[name = string("transpose_12_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_138_y_0 = const()[name = string("mul_138_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3381568)))];
            tensor<fp16, [64, 352]> mul_138 = mul(x = mul_133, y = mul_138_y_0)[name = string("mul_138")];
            tensor<fp16, [88, 352]> tern_3_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3382336))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_3_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_3_k_bias_0 = const()[name = string("tern_3_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [64, 88]> tern_3_k = linear(bias = tern_3_k_bias_0, weight = tern_3_k_weight_0_palettized, x = mul_138)[name = string("tern_3_k")];
            tensor<fp16, [88]> mul_139_y_0 = const()[name = string("mul_139_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3390144)))];
            tensor<fp16, [64, 88]> mul_139 = mul(x = tern_3_k, y = mul_139_y_0)[name = string("mul_139")];
            tensor<int32, [3]> reshape_27_shape_0 = const()[name = string("reshape_27_shape_0"), val = tensor<int32, [3]>([64, 2, 44])];
            tensor<fp16, [64, 2, 44]> reshape_27 = reshape(shape = reshape_27_shape_0, x = mul_139)[name = string("reshape_27")];
            tensor<int32, [3]> transpose_13_perm_0 = const()[name = string("transpose_13_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_142_y_0 = const()[name = string("mul_142_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3390400)))];
            tensor<fp16, [64, 352]> mul_142 = mul(x = mul_133, y = mul_142_y_0)[name = string("mul_142")];
            tensor<fp16, [88, 352]> tern_3_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3391168))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_3_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_3_v_bias_0 = const()[name = string("tern_3_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [64, 88]> tern_3_v = linear(bias = tern_3_v_bias_0, weight = tern_3_v_weight_0_palettized, x = mul_142)[name = string("tern_3_v")];
            tensor<fp16, [88]> mul_143_y_0 = const()[name = string("mul_143_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3398976)))];
            tensor<fp16, [64, 88]> mul_143 = mul(x = tern_3_v, y = mul_143_y_0)[name = string("mul_143")];
            tensor<int32, [3]> reshape_28_shape_0 = const()[name = string("reshape_28_shape_0"), val = tensor<int32, [3]>([64, 2, 44])];
            tensor<fp16, [64, 2, 44]> reshape_28 = reshape(shape = reshape_28_shape_0, x = mul_143)[name = string("reshape_28")];
            tensor<int32, [3]> transpose_14_perm_0 = const()[name = string("transpose_14_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 64, 44]> transpose_12 = transpose(perm = transpose_12_perm_0, x = reshape_26)[name = string("transpose_51")];
            tensor<fp16, [8, 64, 44]> mul_144 = mul(x = transpose_12, y = transpose_12)[name = string("mul_144")];
            tensor<int32, [1]> reduce_mean_31_axes_0 = const()[name = string("reduce_mean_31_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_31_keep_dims_0 = const()[name = string("reduce_mean_31_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 64, 1]> reduce_mean_31 = reduce_mean(axes = reduce_mean_31_axes_0, keep_dims = reduce_mean_31_keep_dims_0, x = mul_144)[name = string("reduce_mean_31")];
            fp32 rsqrt_31_epsilon_0 = const()[name = string("rsqrt_31_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 64, 1]> rsqrt_31 = rsqrt(epsilon = rsqrt_31_epsilon_0, x = reduce_mean_31)[name = string("rsqrt_31")];
            tensor<fp16, [8, 64, 44]> mul_145 = mul(x = transpose_12, y = rsqrt_31)[name = string("mul_145")];
            tensor<fp16, [44]> mul_146_y_0 = const()[name = string("mul_146_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3399232)))];
            tensor<fp16, [8, 64, 44]> mul_146 = mul(x = mul_145, y = mul_146_y_0)[name = string("mul_146")];
            tensor<int32, [3]> slice_by_index_12_begin_0 = const()[name = string("slice_by_index_12_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_12_end_0 = const()[name = string("slice_by_index_12_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_12_end_mask_0 = const()[name = string("slice_by_index_12_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 64, 22]> slice_by_index_12 = slice_by_index(begin = slice_by_index_12_begin_0, end = slice_by_index_12_end_0, end_mask = slice_by_index_12_end_mask_0, x = mul_146)[name = string("slice_by_index_12")];
            tensor<int32, [3]> slice_by_index_13_begin_0 = const()[name = string("slice_by_index_13_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_13_end_0 = const()[name = string("slice_by_index_13_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_13_end_mask_0 = const()[name = string("slice_by_index_13_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 64, 22]> slice_by_index_13 = slice_by_index(begin = slice_by_index_13_begin_0, end = slice_by_index_13_end_0, end_mask = slice_by_index_13_end_mask_0, x = mul_146)[name = string("slice_by_index_13")];
            int32 concat_6_axis_0 = const()[name = string("concat_6_axis_0"), val = int32(-1)];
            bool concat_6_interleave_0 = const()[name = string("concat_6_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 64, 44]> concat_6 = concat(axis = concat_6_axis_0, interleave = concat_6_interleave_0, values = (slice_by_index_13, slice_by_index_12))[name = string("concat_6")];
            tensor<fp16, [44]> mul_147_y_0 = const()[name = string("mul_147_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 64, 44]> mul_147 = mul(x = concat_6, y = mul_147_y_0)[name = string("mul_147")];
            tensor<fp16, [8, 64, 44]> mul_148 = mul(x = mul_146, y = mul_11_y_0)[name = string("mul_148")];
            tensor<fp16, [8, 64, 44]> mul_149 = mul(x = mul_147, y = mul_12_y_0)[name = string("mul_149")];
            tensor<fp16, [8, 64, 44]> add_18 = add(x = mul_148, y = mul_149)[name = string("add_18")];
            tensor<fp16, [2, 64, 44]> transpose_13 = transpose(perm = transpose_13_perm_0, x = reshape_27)[name = string("transpose_50")];
            tensor<fp16, [2, 64, 44]> mul_150 = mul(x = transpose_13, y = transpose_13)[name = string("mul_150")];
            tensor<int32, [1]> reduce_mean_32_axes_0 = const()[name = string("reduce_mean_32_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_32_keep_dims_0 = const()[name = string("reduce_mean_32_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 64, 1]> reduce_mean_32 = reduce_mean(axes = reduce_mean_32_axes_0, keep_dims = reduce_mean_32_keep_dims_0, x = mul_150)[name = string("reduce_mean_32")];
            fp32 rsqrt_32_epsilon_0 = const()[name = string("rsqrt_32_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 64, 1]> rsqrt_32 = rsqrt(epsilon = rsqrt_32_epsilon_0, x = reduce_mean_32)[name = string("rsqrt_32")];
            tensor<fp16, [2, 64, 44]> mul_151 = mul(x = transpose_13, y = rsqrt_32)[name = string("mul_151")];
            tensor<fp16, [44]> mul_152_y_0 = const()[name = string("mul_152_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3399424)))];
            tensor<fp16, [2, 64, 44]> mul_152 = mul(x = mul_151, y = mul_152_y_0)[name = string("mul_152")];
            tensor<int32, [3]> slice_by_index_14_begin_0 = const()[name = string("slice_by_index_14_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_14_end_0 = const()[name = string("slice_by_index_14_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_14_end_mask_0 = const()[name = string("slice_by_index_14_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 64, 22]> slice_by_index_14 = slice_by_index(begin = slice_by_index_14_begin_0, end = slice_by_index_14_end_0, end_mask = slice_by_index_14_end_mask_0, x = mul_152)[name = string("slice_by_index_14")];
            tensor<int32, [3]> slice_by_index_15_begin_0 = const()[name = string("slice_by_index_15_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_15_end_0 = const()[name = string("slice_by_index_15_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_15_end_mask_0 = const()[name = string("slice_by_index_15_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 64, 22]> slice_by_index_15 = slice_by_index(begin = slice_by_index_15_begin_0, end = slice_by_index_15_end_0, end_mask = slice_by_index_15_end_mask_0, x = mul_152)[name = string("slice_by_index_15")];
            int32 concat_7_axis_0 = const()[name = string("concat_7_axis_0"), val = int32(-1)];
            bool concat_7_interleave_0 = const()[name = string("concat_7_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 64, 44]> concat_7 = concat(axis = concat_7_axis_0, interleave = concat_7_interleave_0, values = (slice_by_index_15, slice_by_index_14))[name = string("concat_7")];
            tensor<fp16, [44]> mul_153_y_0 = const()[name = string("mul_153_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 64, 44]> mul_153 = mul(x = concat_7, y = mul_153_y_0)[name = string("mul_153")];
            tensor<fp16, [2, 64, 44]> mul_154 = mul(x = mul_152, y = mul_11_y_0)[name = string("mul_154")];
            tensor<fp16, [2, 64, 44]> mul_155 = mul(x = mul_153, y = mul_12_y_0)[name = string("mul_155")];
            tensor<fp16, [2, 64, 44]> add_19 = add(x = mul_154, y = mul_155)[name = string("add_19")];
            tensor<int32, [4]> reshape_29_shape_0 = const()[name = string("reshape_29_shape_0"), val = tensor<int32, [4]>([2, 1, 64, 44])];
            tensor<fp16, [2, 1, 64, 44]> reshape_29 = reshape(shape = reshape_29_shape_0, x = add_19)[name = string("reshape_29")];
            tensor<int32, [4]> tile_6_reps_0 = const()[name = string("tile_6_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 64, 44]> tile_6 = tile(reps = tile_6_reps_0, x = reshape_29)[name = string("tile_6")];
            tensor<int32, [3]> reshape_30_shape_0 = const()[name = string("reshape_30_shape_0"), val = tensor<int32, [3]>([8, 64, 44])];
            tensor<fp16, [8, 64, 44]> reshape_30 = reshape(shape = reshape_30_shape_0, x = tile_6)[name = string("reshape_30")];
            tensor<int32, [4]> reshape_31_shape_0 = const()[name = string("reshape_31_shape_0"), val = tensor<int32, [4]>([2, 1, 64, 44])];
            tensor<fp16, [2, 64, 44]> transpose_14 = transpose(perm = transpose_14_perm_0, x = reshape_28)[name = string("transpose_49")];
            tensor<fp16, [2, 1, 64, 44]> reshape_31 = reshape(shape = reshape_31_shape_0, x = transpose_14)[name = string("reshape_31")];
            tensor<int32, [4]> tile_7_reps_0 = const()[name = string("tile_7_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 64, 44]> tile_7 = tile(reps = tile_7_reps_0, x = reshape_31)[name = string("tile_7")];
            tensor<int32, [3]> reshape_32_shape_0 = const()[name = string("reshape_32_shape_0"), val = tensor<int32, [3]>([8, 64, 44])];
            tensor<fp16, [8, 64, 44]> reshape_32 = reshape(shape = reshape_32_shape_0, x = tile_7)[name = string("reshape_32")];
            fp16 mul_156_y_0 = const()[name = string("mul_156_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 64, 44]> mul_156 = mul(x = add_18, y = mul_156_y_0)[name = string("mul_156")];
            bool matmul_6_transpose_y_0 = const()[name = string("matmul_6_transpose_y_0"), val = bool(true)];
            bool matmul_6_transpose_x_0 = const()[name = string("matmul_6_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 64, 64]> matmul_6 = matmul(transpose_x = matmul_6_transpose_x_0, transpose_y = matmul_6_transpose_y_0, x = mul_156, y = reshape_30)[name = string("matmul_6")];
            tensor<fp16, [8, 64, 64]> add_20 = add(x = matmul_6, y = reshape_1)[name = string("add_20")];
            int32 softmax_3_axis_0 = const()[name = string("softmax_3_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 64, 64]> softmax_3 = softmax(axis = softmax_3_axis_0, x = add_20)[name = string("softmax_3")];
            bool matmul_7_transpose_x_0 = const()[name = string("matmul_7_transpose_x_0"), val = bool(false)];
            bool matmul_7_transpose_y_0 = const()[name = string("matmul_7_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 64, 44]> matmul_7 = matmul(transpose_x = matmul_7_transpose_x_0, transpose_y = matmul_7_transpose_y_0, x = softmax_3, y = reshape_32)[name = string("matmul_7")];
            tensor<int32, [3]> transpose_15_perm_0 = const()[name = string("transpose_15_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_33_shape_0 = const()[name = string("reshape_33_shape_0"), val = tensor<int32, [2]>([64, 352])];
            tensor<fp16, [64, 8, 44]> transpose_15 = transpose(perm = transpose_15_perm_0, x = matmul_7)[name = string("transpose_48")];
            tensor<fp16, [64, 352]> reshape_33 = reshape(shape = reshape_33_shape_0, x = transpose_15)[name = string("reshape_33")];
            tensor<fp16, [64, 352]> mul_157 = mul(x = reshape_33, y = reshape_33)[name = string("mul_157")];
            tensor<int32, [1]> reduce_mean_33_axes_0 = const()[name = string("reduce_mean_33_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_33_keep_dims_0 = const()[name = string("reduce_mean_33_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_33 = reduce_mean(axes = reduce_mean_33_axes_0, keep_dims = reduce_mean_33_keep_dims_0, x = mul_157)[name = string("reduce_mean_33")];
            fp32 rsqrt_33_epsilon_0 = const()[name = string("rsqrt_33_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_33 = rsqrt(epsilon = rsqrt_33_epsilon_0, x = reduce_mean_33)[name = string("rsqrt_33")];
            tensor<fp16, [64, 352]> mul_158 = mul(x = reshape_33, y = rsqrt_33)[name = string("mul_158")];
            tensor<fp16, [352]> mul_159_y_0 = const()[name = string("mul_159_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3399616)))];
            tensor<fp16, [64, 352]> mul_159 = mul(x = mul_158, y = mul_159_y_0)[name = string("mul_159")];
            tensor<fp16, [352, 352]> tern_3_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3400384))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_3_o_weight_0_palettized")];
            tensor<fp16, [64, 352]> tern_3_o = linear(bias = linear_0_bias_0, weight = tern_3_o_weight_0_palettized, x = mul_159)[name = string("tern_3_o")];
            tensor<fp16, [352]> mul_160_y_0 = const()[name = string("mul_160_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3431424)))];
            tensor<fp16, [64, 352]> mul_160 = mul(x = tern_3_o, y = mul_160_y_0)[name = string("mul_160")];
            tensor<fp16, [64, 352]> add_21 = add(x = add_17, y = mul_160)[name = string("add_21")];
            tensor<fp16, [64, 352]> mul_161 = mul(x = add_21, y = add_21)[name = string("mul_161")];
            tensor<int32, [1]> reduce_mean_34_axes_0 = const()[name = string("reduce_mean_34_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_34_keep_dims_0 = const()[name = string("reduce_mean_34_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_34 = reduce_mean(axes = reduce_mean_34_axes_0, keep_dims = reduce_mean_34_keep_dims_0, x = mul_161)[name = string("reduce_mean_34")];
            fp32 rsqrt_34_epsilon_0 = const()[name = string("rsqrt_34_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_34 = rsqrt(epsilon = rsqrt_34_epsilon_0, x = reduce_mean_34)[name = string("rsqrt_34")];
            tensor<fp16, [64, 352]> mul_162 = mul(x = add_21, y = rsqrt_34)[name = string("mul_162")];
            tensor<fp16, [352]> mul_163_y_0 = const()[name = string("mul_163_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3432192)))];
            tensor<fp16, [64, 352]> mul_163 = mul(x = mul_162, y = mul_163_y_0)[name = string("mul_163")];
            tensor<fp16, [64, 352]> mul_164 = mul(x = mul_163, y = mul_163)[name = string("mul_164")];
            tensor<int32, [1]> reduce_mean_35_axes_0 = const()[name = string("reduce_mean_35_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_35_keep_dims_0 = const()[name = string("reduce_mean_35_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_35 = reduce_mean(axes = reduce_mean_35_axes_0, keep_dims = reduce_mean_35_keep_dims_0, x = mul_164)[name = string("reduce_mean_35")];
            fp32 rsqrt_35_epsilon_0 = const()[name = string("rsqrt_35_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_35 = rsqrt(epsilon = rsqrt_35_epsilon_0, x = reduce_mean_35)[name = string("rsqrt_35")];
            tensor<fp16, [64, 352]> mul_165 = mul(x = mul_163, y = rsqrt_35)[name = string("mul_165")];
            tensor<fp16, [352]> mul_166_y_0 = const()[name = string("mul_166_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3432960)))];
            tensor<fp16, [64, 352]> mul_166 = mul(x = mul_165, y = mul_166_y_0)[name = string("mul_166")];
            tensor<fp16, [960, 352]> tern_3_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3433728))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_3_w1_weight_0_palettized")];
            tensor<fp16, [64, 960]> tern_3_w1 = linear(bias = linear_4_bias_0, weight = tern_3_w1_weight_0_palettized, x = mul_166)[name = string("tern_3_w1")];
            tensor<fp16, [960]> mul_167_y_0 = const()[name = string("mul_167_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3518272)))];
            tensor<fp16, [64, 960]> mul_167 = mul(x = tern_3_w1, y = mul_167_y_0)[name = string("mul_167")];
            tensor<fp16, [352]> mul_170_y_0 = const()[name = string("mul_170_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3520256)))];
            tensor<fp16, [64, 352]> mul_170 = mul(x = mul_165, y = mul_170_y_0)[name = string("mul_170")];
            tensor<fp16, [960, 352]> tern_3_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3521024))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_3_w3_weight_0_palettized")];
            tensor<fp16, [64, 960]> tern_3_w3 = linear(bias = linear_4_bias_0, weight = tern_3_w3_weight_0_palettized, x = mul_170)[name = string("tern_3_w3")];
            tensor<fp16, [960]> mul_171_y_0 = const()[name = string("mul_171_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3605568)))];
            tensor<fp16, [64, 960]> mul_171 = mul(x = tern_3_w3, y = mul_171_y_0)[name = string("mul_171")];
            fp16 mul_172_y_0 = const()[name = string("mul_172_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [64, 960]> mul_172 = mul(x = mul_167, y = mul_172_y_0)[name = string("mul_172")];
            tensor<fp16, [64, 960]> tanh_3 = tanh(x = mul_172)[name = string("tanh_3")];
            fp16 mul_173_x_0 = const()[name = string("mul_173_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [64, 960]> mul_173 = mul(x = mul_173_x_0, y = tanh_3)[name = string("mul_173")];
            fp16 add_22_x_0 = const()[name = string("add_22_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [64, 960]> add_22 = add(x = add_22_x_0, y = mul_173)[name = string("add_22")];
            tensor<fp16, [64, 960]> mul_174 = mul(x = mul_167, y = add_22)[name = string("mul_174")];
            tensor<fp16, [64, 960]> mul_175 = mul(x = mul_174, y = mul_171)[name = string("mul_175")];
            tensor<fp16, [64, 960]> mul_176 = mul(x = mul_175, y = mul_175)[name = string("mul_176")];
            tensor<int32, [1]> reduce_mean_37_axes_0 = const()[name = string("reduce_mean_37_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_37_keep_dims_0 = const()[name = string("reduce_mean_37_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_37 = reduce_mean(axes = reduce_mean_37_axes_0, keep_dims = reduce_mean_37_keep_dims_0, x = mul_176)[name = string("reduce_mean_37")];
            fp32 rsqrt_37_epsilon_0 = const()[name = string("rsqrt_37_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_37 = rsqrt(epsilon = rsqrt_37_epsilon_0, x = reduce_mean_37)[name = string("rsqrt_37")];
            tensor<fp16, [64, 960]> mul_177 = mul(x = mul_175, y = rsqrt_37)[name = string("mul_177")];
            tensor<fp16, [960]> mul_178_y_0 = const()[name = string("mul_178_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3607552)))];
            tensor<fp16, [64, 960]> mul_178 = mul(x = mul_177, y = mul_178_y_0)[name = string("mul_178")];
            tensor<fp16, [352, 960]> tern_3_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3609536))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_3_w2_weight_0_palettized")];
            tensor<fp16, [64, 352]> tern_3_w2 = linear(bias = linear_0_bias_0, weight = tern_3_w2_weight_0_palettized, x = mul_178)[name = string("tern_3_w2")];
            tensor<fp16, [352]> mul_179_y_0 = const()[name = string("mul_179_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3694080)))];
            tensor<fp16, [64, 352]> mul_179 = mul(x = tern_3_w2, y = mul_179_y_0)[name = string("mul_179")];
            tensor<fp16, [64, 352]> add_23 = add(x = add_21, y = mul_179)[name = string("add_23")];
            tensor<fp16, [64, 352]> mul_180 = mul(x = add_23, y = add_23)[name = string("mul_180")];
            tensor<int32, [1]> reduce_mean_38_axes_0 = const()[name = string("reduce_mean_38_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_38_keep_dims_0 = const()[name = string("reduce_mean_38_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_38 = reduce_mean(axes = reduce_mean_38_axes_0, keep_dims = reduce_mean_38_keep_dims_0, x = mul_180)[name = string("reduce_mean_38")];
            fp32 rsqrt_38_epsilon_0 = const()[name = string("rsqrt_38_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_38 = rsqrt(epsilon = rsqrt_38_epsilon_0, x = reduce_mean_38)[name = string("rsqrt_38")];
            tensor<fp16, [64, 352]> mul_181 = mul(x = add_23, y = rsqrt_38)[name = string("mul_181")];
            tensor<fp16, [352]> mul_182_y_0 = const()[name = string("mul_182_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3694848)))];
            tensor<fp16, [64, 352]> mul_182 = mul(x = mul_181, y = mul_182_y_0)[name = string("mul_182")];
            tensor<fp16, [64, 352]> mul_183 = mul(x = mul_182, y = mul_182)[name = string("mul_183")];
            tensor<int32, [1]> reduce_mean_39_axes_0 = const()[name = string("reduce_mean_39_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_39_keep_dims_0 = const()[name = string("reduce_mean_39_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_39 = reduce_mean(axes = reduce_mean_39_axes_0, keep_dims = reduce_mean_39_keep_dims_0, x = mul_183)[name = string("reduce_mean_39")];
            fp32 rsqrt_39_epsilon_0 = const()[name = string("rsqrt_39_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_39 = rsqrt(epsilon = rsqrt_39_epsilon_0, x = reduce_mean_39)[name = string("rsqrt_39")];
            tensor<fp16, [64, 352]> mul_184 = mul(x = mul_182, y = rsqrt_39)[name = string("mul_184")];
            tensor<fp16, [352]> mul_185_y_0 = const()[name = string("mul_185_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3695616)))];
            tensor<fp16, [64, 352]> mul_185 = mul(x = mul_184, y = mul_185_y_0)[name = string("mul_185")];
            tensor<fp16, [352, 352]> tern_4_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3696384))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_4_q_weight_0_palettized")];
            tensor<fp16, [64, 352]> tern_4_q = linear(bias = linear_0_bias_0, weight = tern_4_q_weight_0_palettized, x = mul_185)[name = string("tern_4_q")];
            tensor<fp16, [352]> mul_186_y_0 = const()[name = string("mul_186_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3727424)))];
            tensor<fp16, [64, 352]> mul_186 = mul(x = tern_4_q, y = mul_186_y_0)[name = string("mul_186")];
            tensor<int32, [3]> reshape_34_shape_0 = const()[name = string("reshape_34_shape_0"), val = tensor<int32, [3]>([64, 8, 44])];
            tensor<fp16, [64, 8, 44]> reshape_34 = reshape(shape = reshape_34_shape_0, x = mul_186)[name = string("reshape_34")];
            tensor<int32, [3]> transpose_16_perm_0 = const()[name = string("transpose_16_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_189_y_0 = const()[name = string("mul_189_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3728192)))];
            tensor<fp16, [64, 352]> mul_189 = mul(x = mul_184, y = mul_189_y_0)[name = string("mul_189")];
            tensor<fp16, [88, 352]> tern_4_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3728960))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_4_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_4_k_bias_0 = const()[name = string("tern_4_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [64, 88]> tern_4_k = linear(bias = tern_4_k_bias_0, weight = tern_4_k_weight_0_palettized, x = mul_189)[name = string("tern_4_k")];
            tensor<fp16, [88]> mul_190_y_0 = const()[name = string("mul_190_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3736768)))];
            tensor<fp16, [64, 88]> mul_190 = mul(x = tern_4_k, y = mul_190_y_0)[name = string("mul_190")];
            tensor<int32, [3]> reshape_35_shape_0 = const()[name = string("reshape_35_shape_0"), val = tensor<int32, [3]>([64, 2, 44])];
            tensor<fp16, [64, 2, 44]> reshape_35 = reshape(shape = reshape_35_shape_0, x = mul_190)[name = string("reshape_35")];
            tensor<int32, [3]> transpose_17_perm_0 = const()[name = string("transpose_17_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_193_y_0 = const()[name = string("mul_193_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3737024)))];
            tensor<fp16, [64, 352]> mul_193 = mul(x = mul_184, y = mul_193_y_0)[name = string("mul_193")];
            tensor<fp16, [88, 352]> tern_4_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3737792))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_4_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_4_v_bias_0 = const()[name = string("tern_4_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [64, 88]> tern_4_v = linear(bias = tern_4_v_bias_0, weight = tern_4_v_weight_0_palettized, x = mul_193)[name = string("tern_4_v")];
            tensor<fp16, [88]> mul_194_y_0 = const()[name = string("mul_194_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3745600)))];
            tensor<fp16, [64, 88]> mul_194 = mul(x = tern_4_v, y = mul_194_y_0)[name = string("mul_194")];
            tensor<int32, [3]> reshape_36_shape_0 = const()[name = string("reshape_36_shape_0"), val = tensor<int32, [3]>([64, 2, 44])];
            tensor<fp16, [64, 2, 44]> reshape_36 = reshape(shape = reshape_36_shape_0, x = mul_194)[name = string("reshape_36")];
            tensor<int32, [3]> transpose_18_perm_0 = const()[name = string("transpose_18_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 64, 44]> transpose_16 = transpose(perm = transpose_16_perm_0, x = reshape_34)[name = string("transpose_47")];
            tensor<fp16, [8, 64, 44]> mul_195 = mul(x = transpose_16, y = transpose_16)[name = string("mul_195")];
            tensor<int32, [1]> reduce_mean_42_axes_0 = const()[name = string("reduce_mean_42_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_42_keep_dims_0 = const()[name = string("reduce_mean_42_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 64, 1]> reduce_mean_42 = reduce_mean(axes = reduce_mean_42_axes_0, keep_dims = reduce_mean_42_keep_dims_0, x = mul_195)[name = string("reduce_mean_42")];
            fp32 rsqrt_42_epsilon_0 = const()[name = string("rsqrt_42_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 64, 1]> rsqrt_42 = rsqrt(epsilon = rsqrt_42_epsilon_0, x = reduce_mean_42)[name = string("rsqrt_42")];
            tensor<fp16, [8, 64, 44]> mul_196 = mul(x = transpose_16, y = rsqrt_42)[name = string("mul_196")];
            tensor<fp16, [44]> mul_197_y_0 = const()[name = string("mul_197_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3745856)))];
            tensor<fp16, [8, 64, 44]> mul_197 = mul(x = mul_196, y = mul_197_y_0)[name = string("mul_197")];
            tensor<int32, [3]> slice_by_index_16_begin_0 = const()[name = string("slice_by_index_16_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_16_end_0 = const()[name = string("slice_by_index_16_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_16_end_mask_0 = const()[name = string("slice_by_index_16_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 64, 22]> slice_by_index_16 = slice_by_index(begin = slice_by_index_16_begin_0, end = slice_by_index_16_end_0, end_mask = slice_by_index_16_end_mask_0, x = mul_197)[name = string("slice_by_index_16")];
            tensor<int32, [3]> slice_by_index_17_begin_0 = const()[name = string("slice_by_index_17_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_17_end_0 = const()[name = string("slice_by_index_17_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_17_end_mask_0 = const()[name = string("slice_by_index_17_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 64, 22]> slice_by_index_17 = slice_by_index(begin = slice_by_index_17_begin_0, end = slice_by_index_17_end_0, end_mask = slice_by_index_17_end_mask_0, x = mul_197)[name = string("slice_by_index_17")];
            int32 concat_8_axis_0 = const()[name = string("concat_8_axis_0"), val = int32(-1)];
            bool concat_8_interleave_0 = const()[name = string("concat_8_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 64, 44]> concat_8 = concat(axis = concat_8_axis_0, interleave = concat_8_interleave_0, values = (slice_by_index_17, slice_by_index_16))[name = string("concat_8")];
            tensor<fp16, [44]> mul_198_y_0 = const()[name = string("mul_198_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 64, 44]> mul_198 = mul(x = concat_8, y = mul_198_y_0)[name = string("mul_198")];
            tensor<fp16, [8, 64, 44]> mul_199 = mul(x = mul_197, y = mul_11_y_0)[name = string("mul_199")];
            tensor<fp16, [8, 64, 44]> mul_200 = mul(x = mul_198, y = mul_12_y_0)[name = string("mul_200")];
            tensor<fp16, [8, 64, 44]> add_24 = add(x = mul_199, y = mul_200)[name = string("add_24")];
            tensor<fp16, [2, 64, 44]> transpose_17 = transpose(perm = transpose_17_perm_0, x = reshape_35)[name = string("transpose_46")];
            tensor<fp16, [2, 64, 44]> mul_201 = mul(x = transpose_17, y = transpose_17)[name = string("mul_201")];
            tensor<int32, [1]> reduce_mean_43_axes_0 = const()[name = string("reduce_mean_43_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_43_keep_dims_0 = const()[name = string("reduce_mean_43_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 64, 1]> reduce_mean_43 = reduce_mean(axes = reduce_mean_43_axes_0, keep_dims = reduce_mean_43_keep_dims_0, x = mul_201)[name = string("reduce_mean_43")];
            fp32 rsqrt_43_epsilon_0 = const()[name = string("rsqrt_43_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 64, 1]> rsqrt_43 = rsqrt(epsilon = rsqrt_43_epsilon_0, x = reduce_mean_43)[name = string("rsqrt_43")];
            tensor<fp16, [2, 64, 44]> mul_202 = mul(x = transpose_17, y = rsqrt_43)[name = string("mul_202")];
            tensor<fp16, [44]> mul_203_y_0 = const()[name = string("mul_203_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3746048)))];
            tensor<fp16, [2, 64, 44]> mul_203 = mul(x = mul_202, y = mul_203_y_0)[name = string("mul_203")];
            tensor<int32, [3]> slice_by_index_18_begin_0 = const()[name = string("slice_by_index_18_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_18_end_0 = const()[name = string("slice_by_index_18_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_18_end_mask_0 = const()[name = string("slice_by_index_18_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 64, 22]> slice_by_index_18 = slice_by_index(begin = slice_by_index_18_begin_0, end = slice_by_index_18_end_0, end_mask = slice_by_index_18_end_mask_0, x = mul_203)[name = string("slice_by_index_18")];
            tensor<int32, [3]> slice_by_index_19_begin_0 = const()[name = string("slice_by_index_19_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_19_end_0 = const()[name = string("slice_by_index_19_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_19_end_mask_0 = const()[name = string("slice_by_index_19_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 64, 22]> slice_by_index_19 = slice_by_index(begin = slice_by_index_19_begin_0, end = slice_by_index_19_end_0, end_mask = slice_by_index_19_end_mask_0, x = mul_203)[name = string("slice_by_index_19")];
            int32 concat_9_axis_0 = const()[name = string("concat_9_axis_0"), val = int32(-1)];
            bool concat_9_interleave_0 = const()[name = string("concat_9_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 64, 44]> concat_9 = concat(axis = concat_9_axis_0, interleave = concat_9_interleave_0, values = (slice_by_index_19, slice_by_index_18))[name = string("concat_9")];
            tensor<fp16, [44]> mul_204_y_0 = const()[name = string("mul_204_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 64, 44]> mul_204 = mul(x = concat_9, y = mul_204_y_0)[name = string("mul_204")];
            tensor<fp16, [2, 64, 44]> mul_205 = mul(x = mul_203, y = mul_11_y_0)[name = string("mul_205")];
            tensor<fp16, [2, 64, 44]> mul_206 = mul(x = mul_204, y = mul_12_y_0)[name = string("mul_206")];
            tensor<fp16, [2, 64, 44]> add_25 = add(x = mul_205, y = mul_206)[name = string("add_25")];
            tensor<int32, [4]> reshape_37_shape_0 = const()[name = string("reshape_37_shape_0"), val = tensor<int32, [4]>([2, 1, 64, 44])];
            tensor<fp16, [2, 1, 64, 44]> reshape_37 = reshape(shape = reshape_37_shape_0, x = add_25)[name = string("reshape_37")];
            tensor<int32, [4]> tile_8_reps_0 = const()[name = string("tile_8_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 64, 44]> tile_8 = tile(reps = tile_8_reps_0, x = reshape_37)[name = string("tile_8")];
            tensor<int32, [3]> reshape_38_shape_0 = const()[name = string("reshape_38_shape_0"), val = tensor<int32, [3]>([8, 64, 44])];
            tensor<fp16, [8, 64, 44]> reshape_38 = reshape(shape = reshape_38_shape_0, x = tile_8)[name = string("reshape_38")];
            tensor<int32, [4]> reshape_39_shape_0 = const()[name = string("reshape_39_shape_0"), val = tensor<int32, [4]>([2, 1, 64, 44])];
            tensor<fp16, [2, 64, 44]> transpose_18 = transpose(perm = transpose_18_perm_0, x = reshape_36)[name = string("transpose_45")];
            tensor<fp16, [2, 1, 64, 44]> reshape_39 = reshape(shape = reshape_39_shape_0, x = transpose_18)[name = string("reshape_39")];
            tensor<int32, [4]> tile_9_reps_0 = const()[name = string("tile_9_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 64, 44]> tile_9 = tile(reps = tile_9_reps_0, x = reshape_39)[name = string("tile_9")];
            tensor<int32, [3]> reshape_40_shape_0 = const()[name = string("reshape_40_shape_0"), val = tensor<int32, [3]>([8, 64, 44])];
            tensor<fp16, [8, 64, 44]> reshape_40 = reshape(shape = reshape_40_shape_0, x = tile_9)[name = string("reshape_40")];
            fp16 mul_207_y_0 = const()[name = string("mul_207_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 64, 44]> mul_207 = mul(x = add_24, y = mul_207_y_0)[name = string("mul_207")];
            bool matmul_8_transpose_y_0 = const()[name = string("matmul_8_transpose_y_0"), val = bool(true)];
            bool matmul_8_transpose_x_0 = const()[name = string("matmul_8_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 64, 64]> matmul_8 = matmul(transpose_x = matmul_8_transpose_x_0, transpose_y = matmul_8_transpose_y_0, x = mul_207, y = reshape_38)[name = string("matmul_8")];
            tensor<fp16, [8, 64, 64]> add_26 = add(x = matmul_8, y = reshape_1)[name = string("add_26")];
            int32 softmax_4_axis_0 = const()[name = string("softmax_4_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 64, 64]> softmax_4 = softmax(axis = softmax_4_axis_0, x = add_26)[name = string("softmax_4")];
            bool matmul_9_transpose_x_0 = const()[name = string("matmul_9_transpose_x_0"), val = bool(false)];
            bool matmul_9_transpose_y_0 = const()[name = string("matmul_9_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 64, 44]> matmul_9 = matmul(transpose_x = matmul_9_transpose_x_0, transpose_y = matmul_9_transpose_y_0, x = softmax_4, y = reshape_40)[name = string("matmul_9")];
            tensor<int32, [3]> transpose_19_perm_0 = const()[name = string("transpose_19_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_41_shape_0 = const()[name = string("reshape_41_shape_0"), val = tensor<int32, [2]>([64, 352])];
            tensor<fp16, [64, 8, 44]> transpose_19 = transpose(perm = transpose_19_perm_0, x = matmul_9)[name = string("transpose_44")];
            tensor<fp16, [64, 352]> reshape_41 = reshape(shape = reshape_41_shape_0, x = transpose_19)[name = string("reshape_41")];
            tensor<fp16, [64, 352]> mul_208 = mul(x = reshape_41, y = reshape_41)[name = string("mul_208")];
            tensor<int32, [1]> reduce_mean_44_axes_0 = const()[name = string("reduce_mean_44_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_44_keep_dims_0 = const()[name = string("reduce_mean_44_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_44 = reduce_mean(axes = reduce_mean_44_axes_0, keep_dims = reduce_mean_44_keep_dims_0, x = mul_208)[name = string("reduce_mean_44")];
            fp32 rsqrt_44_epsilon_0 = const()[name = string("rsqrt_44_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_44 = rsqrt(epsilon = rsqrt_44_epsilon_0, x = reduce_mean_44)[name = string("rsqrt_44")];
            tensor<fp16, [64, 352]> mul_209 = mul(x = reshape_41, y = rsqrt_44)[name = string("mul_209")];
            tensor<fp16, [352]> mul_210_y_0 = const()[name = string("mul_210_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3746240)))];
            tensor<fp16, [64, 352]> mul_210 = mul(x = mul_209, y = mul_210_y_0)[name = string("mul_210")];
            tensor<fp16, [352, 352]> tern_4_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3747008))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_4_o_weight_0_palettized")];
            tensor<fp16, [64, 352]> tern_4_o = linear(bias = linear_0_bias_0, weight = tern_4_o_weight_0_palettized, x = mul_210)[name = string("tern_4_o")];
            tensor<fp16, [352]> mul_211_y_0 = const()[name = string("mul_211_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3778048)))];
            tensor<fp16, [64, 352]> mul_211 = mul(x = tern_4_o, y = mul_211_y_0)[name = string("mul_211")];
            tensor<fp16, [64, 352]> add_27 = add(x = add_23, y = mul_211)[name = string("add_27")];
            tensor<fp16, [64, 352]> mul_212 = mul(x = add_27, y = add_27)[name = string("mul_212")];
            tensor<int32, [1]> reduce_mean_45_axes_0 = const()[name = string("reduce_mean_45_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_45_keep_dims_0 = const()[name = string("reduce_mean_45_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_45 = reduce_mean(axes = reduce_mean_45_axes_0, keep_dims = reduce_mean_45_keep_dims_0, x = mul_212)[name = string("reduce_mean_45")];
            fp32 rsqrt_45_epsilon_0 = const()[name = string("rsqrt_45_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_45 = rsqrt(epsilon = rsqrt_45_epsilon_0, x = reduce_mean_45)[name = string("rsqrt_45")];
            tensor<fp16, [64, 352]> mul_213 = mul(x = add_27, y = rsqrt_45)[name = string("mul_213")];
            tensor<fp16, [352]> mul_214_y_0 = const()[name = string("mul_214_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3778816)))];
            tensor<fp16, [64, 352]> mul_214 = mul(x = mul_213, y = mul_214_y_0)[name = string("mul_214")];
            tensor<fp16, [64, 352]> mul_215 = mul(x = mul_214, y = mul_214)[name = string("mul_215")];
            tensor<int32, [1]> reduce_mean_46_axes_0 = const()[name = string("reduce_mean_46_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_46_keep_dims_0 = const()[name = string("reduce_mean_46_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_46 = reduce_mean(axes = reduce_mean_46_axes_0, keep_dims = reduce_mean_46_keep_dims_0, x = mul_215)[name = string("reduce_mean_46")];
            fp32 rsqrt_46_epsilon_0 = const()[name = string("rsqrt_46_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_46 = rsqrt(epsilon = rsqrt_46_epsilon_0, x = reduce_mean_46)[name = string("rsqrt_46")];
            tensor<fp16, [64, 352]> mul_216 = mul(x = mul_214, y = rsqrt_46)[name = string("mul_216")];
            tensor<fp16, [352]> mul_217_y_0 = const()[name = string("mul_217_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3779584)))];
            tensor<fp16, [64, 352]> mul_217 = mul(x = mul_216, y = mul_217_y_0)[name = string("mul_217")];
            tensor<fp16, [960, 352]> tern_4_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3780352))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_4_w1_weight_0_palettized")];
            tensor<fp16, [64, 960]> tern_4_w1 = linear(bias = linear_4_bias_0, weight = tern_4_w1_weight_0_palettized, x = mul_217)[name = string("tern_4_w1")];
            tensor<fp16, [960]> mul_218_y_0 = const()[name = string("mul_218_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3864896)))];
            tensor<fp16, [64, 960]> mul_218 = mul(x = tern_4_w1, y = mul_218_y_0)[name = string("mul_218")];
            tensor<fp16, [352]> mul_221_y_0 = const()[name = string("mul_221_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3866880)))];
            tensor<fp16, [64, 352]> mul_221 = mul(x = mul_216, y = mul_221_y_0)[name = string("mul_221")];
            tensor<fp16, [960, 352]> tern_4_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3867648))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_4_w3_weight_0_palettized")];
            tensor<fp16, [64, 960]> tern_4_w3 = linear(bias = linear_4_bias_0, weight = tern_4_w3_weight_0_palettized, x = mul_221)[name = string("tern_4_w3")];
            tensor<fp16, [960]> mul_222_y_0 = const()[name = string("mul_222_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3952192)))];
            tensor<fp16, [64, 960]> mul_222 = mul(x = tern_4_w3, y = mul_222_y_0)[name = string("mul_222")];
            fp16 mul_223_y_0 = const()[name = string("mul_223_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [64, 960]> mul_223 = mul(x = mul_218, y = mul_223_y_0)[name = string("mul_223")];
            tensor<fp16, [64, 960]> tanh_4 = tanh(x = mul_223)[name = string("tanh_4")];
            fp16 mul_224_x_0 = const()[name = string("mul_224_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [64, 960]> mul_224 = mul(x = mul_224_x_0, y = tanh_4)[name = string("mul_224")];
            fp16 add_28_x_0 = const()[name = string("add_28_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [64, 960]> add_28 = add(x = add_28_x_0, y = mul_224)[name = string("add_28")];
            tensor<fp16, [64, 960]> mul_225 = mul(x = mul_218, y = add_28)[name = string("mul_225")];
            tensor<fp16, [64, 960]> mul_226 = mul(x = mul_225, y = mul_222)[name = string("mul_226")];
            tensor<fp16, [64, 960]> mul_227 = mul(x = mul_226, y = mul_226)[name = string("mul_227")];
            tensor<int32, [1]> reduce_mean_48_axes_0 = const()[name = string("reduce_mean_48_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_48_keep_dims_0 = const()[name = string("reduce_mean_48_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_48 = reduce_mean(axes = reduce_mean_48_axes_0, keep_dims = reduce_mean_48_keep_dims_0, x = mul_227)[name = string("reduce_mean_48")];
            fp32 rsqrt_48_epsilon_0 = const()[name = string("rsqrt_48_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_48 = rsqrt(epsilon = rsqrt_48_epsilon_0, x = reduce_mean_48)[name = string("rsqrt_48")];
            tensor<fp16, [64, 960]> mul_228 = mul(x = mul_226, y = rsqrt_48)[name = string("mul_228")];
            tensor<fp16, [960]> mul_229_y_0 = const()[name = string("mul_229_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3954176)))];
            tensor<fp16, [64, 960]> mul_229 = mul(x = mul_228, y = mul_229_y_0)[name = string("mul_229")];
            tensor<fp16, [352, 960]> tern_4_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3956160))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_4_w2_weight_0_palettized")];
            tensor<fp16, [64, 352]> tern_4_w2 = linear(bias = linear_0_bias_0, weight = tern_4_w2_weight_0_palettized, x = mul_229)[name = string("tern_4_w2")];
            tensor<fp16, [352]> mul_230_y_0 = const()[name = string("mul_230_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4040704)))];
            tensor<fp16, [64, 352]> mul_230 = mul(x = tern_4_w2, y = mul_230_y_0)[name = string("mul_230")];
            tensor<fp16, [64, 352]> add_29 = add(x = add_27, y = mul_230)[name = string("add_29")];
            tensor<fp16, [64, 352]> mul_231 = mul(x = add_29, y = add_29)[name = string("mul_231")];
            tensor<int32, [1]> reduce_mean_49_axes_0 = const()[name = string("reduce_mean_49_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_49_keep_dims_0 = const()[name = string("reduce_mean_49_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_49 = reduce_mean(axes = reduce_mean_49_axes_0, keep_dims = reduce_mean_49_keep_dims_0, x = mul_231)[name = string("reduce_mean_49")];
            fp32 rsqrt_49_epsilon_0 = const()[name = string("rsqrt_49_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_49 = rsqrt(epsilon = rsqrt_49_epsilon_0, x = reduce_mean_49)[name = string("rsqrt_49")];
            tensor<fp16, [64, 352]> mul_232 = mul(x = add_29, y = rsqrt_49)[name = string("mul_232")];
            tensor<fp16, [352]> mul_233_y_0 = const()[name = string("mul_233_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4041472)))];
            tensor<fp16, [64, 352]> mul_233 = mul(x = mul_232, y = mul_233_y_0)[name = string("mul_233")];
            tensor<fp16, [64, 352]> mul_234 = mul(x = mul_233, y = mul_233)[name = string("mul_234")];
            tensor<int32, [1]> reduce_mean_50_axes_0 = const()[name = string("reduce_mean_50_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_50_keep_dims_0 = const()[name = string("reduce_mean_50_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_50 = reduce_mean(axes = reduce_mean_50_axes_0, keep_dims = reduce_mean_50_keep_dims_0, x = mul_234)[name = string("reduce_mean_50")];
            fp32 rsqrt_50_epsilon_0 = const()[name = string("rsqrt_50_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_50 = rsqrt(epsilon = rsqrt_50_epsilon_0, x = reduce_mean_50)[name = string("rsqrt_50")];
            tensor<fp16, [64, 352]> mul_235 = mul(x = mul_233, y = rsqrt_50)[name = string("mul_235")];
            tensor<fp16, [352]> mul_236_y_0 = const()[name = string("mul_236_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4042240)))];
            tensor<fp16, [64, 352]> mul_236 = mul(x = mul_235, y = mul_236_y_0)[name = string("mul_236")];
            tensor<fp16, [352, 352]> tern_5_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4043008))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_5_q_weight_0_palettized")];
            tensor<fp16, [64, 352]> tern_5_q = linear(bias = linear_0_bias_0, weight = tern_5_q_weight_0_palettized, x = mul_236)[name = string("tern_5_q")];
            tensor<fp16, [352]> mul_237_y_0 = const()[name = string("mul_237_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4074048)))];
            tensor<fp16, [64, 352]> mul_237 = mul(x = tern_5_q, y = mul_237_y_0)[name = string("mul_237")];
            tensor<int32, [3]> reshape_42_shape_0 = const()[name = string("reshape_42_shape_0"), val = tensor<int32, [3]>([64, 8, 44])];
            tensor<fp16, [64, 8, 44]> reshape_42 = reshape(shape = reshape_42_shape_0, x = mul_237)[name = string("reshape_42")];
            tensor<int32, [3]> transpose_20_perm_0 = const()[name = string("transpose_20_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_240_y_0 = const()[name = string("mul_240_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4074816)))];
            tensor<fp16, [64, 352]> mul_240 = mul(x = mul_235, y = mul_240_y_0)[name = string("mul_240")];
            tensor<fp16, [88, 352]> tern_5_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4075584))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_5_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_5_k_bias_0 = const()[name = string("tern_5_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [64, 88]> tern_5_k = linear(bias = tern_5_k_bias_0, weight = tern_5_k_weight_0_palettized, x = mul_240)[name = string("tern_5_k")];
            tensor<fp16, [88]> mul_241_y_0 = const()[name = string("mul_241_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4083392)))];
            tensor<fp16, [64, 88]> mul_241 = mul(x = tern_5_k, y = mul_241_y_0)[name = string("mul_241")];
            tensor<int32, [3]> reshape_43_shape_0 = const()[name = string("reshape_43_shape_0"), val = tensor<int32, [3]>([64, 2, 44])];
            tensor<fp16, [64, 2, 44]> reshape_43 = reshape(shape = reshape_43_shape_0, x = mul_241)[name = string("reshape_43")];
            tensor<int32, [3]> transpose_21_perm_0 = const()[name = string("transpose_21_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_244_y_0 = const()[name = string("mul_244_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4083648)))];
            tensor<fp16, [64, 352]> mul_244 = mul(x = mul_235, y = mul_244_y_0)[name = string("mul_244")];
            tensor<fp16, [88, 352]> tern_5_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4084416))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_5_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_5_v_bias_0 = const()[name = string("tern_5_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [64, 88]> tern_5_v = linear(bias = tern_5_v_bias_0, weight = tern_5_v_weight_0_palettized, x = mul_244)[name = string("tern_5_v")];
            tensor<fp16, [88]> mul_245_y_0 = const()[name = string("mul_245_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4092224)))];
            tensor<fp16, [64, 88]> mul_245 = mul(x = tern_5_v, y = mul_245_y_0)[name = string("mul_245")];
            tensor<int32, [3]> reshape_44_shape_0 = const()[name = string("reshape_44_shape_0"), val = tensor<int32, [3]>([64, 2, 44])];
            tensor<fp16, [64, 2, 44]> reshape_44 = reshape(shape = reshape_44_shape_0, x = mul_245)[name = string("reshape_44")];
            tensor<int32, [3]> transpose_22_perm_0 = const()[name = string("transpose_22_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 64, 44]> transpose_20 = transpose(perm = transpose_20_perm_0, x = reshape_42)[name = string("transpose_43")];
            tensor<fp16, [8, 64, 44]> mul_246 = mul(x = transpose_20, y = transpose_20)[name = string("mul_246")];
            tensor<int32, [1]> reduce_mean_53_axes_0 = const()[name = string("reduce_mean_53_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_53_keep_dims_0 = const()[name = string("reduce_mean_53_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 64, 1]> reduce_mean_53 = reduce_mean(axes = reduce_mean_53_axes_0, keep_dims = reduce_mean_53_keep_dims_0, x = mul_246)[name = string("reduce_mean_53")];
            fp32 rsqrt_53_epsilon_0 = const()[name = string("rsqrt_53_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 64, 1]> rsqrt_53 = rsqrt(epsilon = rsqrt_53_epsilon_0, x = reduce_mean_53)[name = string("rsqrt_53")];
            tensor<fp16, [8, 64, 44]> mul_247 = mul(x = transpose_20, y = rsqrt_53)[name = string("mul_247")];
            tensor<fp16, [44]> mul_248_y_0 = const()[name = string("mul_248_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4092480)))];
            tensor<fp16, [8, 64, 44]> mul_248 = mul(x = mul_247, y = mul_248_y_0)[name = string("mul_248")];
            tensor<int32, [3]> slice_by_index_20_begin_0 = const()[name = string("slice_by_index_20_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_20_end_0 = const()[name = string("slice_by_index_20_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_20_end_mask_0 = const()[name = string("slice_by_index_20_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 64, 22]> slice_by_index_20 = slice_by_index(begin = slice_by_index_20_begin_0, end = slice_by_index_20_end_0, end_mask = slice_by_index_20_end_mask_0, x = mul_248)[name = string("slice_by_index_20")];
            tensor<int32, [3]> slice_by_index_21_begin_0 = const()[name = string("slice_by_index_21_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_21_end_0 = const()[name = string("slice_by_index_21_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_21_end_mask_0 = const()[name = string("slice_by_index_21_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 64, 22]> slice_by_index_21 = slice_by_index(begin = slice_by_index_21_begin_0, end = slice_by_index_21_end_0, end_mask = slice_by_index_21_end_mask_0, x = mul_248)[name = string("slice_by_index_21")];
            int32 concat_10_axis_0 = const()[name = string("concat_10_axis_0"), val = int32(-1)];
            bool concat_10_interleave_0 = const()[name = string("concat_10_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 64, 44]> concat_10 = concat(axis = concat_10_axis_0, interleave = concat_10_interleave_0, values = (slice_by_index_21, slice_by_index_20))[name = string("concat_10")];
            tensor<fp16, [44]> mul_249_y_0 = const()[name = string("mul_249_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 64, 44]> mul_249 = mul(x = concat_10, y = mul_249_y_0)[name = string("mul_249")];
            tensor<fp16, [8, 64, 44]> mul_250 = mul(x = mul_248, y = mul_11_y_0)[name = string("mul_250")];
            tensor<fp16, [8, 64, 44]> mul_251 = mul(x = mul_249, y = mul_12_y_0)[name = string("mul_251")];
            tensor<fp16, [8, 64, 44]> add_30 = add(x = mul_250, y = mul_251)[name = string("add_30")];
            tensor<fp16, [2, 64, 44]> transpose_21 = transpose(perm = transpose_21_perm_0, x = reshape_43)[name = string("transpose_42")];
            tensor<fp16, [2, 64, 44]> mul_252 = mul(x = transpose_21, y = transpose_21)[name = string("mul_252")];
            tensor<int32, [1]> reduce_mean_54_axes_0 = const()[name = string("reduce_mean_54_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_54_keep_dims_0 = const()[name = string("reduce_mean_54_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 64, 1]> reduce_mean_54 = reduce_mean(axes = reduce_mean_54_axes_0, keep_dims = reduce_mean_54_keep_dims_0, x = mul_252)[name = string("reduce_mean_54")];
            fp32 rsqrt_54_epsilon_0 = const()[name = string("rsqrt_54_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 64, 1]> rsqrt_54 = rsqrt(epsilon = rsqrt_54_epsilon_0, x = reduce_mean_54)[name = string("rsqrt_54")];
            tensor<fp16, [2, 64, 44]> mul_253 = mul(x = transpose_21, y = rsqrt_54)[name = string("mul_253")];
            tensor<fp16, [44]> mul_254_y_0 = const()[name = string("mul_254_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4092672)))];
            tensor<fp16, [2, 64, 44]> mul_254 = mul(x = mul_253, y = mul_254_y_0)[name = string("mul_254")];
            tensor<int32, [3]> slice_by_index_22_begin_0 = const()[name = string("slice_by_index_22_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_22_end_0 = const()[name = string("slice_by_index_22_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_22_end_mask_0 = const()[name = string("slice_by_index_22_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 64, 22]> slice_by_index_22 = slice_by_index(begin = slice_by_index_22_begin_0, end = slice_by_index_22_end_0, end_mask = slice_by_index_22_end_mask_0, x = mul_254)[name = string("slice_by_index_22")];
            tensor<int32, [3]> slice_by_index_23_begin_0 = const()[name = string("slice_by_index_23_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_23_end_0 = const()[name = string("slice_by_index_23_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_23_end_mask_0 = const()[name = string("slice_by_index_23_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 64, 22]> slice_by_index_23 = slice_by_index(begin = slice_by_index_23_begin_0, end = slice_by_index_23_end_0, end_mask = slice_by_index_23_end_mask_0, x = mul_254)[name = string("slice_by_index_23")];
            int32 concat_11_axis_0 = const()[name = string("concat_11_axis_0"), val = int32(-1)];
            bool concat_11_interleave_0 = const()[name = string("concat_11_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 64, 44]> concat_11 = concat(axis = concat_11_axis_0, interleave = concat_11_interleave_0, values = (slice_by_index_23, slice_by_index_22))[name = string("concat_11")];
            tensor<fp16, [44]> mul_255_y_0 = const()[name = string("mul_255_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 64, 44]> mul_255 = mul(x = concat_11, y = mul_255_y_0)[name = string("mul_255")];
            tensor<fp16, [2, 64, 44]> mul_256 = mul(x = mul_254, y = mul_11_y_0)[name = string("mul_256")];
            tensor<fp16, [2, 64, 44]> mul_257 = mul(x = mul_255, y = mul_12_y_0)[name = string("mul_257")];
            tensor<fp16, [2, 64, 44]> add_31 = add(x = mul_256, y = mul_257)[name = string("add_31")];
            tensor<int32, [4]> reshape_45_shape_0 = const()[name = string("reshape_45_shape_0"), val = tensor<int32, [4]>([2, 1, 64, 44])];
            tensor<fp16, [2, 1, 64, 44]> reshape_45 = reshape(shape = reshape_45_shape_0, x = add_31)[name = string("reshape_45")];
            tensor<int32, [4]> tile_10_reps_0 = const()[name = string("tile_10_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 64, 44]> tile_10 = tile(reps = tile_10_reps_0, x = reshape_45)[name = string("tile_10")];
            tensor<int32, [3]> reshape_46_shape_0 = const()[name = string("reshape_46_shape_0"), val = tensor<int32, [3]>([8, 64, 44])];
            tensor<fp16, [8, 64, 44]> reshape_46 = reshape(shape = reshape_46_shape_0, x = tile_10)[name = string("reshape_46")];
            tensor<int32, [4]> reshape_47_shape_0 = const()[name = string("reshape_47_shape_0"), val = tensor<int32, [4]>([2, 1, 64, 44])];
            tensor<fp16, [2, 64, 44]> transpose_22 = transpose(perm = transpose_22_perm_0, x = reshape_44)[name = string("transpose_41")];
            tensor<fp16, [2, 1, 64, 44]> reshape_47 = reshape(shape = reshape_47_shape_0, x = transpose_22)[name = string("reshape_47")];
            tensor<int32, [4]> tile_11_reps_0 = const()[name = string("tile_11_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 64, 44]> tile_11 = tile(reps = tile_11_reps_0, x = reshape_47)[name = string("tile_11")];
            tensor<int32, [3]> reshape_48_shape_0 = const()[name = string("reshape_48_shape_0"), val = tensor<int32, [3]>([8, 64, 44])];
            tensor<fp16, [8, 64, 44]> reshape_48 = reshape(shape = reshape_48_shape_0, x = tile_11)[name = string("reshape_48")];
            fp16 mul_258_y_0 = const()[name = string("mul_258_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 64, 44]> mul_258 = mul(x = add_30, y = mul_258_y_0)[name = string("mul_258")];
            bool matmul_10_transpose_y_0 = const()[name = string("matmul_10_transpose_y_0"), val = bool(true)];
            bool matmul_10_transpose_x_0 = const()[name = string("matmul_10_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 64, 64]> matmul_10 = matmul(transpose_x = matmul_10_transpose_x_0, transpose_y = matmul_10_transpose_y_0, x = mul_258, y = reshape_46)[name = string("matmul_10")];
            tensor<fp16, [8, 64, 64]> add_32 = add(x = matmul_10, y = reshape_1)[name = string("add_32")];
            int32 softmax_5_axis_0 = const()[name = string("softmax_5_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 64, 64]> softmax_5 = softmax(axis = softmax_5_axis_0, x = add_32)[name = string("softmax_5")];
            bool matmul_11_transpose_x_0 = const()[name = string("matmul_11_transpose_x_0"), val = bool(false)];
            bool matmul_11_transpose_y_0 = const()[name = string("matmul_11_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 64, 44]> matmul_11 = matmul(transpose_x = matmul_11_transpose_x_0, transpose_y = matmul_11_transpose_y_0, x = softmax_5, y = reshape_48)[name = string("matmul_11")];
            tensor<int32, [3]> transpose_23_perm_0 = const()[name = string("transpose_23_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_49_shape_0 = const()[name = string("reshape_49_shape_0"), val = tensor<int32, [2]>([64, 352])];
            tensor<fp16, [64, 8, 44]> transpose_23 = transpose(perm = transpose_23_perm_0, x = matmul_11)[name = string("transpose_40")];
            tensor<fp16, [64, 352]> reshape_49 = reshape(shape = reshape_49_shape_0, x = transpose_23)[name = string("reshape_49")];
            tensor<fp16, [64, 352]> mul_259 = mul(x = reshape_49, y = reshape_49)[name = string("mul_259")];
            tensor<int32, [1]> reduce_mean_55_axes_0 = const()[name = string("reduce_mean_55_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_55_keep_dims_0 = const()[name = string("reduce_mean_55_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_55 = reduce_mean(axes = reduce_mean_55_axes_0, keep_dims = reduce_mean_55_keep_dims_0, x = mul_259)[name = string("reduce_mean_55")];
            fp32 rsqrt_55_epsilon_0 = const()[name = string("rsqrt_55_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_55 = rsqrt(epsilon = rsqrt_55_epsilon_0, x = reduce_mean_55)[name = string("rsqrt_55")];
            tensor<fp16, [64, 352]> mul_260 = mul(x = reshape_49, y = rsqrt_55)[name = string("mul_260")];
            tensor<fp16, [352]> mul_261_y_0 = const()[name = string("mul_261_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4092864)))];
            tensor<fp16, [64, 352]> mul_261 = mul(x = mul_260, y = mul_261_y_0)[name = string("mul_261")];
            tensor<fp16, [352, 352]> tern_5_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4093632))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_5_o_weight_0_palettized")];
            tensor<fp16, [64, 352]> tern_5_o = linear(bias = linear_0_bias_0, weight = tern_5_o_weight_0_palettized, x = mul_261)[name = string("tern_5_o")];
            tensor<fp16, [352]> mul_262_y_0 = const()[name = string("mul_262_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4124672)))];
            tensor<fp16, [64, 352]> mul_262 = mul(x = tern_5_o, y = mul_262_y_0)[name = string("mul_262")];
            tensor<fp16, [64, 352]> add_33 = add(x = add_29, y = mul_262)[name = string("add_33")];
            tensor<fp16, [64, 352]> mul_263 = mul(x = add_33, y = add_33)[name = string("mul_263")];
            tensor<int32, [1]> reduce_mean_56_axes_0 = const()[name = string("reduce_mean_56_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_56_keep_dims_0 = const()[name = string("reduce_mean_56_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_56 = reduce_mean(axes = reduce_mean_56_axes_0, keep_dims = reduce_mean_56_keep_dims_0, x = mul_263)[name = string("reduce_mean_56")];
            fp32 rsqrt_56_epsilon_0 = const()[name = string("rsqrt_56_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_56 = rsqrt(epsilon = rsqrt_56_epsilon_0, x = reduce_mean_56)[name = string("rsqrt_56")];
            tensor<fp16, [64, 352]> mul_264 = mul(x = add_33, y = rsqrt_56)[name = string("mul_264")];
            tensor<fp16, [352]> mul_265_y_0 = const()[name = string("mul_265_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4125440)))];
            tensor<fp16, [64, 352]> mul_265 = mul(x = mul_264, y = mul_265_y_0)[name = string("mul_265")];
            tensor<fp16, [64, 352]> mul_266 = mul(x = mul_265, y = mul_265)[name = string("mul_266")];
            tensor<int32, [1]> reduce_mean_57_axes_0 = const()[name = string("reduce_mean_57_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_57_keep_dims_0 = const()[name = string("reduce_mean_57_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_57 = reduce_mean(axes = reduce_mean_57_axes_0, keep_dims = reduce_mean_57_keep_dims_0, x = mul_266)[name = string("reduce_mean_57")];
            fp32 rsqrt_57_epsilon_0 = const()[name = string("rsqrt_57_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_57 = rsqrt(epsilon = rsqrt_57_epsilon_0, x = reduce_mean_57)[name = string("rsqrt_57")];
            tensor<fp16, [64, 352]> mul_267 = mul(x = mul_265, y = rsqrt_57)[name = string("mul_267")];
            tensor<fp16, [352]> mul_268_y_0 = const()[name = string("mul_268_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4126208)))];
            tensor<fp16, [64, 352]> mul_268 = mul(x = mul_267, y = mul_268_y_0)[name = string("mul_268")];
            tensor<fp16, [960, 352]> tern_5_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4126976))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_5_w1_weight_0_palettized")];
            tensor<fp16, [64, 960]> tern_5_w1 = linear(bias = linear_4_bias_0, weight = tern_5_w1_weight_0_palettized, x = mul_268)[name = string("tern_5_w1")];
            tensor<fp16, [960]> mul_269_y_0 = const()[name = string("mul_269_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4211520)))];
            tensor<fp16, [64, 960]> mul_269 = mul(x = tern_5_w1, y = mul_269_y_0)[name = string("mul_269")];
            tensor<fp16, [352]> mul_272_y_0 = const()[name = string("mul_272_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4213504)))];
            tensor<fp16, [64, 352]> mul_272 = mul(x = mul_267, y = mul_272_y_0)[name = string("mul_272")];
            tensor<fp16, [960, 352]> tern_5_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4214272))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_5_w3_weight_0_palettized")];
            tensor<fp16, [64, 960]> tern_5_w3 = linear(bias = linear_4_bias_0, weight = tern_5_w3_weight_0_palettized, x = mul_272)[name = string("tern_5_w3")];
            tensor<fp16, [960]> mul_273_y_0 = const()[name = string("mul_273_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4298816)))];
            tensor<fp16, [64, 960]> mul_273 = mul(x = tern_5_w3, y = mul_273_y_0)[name = string("mul_273")];
            fp16 mul_274_y_0 = const()[name = string("mul_274_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [64, 960]> mul_274 = mul(x = mul_269, y = mul_274_y_0)[name = string("mul_274")];
            tensor<fp16, [64, 960]> tanh_5 = tanh(x = mul_274)[name = string("tanh_5")];
            fp16 mul_275_x_0 = const()[name = string("mul_275_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [64, 960]> mul_275 = mul(x = mul_275_x_0, y = tanh_5)[name = string("mul_275")];
            fp16 add_34_x_0 = const()[name = string("add_34_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [64, 960]> add_34 = add(x = add_34_x_0, y = mul_275)[name = string("add_34")];
            tensor<fp16, [64, 960]> mul_276 = mul(x = mul_269, y = add_34)[name = string("mul_276")];
            tensor<fp16, [64, 960]> mul_277 = mul(x = mul_276, y = mul_273)[name = string("mul_277")];
            tensor<fp16, [64, 960]> mul_278 = mul(x = mul_277, y = mul_277)[name = string("mul_278")];
            tensor<int32, [1]> reduce_mean_59_axes_0 = const()[name = string("reduce_mean_59_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_59_keep_dims_0 = const()[name = string("reduce_mean_59_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_59 = reduce_mean(axes = reduce_mean_59_axes_0, keep_dims = reduce_mean_59_keep_dims_0, x = mul_278)[name = string("reduce_mean_59")];
            fp32 rsqrt_59_epsilon_0 = const()[name = string("rsqrt_59_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_59 = rsqrt(epsilon = rsqrt_59_epsilon_0, x = reduce_mean_59)[name = string("rsqrt_59")];
            tensor<fp16, [64, 960]> mul_279 = mul(x = mul_277, y = rsqrt_59)[name = string("mul_279")];
            tensor<fp16, [960]> mul_280_y_0 = const()[name = string("mul_280_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4300800)))];
            tensor<fp16, [64, 960]> mul_280 = mul(x = mul_279, y = mul_280_y_0)[name = string("mul_280")];
            tensor<fp16, [352, 960]> tern_5_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4302784))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_5_w2_weight_0_palettized")];
            tensor<fp16, [64, 352]> tern_5_w2 = linear(bias = linear_0_bias_0, weight = tern_5_w2_weight_0_palettized, x = mul_280)[name = string("tern_5_w2")];
            tensor<fp16, [352]> mul_281_y_0 = const()[name = string("mul_281_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4387328)))];
            tensor<fp16, [64, 352]> mul_281 = mul(x = tern_5_w2, y = mul_281_y_0)[name = string("mul_281")];
            tensor<fp16, [64, 352]> add_35 = add(x = add_33, y = mul_281)[name = string("add_35")];
            tensor<fp16, [64, 352]> mul_282 = mul(x = add_35, y = add_35)[name = string("mul_282")];
            tensor<int32, [1]> reduce_mean_60_axes_0 = const()[name = string("reduce_mean_60_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_60_keep_dims_0 = const()[name = string("reduce_mean_60_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_60 = reduce_mean(axes = reduce_mean_60_axes_0, keep_dims = reduce_mean_60_keep_dims_0, x = mul_282)[name = string("reduce_mean_60")];
            fp32 rsqrt_60_epsilon_0 = const()[name = string("rsqrt_60_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_60 = rsqrt(epsilon = rsqrt_60_epsilon_0, x = reduce_mean_60)[name = string("rsqrt_60")];
            tensor<fp16, [64, 352]> mul_283 = mul(x = add_35, y = rsqrt_60)[name = string("mul_283")];
            tensor<fp16, [352]> mul_284_y_0 = const()[name = string("mul_284_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4388096)))];
            tensor<fp16, [64, 352]> mul_284 = mul(x = mul_283, y = mul_284_y_0)[name = string("mul_284")];
            tensor<fp16, [64, 352]> mul_285 = mul(x = mul_284, y = mul_284)[name = string("mul_285")];
            tensor<int32, [1]> reduce_mean_61_axes_0 = const()[name = string("reduce_mean_61_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_61_keep_dims_0 = const()[name = string("reduce_mean_61_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_61 = reduce_mean(axes = reduce_mean_61_axes_0, keep_dims = reduce_mean_61_keep_dims_0, x = mul_285)[name = string("reduce_mean_61")];
            fp32 rsqrt_61_epsilon_0 = const()[name = string("rsqrt_61_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_61 = rsqrt(epsilon = rsqrt_61_epsilon_0, x = reduce_mean_61)[name = string("rsqrt_61")];
            tensor<fp16, [64, 352]> mul_286 = mul(x = mul_284, y = rsqrt_61)[name = string("mul_286")];
            tensor<fp16, [352]> mul_287_y_0 = const()[name = string("mul_287_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4388864)))];
            tensor<fp16, [64, 352]> mul_287 = mul(x = mul_286, y = mul_287_y_0)[name = string("mul_287")];
            tensor<fp16, [352, 352]> tern_6_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4389632))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_6_q_weight_0_palettized")];
            tensor<fp16, [64, 352]> tern_6_q = linear(bias = linear_0_bias_0, weight = tern_6_q_weight_0_palettized, x = mul_287)[name = string("tern_6_q")];
            tensor<fp16, [352]> mul_288_y_0 = const()[name = string("mul_288_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4420672)))];
            tensor<fp16, [64, 352]> mul_288 = mul(x = tern_6_q, y = mul_288_y_0)[name = string("mul_288")];
            tensor<int32, [3]> reshape_50_shape_0 = const()[name = string("reshape_50_shape_0"), val = tensor<int32, [3]>([64, 8, 44])];
            tensor<fp16, [64, 8, 44]> reshape_50 = reshape(shape = reshape_50_shape_0, x = mul_288)[name = string("reshape_50")];
            tensor<int32, [3]> transpose_24_perm_0 = const()[name = string("transpose_24_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_291_y_0 = const()[name = string("mul_291_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4421440)))];
            tensor<fp16, [64, 352]> mul_291 = mul(x = mul_286, y = mul_291_y_0)[name = string("mul_291")];
            tensor<fp16, [88, 352]> tern_6_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4422208))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_6_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_6_k_bias_0 = const()[name = string("tern_6_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [64, 88]> tern_6_k = linear(bias = tern_6_k_bias_0, weight = tern_6_k_weight_0_palettized, x = mul_291)[name = string("tern_6_k")];
            tensor<fp16, [88]> mul_292_y_0 = const()[name = string("mul_292_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4430016)))];
            tensor<fp16, [64, 88]> mul_292 = mul(x = tern_6_k, y = mul_292_y_0)[name = string("mul_292")];
            tensor<int32, [3]> reshape_51_shape_0 = const()[name = string("reshape_51_shape_0"), val = tensor<int32, [3]>([64, 2, 44])];
            tensor<fp16, [64, 2, 44]> reshape_51 = reshape(shape = reshape_51_shape_0, x = mul_292)[name = string("reshape_51")];
            tensor<int32, [3]> transpose_25_perm_0 = const()[name = string("transpose_25_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_295_y_0 = const()[name = string("mul_295_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4430272)))];
            tensor<fp16, [64, 352]> mul_295 = mul(x = mul_286, y = mul_295_y_0)[name = string("mul_295")];
            tensor<fp16, [88, 352]> tern_6_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4431040))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_6_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_6_v_bias_0 = const()[name = string("tern_6_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [64, 88]> tern_6_v = linear(bias = tern_6_v_bias_0, weight = tern_6_v_weight_0_palettized, x = mul_295)[name = string("tern_6_v")];
            tensor<fp16, [88]> mul_296_y_0 = const()[name = string("mul_296_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4438848)))];
            tensor<fp16, [64, 88]> mul_296 = mul(x = tern_6_v, y = mul_296_y_0)[name = string("mul_296")];
            tensor<int32, [3]> reshape_52_shape_0 = const()[name = string("reshape_52_shape_0"), val = tensor<int32, [3]>([64, 2, 44])];
            tensor<fp16, [64, 2, 44]> reshape_52 = reshape(shape = reshape_52_shape_0, x = mul_296)[name = string("reshape_52")];
            tensor<int32, [3]> transpose_26_perm_0 = const()[name = string("transpose_26_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 64, 44]> transpose_24 = transpose(perm = transpose_24_perm_0, x = reshape_50)[name = string("transpose_39")];
            tensor<fp16, [8, 64, 44]> mul_297 = mul(x = transpose_24, y = transpose_24)[name = string("mul_297")];
            tensor<int32, [1]> reduce_mean_64_axes_0 = const()[name = string("reduce_mean_64_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_64_keep_dims_0 = const()[name = string("reduce_mean_64_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 64, 1]> reduce_mean_64 = reduce_mean(axes = reduce_mean_64_axes_0, keep_dims = reduce_mean_64_keep_dims_0, x = mul_297)[name = string("reduce_mean_64")];
            fp32 rsqrt_64_epsilon_0 = const()[name = string("rsqrt_64_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 64, 1]> rsqrt_64 = rsqrt(epsilon = rsqrt_64_epsilon_0, x = reduce_mean_64)[name = string("rsqrt_64")];
            tensor<fp16, [8, 64, 44]> mul_298 = mul(x = transpose_24, y = rsqrt_64)[name = string("mul_298")];
            tensor<fp16, [44]> mul_299_y_0 = const()[name = string("mul_299_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4439104)))];
            tensor<fp16, [8, 64, 44]> mul_299 = mul(x = mul_298, y = mul_299_y_0)[name = string("mul_299")];
            tensor<int32, [3]> slice_by_index_24_begin_0 = const()[name = string("slice_by_index_24_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_24_end_0 = const()[name = string("slice_by_index_24_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_24_end_mask_0 = const()[name = string("slice_by_index_24_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 64, 22]> slice_by_index_24 = slice_by_index(begin = slice_by_index_24_begin_0, end = slice_by_index_24_end_0, end_mask = slice_by_index_24_end_mask_0, x = mul_299)[name = string("slice_by_index_24")];
            tensor<int32, [3]> slice_by_index_25_begin_0 = const()[name = string("slice_by_index_25_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_25_end_0 = const()[name = string("slice_by_index_25_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_25_end_mask_0 = const()[name = string("slice_by_index_25_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 64, 22]> slice_by_index_25 = slice_by_index(begin = slice_by_index_25_begin_0, end = slice_by_index_25_end_0, end_mask = slice_by_index_25_end_mask_0, x = mul_299)[name = string("slice_by_index_25")];
            int32 concat_12_axis_0 = const()[name = string("concat_12_axis_0"), val = int32(-1)];
            bool concat_12_interleave_0 = const()[name = string("concat_12_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 64, 44]> concat_12 = concat(axis = concat_12_axis_0, interleave = concat_12_interleave_0, values = (slice_by_index_25, slice_by_index_24))[name = string("concat_12")];
            tensor<fp16, [44]> mul_300_y_0 = const()[name = string("mul_300_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 64, 44]> mul_300 = mul(x = concat_12, y = mul_300_y_0)[name = string("mul_300")];
            tensor<fp16, [8, 64, 44]> mul_301 = mul(x = mul_299, y = mul_11_y_0)[name = string("mul_301")];
            tensor<fp16, [8, 64, 44]> mul_302 = mul(x = mul_300, y = mul_12_y_0)[name = string("mul_302")];
            tensor<fp16, [8, 64, 44]> add_36 = add(x = mul_301, y = mul_302)[name = string("add_36")];
            tensor<fp16, [2, 64, 44]> transpose_25 = transpose(perm = transpose_25_perm_0, x = reshape_51)[name = string("transpose_38")];
            tensor<fp16, [2, 64, 44]> mul_303 = mul(x = transpose_25, y = transpose_25)[name = string("mul_303")];
            tensor<int32, [1]> reduce_mean_65_axes_0 = const()[name = string("reduce_mean_65_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_65_keep_dims_0 = const()[name = string("reduce_mean_65_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 64, 1]> reduce_mean_65 = reduce_mean(axes = reduce_mean_65_axes_0, keep_dims = reduce_mean_65_keep_dims_0, x = mul_303)[name = string("reduce_mean_65")];
            fp32 rsqrt_65_epsilon_0 = const()[name = string("rsqrt_65_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 64, 1]> rsqrt_65 = rsqrt(epsilon = rsqrt_65_epsilon_0, x = reduce_mean_65)[name = string("rsqrt_65")];
            tensor<fp16, [2, 64, 44]> mul_304 = mul(x = transpose_25, y = rsqrt_65)[name = string("mul_304")];
            tensor<fp16, [44]> mul_305_y_0 = const()[name = string("mul_305_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4439296)))];
            tensor<fp16, [2, 64, 44]> mul_305 = mul(x = mul_304, y = mul_305_y_0)[name = string("mul_305")];
            tensor<int32, [3]> slice_by_index_26_begin_0 = const()[name = string("slice_by_index_26_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_26_end_0 = const()[name = string("slice_by_index_26_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_26_end_mask_0 = const()[name = string("slice_by_index_26_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 64, 22]> slice_by_index_26 = slice_by_index(begin = slice_by_index_26_begin_0, end = slice_by_index_26_end_0, end_mask = slice_by_index_26_end_mask_0, x = mul_305)[name = string("slice_by_index_26")];
            tensor<int32, [3]> slice_by_index_27_begin_0 = const()[name = string("slice_by_index_27_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_27_end_0 = const()[name = string("slice_by_index_27_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_27_end_mask_0 = const()[name = string("slice_by_index_27_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 64, 22]> slice_by_index_27 = slice_by_index(begin = slice_by_index_27_begin_0, end = slice_by_index_27_end_0, end_mask = slice_by_index_27_end_mask_0, x = mul_305)[name = string("slice_by_index_27")];
            int32 concat_13_axis_0 = const()[name = string("concat_13_axis_0"), val = int32(-1)];
            bool concat_13_interleave_0 = const()[name = string("concat_13_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 64, 44]> concat_13 = concat(axis = concat_13_axis_0, interleave = concat_13_interleave_0, values = (slice_by_index_27, slice_by_index_26))[name = string("concat_13")];
            tensor<fp16, [44]> mul_306_y_0 = const()[name = string("mul_306_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 64, 44]> mul_306 = mul(x = concat_13, y = mul_306_y_0)[name = string("mul_306")];
            tensor<fp16, [2, 64, 44]> mul_307 = mul(x = mul_305, y = mul_11_y_0)[name = string("mul_307")];
            tensor<fp16, [2, 64, 44]> mul_308 = mul(x = mul_306, y = mul_12_y_0)[name = string("mul_308")];
            tensor<fp16, [2, 64, 44]> add_37 = add(x = mul_307, y = mul_308)[name = string("add_37")];
            tensor<int32, [4]> reshape_53_shape_0 = const()[name = string("reshape_53_shape_0"), val = tensor<int32, [4]>([2, 1, 64, 44])];
            tensor<fp16, [2, 1, 64, 44]> reshape_53 = reshape(shape = reshape_53_shape_0, x = add_37)[name = string("reshape_53")];
            tensor<int32, [4]> tile_12_reps_0 = const()[name = string("tile_12_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 64, 44]> tile_12 = tile(reps = tile_12_reps_0, x = reshape_53)[name = string("tile_12")];
            tensor<int32, [3]> reshape_54_shape_0 = const()[name = string("reshape_54_shape_0"), val = tensor<int32, [3]>([8, 64, 44])];
            tensor<fp16, [8, 64, 44]> reshape_54 = reshape(shape = reshape_54_shape_0, x = tile_12)[name = string("reshape_54")];
            tensor<int32, [4]> reshape_55_shape_0 = const()[name = string("reshape_55_shape_0"), val = tensor<int32, [4]>([2, 1, 64, 44])];
            tensor<fp16, [2, 64, 44]> transpose_26 = transpose(perm = transpose_26_perm_0, x = reshape_52)[name = string("transpose_37")];
            tensor<fp16, [2, 1, 64, 44]> reshape_55 = reshape(shape = reshape_55_shape_0, x = transpose_26)[name = string("reshape_55")];
            tensor<int32, [4]> tile_13_reps_0 = const()[name = string("tile_13_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 64, 44]> tile_13 = tile(reps = tile_13_reps_0, x = reshape_55)[name = string("tile_13")];
            tensor<int32, [3]> reshape_56_shape_0 = const()[name = string("reshape_56_shape_0"), val = tensor<int32, [3]>([8, 64, 44])];
            tensor<fp16, [8, 64, 44]> reshape_56 = reshape(shape = reshape_56_shape_0, x = tile_13)[name = string("reshape_56")];
            fp16 mul_309_y_0 = const()[name = string("mul_309_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 64, 44]> mul_309 = mul(x = add_36, y = mul_309_y_0)[name = string("mul_309")];
            bool matmul_12_transpose_y_0 = const()[name = string("matmul_12_transpose_y_0"), val = bool(true)];
            bool matmul_12_transpose_x_0 = const()[name = string("matmul_12_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 64, 64]> matmul_12 = matmul(transpose_x = matmul_12_transpose_x_0, transpose_y = matmul_12_transpose_y_0, x = mul_309, y = reshape_54)[name = string("matmul_12")];
            tensor<fp16, [8, 64, 64]> add_38 = add(x = matmul_12, y = reshape_1)[name = string("add_38")];
            int32 softmax_6_axis_0 = const()[name = string("softmax_6_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 64, 64]> softmax_6 = softmax(axis = softmax_6_axis_0, x = add_38)[name = string("softmax_6")];
            bool matmul_13_transpose_x_0 = const()[name = string("matmul_13_transpose_x_0"), val = bool(false)];
            bool matmul_13_transpose_y_0 = const()[name = string("matmul_13_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 64, 44]> matmul_13 = matmul(transpose_x = matmul_13_transpose_x_0, transpose_y = matmul_13_transpose_y_0, x = softmax_6, y = reshape_56)[name = string("matmul_13")];
            tensor<int32, [3]> transpose_27_perm_0 = const()[name = string("transpose_27_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_57_shape_0 = const()[name = string("reshape_57_shape_0"), val = tensor<int32, [2]>([64, 352])];
            tensor<fp16, [64, 8, 44]> transpose_27 = transpose(perm = transpose_27_perm_0, x = matmul_13)[name = string("transpose_36")];
            tensor<fp16, [64, 352]> reshape_57 = reshape(shape = reshape_57_shape_0, x = transpose_27)[name = string("reshape_57")];
            tensor<fp16, [64, 352]> mul_310 = mul(x = reshape_57, y = reshape_57)[name = string("mul_310")];
            tensor<int32, [1]> reduce_mean_66_axes_0 = const()[name = string("reduce_mean_66_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_66_keep_dims_0 = const()[name = string("reduce_mean_66_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_66 = reduce_mean(axes = reduce_mean_66_axes_0, keep_dims = reduce_mean_66_keep_dims_0, x = mul_310)[name = string("reduce_mean_66")];
            fp32 rsqrt_66_epsilon_0 = const()[name = string("rsqrt_66_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_66 = rsqrt(epsilon = rsqrt_66_epsilon_0, x = reduce_mean_66)[name = string("rsqrt_66")];
            tensor<fp16, [64, 352]> mul_311 = mul(x = reshape_57, y = rsqrt_66)[name = string("mul_311")];
            tensor<fp16, [352]> mul_312_y_0 = const()[name = string("mul_312_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4439488)))];
            tensor<fp16, [64, 352]> mul_312 = mul(x = mul_311, y = mul_312_y_0)[name = string("mul_312")];
            tensor<fp16, [352, 352]> tern_6_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4440256))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_6_o_weight_0_palettized")];
            tensor<fp16, [64, 352]> tern_6_o = linear(bias = linear_0_bias_0, weight = tern_6_o_weight_0_palettized, x = mul_312)[name = string("tern_6_o")];
            tensor<fp16, [352]> mul_313_y_0 = const()[name = string("mul_313_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4471296)))];
            tensor<fp16, [64, 352]> mul_313 = mul(x = tern_6_o, y = mul_313_y_0)[name = string("mul_313")];
            tensor<fp16, [64, 352]> add_39 = add(x = add_35, y = mul_313)[name = string("add_39")];
            tensor<fp16, [64, 352]> mul_314 = mul(x = add_39, y = add_39)[name = string("mul_314")];
            tensor<int32, [1]> reduce_mean_67_axes_0 = const()[name = string("reduce_mean_67_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_67_keep_dims_0 = const()[name = string("reduce_mean_67_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_67 = reduce_mean(axes = reduce_mean_67_axes_0, keep_dims = reduce_mean_67_keep_dims_0, x = mul_314)[name = string("reduce_mean_67")];
            fp32 rsqrt_67_epsilon_0 = const()[name = string("rsqrt_67_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_67 = rsqrt(epsilon = rsqrt_67_epsilon_0, x = reduce_mean_67)[name = string("rsqrt_67")];
            tensor<fp16, [64, 352]> mul_315 = mul(x = add_39, y = rsqrt_67)[name = string("mul_315")];
            tensor<fp16, [352]> mul_316_y_0 = const()[name = string("mul_316_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4472064)))];
            tensor<fp16, [64, 352]> mul_316 = mul(x = mul_315, y = mul_316_y_0)[name = string("mul_316")];
            tensor<fp16, [64, 352]> mul_317 = mul(x = mul_316, y = mul_316)[name = string("mul_317")];
            tensor<int32, [1]> reduce_mean_68_axes_0 = const()[name = string("reduce_mean_68_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_68_keep_dims_0 = const()[name = string("reduce_mean_68_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_68 = reduce_mean(axes = reduce_mean_68_axes_0, keep_dims = reduce_mean_68_keep_dims_0, x = mul_317)[name = string("reduce_mean_68")];
            fp32 rsqrt_68_epsilon_0 = const()[name = string("rsqrt_68_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_68 = rsqrt(epsilon = rsqrt_68_epsilon_0, x = reduce_mean_68)[name = string("rsqrt_68")];
            tensor<fp16, [64, 352]> mul_318 = mul(x = mul_316, y = rsqrt_68)[name = string("mul_318")];
            tensor<fp16, [352]> mul_319_y_0 = const()[name = string("mul_319_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4472832)))];
            tensor<fp16, [64, 352]> mul_319 = mul(x = mul_318, y = mul_319_y_0)[name = string("mul_319")];
            tensor<fp16, [960, 352]> tern_6_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4473600))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_6_w1_weight_0_palettized")];
            tensor<fp16, [64, 960]> tern_6_w1 = linear(bias = linear_4_bias_0, weight = tern_6_w1_weight_0_palettized, x = mul_319)[name = string("tern_6_w1")];
            tensor<fp16, [960]> mul_320_y_0 = const()[name = string("mul_320_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4558144)))];
            tensor<fp16, [64, 960]> mul_320 = mul(x = tern_6_w1, y = mul_320_y_0)[name = string("mul_320")];
            tensor<fp16, [352]> mul_323_y_0 = const()[name = string("mul_323_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4560128)))];
            tensor<fp16, [64, 352]> mul_323 = mul(x = mul_318, y = mul_323_y_0)[name = string("mul_323")];
            tensor<fp16, [960, 352]> tern_6_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4560896))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_6_w3_weight_0_palettized")];
            tensor<fp16, [64, 960]> tern_6_w3 = linear(bias = linear_4_bias_0, weight = tern_6_w3_weight_0_palettized, x = mul_323)[name = string("tern_6_w3")];
            tensor<fp16, [960]> mul_324_y_0 = const()[name = string("mul_324_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4645440)))];
            tensor<fp16, [64, 960]> mul_324 = mul(x = tern_6_w3, y = mul_324_y_0)[name = string("mul_324")];
            fp16 mul_325_y_0 = const()[name = string("mul_325_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [64, 960]> mul_325 = mul(x = mul_320, y = mul_325_y_0)[name = string("mul_325")];
            tensor<fp16, [64, 960]> tanh_6 = tanh(x = mul_325)[name = string("tanh_6")];
            fp16 mul_326_x_0 = const()[name = string("mul_326_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [64, 960]> mul_326 = mul(x = mul_326_x_0, y = tanh_6)[name = string("mul_326")];
            fp16 add_40_x_0 = const()[name = string("add_40_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [64, 960]> add_40 = add(x = add_40_x_0, y = mul_326)[name = string("add_40")];
            tensor<fp16, [64, 960]> mul_327 = mul(x = mul_320, y = add_40)[name = string("mul_327")];
            tensor<fp16, [64, 960]> mul_328 = mul(x = mul_327, y = mul_324)[name = string("mul_328")];
            tensor<fp16, [64, 960]> mul_329 = mul(x = mul_328, y = mul_328)[name = string("mul_329")];
            tensor<int32, [1]> reduce_mean_70_axes_0 = const()[name = string("reduce_mean_70_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_70_keep_dims_0 = const()[name = string("reduce_mean_70_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_70 = reduce_mean(axes = reduce_mean_70_axes_0, keep_dims = reduce_mean_70_keep_dims_0, x = mul_329)[name = string("reduce_mean_70")];
            fp32 rsqrt_70_epsilon_0 = const()[name = string("rsqrt_70_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_70 = rsqrt(epsilon = rsqrt_70_epsilon_0, x = reduce_mean_70)[name = string("rsqrt_70")];
            tensor<fp16, [64, 960]> mul_330 = mul(x = mul_328, y = rsqrt_70)[name = string("mul_330")];
            tensor<fp16, [960]> mul_331_y_0 = const()[name = string("mul_331_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4647424)))];
            tensor<fp16, [64, 960]> mul_331 = mul(x = mul_330, y = mul_331_y_0)[name = string("mul_331")];
            tensor<fp16, [352, 960]> tern_6_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4649408))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_6_w2_weight_0_palettized")];
            tensor<fp16, [64, 352]> tern_6_w2 = linear(bias = linear_0_bias_0, weight = tern_6_w2_weight_0_palettized, x = mul_331)[name = string("tern_6_w2")];
            tensor<fp16, [352]> mul_332_y_0 = const()[name = string("mul_332_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4733952)))];
            tensor<fp16, [64, 352]> mul_332 = mul(x = tern_6_w2, y = mul_332_y_0)[name = string("mul_332")];
            tensor<fp16, [64, 352]> add_41 = add(x = add_39, y = mul_332)[name = string("add_41")];
            tensor<fp16, [64, 352]> mul_333 = mul(x = add_41, y = add_41)[name = string("mul_333")];
            tensor<int32, [1]> reduce_mean_71_axes_0 = const()[name = string("reduce_mean_71_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_71_keep_dims_0 = const()[name = string("reduce_mean_71_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_71 = reduce_mean(axes = reduce_mean_71_axes_0, keep_dims = reduce_mean_71_keep_dims_0, x = mul_333)[name = string("reduce_mean_71")];
            fp32 rsqrt_71_epsilon_0 = const()[name = string("rsqrt_71_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_71 = rsqrt(epsilon = rsqrt_71_epsilon_0, x = reduce_mean_71)[name = string("rsqrt_71")];
            tensor<fp16, [64, 352]> mul_334 = mul(x = add_41, y = rsqrt_71)[name = string("mul_334")];
            tensor<fp16, [352]> mul_335_y_0 = const()[name = string("mul_335_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4734720)))];
            tensor<fp16, [64, 352]> mul_335 = mul(x = mul_334, y = mul_335_y_0)[name = string("mul_335")];
            tensor<fp16, [64, 352]> mul_336 = mul(x = mul_335, y = mul_335)[name = string("mul_336")];
            tensor<int32, [1]> reduce_mean_72_axes_0 = const()[name = string("reduce_mean_72_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_72_keep_dims_0 = const()[name = string("reduce_mean_72_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_72 = reduce_mean(axes = reduce_mean_72_axes_0, keep_dims = reduce_mean_72_keep_dims_0, x = mul_336)[name = string("reduce_mean_72")];
            fp32 rsqrt_72_epsilon_0 = const()[name = string("rsqrt_72_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_72 = rsqrt(epsilon = rsqrt_72_epsilon_0, x = reduce_mean_72)[name = string("rsqrt_72")];
            tensor<fp16, [64, 352]> mul_337 = mul(x = mul_335, y = rsqrt_72)[name = string("mul_337")];
            tensor<fp16, [352]> mul_338_y_0 = const()[name = string("mul_338_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4735488)))];
            tensor<fp16, [64, 352]> mul_338 = mul(x = mul_337, y = mul_338_y_0)[name = string("mul_338")];
            tensor<fp16, [352, 352]> tern_7_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4736256))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_7_q_weight_0_palettized")];
            tensor<fp16, [64, 352]> tern_7_q = linear(bias = linear_0_bias_0, weight = tern_7_q_weight_0_palettized, x = mul_338)[name = string("tern_7_q")];
            tensor<fp16, [352]> mul_339_y_0 = const()[name = string("mul_339_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4767296)))];
            tensor<fp16, [64, 352]> mul_339 = mul(x = tern_7_q, y = mul_339_y_0)[name = string("mul_339")];
            tensor<int32, [3]> reshape_58_shape_0 = const()[name = string("reshape_58_shape_0"), val = tensor<int32, [3]>([64, 8, 44])];
            tensor<fp16, [64, 8, 44]> reshape_58 = reshape(shape = reshape_58_shape_0, x = mul_339)[name = string("reshape_58")];
            tensor<int32, [3]> transpose_28_perm_0 = const()[name = string("transpose_28_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_342_y_0 = const()[name = string("mul_342_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4768064)))];
            tensor<fp16, [64, 352]> mul_342 = mul(x = mul_337, y = mul_342_y_0)[name = string("mul_342")];
            tensor<fp16, [88, 352]> tern_7_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4768832))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_7_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_7_k_bias_0 = const()[name = string("tern_7_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [64, 88]> tern_7_k = linear(bias = tern_7_k_bias_0, weight = tern_7_k_weight_0_palettized, x = mul_342)[name = string("tern_7_k")];
            tensor<fp16, [88]> mul_343_y_0 = const()[name = string("mul_343_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4776640)))];
            tensor<fp16, [64, 88]> mul_343 = mul(x = tern_7_k, y = mul_343_y_0)[name = string("mul_343")];
            tensor<int32, [3]> reshape_59_shape_0 = const()[name = string("reshape_59_shape_0"), val = tensor<int32, [3]>([64, 2, 44])];
            tensor<fp16, [64, 2, 44]> reshape_59 = reshape(shape = reshape_59_shape_0, x = mul_343)[name = string("reshape_59")];
            tensor<int32, [3]> transpose_29_perm_0 = const()[name = string("transpose_29_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_346_y_0 = const()[name = string("mul_346_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4776896)))];
            tensor<fp16, [64, 352]> mul_346 = mul(x = mul_337, y = mul_346_y_0)[name = string("mul_346")];
            tensor<fp16, [88, 352]> tern_7_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4777664))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_7_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_7_v_bias_0 = const()[name = string("tern_7_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [64, 88]> tern_7_v = linear(bias = tern_7_v_bias_0, weight = tern_7_v_weight_0_palettized, x = mul_346)[name = string("tern_7_v")];
            tensor<fp16, [88]> mul_347_y_0 = const()[name = string("mul_347_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4785472)))];
            tensor<fp16, [64, 88]> mul_347 = mul(x = tern_7_v, y = mul_347_y_0)[name = string("mul_347")];
            tensor<int32, [3]> reshape_60_shape_0 = const()[name = string("reshape_60_shape_0"), val = tensor<int32, [3]>([64, 2, 44])];
            tensor<fp16, [64, 2, 44]> reshape_60 = reshape(shape = reshape_60_shape_0, x = mul_347)[name = string("reshape_60")];
            tensor<int32, [3]> transpose_30_perm_0 = const()[name = string("transpose_30_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 64, 44]> transpose_28 = transpose(perm = transpose_28_perm_0, x = reshape_58)[name = string("transpose_35")];
            tensor<fp16, [8, 64, 44]> mul_348 = mul(x = transpose_28, y = transpose_28)[name = string("mul_348")];
            tensor<int32, [1]> reduce_mean_75_axes_0 = const()[name = string("reduce_mean_75_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_75_keep_dims_0 = const()[name = string("reduce_mean_75_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 64, 1]> reduce_mean_75 = reduce_mean(axes = reduce_mean_75_axes_0, keep_dims = reduce_mean_75_keep_dims_0, x = mul_348)[name = string("reduce_mean_75")];
            fp32 rsqrt_75_epsilon_0 = const()[name = string("rsqrt_75_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 64, 1]> rsqrt_75 = rsqrt(epsilon = rsqrt_75_epsilon_0, x = reduce_mean_75)[name = string("rsqrt_75")];
            tensor<fp16, [8, 64, 44]> mul_349 = mul(x = transpose_28, y = rsqrt_75)[name = string("mul_349")];
            tensor<fp16, [44]> mul_350_y_0 = const()[name = string("mul_350_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4785728)))];
            tensor<fp16, [8, 64, 44]> mul_350 = mul(x = mul_349, y = mul_350_y_0)[name = string("mul_350")];
            tensor<int32, [3]> slice_by_index_28_begin_0 = const()[name = string("slice_by_index_28_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_28_end_0 = const()[name = string("slice_by_index_28_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_28_end_mask_0 = const()[name = string("slice_by_index_28_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 64, 22]> slice_by_index_28 = slice_by_index(begin = slice_by_index_28_begin_0, end = slice_by_index_28_end_0, end_mask = slice_by_index_28_end_mask_0, x = mul_350)[name = string("slice_by_index_28")];
            tensor<int32, [3]> slice_by_index_29_begin_0 = const()[name = string("slice_by_index_29_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_29_end_0 = const()[name = string("slice_by_index_29_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_29_end_mask_0 = const()[name = string("slice_by_index_29_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 64, 22]> slice_by_index_29 = slice_by_index(begin = slice_by_index_29_begin_0, end = slice_by_index_29_end_0, end_mask = slice_by_index_29_end_mask_0, x = mul_350)[name = string("slice_by_index_29")];
            int32 concat_14_axis_0 = const()[name = string("concat_14_axis_0"), val = int32(-1)];
            bool concat_14_interleave_0 = const()[name = string("concat_14_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 64, 44]> concat_14 = concat(axis = concat_14_axis_0, interleave = concat_14_interleave_0, values = (slice_by_index_29, slice_by_index_28))[name = string("concat_14")];
            tensor<fp16, [44]> mul_351_y_0 = const()[name = string("mul_351_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 64, 44]> mul_351 = mul(x = concat_14, y = mul_351_y_0)[name = string("mul_351")];
            tensor<fp16, [8, 64, 44]> mul_352 = mul(x = mul_350, y = mul_11_y_0)[name = string("mul_352")];
            tensor<fp16, [8, 64, 44]> mul_353 = mul(x = mul_351, y = mul_12_y_0)[name = string("mul_353")];
            tensor<fp16, [8, 64, 44]> add_42 = add(x = mul_352, y = mul_353)[name = string("add_42")];
            tensor<fp16, [2, 64, 44]> transpose_29 = transpose(perm = transpose_29_perm_0, x = reshape_59)[name = string("transpose_34")];
            tensor<fp16, [2, 64, 44]> mul_354 = mul(x = transpose_29, y = transpose_29)[name = string("mul_354")];
            tensor<int32, [1]> reduce_mean_76_axes_0 = const()[name = string("reduce_mean_76_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_76_keep_dims_0 = const()[name = string("reduce_mean_76_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 64, 1]> reduce_mean_76 = reduce_mean(axes = reduce_mean_76_axes_0, keep_dims = reduce_mean_76_keep_dims_0, x = mul_354)[name = string("reduce_mean_76")];
            fp32 rsqrt_76_epsilon_0 = const()[name = string("rsqrt_76_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 64, 1]> rsqrt_76 = rsqrt(epsilon = rsqrt_76_epsilon_0, x = reduce_mean_76)[name = string("rsqrt_76")];
            tensor<fp16, [2, 64, 44]> mul_355 = mul(x = transpose_29, y = rsqrt_76)[name = string("mul_355")];
            tensor<fp16, [44]> mul_356_y_0 = const()[name = string("mul_356_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4785920)))];
            tensor<fp16, [2, 64, 44]> mul_356 = mul(x = mul_355, y = mul_356_y_0)[name = string("mul_356")];
            tensor<int32, [3]> slice_by_index_30_begin_0 = const()[name = string("slice_by_index_30_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_30_end_0 = const()[name = string("slice_by_index_30_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_30_end_mask_0 = const()[name = string("slice_by_index_30_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 64, 22]> slice_by_index_30 = slice_by_index(begin = slice_by_index_30_begin_0, end = slice_by_index_30_end_0, end_mask = slice_by_index_30_end_mask_0, x = mul_356)[name = string("slice_by_index_30")];
            tensor<int32, [3]> slice_by_index_31_begin_0 = const()[name = string("slice_by_index_31_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_31_end_0 = const()[name = string("slice_by_index_31_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_31_end_mask_0 = const()[name = string("slice_by_index_31_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 64, 22]> slice_by_index_31 = slice_by_index(begin = slice_by_index_31_begin_0, end = slice_by_index_31_end_0, end_mask = slice_by_index_31_end_mask_0, x = mul_356)[name = string("slice_by_index_31")];
            int32 concat_15_axis_0 = const()[name = string("concat_15_axis_0"), val = int32(-1)];
            bool concat_15_interleave_0 = const()[name = string("concat_15_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 64, 44]> concat_15 = concat(axis = concat_15_axis_0, interleave = concat_15_interleave_0, values = (slice_by_index_31, slice_by_index_30))[name = string("concat_15")];
            tensor<fp16, [44]> mul_357_y_0 = const()[name = string("mul_357_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 64, 44]> mul_357 = mul(x = concat_15, y = mul_357_y_0)[name = string("mul_357")];
            tensor<fp16, [2, 64, 44]> mul_358 = mul(x = mul_356, y = mul_11_y_0)[name = string("mul_358")];
            tensor<fp16, [2, 64, 44]> mul_359 = mul(x = mul_357, y = mul_12_y_0)[name = string("mul_359")];
            tensor<fp16, [2, 64, 44]> add_43 = add(x = mul_358, y = mul_359)[name = string("add_43")];
            tensor<int32, [4]> reshape_61_shape_0 = const()[name = string("reshape_61_shape_0"), val = tensor<int32, [4]>([2, 1, 64, 44])];
            tensor<fp16, [2, 1, 64, 44]> reshape_61 = reshape(shape = reshape_61_shape_0, x = add_43)[name = string("reshape_61")];
            tensor<int32, [4]> tile_14_reps_0 = const()[name = string("tile_14_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 64, 44]> tile_14 = tile(reps = tile_14_reps_0, x = reshape_61)[name = string("tile_14")];
            tensor<int32, [3]> reshape_62_shape_0 = const()[name = string("reshape_62_shape_0"), val = tensor<int32, [3]>([8, 64, 44])];
            tensor<fp16, [8, 64, 44]> reshape_62 = reshape(shape = reshape_62_shape_0, x = tile_14)[name = string("reshape_62")];
            tensor<int32, [4]> reshape_63_shape_0 = const()[name = string("reshape_63_shape_0"), val = tensor<int32, [4]>([2, 1, 64, 44])];
            tensor<fp16, [2, 64, 44]> transpose_30 = transpose(perm = transpose_30_perm_0, x = reshape_60)[name = string("transpose_33")];
            tensor<fp16, [2, 1, 64, 44]> reshape_63 = reshape(shape = reshape_63_shape_0, x = transpose_30)[name = string("reshape_63")];
            tensor<int32, [4]> tile_15_reps_0 = const()[name = string("tile_15_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 64, 44]> tile_15 = tile(reps = tile_15_reps_0, x = reshape_63)[name = string("tile_15")];
            tensor<int32, [3]> reshape_64_shape_0 = const()[name = string("reshape_64_shape_0"), val = tensor<int32, [3]>([8, 64, 44])];
            tensor<fp16, [8, 64, 44]> reshape_64 = reshape(shape = reshape_64_shape_0, x = tile_15)[name = string("reshape_64")];
            fp16 mul_360_y_0 = const()[name = string("mul_360_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 64, 44]> mul_360 = mul(x = add_42, y = mul_360_y_0)[name = string("mul_360")];
            bool matmul_14_transpose_y_0 = const()[name = string("matmul_14_transpose_y_0"), val = bool(true)];
            bool matmul_14_transpose_x_0 = const()[name = string("matmul_14_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 64, 64]> matmul_14 = matmul(transpose_x = matmul_14_transpose_x_0, transpose_y = matmul_14_transpose_y_0, x = mul_360, y = reshape_62)[name = string("matmul_14")];
            tensor<fp16, [8, 64, 64]> add_44 = add(x = matmul_14, y = reshape_1)[name = string("add_44")];
            int32 softmax_7_axis_0 = const()[name = string("softmax_7_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 64, 64]> softmax_7 = softmax(axis = softmax_7_axis_0, x = add_44)[name = string("softmax_7")];
            bool matmul_15_transpose_x_0 = const()[name = string("matmul_15_transpose_x_0"), val = bool(false)];
            bool matmul_15_transpose_y_0 = const()[name = string("matmul_15_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 64, 44]> matmul_15 = matmul(transpose_x = matmul_15_transpose_x_0, transpose_y = matmul_15_transpose_y_0, x = softmax_7, y = reshape_64)[name = string("matmul_15")];
            tensor<int32, [3]> transpose_31_perm_0 = const()[name = string("transpose_31_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_65_shape_0 = const()[name = string("reshape_65_shape_0"), val = tensor<int32, [2]>([64, 352])];
            tensor<fp16, [64, 8, 44]> transpose_31 = transpose(perm = transpose_31_perm_0, x = matmul_15)[name = string("transpose_32")];
            tensor<fp16, [64, 352]> reshape_65 = reshape(shape = reshape_65_shape_0, x = transpose_31)[name = string("reshape_65")];
            tensor<fp16, [64, 352]> mul_361 = mul(x = reshape_65, y = reshape_65)[name = string("mul_361")];
            tensor<int32, [1]> reduce_mean_77_axes_0 = const()[name = string("reduce_mean_77_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_77_keep_dims_0 = const()[name = string("reduce_mean_77_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_77 = reduce_mean(axes = reduce_mean_77_axes_0, keep_dims = reduce_mean_77_keep_dims_0, x = mul_361)[name = string("reduce_mean_77")];
            fp32 rsqrt_77_epsilon_0 = const()[name = string("rsqrt_77_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_77 = rsqrt(epsilon = rsqrt_77_epsilon_0, x = reduce_mean_77)[name = string("rsqrt_77")];
            tensor<fp16, [64, 352]> mul_362 = mul(x = reshape_65, y = rsqrt_77)[name = string("mul_362")];
            tensor<fp16, [352]> mul_363_y_0 = const()[name = string("mul_363_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4786112)))];
            tensor<fp16, [64, 352]> mul_363 = mul(x = mul_362, y = mul_363_y_0)[name = string("mul_363")];
            tensor<fp16, [352, 352]> tern_7_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4786880))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_7_o_weight_0_palettized")];
            tensor<fp16, [64, 352]> tern_7_o = linear(bias = linear_0_bias_0, weight = tern_7_o_weight_0_palettized, x = mul_363)[name = string("tern_7_o")];
            tensor<fp16, [352]> mul_364_y_0 = const()[name = string("mul_364_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4817920)))];
            tensor<fp16, [64, 352]> mul_364 = mul(x = tern_7_o, y = mul_364_y_0)[name = string("mul_364")];
            tensor<fp16, [64, 352]> add_45 = add(x = add_41, y = mul_364)[name = string("add_45")];
            tensor<fp16, [64, 352]> mul_365 = mul(x = add_45, y = add_45)[name = string("mul_365")];
            tensor<int32, [1]> reduce_mean_78_axes_0 = const()[name = string("reduce_mean_78_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_78_keep_dims_0 = const()[name = string("reduce_mean_78_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_78 = reduce_mean(axes = reduce_mean_78_axes_0, keep_dims = reduce_mean_78_keep_dims_0, x = mul_365)[name = string("reduce_mean_78")];
            fp32 rsqrt_78_epsilon_0 = const()[name = string("rsqrt_78_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_78 = rsqrt(epsilon = rsqrt_78_epsilon_0, x = reduce_mean_78)[name = string("rsqrt_78")];
            tensor<fp16, [64, 352]> mul_366 = mul(x = add_45, y = rsqrt_78)[name = string("mul_366")];
            tensor<fp16, [352]> mul_367_y_0 = const()[name = string("mul_367_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4818688)))];
            tensor<fp16, [64, 352]> mul_367 = mul(x = mul_366, y = mul_367_y_0)[name = string("mul_367")];
            tensor<fp16, [64, 352]> mul_368 = mul(x = mul_367, y = mul_367)[name = string("mul_368")];
            tensor<int32, [1]> reduce_mean_79_axes_0 = const()[name = string("reduce_mean_79_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_79_keep_dims_0 = const()[name = string("reduce_mean_79_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_79 = reduce_mean(axes = reduce_mean_79_axes_0, keep_dims = reduce_mean_79_keep_dims_0, x = mul_368)[name = string("reduce_mean_79")];
            fp32 rsqrt_79_epsilon_0 = const()[name = string("rsqrt_79_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_79 = rsqrt(epsilon = rsqrt_79_epsilon_0, x = reduce_mean_79)[name = string("rsqrt_79")];
            tensor<fp16, [64, 352]> mul_369 = mul(x = mul_367, y = rsqrt_79)[name = string("mul_369")];
            tensor<fp16, [352]> mul_370_y_0 = const()[name = string("mul_370_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4819456)))];
            tensor<fp16, [64, 352]> mul_370 = mul(x = mul_369, y = mul_370_y_0)[name = string("mul_370")];
            tensor<fp16, [960, 352]> tern_7_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4820224))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_7_w1_weight_0_palettized")];
            tensor<fp16, [64, 960]> tern_7_w1 = linear(bias = linear_4_bias_0, weight = tern_7_w1_weight_0_palettized, x = mul_370)[name = string("tern_7_w1")];
            tensor<fp16, [960]> mul_371_y_0 = const()[name = string("mul_371_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4904768)))];
            tensor<fp16, [64, 960]> mul_371 = mul(x = tern_7_w1, y = mul_371_y_0)[name = string("mul_371")];
            tensor<fp16, [352]> mul_374_y_0 = const()[name = string("mul_374_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4906752)))];
            tensor<fp16, [64, 352]> mul_374 = mul(x = mul_369, y = mul_374_y_0)[name = string("mul_374")];
            tensor<fp16, [960, 352]> tern_7_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4907520))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_7_w3_weight_0_palettized")];
            tensor<fp16, [64, 960]> tern_7_w3 = linear(bias = linear_4_bias_0, weight = tern_7_w3_weight_0_palettized, x = mul_374)[name = string("tern_7_w3")];
            tensor<fp16, [960]> mul_375_y_0 = const()[name = string("mul_375_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4992064)))];
            tensor<fp16, [64, 960]> mul_375 = mul(x = tern_7_w3, y = mul_375_y_0)[name = string("mul_375")];
            fp16 mul_376_y_0 = const()[name = string("mul_376_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [64, 960]> mul_376 = mul(x = mul_371, y = mul_376_y_0)[name = string("mul_376")];
            tensor<fp16, [64, 960]> tanh_7 = tanh(x = mul_376)[name = string("tanh_7")];
            fp16 mul_377_x_0 = const()[name = string("mul_377_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [64, 960]> mul_377 = mul(x = mul_377_x_0, y = tanh_7)[name = string("mul_377")];
            fp16 add_46_x_0 = const()[name = string("add_46_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [64, 960]> add_46 = add(x = add_46_x_0, y = mul_377)[name = string("add_46")];
            tensor<fp16, [64, 960]> mul_378 = mul(x = mul_371, y = add_46)[name = string("mul_378")];
            tensor<fp16, [64, 960]> mul_379 = mul(x = mul_378, y = mul_375)[name = string("mul_379")];
            tensor<fp16, [64, 960]> mul_380 = mul(x = mul_379, y = mul_379)[name = string("mul_380")];
            tensor<int32, [1]> reduce_mean_81_axes_0 = const()[name = string("reduce_mean_81_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_81_keep_dims_0 = const()[name = string("reduce_mean_81_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_81 = reduce_mean(axes = reduce_mean_81_axes_0, keep_dims = reduce_mean_81_keep_dims_0, x = mul_380)[name = string("reduce_mean_81")];
            fp32 rsqrt_81_epsilon_0 = const()[name = string("rsqrt_81_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_81 = rsqrt(epsilon = rsqrt_81_epsilon_0, x = reduce_mean_81)[name = string("rsqrt_81")];
            tensor<fp16, [64, 960]> mul_381 = mul(x = mul_379, y = rsqrt_81)[name = string("mul_381")];
            tensor<fp16, [960]> mul_382_y_0 = const()[name = string("mul_382_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4994048)))];
            tensor<fp16, [64, 960]> mul_382 = mul(x = mul_381, y = mul_382_y_0)[name = string("mul_382")];
            tensor<fp16, [352, 960]> tern_7_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4996032))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_7_w2_weight_0_palettized")];
            tensor<fp16, [64, 352]> tern_7_w2 = linear(bias = linear_0_bias_0, weight = tern_7_w2_weight_0_palettized, x = mul_382)[name = string("tern_7_w2")];
            tensor<fp16, [352]> mul_383_y_0 = const()[name = string("mul_383_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5080576)))];
            tensor<fp16, [64, 352]> mul_383 = mul(x = tern_7_w2, y = mul_383_y_0)[name = string("mul_383")];
            tensor<fp16, [64, 352]> add_47 = add(x = add_45, y = mul_383)[name = string("add_47")];
            tensor<fp16, [64, 352]> mul_384 = mul(x = add_47, y = add_47)[name = string("mul_384")];
            tensor<int32, [1]> reduce_mean_82_axes_0 = const()[name = string("reduce_mean_82_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_82_keep_dims_0 = const()[name = string("reduce_mean_82_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_82 = reduce_mean(axes = reduce_mean_82_axes_0, keep_dims = reduce_mean_82_keep_dims_0, x = mul_384)[name = string("reduce_mean_82")];
            fp32 rsqrt_82_epsilon_0 = const()[name = string("rsqrt_82_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_82 = rsqrt(epsilon = rsqrt_82_epsilon_0, x = reduce_mean_82)[name = string("rsqrt_82")];
            tensor<fp16, [64, 352]> mul_385 = mul(x = add_47, y = rsqrt_82)[name = string("mul_385")];
            tensor<fp16, [352]> mul_386_y_0 = const()[name = string("mul_386_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5081344)))];
            tensor<fp16, [64, 352]> mul_386 = mul(x = mul_385, y = mul_386_y_0)[name = string("mul_386")];
            tensor<fp16, [64, 352]> mul_387 = mul(x = mul_386, y = mul_386)[name = string("mul_387")];
            tensor<int32, [1]> reduce_mean_83_axes_0 = const()[name = string("reduce_mean_83_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_83_keep_dims_0 = const()[name = string("reduce_mean_83_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_83 = reduce_mean(axes = reduce_mean_83_axes_0, keep_dims = reduce_mean_83_keep_dims_0, x = mul_387)[name = string("reduce_mean_83")];
            fp32 rsqrt_83_epsilon_0 = const()[name = string("rsqrt_83_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_83 = rsqrt(epsilon = rsqrt_83_epsilon_0, x = reduce_mean_83)[name = string("rsqrt_83")];
            tensor<fp16, [64, 352]> mul_388 = mul(x = mul_386, y = rsqrt_83)[name = string("mul_388")];
            tensor<fp16, [352]> mul_389_y_0 = const()[name = string("mul_389_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5082112)))];
            tensor<fp16, [64, 352]> mul_389 = mul(x = mul_388, y = mul_389_y_0)[name = string("mul_389")];
            tensor<fp16, [352, 352]> tern_8_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5082880))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_8_q_weight_0_palettized")];
            tensor<fp16, [64, 352]> tern_8_q = linear(bias = linear_0_bias_0, weight = tern_8_q_weight_0_palettized, x = mul_389)[name = string("tern_8_q")];
            tensor<fp16, [352]> mul_390_y_0 = const()[name = string("mul_390_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5113920)))];
            tensor<fp16, [64, 352]> mul_390 = mul(x = tern_8_q, y = mul_390_y_0)[name = string("mul_390")];
            tensor<int32, [3]> reshape_66_shape_0 = const()[name = string("reshape_66_shape_0"), val = tensor<int32, [3]>([64, 8, 44])];
            tensor<fp16, [64, 8, 44]> reshape_66 = reshape(shape = reshape_66_shape_0, x = mul_390)[name = string("reshape_66")];
            tensor<int32, [3]> transpose_32_perm_0 = const()[name = string("transpose_32_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_393_y_0 = const()[name = string("mul_393_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5114688)))];
            tensor<fp16, [64, 352]> mul_393 = mul(x = mul_388, y = mul_393_y_0)[name = string("mul_393")];
            tensor<fp16, [88, 352]> tern_8_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5115456))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_8_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_8_k_bias_0 = const()[name = string("tern_8_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [64, 88]> tern_8_k = linear(bias = tern_8_k_bias_0, weight = tern_8_k_weight_0_palettized, x = mul_393)[name = string("tern_8_k")];
            tensor<fp16, [88]> mul_394_y_0 = const()[name = string("mul_394_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5123264)))];
            tensor<fp16, [64, 88]> mul_394 = mul(x = tern_8_k, y = mul_394_y_0)[name = string("mul_394")];
            tensor<int32, [3]> reshape_67_shape_0 = const()[name = string("reshape_67_shape_0"), val = tensor<int32, [3]>([64, 2, 44])];
            tensor<fp16, [64, 2, 44]> reshape_67 = reshape(shape = reshape_67_shape_0, x = mul_394)[name = string("reshape_67")];
            tensor<int32, [3]> transpose_33_perm_0 = const()[name = string("transpose_33_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_397_y_0 = const()[name = string("mul_397_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5123520)))];
            tensor<fp16, [64, 352]> mul_397 = mul(x = mul_388, y = mul_397_y_0)[name = string("mul_397")];
            tensor<fp16, [88, 352]> tern_8_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5124288))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_8_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_8_v_bias_0 = const()[name = string("tern_8_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [64, 88]> tern_8_v = linear(bias = tern_8_v_bias_0, weight = tern_8_v_weight_0_palettized, x = mul_397)[name = string("tern_8_v")];
            tensor<fp16, [88]> mul_398_y_0 = const()[name = string("mul_398_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5132096)))];
            tensor<fp16, [64, 88]> mul_398 = mul(x = tern_8_v, y = mul_398_y_0)[name = string("mul_398")];
            tensor<int32, [3]> reshape_68_shape_0 = const()[name = string("reshape_68_shape_0"), val = tensor<int32, [3]>([64, 2, 44])];
            tensor<fp16, [64, 2, 44]> reshape_68 = reshape(shape = reshape_68_shape_0, x = mul_398)[name = string("reshape_68")];
            tensor<int32, [3]> transpose_34_perm_0 = const()[name = string("transpose_34_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 64, 44]> transpose_32 = transpose(perm = transpose_32_perm_0, x = reshape_66)[name = string("transpose_31")];
            tensor<fp16, [8, 64, 44]> mul_399 = mul(x = transpose_32, y = transpose_32)[name = string("mul_399")];
            tensor<int32, [1]> reduce_mean_86_axes_0 = const()[name = string("reduce_mean_86_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_86_keep_dims_0 = const()[name = string("reduce_mean_86_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 64, 1]> reduce_mean_86 = reduce_mean(axes = reduce_mean_86_axes_0, keep_dims = reduce_mean_86_keep_dims_0, x = mul_399)[name = string("reduce_mean_86")];
            fp32 rsqrt_86_epsilon_0 = const()[name = string("rsqrt_86_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 64, 1]> rsqrt_86 = rsqrt(epsilon = rsqrt_86_epsilon_0, x = reduce_mean_86)[name = string("rsqrt_86")];
            tensor<fp16, [8, 64, 44]> mul_400 = mul(x = transpose_32, y = rsqrt_86)[name = string("mul_400")];
            tensor<fp16, [44]> mul_401_y_0 = const()[name = string("mul_401_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5132352)))];
            tensor<fp16, [8, 64, 44]> mul_401 = mul(x = mul_400, y = mul_401_y_0)[name = string("mul_401")];
            tensor<int32, [3]> slice_by_index_32_begin_0 = const()[name = string("slice_by_index_32_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_32_end_0 = const()[name = string("slice_by_index_32_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_32_end_mask_0 = const()[name = string("slice_by_index_32_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 64, 22]> slice_by_index_32 = slice_by_index(begin = slice_by_index_32_begin_0, end = slice_by_index_32_end_0, end_mask = slice_by_index_32_end_mask_0, x = mul_401)[name = string("slice_by_index_32")];
            tensor<int32, [3]> slice_by_index_33_begin_0 = const()[name = string("slice_by_index_33_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_33_end_0 = const()[name = string("slice_by_index_33_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_33_end_mask_0 = const()[name = string("slice_by_index_33_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 64, 22]> slice_by_index_33 = slice_by_index(begin = slice_by_index_33_begin_0, end = slice_by_index_33_end_0, end_mask = slice_by_index_33_end_mask_0, x = mul_401)[name = string("slice_by_index_33")];
            int32 concat_16_axis_0 = const()[name = string("concat_16_axis_0"), val = int32(-1)];
            bool concat_16_interleave_0 = const()[name = string("concat_16_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 64, 44]> concat_16 = concat(axis = concat_16_axis_0, interleave = concat_16_interleave_0, values = (slice_by_index_33, slice_by_index_32))[name = string("concat_16")];
            tensor<fp16, [44]> mul_402_y_0 = const()[name = string("mul_402_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 64, 44]> mul_402 = mul(x = concat_16, y = mul_402_y_0)[name = string("mul_402")];
            tensor<fp16, [8, 64, 44]> mul_403 = mul(x = mul_401, y = mul_11_y_0)[name = string("mul_403")];
            tensor<fp16, [8, 64, 44]> mul_404 = mul(x = mul_402, y = mul_12_y_0)[name = string("mul_404")];
            tensor<fp16, [8, 64, 44]> add_48 = add(x = mul_403, y = mul_404)[name = string("add_48")];
            tensor<fp16, [2, 64, 44]> transpose_33 = transpose(perm = transpose_33_perm_0, x = reshape_67)[name = string("transpose_30")];
            tensor<fp16, [2, 64, 44]> mul_405 = mul(x = transpose_33, y = transpose_33)[name = string("mul_405")];
            tensor<int32, [1]> reduce_mean_87_axes_0 = const()[name = string("reduce_mean_87_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_87_keep_dims_0 = const()[name = string("reduce_mean_87_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 64, 1]> reduce_mean_87 = reduce_mean(axes = reduce_mean_87_axes_0, keep_dims = reduce_mean_87_keep_dims_0, x = mul_405)[name = string("reduce_mean_87")];
            fp32 rsqrt_87_epsilon_0 = const()[name = string("rsqrt_87_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 64, 1]> rsqrt_87 = rsqrt(epsilon = rsqrt_87_epsilon_0, x = reduce_mean_87)[name = string("rsqrt_87")];
            tensor<fp16, [2, 64, 44]> mul_406 = mul(x = transpose_33, y = rsqrt_87)[name = string("mul_406")];
            tensor<fp16, [44]> mul_407_y_0 = const()[name = string("mul_407_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5132544)))];
            tensor<fp16, [2, 64, 44]> mul_407 = mul(x = mul_406, y = mul_407_y_0)[name = string("mul_407")];
            tensor<int32, [3]> slice_by_index_34_begin_0 = const()[name = string("slice_by_index_34_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_34_end_0 = const()[name = string("slice_by_index_34_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_34_end_mask_0 = const()[name = string("slice_by_index_34_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 64, 22]> slice_by_index_34 = slice_by_index(begin = slice_by_index_34_begin_0, end = slice_by_index_34_end_0, end_mask = slice_by_index_34_end_mask_0, x = mul_407)[name = string("slice_by_index_34")];
            tensor<int32, [3]> slice_by_index_35_begin_0 = const()[name = string("slice_by_index_35_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_35_end_0 = const()[name = string("slice_by_index_35_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_35_end_mask_0 = const()[name = string("slice_by_index_35_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 64, 22]> slice_by_index_35 = slice_by_index(begin = slice_by_index_35_begin_0, end = slice_by_index_35_end_0, end_mask = slice_by_index_35_end_mask_0, x = mul_407)[name = string("slice_by_index_35")];
            int32 concat_17_axis_0 = const()[name = string("concat_17_axis_0"), val = int32(-1)];
            bool concat_17_interleave_0 = const()[name = string("concat_17_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 64, 44]> concat_17 = concat(axis = concat_17_axis_0, interleave = concat_17_interleave_0, values = (slice_by_index_35, slice_by_index_34))[name = string("concat_17")];
            tensor<fp16, [44]> mul_408_y_0 = const()[name = string("mul_408_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 64, 44]> mul_408 = mul(x = concat_17, y = mul_408_y_0)[name = string("mul_408")];
            tensor<fp16, [2, 64, 44]> mul_409 = mul(x = mul_407, y = mul_11_y_0)[name = string("mul_409")];
            tensor<fp16, [2, 64, 44]> mul_410 = mul(x = mul_408, y = mul_12_y_0)[name = string("mul_410")];
            tensor<fp16, [2, 64, 44]> add_49 = add(x = mul_409, y = mul_410)[name = string("add_49")];
            tensor<int32, [4]> reshape_69_shape_0 = const()[name = string("reshape_69_shape_0"), val = tensor<int32, [4]>([2, 1, 64, 44])];
            tensor<fp16, [2, 1, 64, 44]> reshape_69 = reshape(shape = reshape_69_shape_0, x = add_49)[name = string("reshape_69")];
            tensor<int32, [4]> tile_16_reps_0 = const()[name = string("tile_16_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 64, 44]> tile_16 = tile(reps = tile_16_reps_0, x = reshape_69)[name = string("tile_16")];
            tensor<int32, [3]> reshape_70_shape_0 = const()[name = string("reshape_70_shape_0"), val = tensor<int32, [3]>([8, 64, 44])];
            tensor<fp16, [8, 64, 44]> reshape_70 = reshape(shape = reshape_70_shape_0, x = tile_16)[name = string("reshape_70")];
            tensor<int32, [4]> reshape_71_shape_0 = const()[name = string("reshape_71_shape_0"), val = tensor<int32, [4]>([2, 1, 64, 44])];
            tensor<fp16, [2, 64, 44]> transpose_34 = transpose(perm = transpose_34_perm_0, x = reshape_68)[name = string("transpose_29")];
            tensor<fp16, [2, 1, 64, 44]> reshape_71 = reshape(shape = reshape_71_shape_0, x = transpose_34)[name = string("reshape_71")];
            tensor<int32, [4]> tile_17_reps_0 = const()[name = string("tile_17_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 64, 44]> tile_17 = tile(reps = tile_17_reps_0, x = reshape_71)[name = string("tile_17")];
            tensor<int32, [3]> reshape_72_shape_0 = const()[name = string("reshape_72_shape_0"), val = tensor<int32, [3]>([8, 64, 44])];
            tensor<fp16, [8, 64, 44]> reshape_72 = reshape(shape = reshape_72_shape_0, x = tile_17)[name = string("reshape_72")];
            fp16 mul_411_y_0 = const()[name = string("mul_411_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 64, 44]> mul_411 = mul(x = add_48, y = mul_411_y_0)[name = string("mul_411")];
            bool matmul_16_transpose_y_0 = const()[name = string("matmul_16_transpose_y_0"), val = bool(true)];
            bool matmul_16_transpose_x_0 = const()[name = string("matmul_16_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 64, 64]> matmul_16 = matmul(transpose_x = matmul_16_transpose_x_0, transpose_y = matmul_16_transpose_y_0, x = mul_411, y = reshape_70)[name = string("matmul_16")];
            tensor<fp16, [8, 64, 64]> add_50 = add(x = matmul_16, y = reshape_1)[name = string("add_50")];
            int32 softmax_8_axis_0 = const()[name = string("softmax_8_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 64, 64]> softmax_8 = softmax(axis = softmax_8_axis_0, x = add_50)[name = string("softmax_8")];
            bool matmul_17_transpose_x_0 = const()[name = string("matmul_17_transpose_x_0"), val = bool(false)];
            bool matmul_17_transpose_y_0 = const()[name = string("matmul_17_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 64, 44]> matmul_17 = matmul(transpose_x = matmul_17_transpose_x_0, transpose_y = matmul_17_transpose_y_0, x = softmax_8, y = reshape_72)[name = string("matmul_17")];
            tensor<int32, [3]> transpose_35_perm_0 = const()[name = string("transpose_35_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_73_shape_0 = const()[name = string("reshape_73_shape_0"), val = tensor<int32, [2]>([64, 352])];
            tensor<fp16, [64, 8, 44]> transpose_35 = transpose(perm = transpose_35_perm_0, x = matmul_17)[name = string("transpose_28")];
            tensor<fp16, [64, 352]> reshape_73 = reshape(shape = reshape_73_shape_0, x = transpose_35)[name = string("reshape_73")];
            tensor<fp16, [64, 352]> mul_412 = mul(x = reshape_73, y = reshape_73)[name = string("mul_412")];
            tensor<int32, [1]> reduce_mean_88_axes_0 = const()[name = string("reduce_mean_88_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_88_keep_dims_0 = const()[name = string("reduce_mean_88_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_88 = reduce_mean(axes = reduce_mean_88_axes_0, keep_dims = reduce_mean_88_keep_dims_0, x = mul_412)[name = string("reduce_mean_88")];
            fp32 rsqrt_88_epsilon_0 = const()[name = string("rsqrt_88_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_88 = rsqrt(epsilon = rsqrt_88_epsilon_0, x = reduce_mean_88)[name = string("rsqrt_88")];
            tensor<fp16, [64, 352]> mul_413 = mul(x = reshape_73, y = rsqrt_88)[name = string("mul_413")];
            tensor<fp16, [352]> mul_414_y_0 = const()[name = string("mul_414_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5132736)))];
            tensor<fp16, [64, 352]> mul_414 = mul(x = mul_413, y = mul_414_y_0)[name = string("mul_414")];
            tensor<fp16, [352, 352]> tern_8_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5133504))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_8_o_weight_0_palettized")];
            tensor<fp16, [64, 352]> tern_8_o = linear(bias = linear_0_bias_0, weight = tern_8_o_weight_0_palettized, x = mul_414)[name = string("tern_8_o")];
            tensor<fp16, [352]> mul_415_y_0 = const()[name = string("mul_415_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5164544)))];
            tensor<fp16, [64, 352]> mul_415 = mul(x = tern_8_o, y = mul_415_y_0)[name = string("mul_415")];
            tensor<fp16, [64, 352]> add_51 = add(x = add_47, y = mul_415)[name = string("add_51")];
            tensor<fp16, [64, 352]> mul_416 = mul(x = add_51, y = add_51)[name = string("mul_416")];
            tensor<int32, [1]> reduce_mean_89_axes_0 = const()[name = string("reduce_mean_89_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_89_keep_dims_0 = const()[name = string("reduce_mean_89_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_89 = reduce_mean(axes = reduce_mean_89_axes_0, keep_dims = reduce_mean_89_keep_dims_0, x = mul_416)[name = string("reduce_mean_89")];
            fp32 rsqrt_89_epsilon_0 = const()[name = string("rsqrt_89_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_89 = rsqrt(epsilon = rsqrt_89_epsilon_0, x = reduce_mean_89)[name = string("rsqrt_89")];
            tensor<fp16, [64, 352]> mul_417 = mul(x = add_51, y = rsqrt_89)[name = string("mul_417")];
            tensor<fp16, [352]> mul_418_y_0 = const()[name = string("mul_418_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5165312)))];
            tensor<fp16, [64, 352]> mul_418 = mul(x = mul_417, y = mul_418_y_0)[name = string("mul_418")];
            tensor<fp16, [64, 352]> mul_419 = mul(x = mul_418, y = mul_418)[name = string("mul_419")];
            tensor<int32, [1]> reduce_mean_90_axes_0 = const()[name = string("reduce_mean_90_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_90_keep_dims_0 = const()[name = string("reduce_mean_90_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_90 = reduce_mean(axes = reduce_mean_90_axes_0, keep_dims = reduce_mean_90_keep_dims_0, x = mul_419)[name = string("reduce_mean_90")];
            fp32 rsqrt_90_epsilon_0 = const()[name = string("rsqrt_90_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_90 = rsqrt(epsilon = rsqrt_90_epsilon_0, x = reduce_mean_90)[name = string("rsqrt_90")];
            tensor<fp16, [64, 352]> mul_420 = mul(x = mul_418, y = rsqrt_90)[name = string("mul_420")];
            tensor<fp16, [352]> mul_421_y_0 = const()[name = string("mul_421_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5166080)))];
            tensor<fp16, [64, 352]> mul_421 = mul(x = mul_420, y = mul_421_y_0)[name = string("mul_421")];
            tensor<fp16, [960, 352]> tern_8_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5166848))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_8_w1_weight_0_palettized")];
            tensor<fp16, [64, 960]> tern_8_w1 = linear(bias = linear_4_bias_0, weight = tern_8_w1_weight_0_palettized, x = mul_421)[name = string("tern_8_w1")];
            tensor<fp16, [960]> mul_422_y_0 = const()[name = string("mul_422_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5251392)))];
            tensor<fp16, [64, 960]> mul_422 = mul(x = tern_8_w1, y = mul_422_y_0)[name = string("mul_422")];
            tensor<fp16, [352]> mul_425_y_0 = const()[name = string("mul_425_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5253376)))];
            tensor<fp16, [64, 352]> mul_425 = mul(x = mul_420, y = mul_425_y_0)[name = string("mul_425")];
            tensor<fp16, [960, 352]> tern_8_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5254144))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_8_w3_weight_0_palettized")];
            tensor<fp16, [64, 960]> tern_8_w3 = linear(bias = linear_4_bias_0, weight = tern_8_w3_weight_0_palettized, x = mul_425)[name = string("tern_8_w3")];
            tensor<fp16, [960]> mul_426_y_0 = const()[name = string("mul_426_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5338688)))];
            tensor<fp16, [64, 960]> mul_426 = mul(x = tern_8_w3, y = mul_426_y_0)[name = string("mul_426")];
            fp16 mul_427_y_0 = const()[name = string("mul_427_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [64, 960]> mul_427 = mul(x = mul_422, y = mul_427_y_0)[name = string("mul_427")];
            tensor<fp16, [64, 960]> tanh_8 = tanh(x = mul_427)[name = string("tanh_8")];
            fp16 mul_428_x_0 = const()[name = string("mul_428_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [64, 960]> mul_428 = mul(x = mul_428_x_0, y = tanh_8)[name = string("mul_428")];
            fp16 add_52_x_0 = const()[name = string("add_52_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [64, 960]> add_52 = add(x = add_52_x_0, y = mul_428)[name = string("add_52")];
            tensor<fp16, [64, 960]> mul_429 = mul(x = mul_422, y = add_52)[name = string("mul_429")];
            tensor<fp16, [64, 960]> mul_430 = mul(x = mul_429, y = mul_426)[name = string("mul_430")];
            tensor<fp16, [64, 960]> mul_431 = mul(x = mul_430, y = mul_430)[name = string("mul_431")];
            tensor<int32, [1]> reduce_mean_92_axes_0 = const()[name = string("reduce_mean_92_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_92_keep_dims_0 = const()[name = string("reduce_mean_92_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_92 = reduce_mean(axes = reduce_mean_92_axes_0, keep_dims = reduce_mean_92_keep_dims_0, x = mul_431)[name = string("reduce_mean_92")];
            fp32 rsqrt_92_epsilon_0 = const()[name = string("rsqrt_92_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_92 = rsqrt(epsilon = rsqrt_92_epsilon_0, x = reduce_mean_92)[name = string("rsqrt_92")];
            tensor<fp16, [64, 960]> mul_432 = mul(x = mul_430, y = rsqrt_92)[name = string("mul_432")];
            tensor<fp16, [960]> mul_433_y_0 = const()[name = string("mul_433_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5340672)))];
            tensor<fp16, [64, 960]> mul_433 = mul(x = mul_432, y = mul_433_y_0)[name = string("mul_433")];
            tensor<fp16, [352, 960]> tern_8_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5342656))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_8_w2_weight_0_palettized")];
            tensor<fp16, [64, 352]> tern_8_w2 = linear(bias = linear_0_bias_0, weight = tern_8_w2_weight_0_palettized, x = mul_433)[name = string("tern_8_w2")];
            tensor<fp16, [352]> mul_434_y_0 = const()[name = string("mul_434_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5427200)))];
            tensor<fp16, [64, 352]> mul_434 = mul(x = tern_8_w2, y = mul_434_y_0)[name = string("mul_434")];
            tensor<fp16, [64, 352]> add_53 = add(x = add_51, y = mul_434)[name = string("add_53")];
            tensor<fp16, [64, 352]> mul_435 = mul(x = add_53, y = add_53)[name = string("mul_435")];
            tensor<int32, [1]> reduce_mean_93_axes_0 = const()[name = string("reduce_mean_93_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_93_keep_dims_0 = const()[name = string("reduce_mean_93_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_93 = reduce_mean(axes = reduce_mean_93_axes_0, keep_dims = reduce_mean_93_keep_dims_0, x = mul_435)[name = string("reduce_mean_93")];
            fp32 rsqrt_93_epsilon_0 = const()[name = string("rsqrt_93_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_93 = rsqrt(epsilon = rsqrt_93_epsilon_0, x = reduce_mean_93)[name = string("rsqrt_93")];
            tensor<fp16, [64, 352]> mul_436 = mul(x = add_53, y = rsqrt_93)[name = string("mul_436")];
            tensor<fp16, [352]> mul_437_y_0 = const()[name = string("mul_437_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5427968)))];
            tensor<fp16, [64, 352]> mul_437 = mul(x = mul_436, y = mul_437_y_0)[name = string("mul_437")];
            tensor<fp16, [64, 352]> mul_438 = mul(x = mul_437, y = mul_437)[name = string("mul_438")];
            tensor<int32, [1]> reduce_mean_94_axes_0 = const()[name = string("reduce_mean_94_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_94_keep_dims_0 = const()[name = string("reduce_mean_94_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_94 = reduce_mean(axes = reduce_mean_94_axes_0, keep_dims = reduce_mean_94_keep_dims_0, x = mul_438)[name = string("reduce_mean_94")];
            fp32 rsqrt_94_epsilon_0 = const()[name = string("rsqrt_94_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_94 = rsqrt(epsilon = rsqrt_94_epsilon_0, x = reduce_mean_94)[name = string("rsqrt_94")];
            tensor<fp16, [64, 352]> mul_439 = mul(x = mul_437, y = rsqrt_94)[name = string("mul_439")];
            tensor<fp16, [352]> mul_440_y_0 = const()[name = string("mul_440_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5428736)))];
            tensor<fp16, [64, 352]> mul_440 = mul(x = mul_439, y = mul_440_y_0)[name = string("mul_440")];
            tensor<fp16, [352, 352]> tern_9_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5429504))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_9_q_weight_0_palettized")];
            tensor<fp16, [64, 352]> tern_9_q = linear(bias = linear_0_bias_0, weight = tern_9_q_weight_0_palettized, x = mul_440)[name = string("tern_9_q")];
            tensor<fp16, [352]> mul_441_y_0 = const()[name = string("mul_441_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5460544)))];
            tensor<fp16, [64, 352]> mul_441 = mul(x = tern_9_q, y = mul_441_y_0)[name = string("mul_441")];
            tensor<int32, [3]> reshape_74_shape_0 = const()[name = string("reshape_74_shape_0"), val = tensor<int32, [3]>([64, 8, 44])];
            tensor<fp16, [64, 8, 44]> reshape_74 = reshape(shape = reshape_74_shape_0, x = mul_441)[name = string("reshape_74")];
            tensor<int32, [3]> transpose_36_perm_0 = const()[name = string("transpose_36_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_444_y_0 = const()[name = string("mul_444_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5461312)))];
            tensor<fp16, [64, 352]> mul_444 = mul(x = mul_439, y = mul_444_y_0)[name = string("mul_444")];
            tensor<fp16, [88, 352]> tern_9_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5462080))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_9_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_9_k_bias_0 = const()[name = string("tern_9_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [64, 88]> tern_9_k = linear(bias = tern_9_k_bias_0, weight = tern_9_k_weight_0_palettized, x = mul_444)[name = string("tern_9_k")];
            tensor<fp16, [88]> mul_445_y_0 = const()[name = string("mul_445_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5469888)))];
            tensor<fp16, [64, 88]> mul_445 = mul(x = tern_9_k, y = mul_445_y_0)[name = string("mul_445")];
            tensor<int32, [3]> reshape_75_shape_0 = const()[name = string("reshape_75_shape_0"), val = tensor<int32, [3]>([64, 2, 44])];
            tensor<fp16, [64, 2, 44]> reshape_75 = reshape(shape = reshape_75_shape_0, x = mul_445)[name = string("reshape_75")];
            tensor<int32, [3]> transpose_37_perm_0 = const()[name = string("transpose_37_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_448_y_0 = const()[name = string("mul_448_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5470144)))];
            tensor<fp16, [64, 352]> mul_448 = mul(x = mul_439, y = mul_448_y_0)[name = string("mul_448")];
            tensor<fp16, [88, 352]> tern_9_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5470912))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_9_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_9_v_bias_0 = const()[name = string("tern_9_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [64, 88]> tern_9_v = linear(bias = tern_9_v_bias_0, weight = tern_9_v_weight_0_palettized, x = mul_448)[name = string("tern_9_v")];
            tensor<fp16, [88]> mul_449_y_0 = const()[name = string("mul_449_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5478720)))];
            tensor<fp16, [64, 88]> mul_449 = mul(x = tern_9_v, y = mul_449_y_0)[name = string("mul_449")];
            tensor<int32, [3]> reshape_76_shape_0 = const()[name = string("reshape_76_shape_0"), val = tensor<int32, [3]>([64, 2, 44])];
            tensor<fp16, [64, 2, 44]> reshape_76 = reshape(shape = reshape_76_shape_0, x = mul_449)[name = string("reshape_76")];
            tensor<int32, [3]> transpose_38_perm_0 = const()[name = string("transpose_38_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 64, 44]> transpose_36 = transpose(perm = transpose_36_perm_0, x = reshape_74)[name = string("transpose_27")];
            tensor<fp16, [8, 64, 44]> mul_450 = mul(x = transpose_36, y = transpose_36)[name = string("mul_450")];
            tensor<int32, [1]> reduce_mean_97_axes_0 = const()[name = string("reduce_mean_97_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_97_keep_dims_0 = const()[name = string("reduce_mean_97_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 64, 1]> reduce_mean_97 = reduce_mean(axes = reduce_mean_97_axes_0, keep_dims = reduce_mean_97_keep_dims_0, x = mul_450)[name = string("reduce_mean_97")];
            fp32 rsqrt_97_epsilon_0 = const()[name = string("rsqrt_97_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 64, 1]> rsqrt_97 = rsqrt(epsilon = rsqrt_97_epsilon_0, x = reduce_mean_97)[name = string("rsqrt_97")];
            tensor<fp16, [8, 64, 44]> mul_451 = mul(x = transpose_36, y = rsqrt_97)[name = string("mul_451")];
            tensor<fp16, [44]> mul_452_y_0 = const()[name = string("mul_452_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5478976)))];
            tensor<fp16, [8, 64, 44]> mul_452 = mul(x = mul_451, y = mul_452_y_0)[name = string("mul_452")];
            tensor<int32, [3]> slice_by_index_36_begin_0 = const()[name = string("slice_by_index_36_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_36_end_0 = const()[name = string("slice_by_index_36_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_36_end_mask_0 = const()[name = string("slice_by_index_36_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 64, 22]> slice_by_index_36 = slice_by_index(begin = slice_by_index_36_begin_0, end = slice_by_index_36_end_0, end_mask = slice_by_index_36_end_mask_0, x = mul_452)[name = string("slice_by_index_36")];
            tensor<int32, [3]> slice_by_index_37_begin_0 = const()[name = string("slice_by_index_37_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_37_end_0 = const()[name = string("slice_by_index_37_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_37_end_mask_0 = const()[name = string("slice_by_index_37_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 64, 22]> slice_by_index_37 = slice_by_index(begin = slice_by_index_37_begin_0, end = slice_by_index_37_end_0, end_mask = slice_by_index_37_end_mask_0, x = mul_452)[name = string("slice_by_index_37")];
            int32 concat_18_axis_0 = const()[name = string("concat_18_axis_0"), val = int32(-1)];
            bool concat_18_interleave_0 = const()[name = string("concat_18_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 64, 44]> concat_18 = concat(axis = concat_18_axis_0, interleave = concat_18_interleave_0, values = (slice_by_index_37, slice_by_index_36))[name = string("concat_18")];
            tensor<fp16, [44]> mul_453_y_0 = const()[name = string("mul_453_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 64, 44]> mul_453 = mul(x = concat_18, y = mul_453_y_0)[name = string("mul_453")];
            tensor<fp16, [8, 64, 44]> mul_454 = mul(x = mul_452, y = mul_11_y_0)[name = string("mul_454")];
            tensor<fp16, [8, 64, 44]> mul_455 = mul(x = mul_453, y = mul_12_y_0)[name = string("mul_455")];
            tensor<fp16, [8, 64, 44]> add_54 = add(x = mul_454, y = mul_455)[name = string("add_54")];
            tensor<fp16, [2, 64, 44]> transpose_37 = transpose(perm = transpose_37_perm_0, x = reshape_75)[name = string("transpose_26")];
            tensor<fp16, [2, 64, 44]> mul_456 = mul(x = transpose_37, y = transpose_37)[name = string("mul_456")];
            tensor<int32, [1]> reduce_mean_98_axes_0 = const()[name = string("reduce_mean_98_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_98_keep_dims_0 = const()[name = string("reduce_mean_98_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 64, 1]> reduce_mean_98 = reduce_mean(axes = reduce_mean_98_axes_0, keep_dims = reduce_mean_98_keep_dims_0, x = mul_456)[name = string("reduce_mean_98")];
            fp32 rsqrt_98_epsilon_0 = const()[name = string("rsqrt_98_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 64, 1]> rsqrt_98 = rsqrt(epsilon = rsqrt_98_epsilon_0, x = reduce_mean_98)[name = string("rsqrt_98")];
            tensor<fp16, [2, 64, 44]> mul_457 = mul(x = transpose_37, y = rsqrt_98)[name = string("mul_457")];
            tensor<fp16, [44]> mul_458_y_0 = const()[name = string("mul_458_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5479168)))];
            tensor<fp16, [2, 64, 44]> mul_458 = mul(x = mul_457, y = mul_458_y_0)[name = string("mul_458")];
            tensor<int32, [3]> slice_by_index_38_begin_0 = const()[name = string("slice_by_index_38_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_38_end_0 = const()[name = string("slice_by_index_38_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_38_end_mask_0 = const()[name = string("slice_by_index_38_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 64, 22]> slice_by_index_38 = slice_by_index(begin = slice_by_index_38_begin_0, end = slice_by_index_38_end_0, end_mask = slice_by_index_38_end_mask_0, x = mul_458)[name = string("slice_by_index_38")];
            tensor<int32, [3]> slice_by_index_39_begin_0 = const()[name = string("slice_by_index_39_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_39_end_0 = const()[name = string("slice_by_index_39_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_39_end_mask_0 = const()[name = string("slice_by_index_39_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 64, 22]> slice_by_index_39 = slice_by_index(begin = slice_by_index_39_begin_0, end = slice_by_index_39_end_0, end_mask = slice_by_index_39_end_mask_0, x = mul_458)[name = string("slice_by_index_39")];
            int32 concat_19_axis_0 = const()[name = string("concat_19_axis_0"), val = int32(-1)];
            bool concat_19_interleave_0 = const()[name = string("concat_19_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 64, 44]> concat_19 = concat(axis = concat_19_axis_0, interleave = concat_19_interleave_0, values = (slice_by_index_39, slice_by_index_38))[name = string("concat_19")];
            tensor<fp16, [44]> mul_459_y_0 = const()[name = string("mul_459_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 64, 44]> mul_459 = mul(x = concat_19, y = mul_459_y_0)[name = string("mul_459")];
            tensor<fp16, [2, 64, 44]> mul_460 = mul(x = mul_458, y = mul_11_y_0)[name = string("mul_460")];
            tensor<fp16, [2, 64, 44]> mul_461 = mul(x = mul_459, y = mul_12_y_0)[name = string("mul_461")];
            tensor<fp16, [2, 64, 44]> add_55 = add(x = mul_460, y = mul_461)[name = string("add_55")];
            tensor<int32, [4]> reshape_77_shape_0 = const()[name = string("reshape_77_shape_0"), val = tensor<int32, [4]>([2, 1, 64, 44])];
            tensor<fp16, [2, 1, 64, 44]> reshape_77 = reshape(shape = reshape_77_shape_0, x = add_55)[name = string("reshape_77")];
            tensor<int32, [4]> tile_18_reps_0 = const()[name = string("tile_18_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 64, 44]> tile_18 = tile(reps = tile_18_reps_0, x = reshape_77)[name = string("tile_18")];
            tensor<int32, [3]> reshape_78_shape_0 = const()[name = string("reshape_78_shape_0"), val = tensor<int32, [3]>([8, 64, 44])];
            tensor<fp16, [8, 64, 44]> reshape_78 = reshape(shape = reshape_78_shape_0, x = tile_18)[name = string("reshape_78")];
            tensor<int32, [4]> reshape_79_shape_0 = const()[name = string("reshape_79_shape_0"), val = tensor<int32, [4]>([2, 1, 64, 44])];
            tensor<fp16, [2, 64, 44]> transpose_38 = transpose(perm = transpose_38_perm_0, x = reshape_76)[name = string("transpose_25")];
            tensor<fp16, [2, 1, 64, 44]> reshape_79 = reshape(shape = reshape_79_shape_0, x = transpose_38)[name = string("reshape_79")];
            tensor<int32, [4]> tile_19_reps_0 = const()[name = string("tile_19_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 64, 44]> tile_19 = tile(reps = tile_19_reps_0, x = reshape_79)[name = string("tile_19")];
            tensor<int32, [3]> reshape_80_shape_0 = const()[name = string("reshape_80_shape_0"), val = tensor<int32, [3]>([8, 64, 44])];
            tensor<fp16, [8, 64, 44]> reshape_80 = reshape(shape = reshape_80_shape_0, x = tile_19)[name = string("reshape_80")];
            fp16 mul_462_y_0 = const()[name = string("mul_462_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 64, 44]> mul_462 = mul(x = add_54, y = mul_462_y_0)[name = string("mul_462")];
            bool matmul_18_transpose_y_0 = const()[name = string("matmul_18_transpose_y_0"), val = bool(true)];
            bool matmul_18_transpose_x_0 = const()[name = string("matmul_18_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 64, 64]> matmul_18 = matmul(transpose_x = matmul_18_transpose_x_0, transpose_y = matmul_18_transpose_y_0, x = mul_462, y = reshape_78)[name = string("matmul_18")];
            tensor<fp16, [8, 64, 64]> add_56 = add(x = matmul_18, y = reshape_1)[name = string("add_56")];
            int32 softmax_9_axis_0 = const()[name = string("softmax_9_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 64, 64]> softmax_9 = softmax(axis = softmax_9_axis_0, x = add_56)[name = string("softmax_9")];
            bool matmul_19_transpose_x_0 = const()[name = string("matmul_19_transpose_x_0"), val = bool(false)];
            bool matmul_19_transpose_y_0 = const()[name = string("matmul_19_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 64, 44]> matmul_19 = matmul(transpose_x = matmul_19_transpose_x_0, transpose_y = matmul_19_transpose_y_0, x = softmax_9, y = reshape_80)[name = string("matmul_19")];
            tensor<int32, [3]> transpose_39_perm_0 = const()[name = string("transpose_39_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_81_shape_0 = const()[name = string("reshape_81_shape_0"), val = tensor<int32, [2]>([64, 352])];
            tensor<fp16, [64, 8, 44]> transpose_39 = transpose(perm = transpose_39_perm_0, x = matmul_19)[name = string("transpose_24")];
            tensor<fp16, [64, 352]> reshape_81 = reshape(shape = reshape_81_shape_0, x = transpose_39)[name = string("reshape_81")];
            tensor<fp16, [64, 352]> mul_463 = mul(x = reshape_81, y = reshape_81)[name = string("mul_463")];
            tensor<int32, [1]> reduce_mean_99_axes_0 = const()[name = string("reduce_mean_99_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_99_keep_dims_0 = const()[name = string("reduce_mean_99_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_99 = reduce_mean(axes = reduce_mean_99_axes_0, keep_dims = reduce_mean_99_keep_dims_0, x = mul_463)[name = string("reduce_mean_99")];
            fp32 rsqrt_99_epsilon_0 = const()[name = string("rsqrt_99_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_99 = rsqrt(epsilon = rsqrt_99_epsilon_0, x = reduce_mean_99)[name = string("rsqrt_99")];
            tensor<fp16, [64, 352]> mul_464 = mul(x = reshape_81, y = rsqrt_99)[name = string("mul_464")];
            tensor<fp16, [352]> mul_465_y_0 = const()[name = string("mul_465_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5479360)))];
            tensor<fp16, [64, 352]> mul_465 = mul(x = mul_464, y = mul_465_y_0)[name = string("mul_465")];
            tensor<fp16, [352, 352]> tern_9_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5480128))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_9_o_weight_0_palettized")];
            tensor<fp16, [64, 352]> tern_9_o = linear(bias = linear_0_bias_0, weight = tern_9_o_weight_0_palettized, x = mul_465)[name = string("tern_9_o")];
            tensor<fp16, [352]> mul_466_y_0 = const()[name = string("mul_466_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5511168)))];
            tensor<fp16, [64, 352]> mul_466 = mul(x = tern_9_o, y = mul_466_y_0)[name = string("mul_466")];
            tensor<fp16, [64, 352]> add_57 = add(x = add_53, y = mul_466)[name = string("add_57")];
            tensor<fp16, [64, 352]> mul_467 = mul(x = add_57, y = add_57)[name = string("mul_467")];
            tensor<int32, [1]> reduce_mean_100_axes_0 = const()[name = string("reduce_mean_100_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_100_keep_dims_0 = const()[name = string("reduce_mean_100_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_100 = reduce_mean(axes = reduce_mean_100_axes_0, keep_dims = reduce_mean_100_keep_dims_0, x = mul_467)[name = string("reduce_mean_100")];
            fp32 rsqrt_100_epsilon_0 = const()[name = string("rsqrt_100_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_100 = rsqrt(epsilon = rsqrt_100_epsilon_0, x = reduce_mean_100)[name = string("rsqrt_100")];
            tensor<fp16, [64, 352]> mul_468 = mul(x = add_57, y = rsqrt_100)[name = string("mul_468")];
            tensor<fp16, [352]> mul_469_y_0 = const()[name = string("mul_469_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5511936)))];
            tensor<fp16, [64, 352]> mul_469 = mul(x = mul_468, y = mul_469_y_0)[name = string("mul_469")];
            tensor<fp16, [64, 352]> mul_470 = mul(x = mul_469, y = mul_469)[name = string("mul_470")];
            tensor<int32, [1]> reduce_mean_101_axes_0 = const()[name = string("reduce_mean_101_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_101_keep_dims_0 = const()[name = string("reduce_mean_101_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_101 = reduce_mean(axes = reduce_mean_101_axes_0, keep_dims = reduce_mean_101_keep_dims_0, x = mul_470)[name = string("reduce_mean_101")];
            fp32 rsqrt_101_epsilon_0 = const()[name = string("rsqrt_101_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_101 = rsqrt(epsilon = rsqrt_101_epsilon_0, x = reduce_mean_101)[name = string("rsqrt_101")];
            tensor<fp16, [64, 352]> mul_471 = mul(x = mul_469, y = rsqrt_101)[name = string("mul_471")];
            tensor<fp16, [352]> mul_472_y_0 = const()[name = string("mul_472_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5512704)))];
            tensor<fp16, [64, 352]> mul_472 = mul(x = mul_471, y = mul_472_y_0)[name = string("mul_472")];
            tensor<fp16, [960, 352]> tern_9_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5513472))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_9_w1_weight_0_palettized")];
            tensor<fp16, [64, 960]> tern_9_w1 = linear(bias = linear_4_bias_0, weight = tern_9_w1_weight_0_palettized, x = mul_472)[name = string("tern_9_w1")];
            tensor<fp16, [960]> mul_473_y_0 = const()[name = string("mul_473_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5598016)))];
            tensor<fp16, [64, 960]> mul_473 = mul(x = tern_9_w1, y = mul_473_y_0)[name = string("mul_473")];
            tensor<fp16, [352]> mul_476_y_0 = const()[name = string("mul_476_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5600000)))];
            tensor<fp16, [64, 352]> mul_476 = mul(x = mul_471, y = mul_476_y_0)[name = string("mul_476")];
            tensor<fp16, [960, 352]> tern_9_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5600768))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_9_w3_weight_0_palettized")];
            tensor<fp16, [64, 960]> tern_9_w3 = linear(bias = linear_4_bias_0, weight = tern_9_w3_weight_0_palettized, x = mul_476)[name = string("tern_9_w3")];
            tensor<fp16, [960]> mul_477_y_0 = const()[name = string("mul_477_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5685312)))];
            tensor<fp16, [64, 960]> mul_477 = mul(x = tern_9_w3, y = mul_477_y_0)[name = string("mul_477")];
            fp16 mul_478_y_0 = const()[name = string("mul_478_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [64, 960]> mul_478 = mul(x = mul_473, y = mul_478_y_0)[name = string("mul_478")];
            tensor<fp16, [64, 960]> tanh_9 = tanh(x = mul_478)[name = string("tanh_9")];
            fp16 mul_479_x_0 = const()[name = string("mul_479_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [64, 960]> mul_479 = mul(x = mul_479_x_0, y = tanh_9)[name = string("mul_479")];
            fp16 add_58_x_0 = const()[name = string("add_58_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [64, 960]> add_58 = add(x = add_58_x_0, y = mul_479)[name = string("add_58")];
            tensor<fp16, [64, 960]> mul_480 = mul(x = mul_473, y = add_58)[name = string("mul_480")];
            tensor<fp16, [64, 960]> mul_481 = mul(x = mul_480, y = mul_477)[name = string("mul_481")];
            tensor<fp16, [64, 960]> mul_482 = mul(x = mul_481, y = mul_481)[name = string("mul_482")];
            tensor<int32, [1]> reduce_mean_103_axes_0 = const()[name = string("reduce_mean_103_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_103_keep_dims_0 = const()[name = string("reduce_mean_103_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_103 = reduce_mean(axes = reduce_mean_103_axes_0, keep_dims = reduce_mean_103_keep_dims_0, x = mul_482)[name = string("reduce_mean_103")];
            fp32 rsqrt_103_epsilon_0 = const()[name = string("rsqrt_103_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_103 = rsqrt(epsilon = rsqrt_103_epsilon_0, x = reduce_mean_103)[name = string("rsqrt_103")];
            tensor<fp16, [64, 960]> mul_483 = mul(x = mul_481, y = rsqrt_103)[name = string("mul_483")];
            tensor<fp16, [960]> mul_484_y_0 = const()[name = string("mul_484_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5687296)))];
            tensor<fp16, [64, 960]> mul_484 = mul(x = mul_483, y = mul_484_y_0)[name = string("mul_484")];
            tensor<fp16, [352, 960]> tern_9_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5689280))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_9_w2_weight_0_palettized")];
            tensor<fp16, [64, 352]> tern_9_w2 = linear(bias = linear_0_bias_0, weight = tern_9_w2_weight_0_palettized, x = mul_484)[name = string("tern_9_w2")];
            tensor<fp16, [352]> mul_485_y_0 = const()[name = string("mul_485_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5773824)))];
            tensor<fp16, [64, 352]> mul_485 = mul(x = tern_9_w2, y = mul_485_y_0)[name = string("mul_485")];
            tensor<fp16, [64, 352]> add_59 = add(x = add_57, y = mul_485)[name = string("add_59")];
            tensor<fp16, [64, 352]> mul_486 = mul(x = add_59, y = add_59)[name = string("mul_486")];
            tensor<int32, [1]> reduce_mean_104_axes_0 = const()[name = string("reduce_mean_104_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_104_keep_dims_0 = const()[name = string("reduce_mean_104_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_104 = reduce_mean(axes = reduce_mean_104_axes_0, keep_dims = reduce_mean_104_keep_dims_0, x = mul_486)[name = string("reduce_mean_104")];
            fp32 rsqrt_104_epsilon_0 = const()[name = string("rsqrt_104_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_104 = rsqrt(epsilon = rsqrt_104_epsilon_0, x = reduce_mean_104)[name = string("rsqrt_104")];
            tensor<fp16, [64, 352]> mul_487 = mul(x = add_59, y = rsqrt_104)[name = string("mul_487")];
            tensor<fp16, [352]> mul_488_y_0 = const()[name = string("mul_488_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5774592)))];
            tensor<fp16, [64, 352]> mul_488 = mul(x = mul_487, y = mul_488_y_0)[name = string("mul_488")];
            tensor<fp16, [64, 352]> mul_489 = mul(x = mul_488, y = mul_488)[name = string("mul_489")];
            tensor<int32, [1]> reduce_mean_105_axes_0 = const()[name = string("reduce_mean_105_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_105_keep_dims_0 = const()[name = string("reduce_mean_105_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_105 = reduce_mean(axes = reduce_mean_105_axes_0, keep_dims = reduce_mean_105_keep_dims_0, x = mul_489)[name = string("reduce_mean_105")];
            fp32 rsqrt_105_epsilon_0 = const()[name = string("rsqrt_105_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_105 = rsqrt(epsilon = rsqrt_105_epsilon_0, x = reduce_mean_105)[name = string("rsqrt_105")];
            tensor<fp16, [64, 352]> mul_490 = mul(x = mul_488, y = rsqrt_105)[name = string("mul_490")];
            tensor<fp16, [352]> mul_491_y_0 = const()[name = string("mul_491_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5775360)))];
            tensor<fp16, [64, 352]> mul_491 = mul(x = mul_490, y = mul_491_y_0)[name = string("mul_491")];
            tensor<fp16, [352, 352]> tern_10_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5776128))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_10_q_weight_0_palettized")];
            tensor<fp16, [64, 352]> tern_10_q = linear(bias = linear_0_bias_0, weight = tern_10_q_weight_0_palettized, x = mul_491)[name = string("tern_10_q")];
            tensor<fp16, [352]> mul_492_y_0 = const()[name = string("mul_492_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5807168)))];
            tensor<fp16, [64, 352]> mul_492 = mul(x = tern_10_q, y = mul_492_y_0)[name = string("mul_492")];
            tensor<int32, [3]> reshape_82_shape_0 = const()[name = string("reshape_82_shape_0"), val = tensor<int32, [3]>([64, 8, 44])];
            tensor<fp16, [64, 8, 44]> reshape_82 = reshape(shape = reshape_82_shape_0, x = mul_492)[name = string("reshape_82")];
            tensor<int32, [3]> transpose_40_perm_0 = const()[name = string("transpose_40_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_495_y_0 = const()[name = string("mul_495_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5807936)))];
            tensor<fp16, [64, 352]> mul_495 = mul(x = mul_490, y = mul_495_y_0)[name = string("mul_495")];
            tensor<fp16, [88, 352]> tern_10_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5808704))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_10_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_10_k_bias_0 = const()[name = string("tern_10_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [64, 88]> tern_10_k = linear(bias = tern_10_k_bias_0, weight = tern_10_k_weight_0_palettized, x = mul_495)[name = string("tern_10_k")];
            tensor<fp16, [88]> mul_496_y_0 = const()[name = string("mul_496_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5816512)))];
            tensor<fp16, [64, 88]> mul_496 = mul(x = tern_10_k, y = mul_496_y_0)[name = string("mul_496")];
            tensor<int32, [3]> reshape_83_shape_0 = const()[name = string("reshape_83_shape_0"), val = tensor<int32, [3]>([64, 2, 44])];
            tensor<fp16, [64, 2, 44]> reshape_83 = reshape(shape = reshape_83_shape_0, x = mul_496)[name = string("reshape_83")];
            tensor<int32, [3]> transpose_41_perm_0 = const()[name = string("transpose_41_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_499_y_0 = const()[name = string("mul_499_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5816768)))];
            tensor<fp16, [64, 352]> mul_499 = mul(x = mul_490, y = mul_499_y_0)[name = string("mul_499")];
            tensor<fp16, [88, 352]> tern_10_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5817536))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_10_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_10_v_bias_0 = const()[name = string("tern_10_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [64, 88]> tern_10_v = linear(bias = tern_10_v_bias_0, weight = tern_10_v_weight_0_palettized, x = mul_499)[name = string("tern_10_v")];
            tensor<fp16, [88]> mul_500_y_0 = const()[name = string("mul_500_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5825344)))];
            tensor<fp16, [64, 88]> mul_500 = mul(x = tern_10_v, y = mul_500_y_0)[name = string("mul_500")];
            tensor<int32, [3]> reshape_84_shape_0 = const()[name = string("reshape_84_shape_0"), val = tensor<int32, [3]>([64, 2, 44])];
            tensor<fp16, [64, 2, 44]> reshape_84 = reshape(shape = reshape_84_shape_0, x = mul_500)[name = string("reshape_84")];
            tensor<int32, [3]> transpose_42_perm_0 = const()[name = string("transpose_42_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 64, 44]> transpose_40 = transpose(perm = transpose_40_perm_0, x = reshape_82)[name = string("transpose_23")];
            tensor<fp16, [8, 64, 44]> mul_501 = mul(x = transpose_40, y = transpose_40)[name = string("mul_501")];
            tensor<int32, [1]> reduce_mean_108_axes_0 = const()[name = string("reduce_mean_108_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_108_keep_dims_0 = const()[name = string("reduce_mean_108_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 64, 1]> reduce_mean_108 = reduce_mean(axes = reduce_mean_108_axes_0, keep_dims = reduce_mean_108_keep_dims_0, x = mul_501)[name = string("reduce_mean_108")];
            fp32 rsqrt_108_epsilon_0 = const()[name = string("rsqrt_108_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 64, 1]> rsqrt_108 = rsqrt(epsilon = rsqrt_108_epsilon_0, x = reduce_mean_108)[name = string("rsqrt_108")];
            tensor<fp16, [8, 64, 44]> mul_502 = mul(x = transpose_40, y = rsqrt_108)[name = string("mul_502")];
            tensor<fp16, [44]> mul_503_y_0 = const()[name = string("mul_503_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5825600)))];
            tensor<fp16, [8, 64, 44]> mul_503 = mul(x = mul_502, y = mul_503_y_0)[name = string("mul_503")];
            tensor<int32, [3]> slice_by_index_40_begin_0 = const()[name = string("slice_by_index_40_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_40_end_0 = const()[name = string("slice_by_index_40_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_40_end_mask_0 = const()[name = string("slice_by_index_40_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 64, 22]> slice_by_index_40 = slice_by_index(begin = slice_by_index_40_begin_0, end = slice_by_index_40_end_0, end_mask = slice_by_index_40_end_mask_0, x = mul_503)[name = string("slice_by_index_40")];
            tensor<int32, [3]> slice_by_index_41_begin_0 = const()[name = string("slice_by_index_41_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_41_end_0 = const()[name = string("slice_by_index_41_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_41_end_mask_0 = const()[name = string("slice_by_index_41_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 64, 22]> slice_by_index_41 = slice_by_index(begin = slice_by_index_41_begin_0, end = slice_by_index_41_end_0, end_mask = slice_by_index_41_end_mask_0, x = mul_503)[name = string("slice_by_index_41")];
            int32 concat_20_axis_0 = const()[name = string("concat_20_axis_0"), val = int32(-1)];
            bool concat_20_interleave_0 = const()[name = string("concat_20_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 64, 44]> concat_20 = concat(axis = concat_20_axis_0, interleave = concat_20_interleave_0, values = (slice_by_index_41, slice_by_index_40))[name = string("concat_20")];
            tensor<fp16, [44]> mul_504_y_0 = const()[name = string("mul_504_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 64, 44]> mul_504 = mul(x = concat_20, y = mul_504_y_0)[name = string("mul_504")];
            tensor<fp16, [8, 64, 44]> mul_505 = mul(x = mul_503, y = mul_11_y_0)[name = string("mul_505")];
            tensor<fp16, [8, 64, 44]> mul_506 = mul(x = mul_504, y = mul_12_y_0)[name = string("mul_506")];
            tensor<fp16, [8, 64, 44]> add_60 = add(x = mul_505, y = mul_506)[name = string("add_60")];
            tensor<fp16, [2, 64, 44]> transpose_41 = transpose(perm = transpose_41_perm_0, x = reshape_83)[name = string("transpose_22")];
            tensor<fp16, [2, 64, 44]> mul_507 = mul(x = transpose_41, y = transpose_41)[name = string("mul_507")];
            tensor<int32, [1]> reduce_mean_109_axes_0 = const()[name = string("reduce_mean_109_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_109_keep_dims_0 = const()[name = string("reduce_mean_109_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 64, 1]> reduce_mean_109 = reduce_mean(axes = reduce_mean_109_axes_0, keep_dims = reduce_mean_109_keep_dims_0, x = mul_507)[name = string("reduce_mean_109")];
            fp32 rsqrt_109_epsilon_0 = const()[name = string("rsqrt_109_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 64, 1]> rsqrt_109 = rsqrt(epsilon = rsqrt_109_epsilon_0, x = reduce_mean_109)[name = string("rsqrt_109")];
            tensor<fp16, [2, 64, 44]> mul_508 = mul(x = transpose_41, y = rsqrt_109)[name = string("mul_508")];
            tensor<fp16, [44]> mul_509_y_0 = const()[name = string("mul_509_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5825792)))];
            tensor<fp16, [2, 64, 44]> mul_509 = mul(x = mul_508, y = mul_509_y_0)[name = string("mul_509")];
            tensor<int32, [3]> slice_by_index_42_begin_0 = const()[name = string("slice_by_index_42_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_42_end_0 = const()[name = string("slice_by_index_42_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_42_end_mask_0 = const()[name = string("slice_by_index_42_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 64, 22]> slice_by_index_42 = slice_by_index(begin = slice_by_index_42_begin_0, end = slice_by_index_42_end_0, end_mask = slice_by_index_42_end_mask_0, x = mul_509)[name = string("slice_by_index_42")];
            tensor<int32, [3]> slice_by_index_43_begin_0 = const()[name = string("slice_by_index_43_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_43_end_0 = const()[name = string("slice_by_index_43_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_43_end_mask_0 = const()[name = string("slice_by_index_43_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 64, 22]> slice_by_index_43 = slice_by_index(begin = slice_by_index_43_begin_0, end = slice_by_index_43_end_0, end_mask = slice_by_index_43_end_mask_0, x = mul_509)[name = string("slice_by_index_43")];
            int32 concat_21_axis_0 = const()[name = string("concat_21_axis_0"), val = int32(-1)];
            bool concat_21_interleave_0 = const()[name = string("concat_21_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 64, 44]> concat_21 = concat(axis = concat_21_axis_0, interleave = concat_21_interleave_0, values = (slice_by_index_43, slice_by_index_42))[name = string("concat_21")];
            tensor<fp16, [44]> mul_510_y_0 = const()[name = string("mul_510_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 64, 44]> mul_510 = mul(x = concat_21, y = mul_510_y_0)[name = string("mul_510")];
            tensor<fp16, [2, 64, 44]> mul_511 = mul(x = mul_509, y = mul_11_y_0)[name = string("mul_511")];
            tensor<fp16, [2, 64, 44]> mul_512 = mul(x = mul_510, y = mul_12_y_0)[name = string("mul_512")];
            tensor<fp16, [2, 64, 44]> add_61 = add(x = mul_511, y = mul_512)[name = string("add_61")];
            tensor<int32, [4]> reshape_85_shape_0 = const()[name = string("reshape_85_shape_0"), val = tensor<int32, [4]>([2, 1, 64, 44])];
            tensor<fp16, [2, 1, 64, 44]> reshape_85 = reshape(shape = reshape_85_shape_0, x = add_61)[name = string("reshape_85")];
            tensor<int32, [4]> tile_20_reps_0 = const()[name = string("tile_20_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 64, 44]> tile_20 = tile(reps = tile_20_reps_0, x = reshape_85)[name = string("tile_20")];
            tensor<int32, [3]> reshape_86_shape_0 = const()[name = string("reshape_86_shape_0"), val = tensor<int32, [3]>([8, 64, 44])];
            tensor<fp16, [8, 64, 44]> reshape_86 = reshape(shape = reshape_86_shape_0, x = tile_20)[name = string("reshape_86")];
            tensor<int32, [4]> reshape_87_shape_0 = const()[name = string("reshape_87_shape_0"), val = tensor<int32, [4]>([2, 1, 64, 44])];
            tensor<fp16, [2, 64, 44]> transpose_42 = transpose(perm = transpose_42_perm_0, x = reshape_84)[name = string("transpose_21")];
            tensor<fp16, [2, 1, 64, 44]> reshape_87 = reshape(shape = reshape_87_shape_0, x = transpose_42)[name = string("reshape_87")];
            tensor<int32, [4]> tile_21_reps_0 = const()[name = string("tile_21_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 64, 44]> tile_21 = tile(reps = tile_21_reps_0, x = reshape_87)[name = string("tile_21")];
            tensor<int32, [3]> reshape_88_shape_0 = const()[name = string("reshape_88_shape_0"), val = tensor<int32, [3]>([8, 64, 44])];
            tensor<fp16, [8, 64, 44]> reshape_88 = reshape(shape = reshape_88_shape_0, x = tile_21)[name = string("reshape_88")];
            fp16 mul_513_y_0 = const()[name = string("mul_513_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 64, 44]> mul_513 = mul(x = add_60, y = mul_513_y_0)[name = string("mul_513")];
            bool matmul_20_transpose_y_0 = const()[name = string("matmul_20_transpose_y_0"), val = bool(true)];
            bool matmul_20_transpose_x_0 = const()[name = string("matmul_20_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 64, 64]> matmul_20 = matmul(transpose_x = matmul_20_transpose_x_0, transpose_y = matmul_20_transpose_y_0, x = mul_513, y = reshape_86)[name = string("matmul_20")];
            tensor<fp16, [8, 64, 64]> add_62 = add(x = matmul_20, y = reshape_1)[name = string("add_62")];
            int32 softmax_10_axis_0 = const()[name = string("softmax_10_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 64, 64]> softmax_10 = softmax(axis = softmax_10_axis_0, x = add_62)[name = string("softmax_10")];
            bool matmul_21_transpose_x_0 = const()[name = string("matmul_21_transpose_x_0"), val = bool(false)];
            bool matmul_21_transpose_y_0 = const()[name = string("matmul_21_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 64, 44]> matmul_21 = matmul(transpose_x = matmul_21_transpose_x_0, transpose_y = matmul_21_transpose_y_0, x = softmax_10, y = reshape_88)[name = string("matmul_21")];
            tensor<int32, [3]> transpose_43_perm_0 = const()[name = string("transpose_43_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_89_shape_0 = const()[name = string("reshape_89_shape_0"), val = tensor<int32, [2]>([64, 352])];
            tensor<fp16, [64, 8, 44]> transpose_43 = transpose(perm = transpose_43_perm_0, x = matmul_21)[name = string("transpose_20")];
            tensor<fp16, [64, 352]> reshape_89 = reshape(shape = reshape_89_shape_0, x = transpose_43)[name = string("reshape_89")];
            tensor<fp16, [64, 352]> mul_514 = mul(x = reshape_89, y = reshape_89)[name = string("mul_514")];
            tensor<int32, [1]> reduce_mean_110_axes_0 = const()[name = string("reduce_mean_110_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_110_keep_dims_0 = const()[name = string("reduce_mean_110_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_110 = reduce_mean(axes = reduce_mean_110_axes_0, keep_dims = reduce_mean_110_keep_dims_0, x = mul_514)[name = string("reduce_mean_110")];
            fp32 rsqrt_110_epsilon_0 = const()[name = string("rsqrt_110_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_110 = rsqrt(epsilon = rsqrt_110_epsilon_0, x = reduce_mean_110)[name = string("rsqrt_110")];
            tensor<fp16, [64, 352]> mul_515 = mul(x = reshape_89, y = rsqrt_110)[name = string("mul_515")];
            tensor<fp16, [352]> mul_516_y_0 = const()[name = string("mul_516_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5825984)))];
            tensor<fp16, [64, 352]> mul_516 = mul(x = mul_515, y = mul_516_y_0)[name = string("mul_516")];
            tensor<fp16, [352, 352]> tern_10_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5826752))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_10_o_weight_0_palettized")];
            tensor<fp16, [64, 352]> tern_10_o = linear(bias = linear_0_bias_0, weight = tern_10_o_weight_0_palettized, x = mul_516)[name = string("tern_10_o")];
            tensor<fp16, [352]> mul_517_y_0 = const()[name = string("mul_517_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5857792)))];
            tensor<fp16, [64, 352]> mul_517 = mul(x = tern_10_o, y = mul_517_y_0)[name = string("mul_517")];
            tensor<fp16, [64, 352]> add_63 = add(x = add_59, y = mul_517)[name = string("add_63")];
            tensor<fp16, [64, 352]> mul_518 = mul(x = add_63, y = add_63)[name = string("mul_518")];
            tensor<int32, [1]> reduce_mean_111_axes_0 = const()[name = string("reduce_mean_111_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_111_keep_dims_0 = const()[name = string("reduce_mean_111_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_111 = reduce_mean(axes = reduce_mean_111_axes_0, keep_dims = reduce_mean_111_keep_dims_0, x = mul_518)[name = string("reduce_mean_111")];
            fp32 rsqrt_111_epsilon_0 = const()[name = string("rsqrt_111_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_111 = rsqrt(epsilon = rsqrt_111_epsilon_0, x = reduce_mean_111)[name = string("rsqrt_111")];
            tensor<fp16, [64, 352]> mul_519 = mul(x = add_63, y = rsqrt_111)[name = string("mul_519")];
            tensor<fp16, [352]> mul_520_y_0 = const()[name = string("mul_520_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5858560)))];
            tensor<fp16, [64, 352]> mul_520 = mul(x = mul_519, y = mul_520_y_0)[name = string("mul_520")];
            tensor<fp16, [64, 352]> mul_521 = mul(x = mul_520, y = mul_520)[name = string("mul_521")];
            tensor<int32, [1]> reduce_mean_112_axes_0 = const()[name = string("reduce_mean_112_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_112_keep_dims_0 = const()[name = string("reduce_mean_112_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_112 = reduce_mean(axes = reduce_mean_112_axes_0, keep_dims = reduce_mean_112_keep_dims_0, x = mul_521)[name = string("reduce_mean_112")];
            fp32 rsqrt_112_epsilon_0 = const()[name = string("rsqrt_112_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_112 = rsqrt(epsilon = rsqrt_112_epsilon_0, x = reduce_mean_112)[name = string("rsqrt_112")];
            tensor<fp16, [64, 352]> mul_522 = mul(x = mul_520, y = rsqrt_112)[name = string("mul_522")];
            tensor<fp16, [352]> mul_523_y_0 = const()[name = string("mul_523_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5859328)))];
            tensor<fp16, [64, 352]> mul_523 = mul(x = mul_522, y = mul_523_y_0)[name = string("mul_523")];
            tensor<fp16, [960, 352]> tern_10_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5860096))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_10_w1_weight_0_palettized")];
            tensor<fp16, [64, 960]> tern_10_w1 = linear(bias = linear_4_bias_0, weight = tern_10_w1_weight_0_palettized, x = mul_523)[name = string("tern_10_w1")];
            tensor<fp16, [960]> mul_524_y_0 = const()[name = string("mul_524_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5944640)))];
            tensor<fp16, [64, 960]> mul_524 = mul(x = tern_10_w1, y = mul_524_y_0)[name = string("mul_524")];
            tensor<fp16, [352]> mul_527_y_0 = const()[name = string("mul_527_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5946624)))];
            tensor<fp16, [64, 352]> mul_527 = mul(x = mul_522, y = mul_527_y_0)[name = string("mul_527")];
            tensor<fp16, [960, 352]> tern_10_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5947392))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_10_w3_weight_0_palettized")];
            tensor<fp16, [64, 960]> tern_10_w3 = linear(bias = linear_4_bias_0, weight = tern_10_w3_weight_0_palettized, x = mul_527)[name = string("tern_10_w3")];
            tensor<fp16, [960]> mul_528_y_0 = const()[name = string("mul_528_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6031936)))];
            tensor<fp16, [64, 960]> mul_528 = mul(x = tern_10_w3, y = mul_528_y_0)[name = string("mul_528")];
            fp16 mul_529_y_0 = const()[name = string("mul_529_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [64, 960]> mul_529 = mul(x = mul_524, y = mul_529_y_0)[name = string("mul_529")];
            tensor<fp16, [64, 960]> tanh_10 = tanh(x = mul_529)[name = string("tanh_10")];
            fp16 mul_530_x_0 = const()[name = string("mul_530_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [64, 960]> mul_530 = mul(x = mul_530_x_0, y = tanh_10)[name = string("mul_530")];
            fp16 add_64_x_0 = const()[name = string("add_64_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [64, 960]> add_64 = add(x = add_64_x_0, y = mul_530)[name = string("add_64")];
            tensor<fp16, [64, 960]> mul_531 = mul(x = mul_524, y = add_64)[name = string("mul_531")];
            tensor<fp16, [64, 960]> mul_532 = mul(x = mul_531, y = mul_528)[name = string("mul_532")];
            tensor<fp16, [64, 960]> mul_533 = mul(x = mul_532, y = mul_532)[name = string("mul_533")];
            tensor<int32, [1]> reduce_mean_114_axes_0 = const()[name = string("reduce_mean_114_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_114_keep_dims_0 = const()[name = string("reduce_mean_114_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_114 = reduce_mean(axes = reduce_mean_114_axes_0, keep_dims = reduce_mean_114_keep_dims_0, x = mul_533)[name = string("reduce_mean_114")];
            fp32 rsqrt_114_epsilon_0 = const()[name = string("rsqrt_114_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_114 = rsqrt(epsilon = rsqrt_114_epsilon_0, x = reduce_mean_114)[name = string("rsqrt_114")];
            tensor<fp16, [64, 960]> mul_534 = mul(x = mul_532, y = rsqrt_114)[name = string("mul_534")];
            tensor<fp16, [960]> mul_535_y_0 = const()[name = string("mul_535_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6033920)))];
            tensor<fp16, [64, 960]> mul_535 = mul(x = mul_534, y = mul_535_y_0)[name = string("mul_535")];
            tensor<fp16, [352, 960]> tern_10_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6035904))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_10_w2_weight_0_palettized")];
            tensor<fp16, [64, 352]> tern_10_w2 = linear(bias = linear_0_bias_0, weight = tern_10_w2_weight_0_palettized, x = mul_535)[name = string("tern_10_w2")];
            tensor<fp16, [352]> mul_536_y_0 = const()[name = string("mul_536_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6120448)))];
            tensor<fp16, [64, 352]> mul_536 = mul(x = tern_10_w2, y = mul_536_y_0)[name = string("mul_536")];
            tensor<fp16, [64, 352]> add_65 = add(x = add_63, y = mul_536)[name = string("add_65")];
            tensor<fp16, [64, 352]> mul_537 = mul(x = add_65, y = add_65)[name = string("mul_537")];
            tensor<int32, [1]> reduce_mean_115_axes_0 = const()[name = string("reduce_mean_115_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_115_keep_dims_0 = const()[name = string("reduce_mean_115_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_115 = reduce_mean(axes = reduce_mean_115_axes_0, keep_dims = reduce_mean_115_keep_dims_0, x = mul_537)[name = string("reduce_mean_115")];
            fp32 rsqrt_115_epsilon_0 = const()[name = string("rsqrt_115_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_115 = rsqrt(epsilon = rsqrt_115_epsilon_0, x = reduce_mean_115)[name = string("rsqrt_115")];
            tensor<fp16, [64, 352]> mul_538 = mul(x = add_65, y = rsqrt_115)[name = string("mul_538")];
            tensor<fp16, [352]> mul_539_y_0 = const()[name = string("mul_539_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6121216)))];
            tensor<fp16, [64, 352]> mul_539 = mul(x = mul_538, y = mul_539_y_0)[name = string("mul_539")];
            tensor<fp16, [64, 352]> mul_540 = mul(x = mul_539, y = mul_539)[name = string("mul_540")];
            tensor<int32, [1]> reduce_mean_116_axes_0 = const()[name = string("reduce_mean_116_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_116_keep_dims_0 = const()[name = string("reduce_mean_116_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_116 = reduce_mean(axes = reduce_mean_116_axes_0, keep_dims = reduce_mean_116_keep_dims_0, x = mul_540)[name = string("reduce_mean_116")];
            fp32 rsqrt_116_epsilon_0 = const()[name = string("rsqrt_116_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_116 = rsqrt(epsilon = rsqrt_116_epsilon_0, x = reduce_mean_116)[name = string("rsqrt_116")];
            tensor<fp16, [64, 352]> mul_541 = mul(x = mul_539, y = rsqrt_116)[name = string("mul_541")];
            tensor<fp16, [352]> mul_542_y_0 = const()[name = string("mul_542_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6121984)))];
            tensor<fp16, [64, 352]> mul_542 = mul(x = mul_541, y = mul_542_y_0)[name = string("mul_542")];
            tensor<fp16, [352, 352]> tern_11_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6122752))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_11_q_weight_0_palettized")];
            tensor<fp16, [64, 352]> tern_11_q = linear(bias = linear_0_bias_0, weight = tern_11_q_weight_0_palettized, x = mul_542)[name = string("tern_11_q")];
            tensor<fp16, [352]> mul_543_y_0 = const()[name = string("mul_543_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6153792)))];
            tensor<fp16, [64, 352]> mul_543 = mul(x = tern_11_q, y = mul_543_y_0)[name = string("mul_543")];
            tensor<int32, [3]> reshape_90_shape_0 = const()[name = string("reshape_90_shape_0"), val = tensor<int32, [3]>([64, 8, 44])];
            tensor<fp16, [64, 8, 44]> reshape_90 = reshape(shape = reshape_90_shape_0, x = mul_543)[name = string("reshape_90")];
            tensor<int32, [3]> transpose_44_perm_0 = const()[name = string("transpose_44_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_546_y_0 = const()[name = string("mul_546_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6154560)))];
            tensor<fp16, [64, 352]> mul_546 = mul(x = mul_541, y = mul_546_y_0)[name = string("mul_546")];
            tensor<fp16, [88, 352]> tern_11_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6155328))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_11_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_11_k_bias_0 = const()[name = string("tern_11_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [64, 88]> tern_11_k = linear(bias = tern_11_k_bias_0, weight = tern_11_k_weight_0_palettized, x = mul_546)[name = string("tern_11_k")];
            tensor<fp16, [88]> mul_547_y_0 = const()[name = string("mul_547_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6163136)))];
            tensor<fp16, [64, 88]> mul_547 = mul(x = tern_11_k, y = mul_547_y_0)[name = string("mul_547")];
            tensor<int32, [3]> reshape_91_shape_0 = const()[name = string("reshape_91_shape_0"), val = tensor<int32, [3]>([64, 2, 44])];
            tensor<fp16, [64, 2, 44]> reshape_91 = reshape(shape = reshape_91_shape_0, x = mul_547)[name = string("reshape_91")];
            tensor<int32, [3]> transpose_45_perm_0 = const()[name = string("transpose_45_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_550_y_0 = const()[name = string("mul_550_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6163392)))];
            tensor<fp16, [64, 352]> mul_550 = mul(x = mul_541, y = mul_550_y_0)[name = string("mul_550")];
            tensor<fp16, [88, 352]> tern_11_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6164160))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_11_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_11_v_bias_0 = const()[name = string("tern_11_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [64, 88]> tern_11_v = linear(bias = tern_11_v_bias_0, weight = tern_11_v_weight_0_palettized, x = mul_550)[name = string("tern_11_v")];
            tensor<fp16, [88]> mul_551_y_0 = const()[name = string("mul_551_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6171968)))];
            tensor<fp16, [64, 88]> mul_551 = mul(x = tern_11_v, y = mul_551_y_0)[name = string("mul_551")];
            tensor<int32, [3]> reshape_92_shape_0 = const()[name = string("reshape_92_shape_0"), val = tensor<int32, [3]>([64, 2, 44])];
            tensor<fp16, [64, 2, 44]> reshape_92 = reshape(shape = reshape_92_shape_0, x = mul_551)[name = string("reshape_92")];
            tensor<int32, [3]> transpose_46_perm_0 = const()[name = string("transpose_46_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 64, 44]> transpose_44 = transpose(perm = transpose_44_perm_0, x = reshape_90)[name = string("transpose_19")];
            tensor<fp16, [8, 64, 44]> mul_552 = mul(x = transpose_44, y = transpose_44)[name = string("mul_552")];
            tensor<int32, [1]> reduce_mean_119_axes_0 = const()[name = string("reduce_mean_119_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_119_keep_dims_0 = const()[name = string("reduce_mean_119_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 64, 1]> reduce_mean_119 = reduce_mean(axes = reduce_mean_119_axes_0, keep_dims = reduce_mean_119_keep_dims_0, x = mul_552)[name = string("reduce_mean_119")];
            fp32 rsqrt_119_epsilon_0 = const()[name = string("rsqrt_119_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 64, 1]> rsqrt_119 = rsqrt(epsilon = rsqrt_119_epsilon_0, x = reduce_mean_119)[name = string("rsqrt_119")];
            tensor<fp16, [8, 64, 44]> mul_553 = mul(x = transpose_44, y = rsqrt_119)[name = string("mul_553")];
            tensor<fp16, [44]> mul_554_y_0 = const()[name = string("mul_554_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6172224)))];
            tensor<fp16, [8, 64, 44]> mul_554 = mul(x = mul_553, y = mul_554_y_0)[name = string("mul_554")];
            tensor<int32, [3]> slice_by_index_44_begin_0 = const()[name = string("slice_by_index_44_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_44_end_0 = const()[name = string("slice_by_index_44_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_44_end_mask_0 = const()[name = string("slice_by_index_44_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 64, 22]> slice_by_index_44 = slice_by_index(begin = slice_by_index_44_begin_0, end = slice_by_index_44_end_0, end_mask = slice_by_index_44_end_mask_0, x = mul_554)[name = string("slice_by_index_44")];
            tensor<int32, [3]> slice_by_index_45_begin_0 = const()[name = string("slice_by_index_45_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_45_end_0 = const()[name = string("slice_by_index_45_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_45_end_mask_0 = const()[name = string("slice_by_index_45_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 64, 22]> slice_by_index_45 = slice_by_index(begin = slice_by_index_45_begin_0, end = slice_by_index_45_end_0, end_mask = slice_by_index_45_end_mask_0, x = mul_554)[name = string("slice_by_index_45")];
            int32 concat_22_axis_0 = const()[name = string("concat_22_axis_0"), val = int32(-1)];
            bool concat_22_interleave_0 = const()[name = string("concat_22_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 64, 44]> concat_22 = concat(axis = concat_22_axis_0, interleave = concat_22_interleave_0, values = (slice_by_index_45, slice_by_index_44))[name = string("concat_22")];
            tensor<fp16, [44]> mul_555_y_0 = const()[name = string("mul_555_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 64, 44]> mul_555 = mul(x = concat_22, y = mul_555_y_0)[name = string("mul_555")];
            tensor<fp16, [8, 64, 44]> mul_556 = mul(x = mul_554, y = mul_11_y_0)[name = string("mul_556")];
            tensor<fp16, [8, 64, 44]> mul_557 = mul(x = mul_555, y = mul_12_y_0)[name = string("mul_557")];
            tensor<fp16, [8, 64, 44]> add_66 = add(x = mul_556, y = mul_557)[name = string("add_66")];
            tensor<fp16, [2, 64, 44]> transpose_45 = transpose(perm = transpose_45_perm_0, x = reshape_91)[name = string("transpose_18")];
            tensor<fp16, [2, 64, 44]> mul_558 = mul(x = transpose_45, y = transpose_45)[name = string("mul_558")];
            tensor<int32, [1]> reduce_mean_120_axes_0 = const()[name = string("reduce_mean_120_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_120_keep_dims_0 = const()[name = string("reduce_mean_120_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 64, 1]> reduce_mean_120 = reduce_mean(axes = reduce_mean_120_axes_0, keep_dims = reduce_mean_120_keep_dims_0, x = mul_558)[name = string("reduce_mean_120")];
            fp32 rsqrt_120_epsilon_0 = const()[name = string("rsqrt_120_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 64, 1]> rsqrt_120 = rsqrt(epsilon = rsqrt_120_epsilon_0, x = reduce_mean_120)[name = string("rsqrt_120")];
            tensor<fp16, [2, 64, 44]> mul_559 = mul(x = transpose_45, y = rsqrt_120)[name = string("mul_559")];
            tensor<fp16, [44]> mul_560_y_0 = const()[name = string("mul_560_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6172416)))];
            tensor<fp16, [2, 64, 44]> mul_560 = mul(x = mul_559, y = mul_560_y_0)[name = string("mul_560")];
            tensor<int32, [3]> slice_by_index_46_begin_0 = const()[name = string("slice_by_index_46_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_46_end_0 = const()[name = string("slice_by_index_46_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_46_end_mask_0 = const()[name = string("slice_by_index_46_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 64, 22]> slice_by_index_46 = slice_by_index(begin = slice_by_index_46_begin_0, end = slice_by_index_46_end_0, end_mask = slice_by_index_46_end_mask_0, x = mul_560)[name = string("slice_by_index_46")];
            tensor<int32, [3]> slice_by_index_47_begin_0 = const()[name = string("slice_by_index_47_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_47_end_0 = const()[name = string("slice_by_index_47_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_47_end_mask_0 = const()[name = string("slice_by_index_47_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 64, 22]> slice_by_index_47 = slice_by_index(begin = slice_by_index_47_begin_0, end = slice_by_index_47_end_0, end_mask = slice_by_index_47_end_mask_0, x = mul_560)[name = string("slice_by_index_47")];
            int32 concat_23_axis_0 = const()[name = string("concat_23_axis_0"), val = int32(-1)];
            bool concat_23_interleave_0 = const()[name = string("concat_23_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 64, 44]> concat_23 = concat(axis = concat_23_axis_0, interleave = concat_23_interleave_0, values = (slice_by_index_47, slice_by_index_46))[name = string("concat_23")];
            tensor<fp16, [44]> mul_561_y_0 = const()[name = string("mul_561_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 64, 44]> mul_561 = mul(x = concat_23, y = mul_561_y_0)[name = string("mul_561")];
            tensor<fp16, [2, 64, 44]> mul_562 = mul(x = mul_560, y = mul_11_y_0)[name = string("mul_562")];
            tensor<fp16, [2, 64, 44]> mul_563 = mul(x = mul_561, y = mul_12_y_0)[name = string("mul_563")];
            tensor<fp16, [2, 64, 44]> add_67 = add(x = mul_562, y = mul_563)[name = string("add_67")];
            tensor<int32, [4]> reshape_93_shape_0 = const()[name = string("reshape_93_shape_0"), val = tensor<int32, [4]>([2, 1, 64, 44])];
            tensor<fp16, [2, 1, 64, 44]> reshape_93 = reshape(shape = reshape_93_shape_0, x = add_67)[name = string("reshape_93")];
            tensor<int32, [4]> tile_22_reps_0 = const()[name = string("tile_22_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 64, 44]> tile_22 = tile(reps = tile_22_reps_0, x = reshape_93)[name = string("tile_22")];
            tensor<int32, [3]> reshape_94_shape_0 = const()[name = string("reshape_94_shape_0"), val = tensor<int32, [3]>([8, 64, 44])];
            tensor<fp16, [8, 64, 44]> reshape_94 = reshape(shape = reshape_94_shape_0, x = tile_22)[name = string("reshape_94")];
            tensor<int32, [4]> reshape_95_shape_0 = const()[name = string("reshape_95_shape_0"), val = tensor<int32, [4]>([2, 1, 64, 44])];
            tensor<fp16, [2, 64, 44]> transpose_46 = transpose(perm = transpose_46_perm_0, x = reshape_92)[name = string("transpose_17")];
            tensor<fp16, [2, 1, 64, 44]> reshape_95 = reshape(shape = reshape_95_shape_0, x = transpose_46)[name = string("reshape_95")];
            tensor<int32, [4]> tile_23_reps_0 = const()[name = string("tile_23_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 64, 44]> tile_23 = tile(reps = tile_23_reps_0, x = reshape_95)[name = string("tile_23")];
            tensor<int32, [3]> reshape_96_shape_0 = const()[name = string("reshape_96_shape_0"), val = tensor<int32, [3]>([8, 64, 44])];
            tensor<fp16, [8, 64, 44]> reshape_96 = reshape(shape = reshape_96_shape_0, x = tile_23)[name = string("reshape_96")];
            fp16 mul_564_y_0 = const()[name = string("mul_564_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 64, 44]> mul_564 = mul(x = add_66, y = mul_564_y_0)[name = string("mul_564")];
            bool matmul_22_transpose_y_0 = const()[name = string("matmul_22_transpose_y_0"), val = bool(true)];
            bool matmul_22_transpose_x_0 = const()[name = string("matmul_22_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 64, 64]> matmul_22 = matmul(transpose_x = matmul_22_transpose_x_0, transpose_y = matmul_22_transpose_y_0, x = mul_564, y = reshape_94)[name = string("matmul_22")];
            tensor<fp16, [8, 64, 64]> add_68 = add(x = matmul_22, y = reshape_1)[name = string("add_68")];
            int32 softmax_11_axis_0 = const()[name = string("softmax_11_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 64, 64]> softmax_11 = softmax(axis = softmax_11_axis_0, x = add_68)[name = string("softmax_11")];
            bool matmul_23_transpose_x_0 = const()[name = string("matmul_23_transpose_x_0"), val = bool(false)];
            bool matmul_23_transpose_y_0 = const()[name = string("matmul_23_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 64, 44]> matmul_23 = matmul(transpose_x = matmul_23_transpose_x_0, transpose_y = matmul_23_transpose_y_0, x = softmax_11, y = reshape_96)[name = string("matmul_23")];
            tensor<int32, [3]> transpose_47_perm_0 = const()[name = string("transpose_47_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_97_shape_0 = const()[name = string("reshape_97_shape_0"), val = tensor<int32, [2]>([64, 352])];
            tensor<fp16, [64, 8, 44]> transpose_47 = transpose(perm = transpose_47_perm_0, x = matmul_23)[name = string("transpose_16")];
            tensor<fp16, [64, 352]> reshape_97 = reshape(shape = reshape_97_shape_0, x = transpose_47)[name = string("reshape_97")];
            tensor<fp16, [64, 352]> mul_565 = mul(x = reshape_97, y = reshape_97)[name = string("mul_565")];
            tensor<int32, [1]> reduce_mean_121_axes_0 = const()[name = string("reduce_mean_121_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_121_keep_dims_0 = const()[name = string("reduce_mean_121_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_121 = reduce_mean(axes = reduce_mean_121_axes_0, keep_dims = reduce_mean_121_keep_dims_0, x = mul_565)[name = string("reduce_mean_121")];
            fp32 rsqrt_121_epsilon_0 = const()[name = string("rsqrt_121_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_121 = rsqrt(epsilon = rsqrt_121_epsilon_0, x = reduce_mean_121)[name = string("rsqrt_121")];
            tensor<fp16, [64, 352]> mul_566 = mul(x = reshape_97, y = rsqrt_121)[name = string("mul_566")];
            tensor<fp16, [352]> mul_567_y_0 = const()[name = string("mul_567_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6172608)))];
            tensor<fp16, [64, 352]> mul_567 = mul(x = mul_566, y = mul_567_y_0)[name = string("mul_567")];
            tensor<fp16, [352, 352]> tern_11_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6173376))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_11_o_weight_0_palettized")];
            tensor<fp16, [64, 352]> tern_11_o = linear(bias = linear_0_bias_0, weight = tern_11_o_weight_0_palettized, x = mul_567)[name = string("tern_11_o")];
            tensor<fp16, [352]> mul_568_y_0 = const()[name = string("mul_568_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6204416)))];
            tensor<fp16, [64, 352]> mul_568 = mul(x = tern_11_o, y = mul_568_y_0)[name = string("mul_568")];
            tensor<fp16, [64, 352]> add_69 = add(x = add_65, y = mul_568)[name = string("add_69")];
            tensor<fp16, [64, 352]> mul_569 = mul(x = add_69, y = add_69)[name = string("mul_569")];
            tensor<int32, [1]> reduce_mean_122_axes_0 = const()[name = string("reduce_mean_122_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_122_keep_dims_0 = const()[name = string("reduce_mean_122_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_122 = reduce_mean(axes = reduce_mean_122_axes_0, keep_dims = reduce_mean_122_keep_dims_0, x = mul_569)[name = string("reduce_mean_122")];
            fp32 rsqrt_122_epsilon_0 = const()[name = string("rsqrt_122_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_122 = rsqrt(epsilon = rsqrt_122_epsilon_0, x = reduce_mean_122)[name = string("rsqrt_122")];
            tensor<fp16, [64, 352]> mul_570 = mul(x = add_69, y = rsqrt_122)[name = string("mul_570")];
            tensor<fp16, [352]> mul_571_y_0 = const()[name = string("mul_571_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6205184)))];
            tensor<fp16, [64, 352]> mul_571 = mul(x = mul_570, y = mul_571_y_0)[name = string("mul_571")];
            tensor<fp16, [64, 352]> mul_572 = mul(x = mul_571, y = mul_571)[name = string("mul_572")];
            tensor<int32, [1]> reduce_mean_123_axes_0 = const()[name = string("reduce_mean_123_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_123_keep_dims_0 = const()[name = string("reduce_mean_123_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_123 = reduce_mean(axes = reduce_mean_123_axes_0, keep_dims = reduce_mean_123_keep_dims_0, x = mul_572)[name = string("reduce_mean_123")];
            fp32 rsqrt_123_epsilon_0 = const()[name = string("rsqrt_123_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_123 = rsqrt(epsilon = rsqrt_123_epsilon_0, x = reduce_mean_123)[name = string("rsqrt_123")];
            tensor<fp16, [64, 352]> mul_573 = mul(x = mul_571, y = rsqrt_123)[name = string("mul_573")];
            tensor<fp16, [352]> mul_574_y_0 = const()[name = string("mul_574_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6205952)))];
            tensor<fp16, [64, 352]> mul_574 = mul(x = mul_573, y = mul_574_y_0)[name = string("mul_574")];
            tensor<fp16, [960, 352]> tern_11_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6206720))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_11_w1_weight_0_palettized")];
            tensor<fp16, [64, 960]> tern_11_w1 = linear(bias = linear_4_bias_0, weight = tern_11_w1_weight_0_palettized, x = mul_574)[name = string("tern_11_w1")];
            tensor<fp16, [960]> mul_575_y_0 = const()[name = string("mul_575_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6291264)))];
            tensor<fp16, [64, 960]> mul_575 = mul(x = tern_11_w1, y = mul_575_y_0)[name = string("mul_575")];
            tensor<fp16, [352]> mul_578_y_0 = const()[name = string("mul_578_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6293248)))];
            tensor<fp16, [64, 352]> mul_578 = mul(x = mul_573, y = mul_578_y_0)[name = string("mul_578")];
            tensor<fp16, [960, 352]> tern_11_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6294016))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_11_w3_weight_0_palettized")];
            tensor<fp16, [64, 960]> tern_11_w3 = linear(bias = linear_4_bias_0, weight = tern_11_w3_weight_0_palettized, x = mul_578)[name = string("tern_11_w3")];
            tensor<fp16, [960]> mul_579_y_0 = const()[name = string("mul_579_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6378560)))];
            tensor<fp16, [64, 960]> mul_579 = mul(x = tern_11_w3, y = mul_579_y_0)[name = string("mul_579")];
            fp16 mul_580_y_0 = const()[name = string("mul_580_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [64, 960]> mul_580 = mul(x = mul_575, y = mul_580_y_0)[name = string("mul_580")];
            tensor<fp16, [64, 960]> tanh_11 = tanh(x = mul_580)[name = string("tanh_11")];
            fp16 mul_581_x_0 = const()[name = string("mul_581_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [64, 960]> mul_581 = mul(x = mul_581_x_0, y = tanh_11)[name = string("mul_581")];
            fp16 add_70_x_0 = const()[name = string("add_70_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [64, 960]> add_70 = add(x = add_70_x_0, y = mul_581)[name = string("add_70")];
            tensor<fp16, [64, 960]> mul_582 = mul(x = mul_575, y = add_70)[name = string("mul_582")];
            tensor<fp16, [64, 960]> mul_583 = mul(x = mul_582, y = mul_579)[name = string("mul_583")];
            tensor<fp16, [64, 960]> mul_584 = mul(x = mul_583, y = mul_583)[name = string("mul_584")];
            tensor<int32, [1]> reduce_mean_125_axes_0 = const()[name = string("reduce_mean_125_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_125_keep_dims_0 = const()[name = string("reduce_mean_125_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_125 = reduce_mean(axes = reduce_mean_125_axes_0, keep_dims = reduce_mean_125_keep_dims_0, x = mul_584)[name = string("reduce_mean_125")];
            fp32 rsqrt_125_epsilon_0 = const()[name = string("rsqrt_125_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_125 = rsqrt(epsilon = rsqrt_125_epsilon_0, x = reduce_mean_125)[name = string("rsqrt_125")];
            tensor<fp16, [64, 960]> mul_585 = mul(x = mul_583, y = rsqrt_125)[name = string("mul_585")];
            tensor<fp16, [960]> mul_586_y_0 = const()[name = string("mul_586_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6380544)))];
            tensor<fp16, [64, 960]> mul_586 = mul(x = mul_585, y = mul_586_y_0)[name = string("mul_586")];
            tensor<fp16, [352, 960]> tern_11_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6382528))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_11_w2_weight_0_palettized")];
            tensor<fp16, [64, 352]> tern_11_w2 = linear(bias = linear_0_bias_0, weight = tern_11_w2_weight_0_palettized, x = mul_586)[name = string("tern_11_w2")];
            tensor<fp16, [352]> mul_587_y_0 = const()[name = string("mul_587_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6467072)))];
            tensor<fp16, [64, 352]> mul_587 = mul(x = tern_11_w2, y = mul_587_y_0)[name = string("mul_587")];
            tensor<fp16, [64, 352]> add_71 = add(x = add_69, y = mul_587)[name = string("add_71")];
            tensor<fp16, [64, 352]> mul_588 = mul(x = add_71, y = add_71)[name = string("mul_588")];
            tensor<int32, [1]> reduce_mean_126_axes_0 = const()[name = string("reduce_mean_126_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_126_keep_dims_0 = const()[name = string("reduce_mean_126_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_126 = reduce_mean(axes = reduce_mean_126_axes_0, keep_dims = reduce_mean_126_keep_dims_0, x = mul_588)[name = string("reduce_mean_126")];
            fp32 rsqrt_126_epsilon_0 = const()[name = string("rsqrt_126_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_126 = rsqrt(epsilon = rsqrt_126_epsilon_0, x = reduce_mean_126)[name = string("rsqrt_126")];
            tensor<fp16, [64, 352]> mul_589 = mul(x = add_71, y = rsqrt_126)[name = string("mul_589")];
            tensor<fp16, [352]> mul_590_y_0 = const()[name = string("mul_590_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6467840)))];
            tensor<fp16, [64, 352]> mul_590 = mul(x = mul_589, y = mul_590_y_0)[name = string("mul_590")];
            tensor<fp16, [64, 352]> mul_591 = mul(x = mul_590, y = mul_590)[name = string("mul_591")];
            tensor<int32, [1]> reduce_mean_127_axes_0 = const()[name = string("reduce_mean_127_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_127_keep_dims_0 = const()[name = string("reduce_mean_127_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_127 = reduce_mean(axes = reduce_mean_127_axes_0, keep_dims = reduce_mean_127_keep_dims_0, x = mul_591)[name = string("reduce_mean_127")];
            fp32 rsqrt_127_epsilon_0 = const()[name = string("rsqrt_127_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_127 = rsqrt(epsilon = rsqrt_127_epsilon_0, x = reduce_mean_127)[name = string("rsqrt_127")];
            tensor<fp16, [64, 352]> mul_592 = mul(x = mul_590, y = rsqrt_127)[name = string("mul_592")];
            tensor<fp16, [352]> mul_593_y_0 = const()[name = string("mul_593_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6468608)))];
            tensor<fp16, [64, 352]> mul_593 = mul(x = mul_592, y = mul_593_y_0)[name = string("mul_593")];
            tensor<fp16, [352, 352]> tern_12_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6469376))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_12_q_weight_0_palettized")];
            tensor<fp16, [64, 352]> tern_12_q = linear(bias = linear_0_bias_0, weight = tern_12_q_weight_0_palettized, x = mul_593)[name = string("tern_12_q")];
            tensor<fp16, [352]> mul_594_y_0 = const()[name = string("mul_594_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6500416)))];
            tensor<fp16, [64, 352]> mul_594 = mul(x = tern_12_q, y = mul_594_y_0)[name = string("mul_594")];
            tensor<int32, [3]> reshape_98_shape_0 = const()[name = string("reshape_98_shape_0"), val = tensor<int32, [3]>([64, 8, 44])];
            tensor<fp16, [64, 8, 44]> reshape_98 = reshape(shape = reshape_98_shape_0, x = mul_594)[name = string("reshape_98")];
            tensor<int32, [3]> transpose_48_perm_0 = const()[name = string("transpose_48_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_597_y_0 = const()[name = string("mul_597_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6501184)))];
            tensor<fp16, [64, 352]> mul_597 = mul(x = mul_592, y = mul_597_y_0)[name = string("mul_597")];
            tensor<fp16, [88, 352]> tern_12_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6501952))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_12_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_12_k_bias_0 = const()[name = string("tern_12_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [64, 88]> tern_12_k = linear(bias = tern_12_k_bias_0, weight = tern_12_k_weight_0_palettized, x = mul_597)[name = string("tern_12_k")];
            tensor<fp16, [88]> mul_598_y_0 = const()[name = string("mul_598_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6509760)))];
            tensor<fp16, [64, 88]> mul_598 = mul(x = tern_12_k, y = mul_598_y_0)[name = string("mul_598")];
            tensor<int32, [3]> reshape_99_shape_0 = const()[name = string("reshape_99_shape_0"), val = tensor<int32, [3]>([64, 2, 44])];
            tensor<fp16, [64, 2, 44]> reshape_99 = reshape(shape = reshape_99_shape_0, x = mul_598)[name = string("reshape_99")];
            tensor<int32, [3]> transpose_49_perm_0 = const()[name = string("transpose_49_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_601_y_0 = const()[name = string("mul_601_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6510016)))];
            tensor<fp16, [64, 352]> mul_601 = mul(x = mul_592, y = mul_601_y_0)[name = string("mul_601")];
            tensor<fp16, [88, 352]> tern_12_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6510784))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_12_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_12_v_bias_0 = const()[name = string("tern_12_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [64, 88]> tern_12_v = linear(bias = tern_12_v_bias_0, weight = tern_12_v_weight_0_palettized, x = mul_601)[name = string("tern_12_v")];
            tensor<fp16, [88]> mul_602_y_0 = const()[name = string("mul_602_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6518592)))];
            tensor<fp16, [64, 88]> mul_602 = mul(x = tern_12_v, y = mul_602_y_0)[name = string("mul_602")];
            tensor<int32, [3]> reshape_100_shape_0 = const()[name = string("reshape_100_shape_0"), val = tensor<int32, [3]>([64, 2, 44])];
            tensor<fp16, [64, 2, 44]> reshape_100 = reshape(shape = reshape_100_shape_0, x = mul_602)[name = string("reshape_100")];
            tensor<int32, [3]> transpose_50_perm_0 = const()[name = string("transpose_50_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 64, 44]> transpose_48 = transpose(perm = transpose_48_perm_0, x = reshape_98)[name = string("transpose_15")];
            tensor<fp16, [8, 64, 44]> mul_603 = mul(x = transpose_48, y = transpose_48)[name = string("mul_603")];
            tensor<int32, [1]> reduce_mean_130_axes_0 = const()[name = string("reduce_mean_130_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_130_keep_dims_0 = const()[name = string("reduce_mean_130_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 64, 1]> reduce_mean_130 = reduce_mean(axes = reduce_mean_130_axes_0, keep_dims = reduce_mean_130_keep_dims_0, x = mul_603)[name = string("reduce_mean_130")];
            fp32 rsqrt_130_epsilon_0 = const()[name = string("rsqrt_130_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 64, 1]> rsqrt_130 = rsqrt(epsilon = rsqrt_130_epsilon_0, x = reduce_mean_130)[name = string("rsqrt_130")];
            tensor<fp16, [8, 64, 44]> mul_604 = mul(x = transpose_48, y = rsqrt_130)[name = string("mul_604")];
            tensor<fp16, [44]> mul_605_y_0 = const()[name = string("mul_605_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6518848)))];
            tensor<fp16, [8, 64, 44]> mul_605 = mul(x = mul_604, y = mul_605_y_0)[name = string("mul_605")];
            tensor<int32, [3]> slice_by_index_48_begin_0 = const()[name = string("slice_by_index_48_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_48_end_0 = const()[name = string("slice_by_index_48_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_48_end_mask_0 = const()[name = string("slice_by_index_48_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 64, 22]> slice_by_index_48 = slice_by_index(begin = slice_by_index_48_begin_0, end = slice_by_index_48_end_0, end_mask = slice_by_index_48_end_mask_0, x = mul_605)[name = string("slice_by_index_48")];
            tensor<int32, [3]> slice_by_index_49_begin_0 = const()[name = string("slice_by_index_49_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_49_end_0 = const()[name = string("slice_by_index_49_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_49_end_mask_0 = const()[name = string("slice_by_index_49_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 64, 22]> slice_by_index_49 = slice_by_index(begin = slice_by_index_49_begin_0, end = slice_by_index_49_end_0, end_mask = slice_by_index_49_end_mask_0, x = mul_605)[name = string("slice_by_index_49")];
            int32 concat_24_axis_0 = const()[name = string("concat_24_axis_0"), val = int32(-1)];
            bool concat_24_interleave_0 = const()[name = string("concat_24_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 64, 44]> concat_24 = concat(axis = concat_24_axis_0, interleave = concat_24_interleave_0, values = (slice_by_index_49, slice_by_index_48))[name = string("concat_24")];
            tensor<fp16, [44]> mul_606_y_0 = const()[name = string("mul_606_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 64, 44]> mul_606 = mul(x = concat_24, y = mul_606_y_0)[name = string("mul_606")];
            tensor<fp16, [8, 64, 44]> mul_607 = mul(x = mul_605, y = mul_11_y_0)[name = string("mul_607")];
            tensor<fp16, [8, 64, 44]> mul_608 = mul(x = mul_606, y = mul_12_y_0)[name = string("mul_608")];
            tensor<fp16, [8, 64, 44]> add_72 = add(x = mul_607, y = mul_608)[name = string("add_72")];
            tensor<fp16, [2, 64, 44]> transpose_49 = transpose(perm = transpose_49_perm_0, x = reshape_99)[name = string("transpose_14")];
            tensor<fp16, [2, 64, 44]> mul_609 = mul(x = transpose_49, y = transpose_49)[name = string("mul_609")];
            tensor<int32, [1]> reduce_mean_131_axes_0 = const()[name = string("reduce_mean_131_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_131_keep_dims_0 = const()[name = string("reduce_mean_131_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 64, 1]> reduce_mean_131 = reduce_mean(axes = reduce_mean_131_axes_0, keep_dims = reduce_mean_131_keep_dims_0, x = mul_609)[name = string("reduce_mean_131")];
            fp32 rsqrt_131_epsilon_0 = const()[name = string("rsqrt_131_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 64, 1]> rsqrt_131 = rsqrt(epsilon = rsqrt_131_epsilon_0, x = reduce_mean_131)[name = string("rsqrt_131")];
            tensor<fp16, [2, 64, 44]> mul_610 = mul(x = transpose_49, y = rsqrt_131)[name = string("mul_610")];
            tensor<fp16, [44]> mul_611_y_0 = const()[name = string("mul_611_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6519040)))];
            tensor<fp16, [2, 64, 44]> mul_611 = mul(x = mul_610, y = mul_611_y_0)[name = string("mul_611")];
            tensor<int32, [3]> slice_by_index_50_begin_0 = const()[name = string("slice_by_index_50_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_50_end_0 = const()[name = string("slice_by_index_50_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_50_end_mask_0 = const()[name = string("slice_by_index_50_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 64, 22]> slice_by_index_50 = slice_by_index(begin = slice_by_index_50_begin_0, end = slice_by_index_50_end_0, end_mask = slice_by_index_50_end_mask_0, x = mul_611)[name = string("slice_by_index_50")];
            tensor<int32, [3]> slice_by_index_51_begin_0 = const()[name = string("slice_by_index_51_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_51_end_0 = const()[name = string("slice_by_index_51_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_51_end_mask_0 = const()[name = string("slice_by_index_51_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 64, 22]> slice_by_index_51 = slice_by_index(begin = slice_by_index_51_begin_0, end = slice_by_index_51_end_0, end_mask = slice_by_index_51_end_mask_0, x = mul_611)[name = string("slice_by_index_51")];
            int32 concat_25_axis_0 = const()[name = string("concat_25_axis_0"), val = int32(-1)];
            bool concat_25_interleave_0 = const()[name = string("concat_25_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 64, 44]> concat_25 = concat(axis = concat_25_axis_0, interleave = concat_25_interleave_0, values = (slice_by_index_51, slice_by_index_50))[name = string("concat_25")];
            tensor<fp16, [44]> mul_612_y_0 = const()[name = string("mul_612_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 64, 44]> mul_612 = mul(x = concat_25, y = mul_612_y_0)[name = string("mul_612")];
            tensor<fp16, [2, 64, 44]> mul_613 = mul(x = mul_611, y = mul_11_y_0)[name = string("mul_613")];
            tensor<fp16, [2, 64, 44]> mul_614 = mul(x = mul_612, y = mul_12_y_0)[name = string("mul_614")];
            tensor<fp16, [2, 64, 44]> add_73 = add(x = mul_613, y = mul_614)[name = string("add_73")];
            tensor<int32, [4]> reshape_101_shape_0 = const()[name = string("reshape_101_shape_0"), val = tensor<int32, [4]>([2, 1, 64, 44])];
            tensor<fp16, [2, 1, 64, 44]> reshape_101 = reshape(shape = reshape_101_shape_0, x = add_73)[name = string("reshape_101")];
            tensor<int32, [4]> tile_24_reps_0 = const()[name = string("tile_24_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 64, 44]> tile_24 = tile(reps = tile_24_reps_0, x = reshape_101)[name = string("tile_24")];
            tensor<int32, [3]> reshape_102_shape_0 = const()[name = string("reshape_102_shape_0"), val = tensor<int32, [3]>([8, 64, 44])];
            tensor<fp16, [8, 64, 44]> reshape_102 = reshape(shape = reshape_102_shape_0, x = tile_24)[name = string("reshape_102")];
            tensor<int32, [4]> reshape_103_shape_0 = const()[name = string("reshape_103_shape_0"), val = tensor<int32, [4]>([2, 1, 64, 44])];
            tensor<fp16, [2, 64, 44]> transpose_50 = transpose(perm = transpose_50_perm_0, x = reshape_100)[name = string("transpose_13")];
            tensor<fp16, [2, 1, 64, 44]> reshape_103 = reshape(shape = reshape_103_shape_0, x = transpose_50)[name = string("reshape_103")];
            tensor<int32, [4]> tile_25_reps_0 = const()[name = string("tile_25_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 64, 44]> tile_25 = tile(reps = tile_25_reps_0, x = reshape_103)[name = string("tile_25")];
            tensor<int32, [3]> reshape_104_shape_0 = const()[name = string("reshape_104_shape_0"), val = tensor<int32, [3]>([8, 64, 44])];
            tensor<fp16, [8, 64, 44]> reshape_104 = reshape(shape = reshape_104_shape_0, x = tile_25)[name = string("reshape_104")];
            fp16 mul_615_y_0 = const()[name = string("mul_615_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 64, 44]> mul_615 = mul(x = add_72, y = mul_615_y_0)[name = string("mul_615")];
            bool matmul_24_transpose_y_0 = const()[name = string("matmul_24_transpose_y_0"), val = bool(true)];
            bool matmul_24_transpose_x_0 = const()[name = string("matmul_24_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 64, 64]> matmul_24 = matmul(transpose_x = matmul_24_transpose_x_0, transpose_y = matmul_24_transpose_y_0, x = mul_615, y = reshape_102)[name = string("matmul_24")];
            tensor<fp16, [8, 64, 64]> add_74 = add(x = matmul_24, y = reshape_1)[name = string("add_74")];
            int32 softmax_12_axis_0 = const()[name = string("softmax_12_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 64, 64]> softmax_12 = softmax(axis = softmax_12_axis_0, x = add_74)[name = string("softmax_12")];
            bool matmul_25_transpose_x_0 = const()[name = string("matmul_25_transpose_x_0"), val = bool(false)];
            bool matmul_25_transpose_y_0 = const()[name = string("matmul_25_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 64, 44]> matmul_25 = matmul(transpose_x = matmul_25_transpose_x_0, transpose_y = matmul_25_transpose_y_0, x = softmax_12, y = reshape_104)[name = string("matmul_25")];
            tensor<int32, [3]> transpose_51_perm_0 = const()[name = string("transpose_51_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_105_shape_0 = const()[name = string("reshape_105_shape_0"), val = tensor<int32, [2]>([64, 352])];
            tensor<fp16, [64, 8, 44]> transpose_51 = transpose(perm = transpose_51_perm_0, x = matmul_25)[name = string("transpose_12")];
            tensor<fp16, [64, 352]> reshape_105 = reshape(shape = reshape_105_shape_0, x = transpose_51)[name = string("reshape_105")];
            tensor<fp16, [64, 352]> mul_616 = mul(x = reshape_105, y = reshape_105)[name = string("mul_616")];
            tensor<int32, [1]> reduce_mean_132_axes_0 = const()[name = string("reduce_mean_132_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_132_keep_dims_0 = const()[name = string("reduce_mean_132_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_132 = reduce_mean(axes = reduce_mean_132_axes_0, keep_dims = reduce_mean_132_keep_dims_0, x = mul_616)[name = string("reduce_mean_132")];
            fp32 rsqrt_132_epsilon_0 = const()[name = string("rsqrt_132_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_132 = rsqrt(epsilon = rsqrt_132_epsilon_0, x = reduce_mean_132)[name = string("rsqrt_132")];
            tensor<fp16, [64, 352]> mul_617 = mul(x = reshape_105, y = rsqrt_132)[name = string("mul_617")];
            tensor<fp16, [352]> mul_618_y_0 = const()[name = string("mul_618_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6519232)))];
            tensor<fp16, [64, 352]> mul_618 = mul(x = mul_617, y = mul_618_y_0)[name = string("mul_618")];
            tensor<fp16, [352, 352]> tern_12_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6520000))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_12_o_weight_0_palettized")];
            tensor<fp16, [64, 352]> tern_12_o = linear(bias = linear_0_bias_0, weight = tern_12_o_weight_0_palettized, x = mul_618)[name = string("tern_12_o")];
            tensor<fp16, [352]> mul_619_y_0 = const()[name = string("mul_619_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6551040)))];
            tensor<fp16, [64, 352]> mul_619 = mul(x = tern_12_o, y = mul_619_y_0)[name = string("mul_619")];
            tensor<fp16, [64, 352]> add_75 = add(x = add_71, y = mul_619)[name = string("add_75")];
            tensor<fp16, [64, 352]> mul_620 = mul(x = add_75, y = add_75)[name = string("mul_620")];
            tensor<int32, [1]> reduce_mean_133_axes_0 = const()[name = string("reduce_mean_133_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_133_keep_dims_0 = const()[name = string("reduce_mean_133_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_133 = reduce_mean(axes = reduce_mean_133_axes_0, keep_dims = reduce_mean_133_keep_dims_0, x = mul_620)[name = string("reduce_mean_133")];
            fp32 rsqrt_133_epsilon_0 = const()[name = string("rsqrt_133_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_133 = rsqrt(epsilon = rsqrt_133_epsilon_0, x = reduce_mean_133)[name = string("rsqrt_133")];
            tensor<fp16, [64, 352]> mul_621 = mul(x = add_75, y = rsqrt_133)[name = string("mul_621")];
            tensor<fp16, [352]> mul_622_y_0 = const()[name = string("mul_622_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6551808)))];
            tensor<fp16, [64, 352]> mul_622 = mul(x = mul_621, y = mul_622_y_0)[name = string("mul_622")];
            tensor<fp16, [64, 352]> mul_623 = mul(x = mul_622, y = mul_622)[name = string("mul_623")];
            tensor<int32, [1]> reduce_mean_134_axes_0 = const()[name = string("reduce_mean_134_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_134_keep_dims_0 = const()[name = string("reduce_mean_134_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_134 = reduce_mean(axes = reduce_mean_134_axes_0, keep_dims = reduce_mean_134_keep_dims_0, x = mul_623)[name = string("reduce_mean_134")];
            fp32 rsqrt_134_epsilon_0 = const()[name = string("rsqrt_134_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_134 = rsqrt(epsilon = rsqrt_134_epsilon_0, x = reduce_mean_134)[name = string("rsqrt_134")];
            tensor<fp16, [64, 352]> mul_624 = mul(x = mul_622, y = rsqrt_134)[name = string("mul_624")];
            tensor<fp16, [352]> mul_625_y_0 = const()[name = string("mul_625_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6552576)))];
            tensor<fp16, [64, 352]> mul_625 = mul(x = mul_624, y = mul_625_y_0)[name = string("mul_625")];
            tensor<fp16, [960, 352]> tern_12_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6553344))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_12_w1_weight_0_palettized")];
            tensor<fp16, [64, 960]> tern_12_w1 = linear(bias = linear_4_bias_0, weight = tern_12_w1_weight_0_palettized, x = mul_625)[name = string("tern_12_w1")];
            tensor<fp16, [960]> mul_626_y_0 = const()[name = string("mul_626_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6637888)))];
            tensor<fp16, [64, 960]> mul_626 = mul(x = tern_12_w1, y = mul_626_y_0)[name = string("mul_626")];
            tensor<fp16, [352]> mul_629_y_0 = const()[name = string("mul_629_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6639872)))];
            tensor<fp16, [64, 352]> mul_629 = mul(x = mul_624, y = mul_629_y_0)[name = string("mul_629")];
            tensor<fp16, [960, 352]> tern_12_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6640640))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_12_w3_weight_0_palettized")];
            tensor<fp16, [64, 960]> tern_12_w3 = linear(bias = linear_4_bias_0, weight = tern_12_w3_weight_0_palettized, x = mul_629)[name = string("tern_12_w3")];
            tensor<fp16, [960]> mul_630_y_0 = const()[name = string("mul_630_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6725184)))];
            tensor<fp16, [64, 960]> mul_630 = mul(x = tern_12_w3, y = mul_630_y_0)[name = string("mul_630")];
            fp16 mul_631_y_0 = const()[name = string("mul_631_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [64, 960]> mul_631 = mul(x = mul_626, y = mul_631_y_0)[name = string("mul_631")];
            tensor<fp16, [64, 960]> tanh_12 = tanh(x = mul_631)[name = string("tanh_12")];
            fp16 mul_632_x_0 = const()[name = string("mul_632_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [64, 960]> mul_632 = mul(x = mul_632_x_0, y = tanh_12)[name = string("mul_632")];
            fp16 add_76_x_0 = const()[name = string("add_76_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [64, 960]> add_76 = add(x = add_76_x_0, y = mul_632)[name = string("add_76")];
            tensor<fp16, [64, 960]> mul_633 = mul(x = mul_626, y = add_76)[name = string("mul_633")];
            tensor<fp16, [64, 960]> mul_634 = mul(x = mul_633, y = mul_630)[name = string("mul_634")];
            tensor<fp16, [64, 960]> mul_635 = mul(x = mul_634, y = mul_634)[name = string("mul_635")];
            tensor<int32, [1]> reduce_mean_136_axes_0 = const()[name = string("reduce_mean_136_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_136_keep_dims_0 = const()[name = string("reduce_mean_136_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_136 = reduce_mean(axes = reduce_mean_136_axes_0, keep_dims = reduce_mean_136_keep_dims_0, x = mul_635)[name = string("reduce_mean_136")];
            fp32 rsqrt_136_epsilon_0 = const()[name = string("rsqrt_136_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_136 = rsqrt(epsilon = rsqrt_136_epsilon_0, x = reduce_mean_136)[name = string("rsqrt_136")];
            tensor<fp16, [64, 960]> mul_636 = mul(x = mul_634, y = rsqrt_136)[name = string("mul_636")];
            tensor<fp16, [960]> mul_637_y_0 = const()[name = string("mul_637_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6727168)))];
            tensor<fp16, [64, 960]> mul_637 = mul(x = mul_636, y = mul_637_y_0)[name = string("mul_637")];
            tensor<fp16, [352, 960]> tern_12_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6729152))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_12_w2_weight_0_palettized")];
            tensor<fp16, [64, 352]> tern_12_w2 = linear(bias = linear_0_bias_0, weight = tern_12_w2_weight_0_palettized, x = mul_637)[name = string("tern_12_w2")];
            tensor<fp16, [352]> mul_638_y_0 = const()[name = string("mul_638_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6813696)))];
            tensor<fp16, [64, 352]> mul_638 = mul(x = tern_12_w2, y = mul_638_y_0)[name = string("mul_638")];
            tensor<fp16, [64, 352]> add_77 = add(x = add_75, y = mul_638)[name = string("add_77")];
            tensor<fp16, [64, 352]> mul_639 = mul(x = add_77, y = add_77)[name = string("mul_639")];
            tensor<int32, [1]> reduce_mean_137_axes_0 = const()[name = string("reduce_mean_137_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_137_keep_dims_0 = const()[name = string("reduce_mean_137_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_137 = reduce_mean(axes = reduce_mean_137_axes_0, keep_dims = reduce_mean_137_keep_dims_0, x = mul_639)[name = string("reduce_mean_137")];
            fp32 rsqrt_137_epsilon_0 = const()[name = string("rsqrt_137_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_137 = rsqrt(epsilon = rsqrt_137_epsilon_0, x = reduce_mean_137)[name = string("rsqrt_137")];
            tensor<fp16, [64, 352]> mul_640 = mul(x = add_77, y = rsqrt_137)[name = string("mul_640")];
            tensor<fp16, [352]> mul_641_y_0 = const()[name = string("mul_641_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6814464)))];
            tensor<fp16, [64, 352]> mul_641 = mul(x = mul_640, y = mul_641_y_0)[name = string("mul_641")];
            tensor<fp16, [64, 352]> mul_642 = mul(x = mul_641, y = mul_641)[name = string("mul_642")];
            tensor<int32, [1]> reduce_mean_138_axes_0 = const()[name = string("reduce_mean_138_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_138_keep_dims_0 = const()[name = string("reduce_mean_138_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_138 = reduce_mean(axes = reduce_mean_138_axes_0, keep_dims = reduce_mean_138_keep_dims_0, x = mul_642)[name = string("reduce_mean_138")];
            fp32 rsqrt_138_epsilon_0 = const()[name = string("rsqrt_138_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_138 = rsqrt(epsilon = rsqrt_138_epsilon_0, x = reduce_mean_138)[name = string("rsqrt_138")];
            tensor<fp16, [64, 352]> mul_643 = mul(x = mul_641, y = rsqrt_138)[name = string("mul_643")];
            tensor<fp16, [352]> mul_644_y_0 = const()[name = string("mul_644_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6815232)))];
            tensor<fp16, [64, 352]> mul_644 = mul(x = mul_643, y = mul_644_y_0)[name = string("mul_644")];
            tensor<fp16, [352, 352]> tern_13_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6816000))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_13_q_weight_0_palettized")];
            tensor<fp16, [64, 352]> tern_13_q = linear(bias = linear_0_bias_0, weight = tern_13_q_weight_0_palettized, x = mul_644)[name = string("tern_13_q")];
            tensor<fp16, [352]> mul_645_y_0 = const()[name = string("mul_645_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6847040)))];
            tensor<fp16, [64, 352]> mul_645 = mul(x = tern_13_q, y = mul_645_y_0)[name = string("mul_645")];
            tensor<int32, [3]> reshape_106_shape_0 = const()[name = string("reshape_106_shape_0"), val = tensor<int32, [3]>([64, 8, 44])];
            tensor<fp16, [64, 8, 44]> reshape_106 = reshape(shape = reshape_106_shape_0, x = mul_645)[name = string("reshape_106")];
            tensor<int32, [3]> transpose_52_perm_0 = const()[name = string("transpose_52_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_648_y_0 = const()[name = string("mul_648_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6847808)))];
            tensor<fp16, [64, 352]> mul_648 = mul(x = mul_643, y = mul_648_y_0)[name = string("mul_648")];
            tensor<fp16, [88, 352]> tern_13_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6848576))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_13_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_13_k_bias_0 = const()[name = string("tern_13_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [64, 88]> tern_13_k = linear(bias = tern_13_k_bias_0, weight = tern_13_k_weight_0_palettized, x = mul_648)[name = string("tern_13_k")];
            tensor<fp16, [88]> mul_649_y_0 = const()[name = string("mul_649_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6856384)))];
            tensor<fp16, [64, 88]> mul_649 = mul(x = tern_13_k, y = mul_649_y_0)[name = string("mul_649")];
            tensor<int32, [3]> reshape_107_shape_0 = const()[name = string("reshape_107_shape_0"), val = tensor<int32, [3]>([64, 2, 44])];
            tensor<fp16, [64, 2, 44]> reshape_107 = reshape(shape = reshape_107_shape_0, x = mul_649)[name = string("reshape_107")];
            tensor<int32, [3]> transpose_53_perm_0 = const()[name = string("transpose_53_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_652_y_0 = const()[name = string("mul_652_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6856640)))];
            tensor<fp16, [64, 352]> mul_652 = mul(x = mul_643, y = mul_652_y_0)[name = string("mul_652")];
            tensor<fp16, [88, 352]> tern_13_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6857408))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_13_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_13_v_bias_0 = const()[name = string("tern_13_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [64, 88]> tern_13_v = linear(bias = tern_13_v_bias_0, weight = tern_13_v_weight_0_palettized, x = mul_652)[name = string("tern_13_v")];
            tensor<fp16, [88]> mul_653_y_0 = const()[name = string("mul_653_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6865216)))];
            tensor<fp16, [64, 88]> mul_653 = mul(x = tern_13_v, y = mul_653_y_0)[name = string("mul_653")];
            tensor<int32, [3]> reshape_108_shape_0 = const()[name = string("reshape_108_shape_0"), val = tensor<int32, [3]>([64, 2, 44])];
            tensor<fp16, [64, 2, 44]> reshape_108 = reshape(shape = reshape_108_shape_0, x = mul_653)[name = string("reshape_108")];
            tensor<int32, [3]> transpose_54_perm_0 = const()[name = string("transpose_54_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 64, 44]> transpose_52 = transpose(perm = transpose_52_perm_0, x = reshape_106)[name = string("transpose_11")];
            tensor<fp16, [8, 64, 44]> mul_654 = mul(x = transpose_52, y = transpose_52)[name = string("mul_654")];
            tensor<int32, [1]> reduce_mean_141_axes_0 = const()[name = string("reduce_mean_141_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_141_keep_dims_0 = const()[name = string("reduce_mean_141_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 64, 1]> reduce_mean_141 = reduce_mean(axes = reduce_mean_141_axes_0, keep_dims = reduce_mean_141_keep_dims_0, x = mul_654)[name = string("reduce_mean_141")];
            fp32 rsqrt_141_epsilon_0 = const()[name = string("rsqrt_141_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 64, 1]> rsqrt_141 = rsqrt(epsilon = rsqrt_141_epsilon_0, x = reduce_mean_141)[name = string("rsqrt_141")];
            tensor<fp16, [8, 64, 44]> mul_655 = mul(x = transpose_52, y = rsqrt_141)[name = string("mul_655")];
            tensor<fp16, [44]> mul_656_y_0 = const()[name = string("mul_656_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6865472)))];
            tensor<fp16, [8, 64, 44]> mul_656 = mul(x = mul_655, y = mul_656_y_0)[name = string("mul_656")];
            tensor<int32, [3]> slice_by_index_52_begin_0 = const()[name = string("slice_by_index_52_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_52_end_0 = const()[name = string("slice_by_index_52_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_52_end_mask_0 = const()[name = string("slice_by_index_52_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 64, 22]> slice_by_index_52 = slice_by_index(begin = slice_by_index_52_begin_0, end = slice_by_index_52_end_0, end_mask = slice_by_index_52_end_mask_0, x = mul_656)[name = string("slice_by_index_52")];
            tensor<int32, [3]> slice_by_index_53_begin_0 = const()[name = string("slice_by_index_53_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_53_end_0 = const()[name = string("slice_by_index_53_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_53_end_mask_0 = const()[name = string("slice_by_index_53_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 64, 22]> slice_by_index_53 = slice_by_index(begin = slice_by_index_53_begin_0, end = slice_by_index_53_end_0, end_mask = slice_by_index_53_end_mask_0, x = mul_656)[name = string("slice_by_index_53")];
            int32 concat_26_axis_0 = const()[name = string("concat_26_axis_0"), val = int32(-1)];
            bool concat_26_interleave_0 = const()[name = string("concat_26_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 64, 44]> concat_26 = concat(axis = concat_26_axis_0, interleave = concat_26_interleave_0, values = (slice_by_index_53, slice_by_index_52))[name = string("concat_26")];
            tensor<fp16, [44]> mul_657_y_0 = const()[name = string("mul_657_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 64, 44]> mul_657 = mul(x = concat_26, y = mul_657_y_0)[name = string("mul_657")];
            tensor<fp16, [8, 64, 44]> mul_658 = mul(x = mul_656, y = mul_11_y_0)[name = string("mul_658")];
            tensor<fp16, [8, 64, 44]> mul_659 = mul(x = mul_657, y = mul_12_y_0)[name = string("mul_659")];
            tensor<fp16, [8, 64, 44]> add_78 = add(x = mul_658, y = mul_659)[name = string("add_78")];
            tensor<fp16, [2, 64, 44]> transpose_53 = transpose(perm = transpose_53_perm_0, x = reshape_107)[name = string("transpose_10")];
            tensor<fp16, [2, 64, 44]> mul_660 = mul(x = transpose_53, y = transpose_53)[name = string("mul_660")];
            tensor<int32, [1]> reduce_mean_142_axes_0 = const()[name = string("reduce_mean_142_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_142_keep_dims_0 = const()[name = string("reduce_mean_142_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 64, 1]> reduce_mean_142 = reduce_mean(axes = reduce_mean_142_axes_0, keep_dims = reduce_mean_142_keep_dims_0, x = mul_660)[name = string("reduce_mean_142")];
            fp32 rsqrt_142_epsilon_0 = const()[name = string("rsqrt_142_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 64, 1]> rsqrt_142 = rsqrt(epsilon = rsqrt_142_epsilon_0, x = reduce_mean_142)[name = string("rsqrt_142")];
            tensor<fp16, [2, 64, 44]> mul_661 = mul(x = transpose_53, y = rsqrt_142)[name = string("mul_661")];
            tensor<fp16, [44]> mul_662_y_0 = const()[name = string("mul_662_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6865664)))];
            tensor<fp16, [2, 64, 44]> mul_662 = mul(x = mul_661, y = mul_662_y_0)[name = string("mul_662")];
            tensor<int32, [3]> slice_by_index_54_begin_0 = const()[name = string("slice_by_index_54_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_54_end_0 = const()[name = string("slice_by_index_54_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_54_end_mask_0 = const()[name = string("slice_by_index_54_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 64, 22]> slice_by_index_54 = slice_by_index(begin = slice_by_index_54_begin_0, end = slice_by_index_54_end_0, end_mask = slice_by_index_54_end_mask_0, x = mul_662)[name = string("slice_by_index_54")];
            tensor<int32, [3]> slice_by_index_55_begin_0 = const()[name = string("slice_by_index_55_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_55_end_0 = const()[name = string("slice_by_index_55_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_55_end_mask_0 = const()[name = string("slice_by_index_55_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 64, 22]> slice_by_index_55 = slice_by_index(begin = slice_by_index_55_begin_0, end = slice_by_index_55_end_0, end_mask = slice_by_index_55_end_mask_0, x = mul_662)[name = string("slice_by_index_55")];
            int32 concat_27_axis_0 = const()[name = string("concat_27_axis_0"), val = int32(-1)];
            bool concat_27_interleave_0 = const()[name = string("concat_27_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 64, 44]> concat_27 = concat(axis = concat_27_axis_0, interleave = concat_27_interleave_0, values = (slice_by_index_55, slice_by_index_54))[name = string("concat_27")];
            tensor<fp16, [44]> mul_663_y_0 = const()[name = string("mul_663_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 64, 44]> mul_663 = mul(x = concat_27, y = mul_663_y_0)[name = string("mul_663")];
            tensor<fp16, [2, 64, 44]> mul_664 = mul(x = mul_662, y = mul_11_y_0)[name = string("mul_664")];
            tensor<fp16, [2, 64, 44]> mul_665 = mul(x = mul_663, y = mul_12_y_0)[name = string("mul_665")];
            tensor<fp16, [2, 64, 44]> add_79 = add(x = mul_664, y = mul_665)[name = string("add_79")];
            tensor<int32, [4]> reshape_109_shape_0 = const()[name = string("reshape_109_shape_0"), val = tensor<int32, [4]>([2, 1, 64, 44])];
            tensor<fp16, [2, 1, 64, 44]> reshape_109 = reshape(shape = reshape_109_shape_0, x = add_79)[name = string("reshape_109")];
            tensor<int32, [4]> tile_26_reps_0 = const()[name = string("tile_26_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 64, 44]> tile_26 = tile(reps = tile_26_reps_0, x = reshape_109)[name = string("tile_26")];
            tensor<int32, [3]> reshape_110_shape_0 = const()[name = string("reshape_110_shape_0"), val = tensor<int32, [3]>([8, 64, 44])];
            tensor<fp16, [8, 64, 44]> reshape_110 = reshape(shape = reshape_110_shape_0, x = tile_26)[name = string("reshape_110")];
            tensor<int32, [4]> reshape_111_shape_0 = const()[name = string("reshape_111_shape_0"), val = tensor<int32, [4]>([2, 1, 64, 44])];
            tensor<fp16, [2, 64, 44]> transpose_54 = transpose(perm = transpose_54_perm_0, x = reshape_108)[name = string("transpose_9")];
            tensor<fp16, [2, 1, 64, 44]> reshape_111 = reshape(shape = reshape_111_shape_0, x = transpose_54)[name = string("reshape_111")];
            tensor<int32, [4]> tile_27_reps_0 = const()[name = string("tile_27_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 64, 44]> tile_27 = tile(reps = tile_27_reps_0, x = reshape_111)[name = string("tile_27")];
            tensor<int32, [3]> reshape_112_shape_0 = const()[name = string("reshape_112_shape_0"), val = tensor<int32, [3]>([8, 64, 44])];
            tensor<fp16, [8, 64, 44]> reshape_112 = reshape(shape = reshape_112_shape_0, x = tile_27)[name = string("reshape_112")];
            fp16 mul_666_y_0 = const()[name = string("mul_666_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 64, 44]> mul_666 = mul(x = add_78, y = mul_666_y_0)[name = string("mul_666")];
            bool matmul_26_transpose_y_0 = const()[name = string("matmul_26_transpose_y_0"), val = bool(true)];
            bool matmul_26_transpose_x_0 = const()[name = string("matmul_26_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 64, 64]> matmul_26 = matmul(transpose_x = matmul_26_transpose_x_0, transpose_y = matmul_26_transpose_y_0, x = mul_666, y = reshape_110)[name = string("matmul_26")];
            tensor<fp16, [8, 64, 64]> add_80 = add(x = matmul_26, y = reshape_1)[name = string("add_80")];
            int32 softmax_13_axis_0 = const()[name = string("softmax_13_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 64, 64]> softmax_13 = softmax(axis = softmax_13_axis_0, x = add_80)[name = string("softmax_13")];
            bool matmul_27_transpose_x_0 = const()[name = string("matmul_27_transpose_x_0"), val = bool(false)];
            bool matmul_27_transpose_y_0 = const()[name = string("matmul_27_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 64, 44]> matmul_27 = matmul(transpose_x = matmul_27_transpose_x_0, transpose_y = matmul_27_transpose_y_0, x = softmax_13, y = reshape_112)[name = string("matmul_27")];
            tensor<int32, [3]> transpose_55_perm_0 = const()[name = string("transpose_55_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_113_shape_0 = const()[name = string("reshape_113_shape_0"), val = tensor<int32, [2]>([64, 352])];
            tensor<fp16, [64, 8, 44]> transpose_55 = transpose(perm = transpose_55_perm_0, x = matmul_27)[name = string("transpose_8")];
            tensor<fp16, [64, 352]> reshape_113 = reshape(shape = reshape_113_shape_0, x = transpose_55)[name = string("reshape_113")];
            tensor<fp16, [64, 352]> mul_667 = mul(x = reshape_113, y = reshape_113)[name = string("mul_667")];
            tensor<int32, [1]> reduce_mean_143_axes_0 = const()[name = string("reduce_mean_143_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_143_keep_dims_0 = const()[name = string("reduce_mean_143_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_143 = reduce_mean(axes = reduce_mean_143_axes_0, keep_dims = reduce_mean_143_keep_dims_0, x = mul_667)[name = string("reduce_mean_143")];
            fp32 rsqrt_143_epsilon_0 = const()[name = string("rsqrt_143_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_143 = rsqrt(epsilon = rsqrt_143_epsilon_0, x = reduce_mean_143)[name = string("rsqrt_143")];
            tensor<fp16, [64, 352]> mul_668 = mul(x = reshape_113, y = rsqrt_143)[name = string("mul_668")];
            tensor<fp16, [352]> mul_669_y_0 = const()[name = string("mul_669_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6865856)))];
            tensor<fp16, [64, 352]> mul_669 = mul(x = mul_668, y = mul_669_y_0)[name = string("mul_669")];
            tensor<fp16, [352, 352]> tern_13_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6866624))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_13_o_weight_0_palettized")];
            tensor<fp16, [64, 352]> tern_13_o = linear(bias = linear_0_bias_0, weight = tern_13_o_weight_0_palettized, x = mul_669)[name = string("tern_13_o")];
            tensor<fp16, [352]> mul_670_y_0 = const()[name = string("mul_670_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6897664)))];
            tensor<fp16, [64, 352]> mul_670 = mul(x = tern_13_o, y = mul_670_y_0)[name = string("mul_670")];
            tensor<fp16, [64, 352]> add_81 = add(x = add_77, y = mul_670)[name = string("add_81")];
            tensor<fp16, [64, 352]> mul_671 = mul(x = add_81, y = add_81)[name = string("mul_671")];
            tensor<int32, [1]> reduce_mean_144_axes_0 = const()[name = string("reduce_mean_144_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_144_keep_dims_0 = const()[name = string("reduce_mean_144_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_144 = reduce_mean(axes = reduce_mean_144_axes_0, keep_dims = reduce_mean_144_keep_dims_0, x = mul_671)[name = string("reduce_mean_144")];
            fp32 rsqrt_144_epsilon_0 = const()[name = string("rsqrt_144_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_144 = rsqrt(epsilon = rsqrt_144_epsilon_0, x = reduce_mean_144)[name = string("rsqrt_144")];
            tensor<fp16, [64, 352]> mul_672 = mul(x = add_81, y = rsqrt_144)[name = string("mul_672")];
            tensor<fp16, [352]> mul_673_y_0 = const()[name = string("mul_673_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6898432)))];
            tensor<fp16, [64, 352]> mul_673 = mul(x = mul_672, y = mul_673_y_0)[name = string("mul_673")];
            tensor<fp16, [64, 352]> mul_674 = mul(x = mul_673, y = mul_673)[name = string("mul_674")];
            tensor<int32, [1]> reduce_mean_145_axes_0 = const()[name = string("reduce_mean_145_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_145_keep_dims_0 = const()[name = string("reduce_mean_145_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_145 = reduce_mean(axes = reduce_mean_145_axes_0, keep_dims = reduce_mean_145_keep_dims_0, x = mul_674)[name = string("reduce_mean_145")];
            fp32 rsqrt_145_epsilon_0 = const()[name = string("rsqrt_145_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_145 = rsqrt(epsilon = rsqrt_145_epsilon_0, x = reduce_mean_145)[name = string("rsqrt_145")];
            tensor<fp16, [64, 352]> mul_675 = mul(x = mul_673, y = rsqrt_145)[name = string("mul_675")];
            tensor<fp16, [352]> mul_676_y_0 = const()[name = string("mul_676_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6899200)))];
            tensor<fp16, [64, 352]> mul_676 = mul(x = mul_675, y = mul_676_y_0)[name = string("mul_676")];
            tensor<fp16, [960, 352]> tern_13_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6899968))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_13_w1_weight_0_palettized")];
            tensor<fp16, [64, 960]> tern_13_w1 = linear(bias = linear_4_bias_0, weight = tern_13_w1_weight_0_palettized, x = mul_676)[name = string("tern_13_w1")];
            tensor<fp16, [960]> mul_677_y_0 = const()[name = string("mul_677_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6984512)))];
            tensor<fp16, [64, 960]> mul_677 = mul(x = tern_13_w1, y = mul_677_y_0)[name = string("mul_677")];
            tensor<fp16, [352]> mul_680_y_0 = const()[name = string("mul_680_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6986496)))];
            tensor<fp16, [64, 352]> mul_680 = mul(x = mul_675, y = mul_680_y_0)[name = string("mul_680")];
            tensor<fp16, [960, 352]> tern_13_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6987264))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_13_w3_weight_0_palettized")];
            tensor<fp16, [64, 960]> tern_13_w3 = linear(bias = linear_4_bias_0, weight = tern_13_w3_weight_0_palettized, x = mul_680)[name = string("tern_13_w3")];
            tensor<fp16, [960]> mul_681_y_0 = const()[name = string("mul_681_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7071808)))];
            tensor<fp16, [64, 960]> mul_681 = mul(x = tern_13_w3, y = mul_681_y_0)[name = string("mul_681")];
            fp16 mul_682_y_0 = const()[name = string("mul_682_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [64, 960]> mul_682 = mul(x = mul_677, y = mul_682_y_0)[name = string("mul_682")];
            tensor<fp16, [64, 960]> tanh_13 = tanh(x = mul_682)[name = string("tanh_13")];
            fp16 mul_683_x_0 = const()[name = string("mul_683_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [64, 960]> mul_683 = mul(x = mul_683_x_0, y = tanh_13)[name = string("mul_683")];
            fp16 add_82_x_0 = const()[name = string("add_82_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [64, 960]> add_82 = add(x = add_82_x_0, y = mul_683)[name = string("add_82")];
            tensor<fp16, [64, 960]> mul_684 = mul(x = mul_677, y = add_82)[name = string("mul_684")];
            tensor<fp16, [64, 960]> mul_685 = mul(x = mul_684, y = mul_681)[name = string("mul_685")];
            tensor<fp16, [64, 960]> mul_686 = mul(x = mul_685, y = mul_685)[name = string("mul_686")];
            tensor<int32, [1]> reduce_mean_147_axes_0 = const()[name = string("reduce_mean_147_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_147_keep_dims_0 = const()[name = string("reduce_mean_147_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_147 = reduce_mean(axes = reduce_mean_147_axes_0, keep_dims = reduce_mean_147_keep_dims_0, x = mul_686)[name = string("reduce_mean_147")];
            fp32 rsqrt_147_epsilon_0 = const()[name = string("rsqrt_147_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_147 = rsqrt(epsilon = rsqrt_147_epsilon_0, x = reduce_mean_147)[name = string("rsqrt_147")];
            tensor<fp16, [64, 960]> mul_687 = mul(x = mul_685, y = rsqrt_147)[name = string("mul_687")];
            tensor<fp16, [960]> mul_688_y_0 = const()[name = string("mul_688_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7073792)))];
            tensor<fp16, [64, 960]> mul_688 = mul(x = mul_687, y = mul_688_y_0)[name = string("mul_688")];
            tensor<fp16, [352, 960]> tern_13_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7075776))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_13_w2_weight_0_palettized")];
            tensor<fp16, [64, 352]> tern_13_w2 = linear(bias = linear_0_bias_0, weight = tern_13_w2_weight_0_palettized, x = mul_688)[name = string("tern_13_w2")];
            tensor<fp16, [352]> mul_689_y_0 = const()[name = string("mul_689_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7160320)))];
            tensor<fp16, [64, 352]> mul_689 = mul(x = tern_13_w2, y = mul_689_y_0)[name = string("mul_689")];
            tensor<fp16, [64, 352]> add_83 = add(x = add_81, y = mul_689)[name = string("add_83")];
            tensor<fp16, [64, 352]> mul_690 = mul(x = add_83, y = add_83)[name = string("mul_690")];
            tensor<int32, [1]> reduce_mean_148_axes_0 = const()[name = string("reduce_mean_148_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_148_keep_dims_0 = const()[name = string("reduce_mean_148_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_148 = reduce_mean(axes = reduce_mean_148_axes_0, keep_dims = reduce_mean_148_keep_dims_0, x = mul_690)[name = string("reduce_mean_148")];
            fp32 rsqrt_148_epsilon_0 = const()[name = string("rsqrt_148_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_148 = rsqrt(epsilon = rsqrt_148_epsilon_0, x = reduce_mean_148)[name = string("rsqrt_148")];
            tensor<fp16, [64, 352]> mul_691 = mul(x = add_83, y = rsqrt_148)[name = string("mul_691")];
            tensor<fp16, [352]> mul_692_y_0 = const()[name = string("mul_692_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7161088)))];
            tensor<fp16, [64, 352]> mul_692 = mul(x = mul_691, y = mul_692_y_0)[name = string("mul_692")];
            tensor<fp16, [64, 352]> mul_693 = mul(x = mul_692, y = mul_692)[name = string("mul_693")];
            tensor<int32, [1]> reduce_mean_149_axes_0 = const()[name = string("reduce_mean_149_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_149_keep_dims_0 = const()[name = string("reduce_mean_149_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_149 = reduce_mean(axes = reduce_mean_149_axes_0, keep_dims = reduce_mean_149_keep_dims_0, x = mul_693)[name = string("reduce_mean_149")];
            fp32 rsqrt_149_epsilon_0 = const()[name = string("rsqrt_149_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_149 = rsqrt(epsilon = rsqrt_149_epsilon_0, x = reduce_mean_149)[name = string("rsqrt_149")];
            tensor<fp16, [64, 352]> mul_694 = mul(x = mul_692, y = rsqrt_149)[name = string("mul_694")];
            tensor<fp16, [352]> mul_695_y_0 = const()[name = string("mul_695_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7161856)))];
            tensor<fp16, [64, 352]> mul_695 = mul(x = mul_694, y = mul_695_y_0)[name = string("mul_695")];
            tensor<fp16, [352, 352]> tern_14_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7162624))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_14_q_weight_0_palettized")];
            tensor<fp16, [64, 352]> tern_14_q = linear(bias = linear_0_bias_0, weight = tern_14_q_weight_0_palettized, x = mul_695)[name = string("tern_14_q")];
            tensor<fp16, [352]> mul_696_y_0 = const()[name = string("mul_696_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7193664)))];
            tensor<fp16, [64, 352]> mul_696 = mul(x = tern_14_q, y = mul_696_y_0)[name = string("mul_696")];
            tensor<int32, [3]> reshape_114_shape_0 = const()[name = string("reshape_114_shape_0"), val = tensor<int32, [3]>([64, 8, 44])];
            tensor<fp16, [64, 8, 44]> reshape_114 = reshape(shape = reshape_114_shape_0, x = mul_696)[name = string("reshape_114")];
            tensor<int32, [3]> transpose_56_perm_0 = const()[name = string("transpose_56_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_699_y_0 = const()[name = string("mul_699_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7194432)))];
            tensor<fp16, [64, 352]> mul_699 = mul(x = mul_694, y = mul_699_y_0)[name = string("mul_699")];
            tensor<fp16, [88, 352]> tern_14_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7195200))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_14_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_14_k_bias_0 = const()[name = string("tern_14_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [64, 88]> tern_14_k = linear(bias = tern_14_k_bias_0, weight = tern_14_k_weight_0_palettized, x = mul_699)[name = string("tern_14_k")];
            tensor<fp16, [88]> mul_700_y_0 = const()[name = string("mul_700_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7203008)))];
            tensor<fp16, [64, 88]> mul_700 = mul(x = tern_14_k, y = mul_700_y_0)[name = string("mul_700")];
            tensor<int32, [3]> reshape_115_shape_0 = const()[name = string("reshape_115_shape_0"), val = tensor<int32, [3]>([64, 2, 44])];
            tensor<fp16, [64, 2, 44]> reshape_115 = reshape(shape = reshape_115_shape_0, x = mul_700)[name = string("reshape_115")];
            tensor<int32, [3]> transpose_57_perm_0 = const()[name = string("transpose_57_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_703_y_0 = const()[name = string("mul_703_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7203264)))];
            tensor<fp16, [64, 352]> mul_703 = mul(x = mul_694, y = mul_703_y_0)[name = string("mul_703")];
            tensor<fp16, [88, 352]> tern_14_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7204032))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_14_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_14_v_bias_0 = const()[name = string("tern_14_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [64, 88]> tern_14_v = linear(bias = tern_14_v_bias_0, weight = tern_14_v_weight_0_palettized, x = mul_703)[name = string("tern_14_v")];
            tensor<fp16, [88]> mul_704_y_0 = const()[name = string("mul_704_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7211840)))];
            tensor<fp16, [64, 88]> mul_704 = mul(x = tern_14_v, y = mul_704_y_0)[name = string("mul_704")];
            tensor<int32, [3]> reshape_116_shape_0 = const()[name = string("reshape_116_shape_0"), val = tensor<int32, [3]>([64, 2, 44])];
            tensor<fp16, [64, 2, 44]> reshape_116 = reshape(shape = reshape_116_shape_0, x = mul_704)[name = string("reshape_116")];
            tensor<int32, [3]> transpose_58_perm_0 = const()[name = string("transpose_58_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 64, 44]> transpose_56 = transpose(perm = transpose_56_perm_0, x = reshape_114)[name = string("transpose_7")];
            tensor<fp16, [8, 64, 44]> mul_705 = mul(x = transpose_56, y = transpose_56)[name = string("mul_705")];
            tensor<int32, [1]> reduce_mean_152_axes_0 = const()[name = string("reduce_mean_152_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_152_keep_dims_0 = const()[name = string("reduce_mean_152_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 64, 1]> reduce_mean_152 = reduce_mean(axes = reduce_mean_152_axes_0, keep_dims = reduce_mean_152_keep_dims_0, x = mul_705)[name = string("reduce_mean_152")];
            fp32 rsqrt_152_epsilon_0 = const()[name = string("rsqrt_152_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 64, 1]> rsqrt_152 = rsqrt(epsilon = rsqrt_152_epsilon_0, x = reduce_mean_152)[name = string("rsqrt_152")];
            tensor<fp16, [8, 64, 44]> mul_706 = mul(x = transpose_56, y = rsqrt_152)[name = string("mul_706")];
            tensor<fp16, [44]> mul_707_y_0 = const()[name = string("mul_707_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7212096)))];
            tensor<fp16, [8, 64, 44]> mul_707 = mul(x = mul_706, y = mul_707_y_0)[name = string("mul_707")];
            tensor<int32, [3]> slice_by_index_56_begin_0 = const()[name = string("slice_by_index_56_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_56_end_0 = const()[name = string("slice_by_index_56_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_56_end_mask_0 = const()[name = string("slice_by_index_56_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 64, 22]> slice_by_index_56 = slice_by_index(begin = slice_by_index_56_begin_0, end = slice_by_index_56_end_0, end_mask = slice_by_index_56_end_mask_0, x = mul_707)[name = string("slice_by_index_56")];
            tensor<int32, [3]> slice_by_index_57_begin_0 = const()[name = string("slice_by_index_57_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_57_end_0 = const()[name = string("slice_by_index_57_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_57_end_mask_0 = const()[name = string("slice_by_index_57_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 64, 22]> slice_by_index_57 = slice_by_index(begin = slice_by_index_57_begin_0, end = slice_by_index_57_end_0, end_mask = slice_by_index_57_end_mask_0, x = mul_707)[name = string("slice_by_index_57")];
            int32 concat_28_axis_0 = const()[name = string("concat_28_axis_0"), val = int32(-1)];
            bool concat_28_interleave_0 = const()[name = string("concat_28_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 64, 44]> concat_28 = concat(axis = concat_28_axis_0, interleave = concat_28_interleave_0, values = (slice_by_index_57, slice_by_index_56))[name = string("concat_28")];
            tensor<fp16, [44]> mul_708_y_0 = const()[name = string("mul_708_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 64, 44]> mul_708 = mul(x = concat_28, y = mul_708_y_0)[name = string("mul_708")];
            tensor<fp16, [8, 64, 44]> mul_709 = mul(x = mul_707, y = mul_11_y_0)[name = string("mul_709")];
            tensor<fp16, [8, 64, 44]> mul_710 = mul(x = mul_708, y = mul_12_y_0)[name = string("mul_710")];
            tensor<fp16, [8, 64, 44]> add_84 = add(x = mul_709, y = mul_710)[name = string("add_84")];
            tensor<fp16, [2, 64, 44]> transpose_57 = transpose(perm = transpose_57_perm_0, x = reshape_115)[name = string("transpose_6")];
            tensor<fp16, [2, 64, 44]> mul_711 = mul(x = transpose_57, y = transpose_57)[name = string("mul_711")];
            tensor<int32, [1]> reduce_mean_153_axes_0 = const()[name = string("reduce_mean_153_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_153_keep_dims_0 = const()[name = string("reduce_mean_153_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 64, 1]> reduce_mean_153 = reduce_mean(axes = reduce_mean_153_axes_0, keep_dims = reduce_mean_153_keep_dims_0, x = mul_711)[name = string("reduce_mean_153")];
            fp32 rsqrt_153_epsilon_0 = const()[name = string("rsqrt_153_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 64, 1]> rsqrt_153 = rsqrt(epsilon = rsqrt_153_epsilon_0, x = reduce_mean_153)[name = string("rsqrt_153")];
            tensor<fp16, [2, 64, 44]> mul_712 = mul(x = transpose_57, y = rsqrt_153)[name = string("mul_712")];
            tensor<fp16, [44]> mul_713_y_0 = const()[name = string("mul_713_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7212288)))];
            tensor<fp16, [2, 64, 44]> mul_713 = mul(x = mul_712, y = mul_713_y_0)[name = string("mul_713")];
            tensor<int32, [3]> slice_by_index_58_begin_0 = const()[name = string("slice_by_index_58_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_58_end_0 = const()[name = string("slice_by_index_58_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_58_end_mask_0 = const()[name = string("slice_by_index_58_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 64, 22]> slice_by_index_58 = slice_by_index(begin = slice_by_index_58_begin_0, end = slice_by_index_58_end_0, end_mask = slice_by_index_58_end_mask_0, x = mul_713)[name = string("slice_by_index_58")];
            tensor<int32, [3]> slice_by_index_59_begin_0 = const()[name = string("slice_by_index_59_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_59_end_0 = const()[name = string("slice_by_index_59_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_59_end_mask_0 = const()[name = string("slice_by_index_59_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 64, 22]> slice_by_index_59 = slice_by_index(begin = slice_by_index_59_begin_0, end = slice_by_index_59_end_0, end_mask = slice_by_index_59_end_mask_0, x = mul_713)[name = string("slice_by_index_59")];
            int32 concat_29_axis_0 = const()[name = string("concat_29_axis_0"), val = int32(-1)];
            bool concat_29_interleave_0 = const()[name = string("concat_29_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 64, 44]> concat_29 = concat(axis = concat_29_axis_0, interleave = concat_29_interleave_0, values = (slice_by_index_59, slice_by_index_58))[name = string("concat_29")];
            tensor<fp16, [44]> mul_714_y_0 = const()[name = string("mul_714_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 64, 44]> mul_714 = mul(x = concat_29, y = mul_714_y_0)[name = string("mul_714")];
            tensor<fp16, [2, 64, 44]> mul_715 = mul(x = mul_713, y = mul_11_y_0)[name = string("mul_715")];
            tensor<fp16, [2, 64, 44]> mul_716 = mul(x = mul_714, y = mul_12_y_0)[name = string("mul_716")];
            tensor<fp16, [2, 64, 44]> add_85 = add(x = mul_715, y = mul_716)[name = string("add_85")];
            tensor<int32, [4]> reshape_117_shape_0 = const()[name = string("reshape_117_shape_0"), val = tensor<int32, [4]>([2, 1, 64, 44])];
            tensor<fp16, [2, 1, 64, 44]> reshape_117 = reshape(shape = reshape_117_shape_0, x = add_85)[name = string("reshape_117")];
            tensor<int32, [4]> tile_28_reps_0 = const()[name = string("tile_28_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 64, 44]> tile_28 = tile(reps = tile_28_reps_0, x = reshape_117)[name = string("tile_28")];
            tensor<int32, [3]> reshape_118_shape_0 = const()[name = string("reshape_118_shape_0"), val = tensor<int32, [3]>([8, 64, 44])];
            tensor<fp16, [8, 64, 44]> reshape_118 = reshape(shape = reshape_118_shape_0, x = tile_28)[name = string("reshape_118")];
            tensor<int32, [4]> reshape_119_shape_0 = const()[name = string("reshape_119_shape_0"), val = tensor<int32, [4]>([2, 1, 64, 44])];
            tensor<fp16, [2, 64, 44]> transpose_58 = transpose(perm = transpose_58_perm_0, x = reshape_116)[name = string("transpose_5")];
            tensor<fp16, [2, 1, 64, 44]> reshape_119 = reshape(shape = reshape_119_shape_0, x = transpose_58)[name = string("reshape_119")];
            tensor<int32, [4]> tile_29_reps_0 = const()[name = string("tile_29_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 64, 44]> tile_29 = tile(reps = tile_29_reps_0, x = reshape_119)[name = string("tile_29")];
            tensor<int32, [3]> reshape_120_shape_0 = const()[name = string("reshape_120_shape_0"), val = tensor<int32, [3]>([8, 64, 44])];
            tensor<fp16, [8, 64, 44]> reshape_120 = reshape(shape = reshape_120_shape_0, x = tile_29)[name = string("reshape_120")];
            fp16 mul_717_y_0 = const()[name = string("mul_717_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 64, 44]> mul_717 = mul(x = add_84, y = mul_717_y_0)[name = string("mul_717")];
            bool matmul_28_transpose_y_0 = const()[name = string("matmul_28_transpose_y_0"), val = bool(true)];
            bool matmul_28_transpose_x_0 = const()[name = string("matmul_28_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 64, 64]> matmul_28 = matmul(transpose_x = matmul_28_transpose_x_0, transpose_y = matmul_28_transpose_y_0, x = mul_717, y = reshape_118)[name = string("matmul_28")];
            tensor<fp16, [8, 64, 64]> add_86 = add(x = matmul_28, y = reshape_1)[name = string("add_86")];
            int32 softmax_14_axis_0 = const()[name = string("softmax_14_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 64, 64]> softmax_14 = softmax(axis = softmax_14_axis_0, x = add_86)[name = string("softmax_14")];
            bool matmul_29_transpose_x_0 = const()[name = string("matmul_29_transpose_x_0"), val = bool(false)];
            bool matmul_29_transpose_y_0 = const()[name = string("matmul_29_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 64, 44]> matmul_29 = matmul(transpose_x = matmul_29_transpose_x_0, transpose_y = matmul_29_transpose_y_0, x = softmax_14, y = reshape_120)[name = string("matmul_29")];
            tensor<int32, [3]> transpose_59_perm_0 = const()[name = string("transpose_59_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_121_shape_0 = const()[name = string("reshape_121_shape_0"), val = tensor<int32, [2]>([64, 352])];
            tensor<fp16, [64, 8, 44]> transpose_59 = transpose(perm = transpose_59_perm_0, x = matmul_29)[name = string("transpose_4")];
            tensor<fp16, [64, 352]> reshape_121 = reshape(shape = reshape_121_shape_0, x = transpose_59)[name = string("reshape_121")];
            tensor<fp16, [64, 352]> mul_718 = mul(x = reshape_121, y = reshape_121)[name = string("mul_718")];
            tensor<int32, [1]> reduce_mean_154_axes_0 = const()[name = string("reduce_mean_154_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_154_keep_dims_0 = const()[name = string("reduce_mean_154_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_154 = reduce_mean(axes = reduce_mean_154_axes_0, keep_dims = reduce_mean_154_keep_dims_0, x = mul_718)[name = string("reduce_mean_154")];
            fp32 rsqrt_154_epsilon_0 = const()[name = string("rsqrt_154_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_154 = rsqrt(epsilon = rsqrt_154_epsilon_0, x = reduce_mean_154)[name = string("rsqrt_154")];
            tensor<fp16, [64, 352]> mul_719 = mul(x = reshape_121, y = rsqrt_154)[name = string("mul_719")];
            tensor<fp16, [352]> mul_720_y_0 = const()[name = string("mul_720_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7212480)))];
            tensor<fp16, [64, 352]> mul_720 = mul(x = mul_719, y = mul_720_y_0)[name = string("mul_720")];
            tensor<fp16, [352, 352]> tern_14_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7213248))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_14_o_weight_0_palettized")];
            tensor<fp16, [64, 352]> tern_14_o = linear(bias = linear_0_bias_0, weight = tern_14_o_weight_0_palettized, x = mul_720)[name = string("tern_14_o")];
            tensor<fp16, [352]> mul_721_y_0 = const()[name = string("mul_721_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7244288)))];
            tensor<fp16, [64, 352]> mul_721 = mul(x = tern_14_o, y = mul_721_y_0)[name = string("mul_721")];
            tensor<fp16, [64, 352]> add_87 = add(x = add_83, y = mul_721)[name = string("add_87")];
            tensor<fp16, [64, 352]> mul_722 = mul(x = add_87, y = add_87)[name = string("mul_722")];
            tensor<int32, [1]> reduce_mean_155_axes_0 = const()[name = string("reduce_mean_155_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_155_keep_dims_0 = const()[name = string("reduce_mean_155_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_155 = reduce_mean(axes = reduce_mean_155_axes_0, keep_dims = reduce_mean_155_keep_dims_0, x = mul_722)[name = string("reduce_mean_155")];
            fp32 rsqrt_155_epsilon_0 = const()[name = string("rsqrt_155_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_155 = rsqrt(epsilon = rsqrt_155_epsilon_0, x = reduce_mean_155)[name = string("rsqrt_155")];
            tensor<fp16, [64, 352]> mul_723 = mul(x = add_87, y = rsqrt_155)[name = string("mul_723")];
            tensor<fp16, [352]> mul_724_y_0 = const()[name = string("mul_724_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7245056)))];
            tensor<fp16, [64, 352]> mul_724 = mul(x = mul_723, y = mul_724_y_0)[name = string("mul_724")];
            tensor<fp16, [64, 352]> mul_725 = mul(x = mul_724, y = mul_724)[name = string("mul_725")];
            tensor<int32, [1]> reduce_mean_156_axes_0 = const()[name = string("reduce_mean_156_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_156_keep_dims_0 = const()[name = string("reduce_mean_156_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_156 = reduce_mean(axes = reduce_mean_156_axes_0, keep_dims = reduce_mean_156_keep_dims_0, x = mul_725)[name = string("reduce_mean_156")];
            fp32 rsqrt_156_epsilon_0 = const()[name = string("rsqrt_156_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_156 = rsqrt(epsilon = rsqrt_156_epsilon_0, x = reduce_mean_156)[name = string("rsqrt_156")];
            tensor<fp16, [64, 352]> mul_726 = mul(x = mul_724, y = rsqrt_156)[name = string("mul_726")];
            tensor<fp16, [352]> mul_727_y_0 = const()[name = string("mul_727_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7245824)))];
            tensor<fp16, [64, 352]> mul_727 = mul(x = mul_726, y = mul_727_y_0)[name = string("mul_727")];
            tensor<fp16, [960, 352]> tern_14_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7246592))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_14_w1_weight_0_palettized")];
            tensor<fp16, [64, 960]> tern_14_w1 = linear(bias = linear_4_bias_0, weight = tern_14_w1_weight_0_palettized, x = mul_727)[name = string("tern_14_w1")];
            tensor<fp16, [960]> mul_728_y_0 = const()[name = string("mul_728_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7331136)))];
            tensor<fp16, [64, 960]> mul_728 = mul(x = tern_14_w1, y = mul_728_y_0)[name = string("mul_728")];
            tensor<fp16, [352]> mul_731_y_0 = const()[name = string("mul_731_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7333120)))];
            tensor<fp16, [64, 352]> mul_731 = mul(x = mul_726, y = mul_731_y_0)[name = string("mul_731")];
            tensor<fp16, [960, 352]> tern_14_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7333888))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_14_w3_weight_0_palettized")];
            tensor<fp16, [64, 960]> tern_14_w3 = linear(bias = linear_4_bias_0, weight = tern_14_w3_weight_0_palettized, x = mul_731)[name = string("tern_14_w3")];
            tensor<fp16, [960]> mul_732_y_0 = const()[name = string("mul_732_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7418432)))];
            tensor<fp16, [64, 960]> mul_732 = mul(x = tern_14_w3, y = mul_732_y_0)[name = string("mul_732")];
            fp16 mul_733_y_0 = const()[name = string("mul_733_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [64, 960]> mul_733 = mul(x = mul_728, y = mul_733_y_0)[name = string("mul_733")];
            tensor<fp16, [64, 960]> tanh_14 = tanh(x = mul_733)[name = string("tanh_14")];
            fp16 mul_734_x_0 = const()[name = string("mul_734_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [64, 960]> mul_734 = mul(x = mul_734_x_0, y = tanh_14)[name = string("mul_734")];
            fp16 add_88_x_0 = const()[name = string("add_88_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [64, 960]> add_88 = add(x = add_88_x_0, y = mul_734)[name = string("add_88")];
            tensor<fp16, [64, 960]> mul_735 = mul(x = mul_728, y = add_88)[name = string("mul_735")];
            tensor<fp16, [64, 960]> mul_736 = mul(x = mul_735, y = mul_732)[name = string("mul_736")];
            tensor<fp16, [64, 960]> mul_737 = mul(x = mul_736, y = mul_736)[name = string("mul_737")];
            tensor<int32, [1]> reduce_mean_158_axes_0 = const()[name = string("reduce_mean_158_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_158_keep_dims_0 = const()[name = string("reduce_mean_158_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_158 = reduce_mean(axes = reduce_mean_158_axes_0, keep_dims = reduce_mean_158_keep_dims_0, x = mul_737)[name = string("reduce_mean_158")];
            fp32 rsqrt_158_epsilon_0 = const()[name = string("rsqrt_158_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_158 = rsqrt(epsilon = rsqrt_158_epsilon_0, x = reduce_mean_158)[name = string("rsqrt_158")];
            tensor<fp16, [64, 960]> mul_738 = mul(x = mul_736, y = rsqrt_158)[name = string("mul_738")];
            tensor<fp16, [960]> mul_739_y_0 = const()[name = string("mul_739_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7420416)))];
            tensor<fp16, [64, 960]> mul_739 = mul(x = mul_738, y = mul_739_y_0)[name = string("mul_739")];
            tensor<fp16, [352, 960]> tern_14_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7422400))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_14_w2_weight_0_palettized")];
            tensor<fp16, [64, 352]> tern_14_w2 = linear(bias = linear_0_bias_0, weight = tern_14_w2_weight_0_palettized, x = mul_739)[name = string("tern_14_w2")];
            tensor<fp16, [352]> mul_740_y_0 = const()[name = string("mul_740_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7506944)))];
            tensor<fp16, [64, 352]> mul_740 = mul(x = tern_14_w2, y = mul_740_y_0)[name = string("mul_740")];
            tensor<fp16, [64, 352]> add_89 = add(x = add_87, y = mul_740)[name = string("add_89")];
            tensor<fp16, [64, 352]> mul_741 = mul(x = add_89, y = add_89)[name = string("mul_741")];
            tensor<int32, [1]> reduce_mean_159_axes_0 = const()[name = string("reduce_mean_159_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_159_keep_dims_0 = const()[name = string("reduce_mean_159_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_159 = reduce_mean(axes = reduce_mean_159_axes_0, keep_dims = reduce_mean_159_keep_dims_0, x = mul_741)[name = string("reduce_mean_159")];
            fp32 rsqrt_159_epsilon_0 = const()[name = string("rsqrt_159_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_159 = rsqrt(epsilon = rsqrt_159_epsilon_0, x = reduce_mean_159)[name = string("rsqrt_159")];
            tensor<fp16, [64, 352]> mul_742 = mul(x = add_89, y = rsqrt_159)[name = string("mul_742")];
            tensor<fp16, [352]> mul_743_y_0 = const()[name = string("mul_743_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7507712)))];
            tensor<fp16, [64, 352]> mul_743 = mul(x = mul_742, y = mul_743_y_0)[name = string("mul_743")];
            tensor<fp16, [352, 352]> linear_7_weight_0 = const()[name = string("linear_7_weight_0"), val = tensor<fp16, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7508480)))];
            tensor<fp16, [64, 352]> linear_7 = linear(bias = linear_0_bias_0, weight = linear_7_weight_0, x = mul_743)[name = string("linear_7")];
            tensor<int32, [3]> reshape_122_shape_0 = const()[name = string("reshape_122_shape_0"), val = tensor<int32, [3]>([64, 8, 44])];
            tensor<fp16, [64, 8, 44]> reshape_122 = reshape(shape = reshape_122_shape_0, x = linear_7)[name = string("reshape_122")];
            tensor<int32, [3]> transpose_60_perm_0 = const()[name = string("transpose_60_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [88, 352]> linear_8_weight_0 = const()[name = string("linear_8_weight_0"), val = tensor<fp16, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7756352)))];
            tensor<fp16, [88]> linear_8_bias_0 = const()[name = string("linear_8_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [64, 88]> linear_8 = linear(bias = linear_8_bias_0, weight = linear_8_weight_0, x = mul_743)[name = string("linear_8")];
            tensor<int32, [3]> reshape_123_shape_0 = const()[name = string("reshape_123_shape_0"), val = tensor<int32, [3]>([64, 2, 44])];
            tensor<fp16, [64, 2, 44]> reshape_123 = reshape(shape = reshape_123_shape_0, x = linear_8)[name = string("reshape_123")];
            tensor<int32, [3]> transpose_61_perm_0 = const()[name = string("transpose_61_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [88, 352]> linear_9_weight_0 = const()[name = string("linear_9_weight_0"), val = tensor<fp16, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7818368)))];
            tensor<fp16, [88]> linear_9_bias_0 = const()[name = string("linear_9_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [64, 88]> linear_9 = linear(bias = linear_9_bias_0, weight = linear_9_weight_0, x = mul_743)[name = string("linear_9")];
            tensor<int32, [3]> reshape_124_shape_0 = const()[name = string("reshape_124_shape_0"), val = tensor<int32, [3]>([64, 2, 44])];
            tensor<fp16, [64, 2, 44]> reshape_124 = reshape(shape = reshape_124_shape_0, x = linear_9)[name = string("reshape_124")];
            tensor<int32, [3]> transpose_62_perm_0 = const()[name = string("transpose_62_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 64, 44]> transpose_60 = transpose(perm = transpose_60_perm_0, x = reshape_122)[name = string("transpose_3")];
            tensor<fp16, [8, 64, 44]> mul_744 = mul(x = transpose_60, y = transpose_60)[name = string("mul_744")];
            tensor<int32, [1]> reduce_mean_160_axes_0 = const()[name = string("reduce_mean_160_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_160_keep_dims_0 = const()[name = string("reduce_mean_160_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 64, 1]> reduce_mean_160 = reduce_mean(axes = reduce_mean_160_axes_0, keep_dims = reduce_mean_160_keep_dims_0, x = mul_744)[name = string("reduce_mean_160")];
            fp32 rsqrt_160_epsilon_0 = const()[name = string("rsqrt_160_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 64, 1]> rsqrt_160 = rsqrt(epsilon = rsqrt_160_epsilon_0, x = reduce_mean_160)[name = string("rsqrt_160")];
            tensor<fp16, [8, 64, 44]> mul_745 = mul(x = transpose_60, y = rsqrt_160)[name = string("mul_745")];
            tensor<fp16, [44]> mul_746_y_0 = const()[name = string("mul_746_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7880384)))];
            tensor<fp16, [8, 64, 44]> mul_746 = mul(x = mul_745, y = mul_746_y_0)[name = string("mul_746")];
            tensor<int32, [3]> slice_by_index_60_begin_0 = const()[name = string("slice_by_index_60_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_60_end_0 = const()[name = string("slice_by_index_60_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_60_end_mask_0 = const()[name = string("slice_by_index_60_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 64, 22]> slice_by_index_60 = slice_by_index(begin = slice_by_index_60_begin_0, end = slice_by_index_60_end_0, end_mask = slice_by_index_60_end_mask_0, x = mul_746)[name = string("slice_by_index_60")];
            tensor<int32, [3]> slice_by_index_61_begin_0 = const()[name = string("slice_by_index_61_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_61_end_0 = const()[name = string("slice_by_index_61_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_61_end_mask_0 = const()[name = string("slice_by_index_61_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 64, 22]> slice_by_index_61 = slice_by_index(begin = slice_by_index_61_begin_0, end = slice_by_index_61_end_0, end_mask = slice_by_index_61_end_mask_0, x = mul_746)[name = string("slice_by_index_61")];
            int32 concat_30_axis_0 = const()[name = string("concat_30_axis_0"), val = int32(-1)];
            bool concat_30_interleave_0 = const()[name = string("concat_30_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 64, 44]> concat_30 = concat(axis = concat_30_axis_0, interleave = concat_30_interleave_0, values = (slice_by_index_61, slice_by_index_60))[name = string("concat_30")];
            tensor<fp16, [44]> mul_747_y_0 = const()[name = string("mul_747_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 64, 44]> mul_747 = mul(x = concat_30, y = mul_747_y_0)[name = string("mul_747")];
            tensor<fp16, [8, 64, 44]> mul_748 = mul(x = mul_746, y = mul_11_y_0)[name = string("mul_748")];
            tensor<fp16, [8, 64, 44]> mul_749 = mul(x = mul_747, y = mul_12_y_0)[name = string("mul_749")];
            tensor<fp16, [8, 64, 44]> add_90 = add(x = mul_748, y = mul_749)[name = string("add_90")];
            tensor<fp16, [2, 64, 44]> transpose_61 = transpose(perm = transpose_61_perm_0, x = reshape_123)[name = string("transpose_2")];
            tensor<fp16, [2, 64, 44]> mul_750 = mul(x = transpose_61, y = transpose_61)[name = string("mul_750")];
            tensor<int32, [1]> reduce_mean_161_axes_0 = const()[name = string("reduce_mean_161_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_161_keep_dims_0 = const()[name = string("reduce_mean_161_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 64, 1]> reduce_mean_161 = reduce_mean(axes = reduce_mean_161_axes_0, keep_dims = reduce_mean_161_keep_dims_0, x = mul_750)[name = string("reduce_mean_161")];
            fp32 rsqrt_161_epsilon_0 = const()[name = string("rsqrt_161_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 64, 1]> rsqrt_161 = rsqrt(epsilon = rsqrt_161_epsilon_0, x = reduce_mean_161)[name = string("rsqrt_161")];
            tensor<fp16, [2, 64, 44]> mul_751 = mul(x = transpose_61, y = rsqrt_161)[name = string("mul_751")];
            tensor<fp16, [44]> mul_752_y_0 = const()[name = string("mul_752_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7880576)))];
            tensor<fp16, [2, 64, 44]> mul_752 = mul(x = mul_751, y = mul_752_y_0)[name = string("mul_752")];
            tensor<int32, [3]> slice_by_index_62_begin_0 = const()[name = string("slice_by_index_62_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_62_end_0 = const()[name = string("slice_by_index_62_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_62_end_mask_0 = const()[name = string("slice_by_index_62_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 64, 22]> slice_by_index_62 = slice_by_index(begin = slice_by_index_62_begin_0, end = slice_by_index_62_end_0, end_mask = slice_by_index_62_end_mask_0, x = mul_752)[name = string("slice_by_index_62")];
            tensor<int32, [3]> slice_by_index_63_begin_0 = const()[name = string("slice_by_index_63_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_63_end_0 = const()[name = string("slice_by_index_63_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_63_end_mask_0 = const()[name = string("slice_by_index_63_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 64, 22]> slice_by_index_63 = slice_by_index(begin = slice_by_index_63_begin_0, end = slice_by_index_63_end_0, end_mask = slice_by_index_63_end_mask_0, x = mul_752)[name = string("slice_by_index_63")];
            int32 concat_31_axis_0 = const()[name = string("concat_31_axis_0"), val = int32(-1)];
            bool concat_31_interleave_0 = const()[name = string("concat_31_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 64, 44]> concat_31 = concat(axis = concat_31_axis_0, interleave = concat_31_interleave_0, values = (slice_by_index_63, slice_by_index_62))[name = string("concat_31")];
            tensor<fp16, [44]> mul_753_y_0 = const()[name = string("mul_753_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 64, 44]> mul_753 = mul(x = concat_31, y = mul_753_y_0)[name = string("mul_753")];
            tensor<fp16, [2, 64, 44]> mul_754 = mul(x = mul_752, y = mul_11_y_0)[name = string("mul_754")];
            tensor<fp16, [2, 64, 44]> mul_755 = mul(x = mul_753, y = mul_12_y_0)[name = string("mul_755")];
            tensor<fp16, [2, 64, 44]> add_91 = add(x = mul_754, y = mul_755)[name = string("add_91")];
            tensor<int32, [4]> reshape_125_shape_0 = const()[name = string("reshape_125_shape_0"), val = tensor<int32, [4]>([2, 1, 64, 44])];
            tensor<fp16, [2, 1, 64, 44]> reshape_125 = reshape(shape = reshape_125_shape_0, x = add_91)[name = string("reshape_125")];
            tensor<int32, [4]> tile_30_reps_0 = const()[name = string("tile_30_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 64, 44]> tile_30 = tile(reps = tile_30_reps_0, x = reshape_125)[name = string("tile_30")];
            tensor<int32, [3]> reshape_126_shape_0 = const()[name = string("reshape_126_shape_0"), val = tensor<int32, [3]>([8, 64, 44])];
            tensor<fp16, [8, 64, 44]> reshape_126 = reshape(shape = reshape_126_shape_0, x = tile_30)[name = string("reshape_126")];
            tensor<int32, [4]> reshape_127_shape_0 = const()[name = string("reshape_127_shape_0"), val = tensor<int32, [4]>([2, 1, 64, 44])];
            tensor<fp16, [2, 64, 44]> transpose_62 = transpose(perm = transpose_62_perm_0, x = reshape_124)[name = string("transpose_1")];
            tensor<fp16, [2, 1, 64, 44]> reshape_127 = reshape(shape = reshape_127_shape_0, x = transpose_62)[name = string("reshape_127")];
            tensor<int32, [4]> tile_31_reps_0 = const()[name = string("tile_31_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 64, 44]> tile_31 = tile(reps = tile_31_reps_0, x = reshape_127)[name = string("tile_31")];
            tensor<int32, [3]> reshape_128_shape_0 = const()[name = string("reshape_128_shape_0"), val = tensor<int32, [3]>([8, 64, 44])];
            tensor<fp16, [8, 64, 44]> reshape_128 = reshape(shape = reshape_128_shape_0, x = tile_31)[name = string("reshape_128")];
            fp16 mul_756_y_0 = const()[name = string("mul_756_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 64, 44]> mul_756 = mul(x = add_90, y = mul_756_y_0)[name = string("mul_756")];
            bool matmul_30_transpose_y_0 = const()[name = string("matmul_30_transpose_y_0"), val = bool(true)];
            bool matmul_30_transpose_x_0 = const()[name = string("matmul_30_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 64, 64]> matmul_30 = matmul(transpose_x = matmul_30_transpose_x_0, transpose_y = matmul_30_transpose_y_0, x = mul_756, y = reshape_126)[name = string("matmul_30")];
            tensor<fp16, [8, 64, 64]> add_92 = add(x = matmul_30, y = reshape_1)[name = string("add_92")];
            int32 softmax_15_axis_0 = const()[name = string("softmax_15_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 64, 64]> softmax_15 = softmax(axis = softmax_15_axis_0, x = add_92)[name = string("softmax_15")];
            bool matmul_31_transpose_x_0 = const()[name = string("matmul_31_transpose_x_0"), val = bool(false)];
            bool matmul_31_transpose_y_0 = const()[name = string("matmul_31_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 64, 44]> matmul_31 = matmul(transpose_x = matmul_31_transpose_x_0, transpose_y = matmul_31_transpose_y_0, x = softmax_15, y = reshape_128)[name = string("matmul_31")];
            tensor<int32, [3]> transpose_63_perm_0 = const()[name = string("transpose_63_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_129_shape_0 = const()[name = string("reshape_129_shape_0"), val = tensor<int32, [2]>([64, 352])];
            tensor<fp16, [64, 8, 44]> transpose_63 = transpose(perm = transpose_63_perm_0, x = matmul_31)[name = string("transpose_0")];
            tensor<fp16, [64, 352]> reshape_129 = reshape(shape = reshape_129_shape_0, x = transpose_63)[name = string("reshape_129")];
            tensor<fp16, [352, 352]> linear_10_weight_0 = const()[name = string("linear_10_weight_0"), val = tensor<fp16, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7880768)))];
            tensor<fp16, [64, 352]> linear_10 = linear(bias = linear_0_bias_0, weight = linear_10_weight_0, x = reshape_129)[name = string("linear_10")];
            tensor<fp16, [64, 352]> add_93 = add(x = add_89, y = linear_10)[name = string("add_93")];
            tensor<fp16, [64, 352]> mul_757 = mul(x = add_93, y = add_93)[name = string("mul_757")];
            tensor<int32, [1]> reduce_mean_162_axes_0 = const()[name = string("reduce_mean_162_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_162_keep_dims_0 = const()[name = string("reduce_mean_162_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_162 = reduce_mean(axes = reduce_mean_162_axes_0, keep_dims = reduce_mean_162_keep_dims_0, x = mul_757)[name = string("reduce_mean_162")];
            fp32 rsqrt_162_epsilon_0 = const()[name = string("rsqrt_162_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_162 = rsqrt(epsilon = rsqrt_162_epsilon_0, x = reduce_mean_162)[name = string("rsqrt_162")];
            tensor<fp16, [64, 352]> mul_758 = mul(x = add_93, y = rsqrt_162)[name = string("mul_758")];
            tensor<fp16, [352]> mul_759_y_0 = const()[name = string("mul_759_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8128640)))];
            tensor<fp16, [64, 352]> mul_759 = mul(x = mul_758, y = mul_759_y_0)[name = string("mul_759")];
            tensor<fp16, [960, 352]> linear_11_weight_0 = const()[name = string("linear_11_weight_0"), val = tensor<fp16, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8129408)))];
            tensor<fp16, [64, 960]> linear_11 = linear(bias = linear_4_bias_0, weight = linear_11_weight_0, x = mul_759)[name = string("linear_11")];
            tensor<fp16, [960, 352]> linear_12_weight_0 = const()[name = string("linear_12_weight_0"), val = tensor<fp16, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8805312)))];
            tensor<fp16, [64, 960]> linear_12 = linear(bias = linear_4_bias_0, weight = linear_12_weight_0, x = mul_759)[name = string("linear_12")];
            fp16 mul_760_y_0 = const()[name = string("mul_760_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [64, 960]> mul_760 = mul(x = linear_11, y = mul_760_y_0)[name = string("mul_760")];
            tensor<fp16, [64, 960]> tanh_15 = tanh(x = mul_760)[name = string("tanh_15")];
            fp16 mul_761_x_0 = const()[name = string("mul_761_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [64, 960]> mul_761 = mul(x = mul_761_x_0, y = tanh_15)[name = string("mul_761")];
            fp16 add_94_x_0 = const()[name = string("add_94_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [64, 960]> add_94 = add(x = add_94_x_0, y = mul_761)[name = string("add_94")];
            tensor<fp16, [64, 960]> mul_762 = mul(x = linear_11, y = add_94)[name = string("mul_762")];
            tensor<fp16, [64, 960]> mul_763 = mul(x = mul_762, y = linear_12)[name = string("mul_763")];
            tensor<fp16, [352, 960]> linear_13_weight_0 = const()[name = string("linear_13_weight_0"), val = tensor<fp16, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9481216)))];
            tensor<fp16, [64, 352]> linear_13 = linear(bias = linear_0_bias_0, weight = linear_13_weight_0, x = mul_763)[name = string("linear_13")];
            tensor<fp16, [64, 352]> add_95 = add(x = add_93, y = linear_13)[name = string("add_95")];
            tensor<fp16, [64, 352]> mul_764 = mul(x = add_95, y = add_95)[name = string("mul_764")];
            tensor<int32, [1]> reduce_mean_163_axes_0 = const()[name = string("reduce_mean_163_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_163_keep_dims_0 = const()[name = string("reduce_mean_163_keep_dims_0"), val = bool(true)];
            tensor<fp16, [64, 1]> reduce_mean_163 = reduce_mean(axes = reduce_mean_163_axes_0, keep_dims = reduce_mean_163_keep_dims_0, x = mul_764)[name = string("reduce_mean_163")];
            fp32 rsqrt_163_epsilon_0 = const()[name = string("rsqrt_163_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [64, 1]> rsqrt_163 = rsqrt(epsilon = rsqrt_163_epsilon_0, x = reduce_mean_163)[name = string("rsqrt_163")];
            tensor<fp16, [64, 352]> mul_765 = mul(x = add_95, y = rsqrt_163)[name = string("mul_765")];
            tensor<fp16, [352]> mul_766_y_0 = const()[name = string("mul_766_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10157120)))];
            tensor<fp16, [64, 352]> mul_766 = mul(x = mul_765, y = mul_766_y_0)[name = string("mul_766")];
            tensor<fp16, [8342, 352]> linear_14_weight_0 = const()[name = string("linear_14_weight_0"), val = tensor<fp16, [8342, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10157888)))];
            tensor<fp16, [8342]> linear_14_bias_0 = const()[name = string("linear_14_bias_0"), val = tensor<fp16, [8342]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16030720)))];
            tensor<fp16, [64, 8342]> linear_14 = linear(bias = linear_14_bias_0, weight = linear_14_weight_0, x = mul_766)[name = string("linear_14")];
            tensor<int32, [3]> logits_shape_0 = const()[name = string("logits_shape_0"), val = tensor<int32, [3]>([1, 64, 8342])];
            tensor<fp16, [1, 64, 8342]> logits = reshape(shape = logits_shape_0, x = linear_14)[name = string("logits")];
        } -> (logits);
    func L8<ios18>(tensor<fp16, [1, 8, 352]> ids, tensor<fp16, [1, 8]> mask) {
            tensor<int32, [2]> reshape_0_shape_0 = const()[name = string("reshape_0_shape_0"), val = tensor<int32, [2]>([8, 352])];
            tensor<fp16, [8, 352]> reshape_0 = reshape(shape = reshape_0_shape_0, x = ids)[name = string("reshape_0")];
            tensor<fp16, [8, 352]> mul_0 = mul(x = reshape_0, y = reshape_0)[name = string("mul_0")];
            tensor<int32, [1]> reduce_mean_0_axes_0 = const()[name = string("reduce_mean_0_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_0_keep_dims_0 = const()[name = string("reduce_mean_0_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_0 = reduce_mean(axes = reduce_mean_0_axes_0, keep_dims = reduce_mean_0_keep_dims_0, x = mul_0)[name = string("reduce_mean_0")];
            fp32 rsqrt_0_epsilon_0 = const()[name = string("rsqrt_0_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_0 = rsqrt(epsilon = rsqrt_0_epsilon_0, x = reduce_mean_0)[name = string("rsqrt_0")];
            tensor<fp16, [8, 352]> mul_1 = mul(x = reshape_0, y = rsqrt_0)[name = string("mul_1")];
            tensor<fp16, [352]> mul_2_y_0 = const()[name = string("mul_2_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(64)))];
            tensor<fp16, [8, 352]> mul_2 = mul(x = mul_1, y = mul_2_y_0)[name = string("mul_2")];
            fp16 sub_0_y_0 = const()[name = string("sub_0_y_0"), val = fp16(0x1p+0)];
            tensor<fp16, [1, 8]> sub_0 = sub(x = mask, y = sub_0_y_0)[name = string("sub_0")];
            fp16 mul_3_y_0 = const()[name = string("mul_3_y_0"), val = fp16(0x1.388p+13)];
            tensor<fp16, [1, 8]> mul_3 = mul(x = sub_0, y = mul_3_y_0)[name = string("mul_3")];
            tensor<int32, [3]> reshape_1_shape_0 = const()[name = string("reshape_1_shape_0"), val = tensor<int32, [3]>([1, 1, 8])];
            tensor<fp16, [1, 1, 8]> reshape_1 = reshape(shape = reshape_1_shape_0, x = mul_3)[name = string("reshape_1")];
            tensor<fp16, [8, 352]> mul_4 = mul(x = mul_2, y = mul_2)[name = string("mul_4")];
            tensor<int32, [1]> reduce_mean_1_axes_0 = const()[name = string("reduce_mean_1_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_1_keep_dims_0 = const()[name = string("reduce_mean_1_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_1 = reduce_mean(axes = reduce_mean_1_axes_0, keep_dims = reduce_mean_1_keep_dims_0, x = mul_4)[name = string("reduce_mean_1")];
            fp32 rsqrt_1_epsilon_0 = const()[name = string("rsqrt_1_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_1 = rsqrt(epsilon = rsqrt_1_epsilon_0, x = reduce_mean_1)[name = string("rsqrt_1")];
            tensor<fp16, [8, 352]> mul_5 = mul(x = mul_2, y = rsqrt_1)[name = string("mul_5")];
            tensor<fp16, [352]> mul_6_y_0 = const()[name = string("mul_6_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(832)))];
            tensor<fp16, [8, 352]> mul_6 = mul(x = mul_5, y = mul_6_y_0)[name = string("mul_6")];
            tensor<fp16, [352, 352]> linear_0_weight_0 = const()[name = string("linear_0_weight_0"), val = tensor<fp16, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1600)))];
            tensor<fp16, [352]> linear_0_bias_0 = const()[name = string("linear_0_bias_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(249472)))];
            tensor<fp16, [8, 352]> linear_0 = linear(bias = linear_0_bias_0, weight = linear_0_weight_0, x = mul_6)[name = string("linear_0")];
            tensor<int32, [3]> reshape_2_shape_0 = const()[name = string("reshape_2_shape_0"), val = tensor<int32, [3]>([8, 8, 44])];
            tensor<fp16, [8, 8, 44]> reshape_2 = reshape(shape = reshape_2_shape_0, x = linear_0)[name = string("reshape_2")];
            tensor<int32, [3]> transpose_0_perm_0 = const()[name = string("transpose_0_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [88, 352]> linear_1_weight_0 = const()[name = string("linear_1_weight_0"), val = tensor<fp16, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(250240)))];
            tensor<fp16, [88]> linear_1_bias_0 = const()[name = string("linear_1_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [8, 88]> linear_1 = linear(bias = linear_1_bias_0, weight = linear_1_weight_0, x = mul_6)[name = string("linear_1")];
            tensor<int32, [3]> reshape_3_shape_0 = const()[name = string("reshape_3_shape_0"), val = tensor<int32, [3]>([8, 2, 44])];
            tensor<fp16, [8, 2, 44]> reshape_3 = reshape(shape = reshape_3_shape_0, x = linear_1)[name = string("reshape_3")];
            tensor<int32, [3]> transpose_1_perm_0 = const()[name = string("transpose_1_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [88, 352]> linear_2_weight_0 = const()[name = string("linear_2_weight_0"), val = tensor<fp16, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312512)))];
            tensor<fp16, [88]> linear_2_bias_0 = const()[name = string("linear_2_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [8, 88]> linear_2 = linear(bias = linear_2_bias_0, weight = linear_2_weight_0, x = mul_6)[name = string("linear_2")];
            tensor<int32, [3]> reshape_4_shape_0 = const()[name = string("reshape_4_shape_0"), val = tensor<int32, [3]>([8, 2, 44])];
            tensor<fp16, [8, 2, 44]> reshape_4 = reshape(shape = reshape_4_shape_0, x = linear_2)[name = string("reshape_4")];
            tensor<int32, [3]> transpose_2_perm_0 = const()[name = string("transpose_2_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 8, 44]> transpose_0 = transpose(perm = transpose_0_perm_0, x = reshape_2)[name = string("transpose_63")];
            tensor<fp16, [8, 8, 44]> mul_7 = mul(x = transpose_0, y = transpose_0)[name = string("mul_7")];
            tensor<int32, [1]> reduce_mean_2_axes_0 = const()[name = string("reduce_mean_2_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_2_keep_dims_0 = const()[name = string("reduce_mean_2_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 8, 1]> reduce_mean_2 = reduce_mean(axes = reduce_mean_2_axes_0, keep_dims = reduce_mean_2_keep_dims_0, x = mul_7)[name = string("reduce_mean_2")];
            fp32 rsqrt_2_epsilon_0 = const()[name = string("rsqrt_2_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 8, 1]> rsqrt_2 = rsqrt(epsilon = rsqrt_2_epsilon_0, x = reduce_mean_2)[name = string("rsqrt_2")];
            tensor<fp16, [8, 8, 44]> mul_8 = mul(x = transpose_0, y = rsqrt_2)[name = string("mul_8")];
            tensor<fp16, [44]> mul_9_y_0 = const()[name = string("mul_9_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374528)))];
            tensor<fp16, [8, 8, 44]> mul_9 = mul(x = mul_8, y = mul_9_y_0)[name = string("mul_9")];
            tensor<int32, [3]> slice_by_index_0_begin_0 = const()[name = string("slice_by_index_0_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_0_end_0 = const()[name = string("slice_by_index_0_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_0_end_mask_0 = const()[name = string("slice_by_index_0_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 8, 22]> slice_by_index_0 = slice_by_index(begin = slice_by_index_0_begin_0, end = slice_by_index_0_end_0, end_mask = slice_by_index_0_end_mask_0, x = mul_9)[name = string("slice_by_index_0")];
            tensor<int32, [3]> slice_by_index_1_begin_0 = const()[name = string("slice_by_index_1_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_1_end_0 = const()[name = string("slice_by_index_1_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_1_end_mask_0 = const()[name = string("slice_by_index_1_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 8, 22]> slice_by_index_1 = slice_by_index(begin = slice_by_index_1_begin_0, end = slice_by_index_1_end_0, end_mask = slice_by_index_1_end_mask_0, x = mul_9)[name = string("slice_by_index_1")];
            int32 concat_0_axis_0 = const()[name = string("concat_0_axis_0"), val = int32(-1)];
            bool concat_0_interleave_0 = const()[name = string("concat_0_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 8, 44]> concat_0 = concat(axis = concat_0_axis_0, interleave = concat_0_interleave_0, values = (slice_by_index_1, slice_by_index_0))[name = string("concat_0")];
            tensor<fp16, [44]> mul_10_y_0 = const()[name = string("mul_10_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 8, 44]> mul_10 = mul(x = concat_0, y = mul_10_y_0)[name = string("mul_10")];
            tensor<fp16, [1, 8, 44]> mul_11_y_0 = const()[name = string("mul_11_y_0"), val = tensor<fp16, [1, 8, 44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374912)))];
            tensor<fp16, [8, 8, 44]> mul_11 = mul(x = mul_9, y = mul_11_y_0)[name = string("mul_11")];
            tensor<fp16, [1, 8, 44]> mul_12_y_0 = const()[name = string("mul_12_y_0"), val = tensor<fp16, [1, 8, 44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(375680)))];
            tensor<fp16, [8, 8, 44]> mul_12 = mul(x = mul_10, y = mul_12_y_0)[name = string("mul_12")];
            tensor<fp16, [8, 8, 44]> add_0 = add(x = mul_11, y = mul_12)[name = string("add_0")];
            tensor<fp16, [2, 8, 44]> transpose_1 = transpose(perm = transpose_1_perm_0, x = reshape_3)[name = string("transpose_62")];
            tensor<fp16, [2, 8, 44]> mul_13 = mul(x = transpose_1, y = transpose_1)[name = string("mul_13")];
            tensor<int32, [1]> reduce_mean_3_axes_0 = const()[name = string("reduce_mean_3_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_3_keep_dims_0 = const()[name = string("reduce_mean_3_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 8, 1]> reduce_mean_3 = reduce_mean(axes = reduce_mean_3_axes_0, keep_dims = reduce_mean_3_keep_dims_0, x = mul_13)[name = string("reduce_mean_3")];
            fp32 rsqrt_3_epsilon_0 = const()[name = string("rsqrt_3_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 8, 1]> rsqrt_3 = rsqrt(epsilon = rsqrt_3_epsilon_0, x = reduce_mean_3)[name = string("rsqrt_3")];
            tensor<fp16, [2, 8, 44]> mul_14 = mul(x = transpose_1, y = rsqrt_3)[name = string("mul_14")];
            tensor<fp16, [44]> mul_15_y_0 = const()[name = string("mul_15_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(376448)))];
            tensor<fp16, [2, 8, 44]> mul_15 = mul(x = mul_14, y = mul_15_y_0)[name = string("mul_15")];
            tensor<int32, [3]> slice_by_index_2_begin_0 = const()[name = string("slice_by_index_2_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_2_end_0 = const()[name = string("slice_by_index_2_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_2_end_mask_0 = const()[name = string("slice_by_index_2_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 8, 22]> slice_by_index_2 = slice_by_index(begin = slice_by_index_2_begin_0, end = slice_by_index_2_end_0, end_mask = slice_by_index_2_end_mask_0, x = mul_15)[name = string("slice_by_index_2")];
            tensor<int32, [3]> slice_by_index_3_begin_0 = const()[name = string("slice_by_index_3_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_3_end_0 = const()[name = string("slice_by_index_3_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_3_end_mask_0 = const()[name = string("slice_by_index_3_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 8, 22]> slice_by_index_3 = slice_by_index(begin = slice_by_index_3_begin_0, end = slice_by_index_3_end_0, end_mask = slice_by_index_3_end_mask_0, x = mul_15)[name = string("slice_by_index_3")];
            int32 concat_1_axis_0 = const()[name = string("concat_1_axis_0"), val = int32(-1)];
            bool concat_1_interleave_0 = const()[name = string("concat_1_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 8, 44]> concat_1 = concat(axis = concat_1_axis_0, interleave = concat_1_interleave_0, values = (slice_by_index_3, slice_by_index_2))[name = string("concat_1")];
            tensor<fp16, [44]> mul_16_y_0 = const()[name = string("mul_16_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 8, 44]> mul_16 = mul(x = concat_1, y = mul_16_y_0)[name = string("mul_16")];
            tensor<fp16, [2, 8, 44]> mul_17 = mul(x = mul_15, y = mul_11_y_0)[name = string("mul_17")];
            tensor<fp16, [2, 8, 44]> mul_18 = mul(x = mul_16, y = mul_12_y_0)[name = string("mul_18")];
            tensor<fp16, [2, 8, 44]> add_1 = add(x = mul_17, y = mul_18)[name = string("add_1")];
            tensor<int32, [4]> reshape_5_shape_0 = const()[name = string("reshape_5_shape_0"), val = tensor<int32, [4]>([2, 1, 8, 44])];
            tensor<fp16, [2, 1, 8, 44]> reshape_5 = reshape(shape = reshape_5_shape_0, x = add_1)[name = string("reshape_5")];
            tensor<int32, [4]> tile_0_reps_0 = const()[name = string("tile_0_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 8, 44]> tile_0 = tile(reps = tile_0_reps_0, x = reshape_5)[name = string("tile_0")];
            tensor<int32, [3]> reshape_6_shape_0 = const()[name = string("reshape_6_shape_0"), val = tensor<int32, [3]>([8, 8, 44])];
            tensor<fp16, [8, 8, 44]> reshape_6 = reshape(shape = reshape_6_shape_0, x = tile_0)[name = string("reshape_6")];
            tensor<int32, [4]> reshape_7_shape_0 = const()[name = string("reshape_7_shape_0"), val = tensor<int32, [4]>([2, 1, 8, 44])];
            tensor<fp16, [2, 8, 44]> transpose_2 = transpose(perm = transpose_2_perm_0, x = reshape_4)[name = string("transpose_61")];
            tensor<fp16, [2, 1, 8, 44]> reshape_7 = reshape(shape = reshape_7_shape_0, x = transpose_2)[name = string("reshape_7")];
            tensor<int32, [4]> tile_1_reps_0 = const()[name = string("tile_1_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 8, 44]> tile_1 = tile(reps = tile_1_reps_0, x = reshape_7)[name = string("tile_1")];
            tensor<int32, [3]> reshape_8_shape_0 = const()[name = string("reshape_8_shape_0"), val = tensor<int32, [3]>([8, 8, 44])];
            tensor<fp16, [8, 8, 44]> reshape_8 = reshape(shape = reshape_8_shape_0, x = tile_1)[name = string("reshape_8")];
            fp16 mul_19_y_0 = const()[name = string("mul_19_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 8, 44]> mul_19 = mul(x = add_0, y = mul_19_y_0)[name = string("mul_19")];
            bool matmul_0_transpose_y_0 = const()[name = string("matmul_0_transpose_y_0"), val = bool(true)];
            bool matmul_0_transpose_x_0 = const()[name = string("matmul_0_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 8, 8]> matmul_0 = matmul(transpose_x = matmul_0_transpose_x_0, transpose_y = matmul_0_transpose_y_0, x = mul_19, y = reshape_6)[name = string("matmul_0")];
            tensor<fp16, [8, 8, 8]> add_2 = add(x = matmul_0, y = reshape_1)[name = string("add_2")];
            int32 softmax_0_axis_0 = const()[name = string("softmax_0_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 8, 8]> softmax_0 = softmax(axis = softmax_0_axis_0, x = add_2)[name = string("softmax_0")];
            bool matmul_1_transpose_x_0 = const()[name = string("matmul_1_transpose_x_0"), val = bool(false)];
            bool matmul_1_transpose_y_0 = const()[name = string("matmul_1_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 8, 44]> matmul_1 = matmul(transpose_x = matmul_1_transpose_x_0, transpose_y = matmul_1_transpose_y_0, x = softmax_0, y = reshape_8)[name = string("matmul_1")];
            tensor<int32, [3]> transpose_3_perm_0 = const()[name = string("transpose_3_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_9_shape_0 = const()[name = string("reshape_9_shape_0"), val = tensor<int32, [2]>([8, 352])];
            tensor<fp16, [8, 8, 44]> transpose_3 = transpose(perm = transpose_3_perm_0, x = matmul_1)[name = string("transpose_60")];
            tensor<fp16, [8, 352]> reshape_9 = reshape(shape = reshape_9_shape_0, x = transpose_3)[name = string("reshape_9")];
            tensor<fp16, [352, 352]> linear_3_weight_0 = const()[name = string("linear_3_weight_0"), val = tensor<fp16, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(376640)))];
            tensor<fp16, [8, 352]> linear_3 = linear(bias = linear_0_bias_0, weight = linear_3_weight_0, x = reshape_9)[name = string("linear_3")];
            tensor<fp16, [8, 352]> add_3 = add(x = mul_2, y = linear_3)[name = string("add_3")];
            tensor<fp16, [8, 352]> mul_20 = mul(x = add_3, y = add_3)[name = string("mul_20")];
            tensor<int32, [1]> reduce_mean_4_axes_0 = const()[name = string("reduce_mean_4_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_4_keep_dims_0 = const()[name = string("reduce_mean_4_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_4 = reduce_mean(axes = reduce_mean_4_axes_0, keep_dims = reduce_mean_4_keep_dims_0, x = mul_20)[name = string("reduce_mean_4")];
            fp32 rsqrt_4_epsilon_0 = const()[name = string("rsqrt_4_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_4 = rsqrt(epsilon = rsqrt_4_epsilon_0, x = reduce_mean_4)[name = string("rsqrt_4")];
            tensor<fp16, [8, 352]> mul_21 = mul(x = add_3, y = rsqrt_4)[name = string("mul_21")];
            tensor<fp16, [352]> mul_22_y_0 = const()[name = string("mul_22_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(624512)))];
            tensor<fp16, [8, 352]> mul_22 = mul(x = mul_21, y = mul_22_y_0)[name = string("mul_22")];
            tensor<fp16, [960, 352]> linear_4_weight_0 = const()[name = string("linear_4_weight_0"), val = tensor<fp16, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(625280)))];
            tensor<fp16, [960]> linear_4_bias_0 = const()[name = string("linear_4_bias_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1301184)))];
            tensor<fp16, [8, 960]> linear_4 = linear(bias = linear_4_bias_0, weight = linear_4_weight_0, x = mul_22)[name = string("linear_4")];
            tensor<fp16, [960, 352]> linear_5_weight_0 = const()[name = string("linear_5_weight_0"), val = tensor<fp16, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1303168)))];
            tensor<fp16, [8, 960]> linear_5 = linear(bias = linear_4_bias_0, weight = linear_5_weight_0, x = mul_22)[name = string("linear_5")];
            fp16 mul_23_y_0 = const()[name = string("mul_23_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [8, 960]> mul_23 = mul(x = linear_4, y = mul_23_y_0)[name = string("mul_23")];
            tensor<fp16, [8, 960]> tanh_0 = tanh(x = mul_23)[name = string("tanh_0")];
            fp16 mul_24_x_0 = const()[name = string("mul_24_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [8, 960]> mul_24 = mul(x = mul_24_x_0, y = tanh_0)[name = string("mul_24")];
            fp16 add_4_x_0 = const()[name = string("add_4_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [8, 960]> add_4 = add(x = add_4_x_0, y = mul_24)[name = string("add_4")];
            tensor<fp16, [8, 960]> mul_25 = mul(x = linear_4, y = add_4)[name = string("mul_25")];
            tensor<fp16, [8, 960]> mul_26 = mul(x = mul_25, y = linear_5)[name = string("mul_26")];
            tensor<fp16, [352, 960]> linear_6_weight_0 = const()[name = string("linear_6_weight_0"), val = tensor<fp16, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1979072)))];
            tensor<fp16, [8, 352]> linear_6 = linear(bias = linear_0_bias_0, weight = linear_6_weight_0, x = mul_26)[name = string("linear_6")];
            tensor<fp16, [8, 352]> add_5 = add(x = add_3, y = linear_6)[name = string("add_5")];
            tensor<fp16, [8, 352]> mul_27 = mul(x = add_5, y = add_5)[name = string("mul_27")];
            tensor<int32, [1]> reduce_mean_5_axes_0 = const()[name = string("reduce_mean_5_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_5_keep_dims_0 = const()[name = string("reduce_mean_5_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_5 = reduce_mean(axes = reduce_mean_5_axes_0, keep_dims = reduce_mean_5_keep_dims_0, x = mul_27)[name = string("reduce_mean_5")];
            fp32 rsqrt_5_epsilon_0 = const()[name = string("rsqrt_5_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_5 = rsqrt(epsilon = rsqrt_5_epsilon_0, x = reduce_mean_5)[name = string("rsqrt_5")];
            tensor<fp16, [8, 352]> mul_28 = mul(x = add_5, y = rsqrt_5)[name = string("mul_28")];
            tensor<fp16, [352]> mul_29_y_0 = const()[name = string("mul_29_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2654976)))];
            tensor<fp16, [8, 352]> mul_29 = mul(x = mul_28, y = mul_29_y_0)[name = string("mul_29")];
            tensor<fp16, [8, 352]> mul_30 = mul(x = mul_29, y = mul_29)[name = string("mul_30")];
            tensor<int32, [1]> reduce_mean_6_axes_0 = const()[name = string("reduce_mean_6_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_6_keep_dims_0 = const()[name = string("reduce_mean_6_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_6 = reduce_mean(axes = reduce_mean_6_axes_0, keep_dims = reduce_mean_6_keep_dims_0, x = mul_30)[name = string("reduce_mean_6")];
            fp32 rsqrt_6_epsilon_0 = const()[name = string("rsqrt_6_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_6 = rsqrt(epsilon = rsqrt_6_epsilon_0, x = reduce_mean_6)[name = string("rsqrt_6")];
            tensor<fp16, [8, 352]> mul_31 = mul(x = mul_29, y = rsqrt_6)[name = string("mul_31")];
            tensor<fp16, [352]> mul_32_y_0 = const()[name = string("mul_32_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2655744)))];
            tensor<fp16, [8, 352]> mul_32 = mul(x = mul_31, y = mul_32_y_0)[name = string("mul_32")];
            tensor<fp16, [352, 352]> tern_1_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2656512))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_1_q_weight_0_palettized")];
            tensor<fp16, [8, 352]> tern_1_q = linear(bias = linear_0_bias_0, weight = tern_1_q_weight_0_palettized, x = mul_32)[name = string("tern_1_q")];
            tensor<fp16, [352]> mul_33_y_0 = const()[name = string("mul_33_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2687552)))];
            tensor<fp16, [8, 352]> mul_33 = mul(x = tern_1_q, y = mul_33_y_0)[name = string("mul_33")];
            tensor<int32, [3]> reshape_10_shape_0 = const()[name = string("reshape_10_shape_0"), val = tensor<int32, [3]>([8, 8, 44])];
            tensor<fp16, [8, 8, 44]> reshape_10 = reshape(shape = reshape_10_shape_0, x = mul_33)[name = string("reshape_10")];
            tensor<int32, [3]> transpose_4_perm_0 = const()[name = string("transpose_4_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_36_y_0 = const()[name = string("mul_36_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2688320)))];
            tensor<fp16, [8, 352]> mul_36 = mul(x = mul_31, y = mul_36_y_0)[name = string("mul_36")];
            tensor<fp16, [88, 352]> tern_1_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2689088))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_1_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_1_k_bias_0 = const()[name = string("tern_1_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [8, 88]> tern_1_k = linear(bias = tern_1_k_bias_0, weight = tern_1_k_weight_0_palettized, x = mul_36)[name = string("tern_1_k")];
            tensor<fp16, [88]> mul_37_y_0 = const()[name = string("mul_37_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2696896)))];
            tensor<fp16, [8, 88]> mul_37 = mul(x = tern_1_k, y = mul_37_y_0)[name = string("mul_37")];
            tensor<int32, [3]> reshape_11_shape_0 = const()[name = string("reshape_11_shape_0"), val = tensor<int32, [3]>([8, 2, 44])];
            tensor<fp16, [8, 2, 44]> reshape_11 = reshape(shape = reshape_11_shape_0, x = mul_37)[name = string("reshape_11")];
            tensor<int32, [3]> transpose_5_perm_0 = const()[name = string("transpose_5_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_40_y_0 = const()[name = string("mul_40_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2697152)))];
            tensor<fp16, [8, 352]> mul_40 = mul(x = mul_31, y = mul_40_y_0)[name = string("mul_40")];
            tensor<fp16, [88, 352]> tern_1_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2697920))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_1_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_1_v_bias_0 = const()[name = string("tern_1_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [8, 88]> tern_1_v = linear(bias = tern_1_v_bias_0, weight = tern_1_v_weight_0_palettized, x = mul_40)[name = string("tern_1_v")];
            tensor<fp16, [88]> mul_41_y_0 = const()[name = string("mul_41_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2705728)))];
            tensor<fp16, [8, 88]> mul_41 = mul(x = tern_1_v, y = mul_41_y_0)[name = string("mul_41")];
            tensor<int32, [3]> reshape_12_shape_0 = const()[name = string("reshape_12_shape_0"), val = tensor<int32, [3]>([8, 2, 44])];
            tensor<fp16, [8, 2, 44]> reshape_12 = reshape(shape = reshape_12_shape_0, x = mul_41)[name = string("reshape_12")];
            tensor<int32, [3]> transpose_6_perm_0 = const()[name = string("transpose_6_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 8, 44]> transpose_4 = transpose(perm = transpose_4_perm_0, x = reshape_10)[name = string("transpose_59")];
            tensor<fp16, [8, 8, 44]> mul_42 = mul(x = transpose_4, y = transpose_4)[name = string("mul_42")];
            tensor<int32, [1]> reduce_mean_9_axes_0 = const()[name = string("reduce_mean_9_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_9_keep_dims_0 = const()[name = string("reduce_mean_9_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 8, 1]> reduce_mean_9 = reduce_mean(axes = reduce_mean_9_axes_0, keep_dims = reduce_mean_9_keep_dims_0, x = mul_42)[name = string("reduce_mean_9")];
            fp32 rsqrt_9_epsilon_0 = const()[name = string("rsqrt_9_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 8, 1]> rsqrt_9 = rsqrt(epsilon = rsqrt_9_epsilon_0, x = reduce_mean_9)[name = string("rsqrt_9")];
            tensor<fp16, [8, 8, 44]> mul_43 = mul(x = transpose_4, y = rsqrt_9)[name = string("mul_43")];
            tensor<fp16, [44]> mul_44_y_0 = const()[name = string("mul_44_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2705984)))];
            tensor<fp16, [8, 8, 44]> mul_44 = mul(x = mul_43, y = mul_44_y_0)[name = string("mul_44")];
            tensor<int32, [3]> slice_by_index_4_begin_0 = const()[name = string("slice_by_index_4_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_4_end_0 = const()[name = string("slice_by_index_4_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_4_end_mask_0 = const()[name = string("slice_by_index_4_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 8, 22]> slice_by_index_4 = slice_by_index(begin = slice_by_index_4_begin_0, end = slice_by_index_4_end_0, end_mask = slice_by_index_4_end_mask_0, x = mul_44)[name = string("slice_by_index_4")];
            tensor<int32, [3]> slice_by_index_5_begin_0 = const()[name = string("slice_by_index_5_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_5_end_0 = const()[name = string("slice_by_index_5_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_5_end_mask_0 = const()[name = string("slice_by_index_5_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 8, 22]> slice_by_index_5 = slice_by_index(begin = slice_by_index_5_begin_0, end = slice_by_index_5_end_0, end_mask = slice_by_index_5_end_mask_0, x = mul_44)[name = string("slice_by_index_5")];
            int32 concat_2_axis_0 = const()[name = string("concat_2_axis_0"), val = int32(-1)];
            bool concat_2_interleave_0 = const()[name = string("concat_2_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 8, 44]> concat_2 = concat(axis = concat_2_axis_0, interleave = concat_2_interleave_0, values = (slice_by_index_5, slice_by_index_4))[name = string("concat_2")];
            tensor<fp16, [44]> mul_45_y_0 = const()[name = string("mul_45_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 8, 44]> mul_45 = mul(x = concat_2, y = mul_45_y_0)[name = string("mul_45")];
            tensor<fp16, [8, 8, 44]> mul_46 = mul(x = mul_44, y = mul_11_y_0)[name = string("mul_46")];
            tensor<fp16, [8, 8, 44]> mul_47 = mul(x = mul_45, y = mul_12_y_0)[name = string("mul_47")];
            tensor<fp16, [8, 8, 44]> add_6 = add(x = mul_46, y = mul_47)[name = string("add_6")];
            tensor<fp16, [2, 8, 44]> transpose_5 = transpose(perm = transpose_5_perm_0, x = reshape_11)[name = string("transpose_58")];
            tensor<fp16, [2, 8, 44]> mul_48 = mul(x = transpose_5, y = transpose_5)[name = string("mul_48")];
            tensor<int32, [1]> reduce_mean_10_axes_0 = const()[name = string("reduce_mean_10_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_10_keep_dims_0 = const()[name = string("reduce_mean_10_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 8, 1]> reduce_mean_10 = reduce_mean(axes = reduce_mean_10_axes_0, keep_dims = reduce_mean_10_keep_dims_0, x = mul_48)[name = string("reduce_mean_10")];
            fp32 rsqrt_10_epsilon_0 = const()[name = string("rsqrt_10_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 8, 1]> rsqrt_10 = rsqrt(epsilon = rsqrt_10_epsilon_0, x = reduce_mean_10)[name = string("rsqrt_10")];
            tensor<fp16, [2, 8, 44]> mul_49 = mul(x = transpose_5, y = rsqrt_10)[name = string("mul_49")];
            tensor<fp16, [44]> mul_50_y_0 = const()[name = string("mul_50_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2706176)))];
            tensor<fp16, [2, 8, 44]> mul_50 = mul(x = mul_49, y = mul_50_y_0)[name = string("mul_50")];
            tensor<int32, [3]> slice_by_index_6_begin_0 = const()[name = string("slice_by_index_6_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_6_end_0 = const()[name = string("slice_by_index_6_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_6_end_mask_0 = const()[name = string("slice_by_index_6_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 8, 22]> slice_by_index_6 = slice_by_index(begin = slice_by_index_6_begin_0, end = slice_by_index_6_end_0, end_mask = slice_by_index_6_end_mask_0, x = mul_50)[name = string("slice_by_index_6")];
            tensor<int32, [3]> slice_by_index_7_begin_0 = const()[name = string("slice_by_index_7_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_7_end_0 = const()[name = string("slice_by_index_7_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_7_end_mask_0 = const()[name = string("slice_by_index_7_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 8, 22]> slice_by_index_7 = slice_by_index(begin = slice_by_index_7_begin_0, end = slice_by_index_7_end_0, end_mask = slice_by_index_7_end_mask_0, x = mul_50)[name = string("slice_by_index_7")];
            int32 concat_3_axis_0 = const()[name = string("concat_3_axis_0"), val = int32(-1)];
            bool concat_3_interleave_0 = const()[name = string("concat_3_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 8, 44]> concat_3 = concat(axis = concat_3_axis_0, interleave = concat_3_interleave_0, values = (slice_by_index_7, slice_by_index_6))[name = string("concat_3")];
            tensor<fp16, [44]> mul_51_y_0 = const()[name = string("mul_51_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 8, 44]> mul_51 = mul(x = concat_3, y = mul_51_y_0)[name = string("mul_51")];
            tensor<fp16, [2, 8, 44]> mul_52 = mul(x = mul_50, y = mul_11_y_0)[name = string("mul_52")];
            tensor<fp16, [2, 8, 44]> mul_53 = mul(x = mul_51, y = mul_12_y_0)[name = string("mul_53")];
            tensor<fp16, [2, 8, 44]> add_7 = add(x = mul_52, y = mul_53)[name = string("add_7")];
            tensor<int32, [4]> reshape_13_shape_0 = const()[name = string("reshape_13_shape_0"), val = tensor<int32, [4]>([2, 1, 8, 44])];
            tensor<fp16, [2, 1, 8, 44]> reshape_13 = reshape(shape = reshape_13_shape_0, x = add_7)[name = string("reshape_13")];
            tensor<int32, [4]> tile_2_reps_0 = const()[name = string("tile_2_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 8, 44]> tile_2 = tile(reps = tile_2_reps_0, x = reshape_13)[name = string("tile_2")];
            tensor<int32, [3]> reshape_14_shape_0 = const()[name = string("reshape_14_shape_0"), val = tensor<int32, [3]>([8, 8, 44])];
            tensor<fp16, [8, 8, 44]> reshape_14 = reshape(shape = reshape_14_shape_0, x = tile_2)[name = string("reshape_14")];
            tensor<int32, [4]> reshape_15_shape_0 = const()[name = string("reshape_15_shape_0"), val = tensor<int32, [4]>([2, 1, 8, 44])];
            tensor<fp16, [2, 8, 44]> transpose_6 = transpose(perm = transpose_6_perm_0, x = reshape_12)[name = string("transpose_57")];
            tensor<fp16, [2, 1, 8, 44]> reshape_15 = reshape(shape = reshape_15_shape_0, x = transpose_6)[name = string("reshape_15")];
            tensor<int32, [4]> tile_3_reps_0 = const()[name = string("tile_3_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 8, 44]> tile_3 = tile(reps = tile_3_reps_0, x = reshape_15)[name = string("tile_3")];
            tensor<int32, [3]> reshape_16_shape_0 = const()[name = string("reshape_16_shape_0"), val = tensor<int32, [3]>([8, 8, 44])];
            tensor<fp16, [8, 8, 44]> reshape_16 = reshape(shape = reshape_16_shape_0, x = tile_3)[name = string("reshape_16")];
            fp16 mul_54_y_0 = const()[name = string("mul_54_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 8, 44]> mul_54 = mul(x = add_6, y = mul_54_y_0)[name = string("mul_54")];
            bool matmul_2_transpose_y_0 = const()[name = string("matmul_2_transpose_y_0"), val = bool(true)];
            bool matmul_2_transpose_x_0 = const()[name = string("matmul_2_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 8, 8]> matmul_2 = matmul(transpose_x = matmul_2_transpose_x_0, transpose_y = matmul_2_transpose_y_0, x = mul_54, y = reshape_14)[name = string("matmul_2")];
            tensor<fp16, [8, 8, 8]> add_8 = add(x = matmul_2, y = reshape_1)[name = string("add_8")];
            int32 softmax_1_axis_0 = const()[name = string("softmax_1_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 8, 8]> softmax_1 = softmax(axis = softmax_1_axis_0, x = add_8)[name = string("softmax_1")];
            bool matmul_3_transpose_x_0 = const()[name = string("matmul_3_transpose_x_0"), val = bool(false)];
            bool matmul_3_transpose_y_0 = const()[name = string("matmul_3_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 8, 44]> matmul_3 = matmul(transpose_x = matmul_3_transpose_x_0, transpose_y = matmul_3_transpose_y_0, x = softmax_1, y = reshape_16)[name = string("matmul_3")];
            tensor<int32, [3]> transpose_7_perm_0 = const()[name = string("transpose_7_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_17_shape_0 = const()[name = string("reshape_17_shape_0"), val = tensor<int32, [2]>([8, 352])];
            tensor<fp16, [8, 8, 44]> transpose_7 = transpose(perm = transpose_7_perm_0, x = matmul_3)[name = string("transpose_56")];
            tensor<fp16, [8, 352]> reshape_17 = reshape(shape = reshape_17_shape_0, x = transpose_7)[name = string("reshape_17")];
            tensor<fp16, [8, 352]> mul_55 = mul(x = reshape_17, y = reshape_17)[name = string("mul_55")];
            tensor<int32, [1]> reduce_mean_11_axes_0 = const()[name = string("reduce_mean_11_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_11_keep_dims_0 = const()[name = string("reduce_mean_11_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_11 = reduce_mean(axes = reduce_mean_11_axes_0, keep_dims = reduce_mean_11_keep_dims_0, x = mul_55)[name = string("reduce_mean_11")];
            fp32 rsqrt_11_epsilon_0 = const()[name = string("rsqrt_11_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_11 = rsqrt(epsilon = rsqrt_11_epsilon_0, x = reduce_mean_11)[name = string("rsqrt_11")];
            tensor<fp16, [8, 352]> mul_56 = mul(x = reshape_17, y = rsqrt_11)[name = string("mul_56")];
            tensor<fp16, [352]> mul_57_y_0 = const()[name = string("mul_57_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2706368)))];
            tensor<fp16, [8, 352]> mul_57 = mul(x = mul_56, y = mul_57_y_0)[name = string("mul_57")];
            tensor<fp16, [352, 352]> tern_1_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2707136))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_1_o_weight_0_palettized")];
            tensor<fp16, [8, 352]> tern_1_o = linear(bias = linear_0_bias_0, weight = tern_1_o_weight_0_palettized, x = mul_57)[name = string("tern_1_o")];
            tensor<fp16, [352]> mul_58_y_0 = const()[name = string("mul_58_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2738176)))];
            tensor<fp16, [8, 352]> mul_58 = mul(x = tern_1_o, y = mul_58_y_0)[name = string("mul_58")];
            tensor<fp16, [8, 352]> add_9 = add(x = add_5, y = mul_58)[name = string("add_9")];
            tensor<fp16, [8, 352]> mul_59 = mul(x = add_9, y = add_9)[name = string("mul_59")];
            tensor<int32, [1]> reduce_mean_12_axes_0 = const()[name = string("reduce_mean_12_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_12_keep_dims_0 = const()[name = string("reduce_mean_12_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_12 = reduce_mean(axes = reduce_mean_12_axes_0, keep_dims = reduce_mean_12_keep_dims_0, x = mul_59)[name = string("reduce_mean_12")];
            fp32 rsqrt_12_epsilon_0 = const()[name = string("rsqrt_12_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_12 = rsqrt(epsilon = rsqrt_12_epsilon_0, x = reduce_mean_12)[name = string("rsqrt_12")];
            tensor<fp16, [8, 352]> mul_60 = mul(x = add_9, y = rsqrt_12)[name = string("mul_60")];
            tensor<fp16, [352]> mul_61_y_0 = const()[name = string("mul_61_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2738944)))];
            tensor<fp16, [8, 352]> mul_61 = mul(x = mul_60, y = mul_61_y_0)[name = string("mul_61")];
            tensor<fp16, [8, 352]> mul_62 = mul(x = mul_61, y = mul_61)[name = string("mul_62")];
            tensor<int32, [1]> reduce_mean_13_axes_0 = const()[name = string("reduce_mean_13_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_13_keep_dims_0 = const()[name = string("reduce_mean_13_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_13 = reduce_mean(axes = reduce_mean_13_axes_0, keep_dims = reduce_mean_13_keep_dims_0, x = mul_62)[name = string("reduce_mean_13")];
            fp32 rsqrt_13_epsilon_0 = const()[name = string("rsqrt_13_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_13 = rsqrt(epsilon = rsqrt_13_epsilon_0, x = reduce_mean_13)[name = string("rsqrt_13")];
            tensor<fp16, [8, 352]> mul_63 = mul(x = mul_61, y = rsqrt_13)[name = string("mul_63")];
            tensor<fp16, [352]> mul_64_y_0 = const()[name = string("mul_64_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2739712)))];
            tensor<fp16, [8, 352]> mul_64 = mul(x = mul_63, y = mul_64_y_0)[name = string("mul_64")];
            tensor<fp16, [960, 352]> tern_1_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2740480))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_1_w1_weight_0_palettized")];
            tensor<fp16, [8, 960]> tern_1_w1 = linear(bias = linear_4_bias_0, weight = tern_1_w1_weight_0_palettized, x = mul_64)[name = string("tern_1_w1")];
            tensor<fp16, [960]> mul_65_y_0 = const()[name = string("mul_65_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2825024)))];
            tensor<fp16, [8, 960]> mul_65 = mul(x = tern_1_w1, y = mul_65_y_0)[name = string("mul_65")];
            tensor<fp16, [352]> mul_68_y_0 = const()[name = string("mul_68_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2827008)))];
            tensor<fp16, [8, 352]> mul_68 = mul(x = mul_63, y = mul_68_y_0)[name = string("mul_68")];
            tensor<fp16, [960, 352]> tern_1_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2827776))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_1_w3_weight_0_palettized")];
            tensor<fp16, [8, 960]> tern_1_w3 = linear(bias = linear_4_bias_0, weight = tern_1_w3_weight_0_palettized, x = mul_68)[name = string("tern_1_w3")];
            tensor<fp16, [960]> mul_69_y_0 = const()[name = string("mul_69_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2912320)))];
            tensor<fp16, [8, 960]> mul_69 = mul(x = tern_1_w3, y = mul_69_y_0)[name = string("mul_69")];
            fp16 mul_70_y_0 = const()[name = string("mul_70_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [8, 960]> mul_70 = mul(x = mul_65, y = mul_70_y_0)[name = string("mul_70")];
            tensor<fp16, [8, 960]> tanh_1 = tanh(x = mul_70)[name = string("tanh_1")];
            fp16 mul_71_x_0 = const()[name = string("mul_71_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [8, 960]> mul_71 = mul(x = mul_71_x_0, y = tanh_1)[name = string("mul_71")];
            fp16 add_10_x_0 = const()[name = string("add_10_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [8, 960]> add_10 = add(x = add_10_x_0, y = mul_71)[name = string("add_10")];
            tensor<fp16, [8, 960]> mul_72 = mul(x = mul_65, y = add_10)[name = string("mul_72")];
            tensor<fp16, [8, 960]> mul_73 = mul(x = mul_72, y = mul_69)[name = string("mul_73")];
            tensor<fp16, [8, 960]> mul_74 = mul(x = mul_73, y = mul_73)[name = string("mul_74")];
            tensor<int32, [1]> reduce_mean_15_axes_0 = const()[name = string("reduce_mean_15_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_15_keep_dims_0 = const()[name = string("reduce_mean_15_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_15 = reduce_mean(axes = reduce_mean_15_axes_0, keep_dims = reduce_mean_15_keep_dims_0, x = mul_74)[name = string("reduce_mean_15")];
            fp32 rsqrt_15_epsilon_0 = const()[name = string("rsqrt_15_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_15 = rsqrt(epsilon = rsqrt_15_epsilon_0, x = reduce_mean_15)[name = string("rsqrt_15")];
            tensor<fp16, [8, 960]> mul_75 = mul(x = mul_73, y = rsqrt_15)[name = string("mul_75")];
            tensor<fp16, [960]> mul_76_y_0 = const()[name = string("mul_76_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2914304)))];
            tensor<fp16, [8, 960]> mul_76 = mul(x = mul_75, y = mul_76_y_0)[name = string("mul_76")];
            tensor<fp16, [352, 960]> tern_1_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(2916288))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_1_w2_weight_0_palettized")];
            tensor<fp16, [8, 352]> tern_1_w2 = linear(bias = linear_0_bias_0, weight = tern_1_w2_weight_0_palettized, x = mul_76)[name = string("tern_1_w2")];
            tensor<fp16, [352]> mul_77_y_0 = const()[name = string("mul_77_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3000832)))];
            tensor<fp16, [8, 352]> mul_77 = mul(x = tern_1_w2, y = mul_77_y_0)[name = string("mul_77")];
            tensor<fp16, [8, 352]> add_11 = add(x = add_9, y = mul_77)[name = string("add_11")];
            tensor<fp16, [8, 352]> mul_78 = mul(x = add_11, y = add_11)[name = string("mul_78")];
            tensor<int32, [1]> reduce_mean_16_axes_0 = const()[name = string("reduce_mean_16_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_16_keep_dims_0 = const()[name = string("reduce_mean_16_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_16 = reduce_mean(axes = reduce_mean_16_axes_0, keep_dims = reduce_mean_16_keep_dims_0, x = mul_78)[name = string("reduce_mean_16")];
            fp32 rsqrt_16_epsilon_0 = const()[name = string("rsqrt_16_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_16 = rsqrt(epsilon = rsqrt_16_epsilon_0, x = reduce_mean_16)[name = string("rsqrt_16")];
            tensor<fp16, [8, 352]> mul_79 = mul(x = add_11, y = rsqrt_16)[name = string("mul_79")];
            tensor<fp16, [352]> mul_80_y_0 = const()[name = string("mul_80_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3001600)))];
            tensor<fp16, [8, 352]> mul_80 = mul(x = mul_79, y = mul_80_y_0)[name = string("mul_80")];
            tensor<fp16, [8, 352]> mul_81 = mul(x = mul_80, y = mul_80)[name = string("mul_81")];
            tensor<int32, [1]> reduce_mean_17_axes_0 = const()[name = string("reduce_mean_17_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_17_keep_dims_0 = const()[name = string("reduce_mean_17_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_17 = reduce_mean(axes = reduce_mean_17_axes_0, keep_dims = reduce_mean_17_keep_dims_0, x = mul_81)[name = string("reduce_mean_17")];
            fp32 rsqrt_17_epsilon_0 = const()[name = string("rsqrt_17_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_17 = rsqrt(epsilon = rsqrt_17_epsilon_0, x = reduce_mean_17)[name = string("rsqrt_17")];
            tensor<fp16, [8, 352]> mul_82 = mul(x = mul_80, y = rsqrt_17)[name = string("mul_82")];
            tensor<fp16, [352]> mul_83_y_0 = const()[name = string("mul_83_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3002368)))];
            tensor<fp16, [8, 352]> mul_83 = mul(x = mul_82, y = mul_83_y_0)[name = string("mul_83")];
            tensor<fp16, [352, 352]> tern_2_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3003136))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_2_q_weight_0_palettized")];
            tensor<fp16, [8, 352]> tern_2_q = linear(bias = linear_0_bias_0, weight = tern_2_q_weight_0_palettized, x = mul_83)[name = string("tern_2_q")];
            tensor<fp16, [352]> mul_84_y_0 = const()[name = string("mul_84_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3034176)))];
            tensor<fp16, [8, 352]> mul_84 = mul(x = tern_2_q, y = mul_84_y_0)[name = string("mul_84")];
            tensor<int32, [3]> reshape_18_shape_0 = const()[name = string("reshape_18_shape_0"), val = tensor<int32, [3]>([8, 8, 44])];
            tensor<fp16, [8, 8, 44]> reshape_18 = reshape(shape = reshape_18_shape_0, x = mul_84)[name = string("reshape_18")];
            tensor<int32, [3]> transpose_8_perm_0 = const()[name = string("transpose_8_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_87_y_0 = const()[name = string("mul_87_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3034944)))];
            tensor<fp16, [8, 352]> mul_87 = mul(x = mul_82, y = mul_87_y_0)[name = string("mul_87")];
            tensor<fp16, [88, 352]> tern_2_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3035712))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_2_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_2_k_bias_0 = const()[name = string("tern_2_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [8, 88]> tern_2_k = linear(bias = tern_2_k_bias_0, weight = tern_2_k_weight_0_palettized, x = mul_87)[name = string("tern_2_k")];
            tensor<fp16, [88]> mul_88_y_0 = const()[name = string("mul_88_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3043520)))];
            tensor<fp16, [8, 88]> mul_88 = mul(x = tern_2_k, y = mul_88_y_0)[name = string("mul_88")];
            tensor<int32, [3]> reshape_19_shape_0 = const()[name = string("reshape_19_shape_0"), val = tensor<int32, [3]>([8, 2, 44])];
            tensor<fp16, [8, 2, 44]> reshape_19 = reshape(shape = reshape_19_shape_0, x = mul_88)[name = string("reshape_19")];
            tensor<int32, [3]> transpose_9_perm_0 = const()[name = string("transpose_9_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_91_y_0 = const()[name = string("mul_91_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3043776)))];
            tensor<fp16, [8, 352]> mul_91 = mul(x = mul_82, y = mul_91_y_0)[name = string("mul_91")];
            tensor<fp16, [88, 352]> tern_2_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3044544))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_2_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_2_v_bias_0 = const()[name = string("tern_2_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [8, 88]> tern_2_v = linear(bias = tern_2_v_bias_0, weight = tern_2_v_weight_0_palettized, x = mul_91)[name = string("tern_2_v")];
            tensor<fp16, [88]> mul_92_y_0 = const()[name = string("mul_92_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3052352)))];
            tensor<fp16, [8, 88]> mul_92 = mul(x = tern_2_v, y = mul_92_y_0)[name = string("mul_92")];
            tensor<int32, [3]> reshape_20_shape_0 = const()[name = string("reshape_20_shape_0"), val = tensor<int32, [3]>([8, 2, 44])];
            tensor<fp16, [8, 2, 44]> reshape_20 = reshape(shape = reshape_20_shape_0, x = mul_92)[name = string("reshape_20")];
            tensor<int32, [3]> transpose_10_perm_0 = const()[name = string("transpose_10_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 8, 44]> transpose_8 = transpose(perm = transpose_8_perm_0, x = reshape_18)[name = string("transpose_55")];
            tensor<fp16, [8, 8, 44]> mul_93 = mul(x = transpose_8, y = transpose_8)[name = string("mul_93")];
            tensor<int32, [1]> reduce_mean_20_axes_0 = const()[name = string("reduce_mean_20_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_20_keep_dims_0 = const()[name = string("reduce_mean_20_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 8, 1]> reduce_mean_20 = reduce_mean(axes = reduce_mean_20_axes_0, keep_dims = reduce_mean_20_keep_dims_0, x = mul_93)[name = string("reduce_mean_20")];
            fp32 rsqrt_20_epsilon_0 = const()[name = string("rsqrt_20_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 8, 1]> rsqrt_20 = rsqrt(epsilon = rsqrt_20_epsilon_0, x = reduce_mean_20)[name = string("rsqrt_20")];
            tensor<fp16, [8, 8, 44]> mul_94 = mul(x = transpose_8, y = rsqrt_20)[name = string("mul_94")];
            tensor<fp16, [44]> mul_95_y_0 = const()[name = string("mul_95_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3052608)))];
            tensor<fp16, [8, 8, 44]> mul_95 = mul(x = mul_94, y = mul_95_y_0)[name = string("mul_95")];
            tensor<int32, [3]> slice_by_index_8_begin_0 = const()[name = string("slice_by_index_8_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_8_end_0 = const()[name = string("slice_by_index_8_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_8_end_mask_0 = const()[name = string("slice_by_index_8_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 8, 22]> slice_by_index_8 = slice_by_index(begin = slice_by_index_8_begin_0, end = slice_by_index_8_end_0, end_mask = slice_by_index_8_end_mask_0, x = mul_95)[name = string("slice_by_index_8")];
            tensor<int32, [3]> slice_by_index_9_begin_0 = const()[name = string("slice_by_index_9_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_9_end_0 = const()[name = string("slice_by_index_9_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_9_end_mask_0 = const()[name = string("slice_by_index_9_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 8, 22]> slice_by_index_9 = slice_by_index(begin = slice_by_index_9_begin_0, end = slice_by_index_9_end_0, end_mask = slice_by_index_9_end_mask_0, x = mul_95)[name = string("slice_by_index_9")];
            int32 concat_4_axis_0 = const()[name = string("concat_4_axis_0"), val = int32(-1)];
            bool concat_4_interleave_0 = const()[name = string("concat_4_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 8, 44]> concat_4 = concat(axis = concat_4_axis_0, interleave = concat_4_interleave_0, values = (slice_by_index_9, slice_by_index_8))[name = string("concat_4")];
            tensor<fp16, [44]> mul_96_y_0 = const()[name = string("mul_96_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 8, 44]> mul_96 = mul(x = concat_4, y = mul_96_y_0)[name = string("mul_96")];
            tensor<fp16, [8, 8, 44]> mul_97 = mul(x = mul_95, y = mul_11_y_0)[name = string("mul_97")];
            tensor<fp16, [8, 8, 44]> mul_98 = mul(x = mul_96, y = mul_12_y_0)[name = string("mul_98")];
            tensor<fp16, [8, 8, 44]> add_12 = add(x = mul_97, y = mul_98)[name = string("add_12")];
            tensor<fp16, [2, 8, 44]> transpose_9 = transpose(perm = transpose_9_perm_0, x = reshape_19)[name = string("transpose_54")];
            tensor<fp16, [2, 8, 44]> mul_99 = mul(x = transpose_9, y = transpose_9)[name = string("mul_99")];
            tensor<int32, [1]> reduce_mean_21_axes_0 = const()[name = string("reduce_mean_21_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_21_keep_dims_0 = const()[name = string("reduce_mean_21_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 8, 1]> reduce_mean_21 = reduce_mean(axes = reduce_mean_21_axes_0, keep_dims = reduce_mean_21_keep_dims_0, x = mul_99)[name = string("reduce_mean_21")];
            fp32 rsqrt_21_epsilon_0 = const()[name = string("rsqrt_21_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 8, 1]> rsqrt_21 = rsqrt(epsilon = rsqrt_21_epsilon_0, x = reduce_mean_21)[name = string("rsqrt_21")];
            tensor<fp16, [2, 8, 44]> mul_100 = mul(x = transpose_9, y = rsqrt_21)[name = string("mul_100")];
            tensor<fp16, [44]> mul_101_y_0 = const()[name = string("mul_101_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3052800)))];
            tensor<fp16, [2, 8, 44]> mul_101 = mul(x = mul_100, y = mul_101_y_0)[name = string("mul_101")];
            tensor<int32, [3]> slice_by_index_10_begin_0 = const()[name = string("slice_by_index_10_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_10_end_0 = const()[name = string("slice_by_index_10_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_10_end_mask_0 = const()[name = string("slice_by_index_10_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 8, 22]> slice_by_index_10 = slice_by_index(begin = slice_by_index_10_begin_0, end = slice_by_index_10_end_0, end_mask = slice_by_index_10_end_mask_0, x = mul_101)[name = string("slice_by_index_10")];
            tensor<int32, [3]> slice_by_index_11_begin_0 = const()[name = string("slice_by_index_11_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_11_end_0 = const()[name = string("slice_by_index_11_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_11_end_mask_0 = const()[name = string("slice_by_index_11_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 8, 22]> slice_by_index_11 = slice_by_index(begin = slice_by_index_11_begin_0, end = slice_by_index_11_end_0, end_mask = slice_by_index_11_end_mask_0, x = mul_101)[name = string("slice_by_index_11")];
            int32 concat_5_axis_0 = const()[name = string("concat_5_axis_0"), val = int32(-1)];
            bool concat_5_interleave_0 = const()[name = string("concat_5_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 8, 44]> concat_5 = concat(axis = concat_5_axis_0, interleave = concat_5_interleave_0, values = (slice_by_index_11, slice_by_index_10))[name = string("concat_5")];
            tensor<fp16, [44]> mul_102_y_0 = const()[name = string("mul_102_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 8, 44]> mul_102 = mul(x = concat_5, y = mul_102_y_0)[name = string("mul_102")];
            tensor<fp16, [2, 8, 44]> mul_103 = mul(x = mul_101, y = mul_11_y_0)[name = string("mul_103")];
            tensor<fp16, [2, 8, 44]> mul_104 = mul(x = mul_102, y = mul_12_y_0)[name = string("mul_104")];
            tensor<fp16, [2, 8, 44]> add_13 = add(x = mul_103, y = mul_104)[name = string("add_13")];
            tensor<int32, [4]> reshape_21_shape_0 = const()[name = string("reshape_21_shape_0"), val = tensor<int32, [4]>([2, 1, 8, 44])];
            tensor<fp16, [2, 1, 8, 44]> reshape_21 = reshape(shape = reshape_21_shape_0, x = add_13)[name = string("reshape_21")];
            tensor<int32, [4]> tile_4_reps_0 = const()[name = string("tile_4_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 8, 44]> tile_4 = tile(reps = tile_4_reps_0, x = reshape_21)[name = string("tile_4")];
            tensor<int32, [3]> reshape_22_shape_0 = const()[name = string("reshape_22_shape_0"), val = tensor<int32, [3]>([8, 8, 44])];
            tensor<fp16, [8, 8, 44]> reshape_22 = reshape(shape = reshape_22_shape_0, x = tile_4)[name = string("reshape_22")];
            tensor<int32, [4]> reshape_23_shape_0 = const()[name = string("reshape_23_shape_0"), val = tensor<int32, [4]>([2, 1, 8, 44])];
            tensor<fp16, [2, 8, 44]> transpose_10 = transpose(perm = transpose_10_perm_0, x = reshape_20)[name = string("transpose_53")];
            tensor<fp16, [2, 1, 8, 44]> reshape_23 = reshape(shape = reshape_23_shape_0, x = transpose_10)[name = string("reshape_23")];
            tensor<int32, [4]> tile_5_reps_0 = const()[name = string("tile_5_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 8, 44]> tile_5 = tile(reps = tile_5_reps_0, x = reshape_23)[name = string("tile_5")];
            tensor<int32, [3]> reshape_24_shape_0 = const()[name = string("reshape_24_shape_0"), val = tensor<int32, [3]>([8, 8, 44])];
            tensor<fp16, [8, 8, 44]> reshape_24 = reshape(shape = reshape_24_shape_0, x = tile_5)[name = string("reshape_24")];
            fp16 mul_105_y_0 = const()[name = string("mul_105_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 8, 44]> mul_105 = mul(x = add_12, y = mul_105_y_0)[name = string("mul_105")];
            bool matmul_4_transpose_y_0 = const()[name = string("matmul_4_transpose_y_0"), val = bool(true)];
            bool matmul_4_transpose_x_0 = const()[name = string("matmul_4_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 8, 8]> matmul_4 = matmul(transpose_x = matmul_4_transpose_x_0, transpose_y = matmul_4_transpose_y_0, x = mul_105, y = reshape_22)[name = string("matmul_4")];
            tensor<fp16, [8, 8, 8]> add_14 = add(x = matmul_4, y = reshape_1)[name = string("add_14")];
            int32 softmax_2_axis_0 = const()[name = string("softmax_2_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 8, 8]> softmax_2 = softmax(axis = softmax_2_axis_0, x = add_14)[name = string("softmax_2")];
            bool matmul_5_transpose_x_0 = const()[name = string("matmul_5_transpose_x_0"), val = bool(false)];
            bool matmul_5_transpose_y_0 = const()[name = string("matmul_5_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 8, 44]> matmul_5 = matmul(transpose_x = matmul_5_transpose_x_0, transpose_y = matmul_5_transpose_y_0, x = softmax_2, y = reshape_24)[name = string("matmul_5")];
            tensor<int32, [3]> transpose_11_perm_0 = const()[name = string("transpose_11_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_25_shape_0 = const()[name = string("reshape_25_shape_0"), val = tensor<int32, [2]>([8, 352])];
            tensor<fp16, [8, 8, 44]> transpose_11 = transpose(perm = transpose_11_perm_0, x = matmul_5)[name = string("transpose_52")];
            tensor<fp16, [8, 352]> reshape_25 = reshape(shape = reshape_25_shape_0, x = transpose_11)[name = string("reshape_25")];
            tensor<fp16, [8, 352]> mul_106 = mul(x = reshape_25, y = reshape_25)[name = string("mul_106")];
            tensor<int32, [1]> reduce_mean_22_axes_0 = const()[name = string("reduce_mean_22_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_22_keep_dims_0 = const()[name = string("reduce_mean_22_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_22 = reduce_mean(axes = reduce_mean_22_axes_0, keep_dims = reduce_mean_22_keep_dims_0, x = mul_106)[name = string("reduce_mean_22")];
            fp32 rsqrt_22_epsilon_0 = const()[name = string("rsqrt_22_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_22 = rsqrt(epsilon = rsqrt_22_epsilon_0, x = reduce_mean_22)[name = string("rsqrt_22")];
            tensor<fp16, [8, 352]> mul_107 = mul(x = reshape_25, y = rsqrt_22)[name = string("mul_107")];
            tensor<fp16, [352]> mul_108_y_0 = const()[name = string("mul_108_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3052992)))];
            tensor<fp16, [8, 352]> mul_108 = mul(x = mul_107, y = mul_108_y_0)[name = string("mul_108")];
            tensor<fp16, [352, 352]> tern_2_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3053760))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_2_o_weight_0_palettized")];
            tensor<fp16, [8, 352]> tern_2_o = linear(bias = linear_0_bias_0, weight = tern_2_o_weight_0_palettized, x = mul_108)[name = string("tern_2_o")];
            tensor<fp16, [352]> mul_109_y_0 = const()[name = string("mul_109_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3084800)))];
            tensor<fp16, [8, 352]> mul_109 = mul(x = tern_2_o, y = mul_109_y_0)[name = string("mul_109")];
            tensor<fp16, [8, 352]> add_15 = add(x = add_11, y = mul_109)[name = string("add_15")];
            tensor<fp16, [8, 352]> mul_110 = mul(x = add_15, y = add_15)[name = string("mul_110")];
            tensor<int32, [1]> reduce_mean_23_axes_0 = const()[name = string("reduce_mean_23_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_23_keep_dims_0 = const()[name = string("reduce_mean_23_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_23 = reduce_mean(axes = reduce_mean_23_axes_0, keep_dims = reduce_mean_23_keep_dims_0, x = mul_110)[name = string("reduce_mean_23")];
            fp32 rsqrt_23_epsilon_0 = const()[name = string("rsqrt_23_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_23 = rsqrt(epsilon = rsqrt_23_epsilon_0, x = reduce_mean_23)[name = string("rsqrt_23")];
            tensor<fp16, [8, 352]> mul_111 = mul(x = add_15, y = rsqrt_23)[name = string("mul_111")];
            tensor<fp16, [352]> mul_112_y_0 = const()[name = string("mul_112_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3085568)))];
            tensor<fp16, [8, 352]> mul_112 = mul(x = mul_111, y = mul_112_y_0)[name = string("mul_112")];
            tensor<fp16, [8, 352]> mul_113 = mul(x = mul_112, y = mul_112)[name = string("mul_113")];
            tensor<int32, [1]> reduce_mean_24_axes_0 = const()[name = string("reduce_mean_24_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_24_keep_dims_0 = const()[name = string("reduce_mean_24_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_24 = reduce_mean(axes = reduce_mean_24_axes_0, keep_dims = reduce_mean_24_keep_dims_0, x = mul_113)[name = string("reduce_mean_24")];
            fp32 rsqrt_24_epsilon_0 = const()[name = string("rsqrt_24_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_24 = rsqrt(epsilon = rsqrt_24_epsilon_0, x = reduce_mean_24)[name = string("rsqrt_24")];
            tensor<fp16, [8, 352]> mul_114 = mul(x = mul_112, y = rsqrt_24)[name = string("mul_114")];
            tensor<fp16, [352]> mul_115_y_0 = const()[name = string("mul_115_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3086336)))];
            tensor<fp16, [8, 352]> mul_115 = mul(x = mul_114, y = mul_115_y_0)[name = string("mul_115")];
            tensor<fp16, [960, 352]> tern_2_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3087104))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_2_w1_weight_0_palettized")];
            tensor<fp16, [8, 960]> tern_2_w1 = linear(bias = linear_4_bias_0, weight = tern_2_w1_weight_0_palettized, x = mul_115)[name = string("tern_2_w1")];
            tensor<fp16, [960]> mul_116_y_0 = const()[name = string("mul_116_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3171648)))];
            tensor<fp16, [8, 960]> mul_116 = mul(x = tern_2_w1, y = mul_116_y_0)[name = string("mul_116")];
            tensor<fp16, [352]> mul_119_y_0 = const()[name = string("mul_119_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3173632)))];
            tensor<fp16, [8, 352]> mul_119 = mul(x = mul_114, y = mul_119_y_0)[name = string("mul_119")];
            tensor<fp16, [960, 352]> tern_2_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3174400))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_2_w3_weight_0_palettized")];
            tensor<fp16, [8, 960]> tern_2_w3 = linear(bias = linear_4_bias_0, weight = tern_2_w3_weight_0_palettized, x = mul_119)[name = string("tern_2_w3")];
            tensor<fp16, [960]> mul_120_y_0 = const()[name = string("mul_120_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3258944)))];
            tensor<fp16, [8, 960]> mul_120 = mul(x = tern_2_w3, y = mul_120_y_0)[name = string("mul_120")];
            fp16 mul_121_y_0 = const()[name = string("mul_121_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [8, 960]> mul_121 = mul(x = mul_116, y = mul_121_y_0)[name = string("mul_121")];
            tensor<fp16, [8, 960]> tanh_2 = tanh(x = mul_121)[name = string("tanh_2")];
            fp16 mul_122_x_0 = const()[name = string("mul_122_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [8, 960]> mul_122 = mul(x = mul_122_x_0, y = tanh_2)[name = string("mul_122")];
            fp16 add_16_x_0 = const()[name = string("add_16_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [8, 960]> add_16 = add(x = add_16_x_0, y = mul_122)[name = string("add_16")];
            tensor<fp16, [8, 960]> mul_123 = mul(x = mul_116, y = add_16)[name = string("mul_123")];
            tensor<fp16, [8, 960]> mul_124 = mul(x = mul_123, y = mul_120)[name = string("mul_124")];
            tensor<fp16, [8, 960]> mul_125 = mul(x = mul_124, y = mul_124)[name = string("mul_125")];
            tensor<int32, [1]> reduce_mean_26_axes_0 = const()[name = string("reduce_mean_26_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_26_keep_dims_0 = const()[name = string("reduce_mean_26_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_26 = reduce_mean(axes = reduce_mean_26_axes_0, keep_dims = reduce_mean_26_keep_dims_0, x = mul_125)[name = string("reduce_mean_26")];
            fp32 rsqrt_26_epsilon_0 = const()[name = string("rsqrt_26_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_26 = rsqrt(epsilon = rsqrt_26_epsilon_0, x = reduce_mean_26)[name = string("rsqrt_26")];
            tensor<fp16, [8, 960]> mul_126 = mul(x = mul_124, y = rsqrt_26)[name = string("mul_126")];
            tensor<fp16, [960]> mul_127_y_0 = const()[name = string("mul_127_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3260928)))];
            tensor<fp16, [8, 960]> mul_127 = mul(x = mul_126, y = mul_127_y_0)[name = string("mul_127")];
            tensor<fp16, [352, 960]> tern_2_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3262912))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_2_w2_weight_0_palettized")];
            tensor<fp16, [8, 352]> tern_2_w2 = linear(bias = linear_0_bias_0, weight = tern_2_w2_weight_0_palettized, x = mul_127)[name = string("tern_2_w2")];
            tensor<fp16, [352]> mul_128_y_0 = const()[name = string("mul_128_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3347456)))];
            tensor<fp16, [8, 352]> mul_128 = mul(x = tern_2_w2, y = mul_128_y_0)[name = string("mul_128")];
            tensor<fp16, [8, 352]> add_17 = add(x = add_15, y = mul_128)[name = string("add_17")];
            tensor<fp16, [8, 352]> mul_129 = mul(x = add_17, y = add_17)[name = string("mul_129")];
            tensor<int32, [1]> reduce_mean_27_axes_0 = const()[name = string("reduce_mean_27_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_27_keep_dims_0 = const()[name = string("reduce_mean_27_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_27 = reduce_mean(axes = reduce_mean_27_axes_0, keep_dims = reduce_mean_27_keep_dims_0, x = mul_129)[name = string("reduce_mean_27")];
            fp32 rsqrt_27_epsilon_0 = const()[name = string("rsqrt_27_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_27 = rsqrt(epsilon = rsqrt_27_epsilon_0, x = reduce_mean_27)[name = string("rsqrt_27")];
            tensor<fp16, [8, 352]> mul_130 = mul(x = add_17, y = rsqrt_27)[name = string("mul_130")];
            tensor<fp16, [352]> mul_131_y_0 = const()[name = string("mul_131_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3348224)))];
            tensor<fp16, [8, 352]> mul_131 = mul(x = mul_130, y = mul_131_y_0)[name = string("mul_131")];
            tensor<fp16, [8, 352]> mul_132 = mul(x = mul_131, y = mul_131)[name = string("mul_132")];
            tensor<int32, [1]> reduce_mean_28_axes_0 = const()[name = string("reduce_mean_28_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_28_keep_dims_0 = const()[name = string("reduce_mean_28_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_28 = reduce_mean(axes = reduce_mean_28_axes_0, keep_dims = reduce_mean_28_keep_dims_0, x = mul_132)[name = string("reduce_mean_28")];
            fp32 rsqrt_28_epsilon_0 = const()[name = string("rsqrt_28_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_28 = rsqrt(epsilon = rsqrt_28_epsilon_0, x = reduce_mean_28)[name = string("rsqrt_28")];
            tensor<fp16, [8, 352]> mul_133 = mul(x = mul_131, y = rsqrt_28)[name = string("mul_133")];
            tensor<fp16, [352]> mul_134_y_0 = const()[name = string("mul_134_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3348992)))];
            tensor<fp16, [8, 352]> mul_134 = mul(x = mul_133, y = mul_134_y_0)[name = string("mul_134")];
            tensor<fp16, [352, 352]> tern_3_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3349760))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_3_q_weight_0_palettized")];
            tensor<fp16, [8, 352]> tern_3_q = linear(bias = linear_0_bias_0, weight = tern_3_q_weight_0_palettized, x = mul_134)[name = string("tern_3_q")];
            tensor<fp16, [352]> mul_135_y_0 = const()[name = string("mul_135_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3380800)))];
            tensor<fp16, [8, 352]> mul_135 = mul(x = tern_3_q, y = mul_135_y_0)[name = string("mul_135")];
            tensor<int32, [3]> reshape_26_shape_0 = const()[name = string("reshape_26_shape_0"), val = tensor<int32, [3]>([8, 8, 44])];
            tensor<fp16, [8, 8, 44]> reshape_26 = reshape(shape = reshape_26_shape_0, x = mul_135)[name = string("reshape_26")];
            tensor<int32, [3]> transpose_12_perm_0 = const()[name = string("transpose_12_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_138_y_0 = const()[name = string("mul_138_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3381568)))];
            tensor<fp16, [8, 352]> mul_138 = mul(x = mul_133, y = mul_138_y_0)[name = string("mul_138")];
            tensor<fp16, [88, 352]> tern_3_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3382336))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_3_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_3_k_bias_0 = const()[name = string("tern_3_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [8, 88]> tern_3_k = linear(bias = tern_3_k_bias_0, weight = tern_3_k_weight_0_palettized, x = mul_138)[name = string("tern_3_k")];
            tensor<fp16, [88]> mul_139_y_0 = const()[name = string("mul_139_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3390144)))];
            tensor<fp16, [8, 88]> mul_139 = mul(x = tern_3_k, y = mul_139_y_0)[name = string("mul_139")];
            tensor<int32, [3]> reshape_27_shape_0 = const()[name = string("reshape_27_shape_0"), val = tensor<int32, [3]>([8, 2, 44])];
            tensor<fp16, [8, 2, 44]> reshape_27 = reshape(shape = reshape_27_shape_0, x = mul_139)[name = string("reshape_27")];
            tensor<int32, [3]> transpose_13_perm_0 = const()[name = string("transpose_13_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_142_y_0 = const()[name = string("mul_142_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3390400)))];
            tensor<fp16, [8, 352]> mul_142 = mul(x = mul_133, y = mul_142_y_0)[name = string("mul_142")];
            tensor<fp16, [88, 352]> tern_3_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3391168))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_3_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_3_v_bias_0 = const()[name = string("tern_3_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [8, 88]> tern_3_v = linear(bias = tern_3_v_bias_0, weight = tern_3_v_weight_0_palettized, x = mul_142)[name = string("tern_3_v")];
            tensor<fp16, [88]> mul_143_y_0 = const()[name = string("mul_143_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3398976)))];
            tensor<fp16, [8, 88]> mul_143 = mul(x = tern_3_v, y = mul_143_y_0)[name = string("mul_143")];
            tensor<int32, [3]> reshape_28_shape_0 = const()[name = string("reshape_28_shape_0"), val = tensor<int32, [3]>([8, 2, 44])];
            tensor<fp16, [8, 2, 44]> reshape_28 = reshape(shape = reshape_28_shape_0, x = mul_143)[name = string("reshape_28")];
            tensor<int32, [3]> transpose_14_perm_0 = const()[name = string("transpose_14_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 8, 44]> transpose_12 = transpose(perm = transpose_12_perm_0, x = reshape_26)[name = string("transpose_51")];
            tensor<fp16, [8, 8, 44]> mul_144 = mul(x = transpose_12, y = transpose_12)[name = string("mul_144")];
            tensor<int32, [1]> reduce_mean_31_axes_0 = const()[name = string("reduce_mean_31_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_31_keep_dims_0 = const()[name = string("reduce_mean_31_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 8, 1]> reduce_mean_31 = reduce_mean(axes = reduce_mean_31_axes_0, keep_dims = reduce_mean_31_keep_dims_0, x = mul_144)[name = string("reduce_mean_31")];
            fp32 rsqrt_31_epsilon_0 = const()[name = string("rsqrt_31_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 8, 1]> rsqrt_31 = rsqrt(epsilon = rsqrt_31_epsilon_0, x = reduce_mean_31)[name = string("rsqrt_31")];
            tensor<fp16, [8, 8, 44]> mul_145 = mul(x = transpose_12, y = rsqrt_31)[name = string("mul_145")];
            tensor<fp16, [44]> mul_146_y_0 = const()[name = string("mul_146_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3399232)))];
            tensor<fp16, [8, 8, 44]> mul_146 = mul(x = mul_145, y = mul_146_y_0)[name = string("mul_146")];
            tensor<int32, [3]> slice_by_index_12_begin_0 = const()[name = string("slice_by_index_12_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_12_end_0 = const()[name = string("slice_by_index_12_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_12_end_mask_0 = const()[name = string("slice_by_index_12_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 8, 22]> slice_by_index_12 = slice_by_index(begin = slice_by_index_12_begin_0, end = slice_by_index_12_end_0, end_mask = slice_by_index_12_end_mask_0, x = mul_146)[name = string("slice_by_index_12")];
            tensor<int32, [3]> slice_by_index_13_begin_0 = const()[name = string("slice_by_index_13_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_13_end_0 = const()[name = string("slice_by_index_13_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_13_end_mask_0 = const()[name = string("slice_by_index_13_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 8, 22]> slice_by_index_13 = slice_by_index(begin = slice_by_index_13_begin_0, end = slice_by_index_13_end_0, end_mask = slice_by_index_13_end_mask_0, x = mul_146)[name = string("slice_by_index_13")];
            int32 concat_6_axis_0 = const()[name = string("concat_6_axis_0"), val = int32(-1)];
            bool concat_6_interleave_0 = const()[name = string("concat_6_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 8, 44]> concat_6 = concat(axis = concat_6_axis_0, interleave = concat_6_interleave_0, values = (slice_by_index_13, slice_by_index_12))[name = string("concat_6")];
            tensor<fp16, [44]> mul_147_y_0 = const()[name = string("mul_147_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 8, 44]> mul_147 = mul(x = concat_6, y = mul_147_y_0)[name = string("mul_147")];
            tensor<fp16, [8, 8, 44]> mul_148 = mul(x = mul_146, y = mul_11_y_0)[name = string("mul_148")];
            tensor<fp16, [8, 8, 44]> mul_149 = mul(x = mul_147, y = mul_12_y_0)[name = string("mul_149")];
            tensor<fp16, [8, 8, 44]> add_18 = add(x = mul_148, y = mul_149)[name = string("add_18")];
            tensor<fp16, [2, 8, 44]> transpose_13 = transpose(perm = transpose_13_perm_0, x = reshape_27)[name = string("transpose_50")];
            tensor<fp16, [2, 8, 44]> mul_150 = mul(x = transpose_13, y = transpose_13)[name = string("mul_150")];
            tensor<int32, [1]> reduce_mean_32_axes_0 = const()[name = string("reduce_mean_32_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_32_keep_dims_0 = const()[name = string("reduce_mean_32_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 8, 1]> reduce_mean_32 = reduce_mean(axes = reduce_mean_32_axes_0, keep_dims = reduce_mean_32_keep_dims_0, x = mul_150)[name = string("reduce_mean_32")];
            fp32 rsqrt_32_epsilon_0 = const()[name = string("rsqrt_32_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 8, 1]> rsqrt_32 = rsqrt(epsilon = rsqrt_32_epsilon_0, x = reduce_mean_32)[name = string("rsqrt_32")];
            tensor<fp16, [2, 8, 44]> mul_151 = mul(x = transpose_13, y = rsqrt_32)[name = string("mul_151")];
            tensor<fp16, [44]> mul_152_y_0 = const()[name = string("mul_152_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3399424)))];
            tensor<fp16, [2, 8, 44]> mul_152 = mul(x = mul_151, y = mul_152_y_0)[name = string("mul_152")];
            tensor<int32, [3]> slice_by_index_14_begin_0 = const()[name = string("slice_by_index_14_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_14_end_0 = const()[name = string("slice_by_index_14_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_14_end_mask_0 = const()[name = string("slice_by_index_14_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 8, 22]> slice_by_index_14 = slice_by_index(begin = slice_by_index_14_begin_0, end = slice_by_index_14_end_0, end_mask = slice_by_index_14_end_mask_0, x = mul_152)[name = string("slice_by_index_14")];
            tensor<int32, [3]> slice_by_index_15_begin_0 = const()[name = string("slice_by_index_15_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_15_end_0 = const()[name = string("slice_by_index_15_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_15_end_mask_0 = const()[name = string("slice_by_index_15_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 8, 22]> slice_by_index_15 = slice_by_index(begin = slice_by_index_15_begin_0, end = slice_by_index_15_end_0, end_mask = slice_by_index_15_end_mask_0, x = mul_152)[name = string("slice_by_index_15")];
            int32 concat_7_axis_0 = const()[name = string("concat_7_axis_0"), val = int32(-1)];
            bool concat_7_interleave_0 = const()[name = string("concat_7_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 8, 44]> concat_7 = concat(axis = concat_7_axis_0, interleave = concat_7_interleave_0, values = (slice_by_index_15, slice_by_index_14))[name = string("concat_7")];
            tensor<fp16, [44]> mul_153_y_0 = const()[name = string("mul_153_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 8, 44]> mul_153 = mul(x = concat_7, y = mul_153_y_0)[name = string("mul_153")];
            tensor<fp16, [2, 8, 44]> mul_154 = mul(x = mul_152, y = mul_11_y_0)[name = string("mul_154")];
            tensor<fp16, [2, 8, 44]> mul_155 = mul(x = mul_153, y = mul_12_y_0)[name = string("mul_155")];
            tensor<fp16, [2, 8, 44]> add_19 = add(x = mul_154, y = mul_155)[name = string("add_19")];
            tensor<int32, [4]> reshape_29_shape_0 = const()[name = string("reshape_29_shape_0"), val = tensor<int32, [4]>([2, 1, 8, 44])];
            tensor<fp16, [2, 1, 8, 44]> reshape_29 = reshape(shape = reshape_29_shape_0, x = add_19)[name = string("reshape_29")];
            tensor<int32, [4]> tile_6_reps_0 = const()[name = string("tile_6_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 8, 44]> tile_6 = tile(reps = tile_6_reps_0, x = reshape_29)[name = string("tile_6")];
            tensor<int32, [3]> reshape_30_shape_0 = const()[name = string("reshape_30_shape_0"), val = tensor<int32, [3]>([8, 8, 44])];
            tensor<fp16, [8, 8, 44]> reshape_30 = reshape(shape = reshape_30_shape_0, x = tile_6)[name = string("reshape_30")];
            tensor<int32, [4]> reshape_31_shape_0 = const()[name = string("reshape_31_shape_0"), val = tensor<int32, [4]>([2, 1, 8, 44])];
            tensor<fp16, [2, 8, 44]> transpose_14 = transpose(perm = transpose_14_perm_0, x = reshape_28)[name = string("transpose_49")];
            tensor<fp16, [2, 1, 8, 44]> reshape_31 = reshape(shape = reshape_31_shape_0, x = transpose_14)[name = string("reshape_31")];
            tensor<int32, [4]> tile_7_reps_0 = const()[name = string("tile_7_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 8, 44]> tile_7 = tile(reps = tile_7_reps_0, x = reshape_31)[name = string("tile_7")];
            tensor<int32, [3]> reshape_32_shape_0 = const()[name = string("reshape_32_shape_0"), val = tensor<int32, [3]>([8, 8, 44])];
            tensor<fp16, [8, 8, 44]> reshape_32 = reshape(shape = reshape_32_shape_0, x = tile_7)[name = string("reshape_32")];
            fp16 mul_156_y_0 = const()[name = string("mul_156_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 8, 44]> mul_156 = mul(x = add_18, y = mul_156_y_0)[name = string("mul_156")];
            bool matmul_6_transpose_y_0 = const()[name = string("matmul_6_transpose_y_0"), val = bool(true)];
            bool matmul_6_transpose_x_0 = const()[name = string("matmul_6_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 8, 8]> matmul_6 = matmul(transpose_x = matmul_6_transpose_x_0, transpose_y = matmul_6_transpose_y_0, x = mul_156, y = reshape_30)[name = string("matmul_6")];
            tensor<fp16, [8, 8, 8]> add_20 = add(x = matmul_6, y = reshape_1)[name = string("add_20")];
            int32 softmax_3_axis_0 = const()[name = string("softmax_3_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 8, 8]> softmax_3 = softmax(axis = softmax_3_axis_0, x = add_20)[name = string("softmax_3")];
            bool matmul_7_transpose_x_0 = const()[name = string("matmul_7_transpose_x_0"), val = bool(false)];
            bool matmul_7_transpose_y_0 = const()[name = string("matmul_7_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 8, 44]> matmul_7 = matmul(transpose_x = matmul_7_transpose_x_0, transpose_y = matmul_7_transpose_y_0, x = softmax_3, y = reshape_32)[name = string("matmul_7")];
            tensor<int32, [3]> transpose_15_perm_0 = const()[name = string("transpose_15_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_33_shape_0 = const()[name = string("reshape_33_shape_0"), val = tensor<int32, [2]>([8, 352])];
            tensor<fp16, [8, 8, 44]> transpose_15 = transpose(perm = transpose_15_perm_0, x = matmul_7)[name = string("transpose_48")];
            tensor<fp16, [8, 352]> reshape_33 = reshape(shape = reshape_33_shape_0, x = transpose_15)[name = string("reshape_33")];
            tensor<fp16, [8, 352]> mul_157 = mul(x = reshape_33, y = reshape_33)[name = string("mul_157")];
            tensor<int32, [1]> reduce_mean_33_axes_0 = const()[name = string("reduce_mean_33_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_33_keep_dims_0 = const()[name = string("reduce_mean_33_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_33 = reduce_mean(axes = reduce_mean_33_axes_0, keep_dims = reduce_mean_33_keep_dims_0, x = mul_157)[name = string("reduce_mean_33")];
            fp32 rsqrt_33_epsilon_0 = const()[name = string("rsqrt_33_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_33 = rsqrt(epsilon = rsqrt_33_epsilon_0, x = reduce_mean_33)[name = string("rsqrt_33")];
            tensor<fp16, [8, 352]> mul_158 = mul(x = reshape_33, y = rsqrt_33)[name = string("mul_158")];
            tensor<fp16, [352]> mul_159_y_0 = const()[name = string("mul_159_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3399616)))];
            tensor<fp16, [8, 352]> mul_159 = mul(x = mul_158, y = mul_159_y_0)[name = string("mul_159")];
            tensor<fp16, [352, 352]> tern_3_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3400384))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_3_o_weight_0_palettized")];
            tensor<fp16, [8, 352]> tern_3_o = linear(bias = linear_0_bias_0, weight = tern_3_o_weight_0_palettized, x = mul_159)[name = string("tern_3_o")];
            tensor<fp16, [352]> mul_160_y_0 = const()[name = string("mul_160_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3431424)))];
            tensor<fp16, [8, 352]> mul_160 = mul(x = tern_3_o, y = mul_160_y_0)[name = string("mul_160")];
            tensor<fp16, [8, 352]> add_21 = add(x = add_17, y = mul_160)[name = string("add_21")];
            tensor<fp16, [8, 352]> mul_161 = mul(x = add_21, y = add_21)[name = string("mul_161")];
            tensor<int32, [1]> reduce_mean_34_axes_0 = const()[name = string("reduce_mean_34_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_34_keep_dims_0 = const()[name = string("reduce_mean_34_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_34 = reduce_mean(axes = reduce_mean_34_axes_0, keep_dims = reduce_mean_34_keep_dims_0, x = mul_161)[name = string("reduce_mean_34")];
            fp32 rsqrt_34_epsilon_0 = const()[name = string("rsqrt_34_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_34 = rsqrt(epsilon = rsqrt_34_epsilon_0, x = reduce_mean_34)[name = string("rsqrt_34")];
            tensor<fp16, [8, 352]> mul_162 = mul(x = add_21, y = rsqrt_34)[name = string("mul_162")];
            tensor<fp16, [352]> mul_163_y_0 = const()[name = string("mul_163_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3432192)))];
            tensor<fp16, [8, 352]> mul_163 = mul(x = mul_162, y = mul_163_y_0)[name = string("mul_163")];
            tensor<fp16, [8, 352]> mul_164 = mul(x = mul_163, y = mul_163)[name = string("mul_164")];
            tensor<int32, [1]> reduce_mean_35_axes_0 = const()[name = string("reduce_mean_35_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_35_keep_dims_0 = const()[name = string("reduce_mean_35_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_35 = reduce_mean(axes = reduce_mean_35_axes_0, keep_dims = reduce_mean_35_keep_dims_0, x = mul_164)[name = string("reduce_mean_35")];
            fp32 rsqrt_35_epsilon_0 = const()[name = string("rsqrt_35_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_35 = rsqrt(epsilon = rsqrt_35_epsilon_0, x = reduce_mean_35)[name = string("rsqrt_35")];
            tensor<fp16, [8, 352]> mul_165 = mul(x = mul_163, y = rsqrt_35)[name = string("mul_165")];
            tensor<fp16, [352]> mul_166_y_0 = const()[name = string("mul_166_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3432960)))];
            tensor<fp16, [8, 352]> mul_166 = mul(x = mul_165, y = mul_166_y_0)[name = string("mul_166")];
            tensor<fp16, [960, 352]> tern_3_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3433728))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_3_w1_weight_0_palettized")];
            tensor<fp16, [8, 960]> tern_3_w1 = linear(bias = linear_4_bias_0, weight = tern_3_w1_weight_0_palettized, x = mul_166)[name = string("tern_3_w1")];
            tensor<fp16, [960]> mul_167_y_0 = const()[name = string("mul_167_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3518272)))];
            tensor<fp16, [8, 960]> mul_167 = mul(x = tern_3_w1, y = mul_167_y_0)[name = string("mul_167")];
            tensor<fp16, [352]> mul_170_y_0 = const()[name = string("mul_170_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3520256)))];
            tensor<fp16, [8, 352]> mul_170 = mul(x = mul_165, y = mul_170_y_0)[name = string("mul_170")];
            tensor<fp16, [960, 352]> tern_3_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3521024))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_3_w3_weight_0_palettized")];
            tensor<fp16, [8, 960]> tern_3_w3 = linear(bias = linear_4_bias_0, weight = tern_3_w3_weight_0_palettized, x = mul_170)[name = string("tern_3_w3")];
            tensor<fp16, [960]> mul_171_y_0 = const()[name = string("mul_171_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3605568)))];
            tensor<fp16, [8, 960]> mul_171 = mul(x = tern_3_w3, y = mul_171_y_0)[name = string("mul_171")];
            fp16 mul_172_y_0 = const()[name = string("mul_172_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [8, 960]> mul_172 = mul(x = mul_167, y = mul_172_y_0)[name = string("mul_172")];
            tensor<fp16, [8, 960]> tanh_3 = tanh(x = mul_172)[name = string("tanh_3")];
            fp16 mul_173_x_0 = const()[name = string("mul_173_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [8, 960]> mul_173 = mul(x = mul_173_x_0, y = tanh_3)[name = string("mul_173")];
            fp16 add_22_x_0 = const()[name = string("add_22_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [8, 960]> add_22 = add(x = add_22_x_0, y = mul_173)[name = string("add_22")];
            tensor<fp16, [8, 960]> mul_174 = mul(x = mul_167, y = add_22)[name = string("mul_174")];
            tensor<fp16, [8, 960]> mul_175 = mul(x = mul_174, y = mul_171)[name = string("mul_175")];
            tensor<fp16, [8, 960]> mul_176 = mul(x = mul_175, y = mul_175)[name = string("mul_176")];
            tensor<int32, [1]> reduce_mean_37_axes_0 = const()[name = string("reduce_mean_37_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_37_keep_dims_0 = const()[name = string("reduce_mean_37_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_37 = reduce_mean(axes = reduce_mean_37_axes_0, keep_dims = reduce_mean_37_keep_dims_0, x = mul_176)[name = string("reduce_mean_37")];
            fp32 rsqrt_37_epsilon_0 = const()[name = string("rsqrt_37_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_37 = rsqrt(epsilon = rsqrt_37_epsilon_0, x = reduce_mean_37)[name = string("rsqrt_37")];
            tensor<fp16, [8, 960]> mul_177 = mul(x = mul_175, y = rsqrt_37)[name = string("mul_177")];
            tensor<fp16, [960]> mul_178_y_0 = const()[name = string("mul_178_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3607552)))];
            tensor<fp16, [8, 960]> mul_178 = mul(x = mul_177, y = mul_178_y_0)[name = string("mul_178")];
            tensor<fp16, [352, 960]> tern_3_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3609536))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_3_w2_weight_0_palettized")];
            tensor<fp16, [8, 352]> tern_3_w2 = linear(bias = linear_0_bias_0, weight = tern_3_w2_weight_0_palettized, x = mul_178)[name = string("tern_3_w2")];
            tensor<fp16, [352]> mul_179_y_0 = const()[name = string("mul_179_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3694080)))];
            tensor<fp16, [8, 352]> mul_179 = mul(x = tern_3_w2, y = mul_179_y_0)[name = string("mul_179")];
            tensor<fp16, [8, 352]> add_23 = add(x = add_21, y = mul_179)[name = string("add_23")];
            tensor<fp16, [8, 352]> mul_180 = mul(x = add_23, y = add_23)[name = string("mul_180")];
            tensor<int32, [1]> reduce_mean_38_axes_0 = const()[name = string("reduce_mean_38_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_38_keep_dims_0 = const()[name = string("reduce_mean_38_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_38 = reduce_mean(axes = reduce_mean_38_axes_0, keep_dims = reduce_mean_38_keep_dims_0, x = mul_180)[name = string("reduce_mean_38")];
            fp32 rsqrt_38_epsilon_0 = const()[name = string("rsqrt_38_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_38 = rsqrt(epsilon = rsqrt_38_epsilon_0, x = reduce_mean_38)[name = string("rsqrt_38")];
            tensor<fp16, [8, 352]> mul_181 = mul(x = add_23, y = rsqrt_38)[name = string("mul_181")];
            tensor<fp16, [352]> mul_182_y_0 = const()[name = string("mul_182_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3694848)))];
            tensor<fp16, [8, 352]> mul_182 = mul(x = mul_181, y = mul_182_y_0)[name = string("mul_182")];
            tensor<fp16, [8, 352]> mul_183 = mul(x = mul_182, y = mul_182)[name = string("mul_183")];
            tensor<int32, [1]> reduce_mean_39_axes_0 = const()[name = string("reduce_mean_39_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_39_keep_dims_0 = const()[name = string("reduce_mean_39_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_39 = reduce_mean(axes = reduce_mean_39_axes_0, keep_dims = reduce_mean_39_keep_dims_0, x = mul_183)[name = string("reduce_mean_39")];
            fp32 rsqrt_39_epsilon_0 = const()[name = string("rsqrt_39_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_39 = rsqrt(epsilon = rsqrt_39_epsilon_0, x = reduce_mean_39)[name = string("rsqrt_39")];
            tensor<fp16, [8, 352]> mul_184 = mul(x = mul_182, y = rsqrt_39)[name = string("mul_184")];
            tensor<fp16, [352]> mul_185_y_0 = const()[name = string("mul_185_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3695616)))];
            tensor<fp16, [8, 352]> mul_185 = mul(x = mul_184, y = mul_185_y_0)[name = string("mul_185")];
            tensor<fp16, [352, 352]> tern_4_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3696384))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_4_q_weight_0_palettized")];
            tensor<fp16, [8, 352]> tern_4_q = linear(bias = linear_0_bias_0, weight = tern_4_q_weight_0_palettized, x = mul_185)[name = string("tern_4_q")];
            tensor<fp16, [352]> mul_186_y_0 = const()[name = string("mul_186_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3727424)))];
            tensor<fp16, [8, 352]> mul_186 = mul(x = tern_4_q, y = mul_186_y_0)[name = string("mul_186")];
            tensor<int32, [3]> reshape_34_shape_0 = const()[name = string("reshape_34_shape_0"), val = tensor<int32, [3]>([8, 8, 44])];
            tensor<fp16, [8, 8, 44]> reshape_34 = reshape(shape = reshape_34_shape_0, x = mul_186)[name = string("reshape_34")];
            tensor<int32, [3]> transpose_16_perm_0 = const()[name = string("transpose_16_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_189_y_0 = const()[name = string("mul_189_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3728192)))];
            tensor<fp16, [8, 352]> mul_189 = mul(x = mul_184, y = mul_189_y_0)[name = string("mul_189")];
            tensor<fp16, [88, 352]> tern_4_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3728960))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_4_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_4_k_bias_0 = const()[name = string("tern_4_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [8, 88]> tern_4_k = linear(bias = tern_4_k_bias_0, weight = tern_4_k_weight_0_palettized, x = mul_189)[name = string("tern_4_k")];
            tensor<fp16, [88]> mul_190_y_0 = const()[name = string("mul_190_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3736768)))];
            tensor<fp16, [8, 88]> mul_190 = mul(x = tern_4_k, y = mul_190_y_0)[name = string("mul_190")];
            tensor<int32, [3]> reshape_35_shape_0 = const()[name = string("reshape_35_shape_0"), val = tensor<int32, [3]>([8, 2, 44])];
            tensor<fp16, [8, 2, 44]> reshape_35 = reshape(shape = reshape_35_shape_0, x = mul_190)[name = string("reshape_35")];
            tensor<int32, [3]> transpose_17_perm_0 = const()[name = string("transpose_17_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_193_y_0 = const()[name = string("mul_193_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3737024)))];
            tensor<fp16, [8, 352]> mul_193 = mul(x = mul_184, y = mul_193_y_0)[name = string("mul_193")];
            tensor<fp16, [88, 352]> tern_4_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3737792))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_4_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_4_v_bias_0 = const()[name = string("tern_4_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [8, 88]> tern_4_v = linear(bias = tern_4_v_bias_0, weight = tern_4_v_weight_0_palettized, x = mul_193)[name = string("tern_4_v")];
            tensor<fp16, [88]> mul_194_y_0 = const()[name = string("mul_194_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3745600)))];
            tensor<fp16, [8, 88]> mul_194 = mul(x = tern_4_v, y = mul_194_y_0)[name = string("mul_194")];
            tensor<int32, [3]> reshape_36_shape_0 = const()[name = string("reshape_36_shape_0"), val = tensor<int32, [3]>([8, 2, 44])];
            tensor<fp16, [8, 2, 44]> reshape_36 = reshape(shape = reshape_36_shape_0, x = mul_194)[name = string("reshape_36")];
            tensor<int32, [3]> transpose_18_perm_0 = const()[name = string("transpose_18_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 8, 44]> transpose_16 = transpose(perm = transpose_16_perm_0, x = reshape_34)[name = string("transpose_47")];
            tensor<fp16, [8, 8, 44]> mul_195 = mul(x = transpose_16, y = transpose_16)[name = string("mul_195")];
            tensor<int32, [1]> reduce_mean_42_axes_0 = const()[name = string("reduce_mean_42_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_42_keep_dims_0 = const()[name = string("reduce_mean_42_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 8, 1]> reduce_mean_42 = reduce_mean(axes = reduce_mean_42_axes_0, keep_dims = reduce_mean_42_keep_dims_0, x = mul_195)[name = string("reduce_mean_42")];
            fp32 rsqrt_42_epsilon_0 = const()[name = string("rsqrt_42_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 8, 1]> rsqrt_42 = rsqrt(epsilon = rsqrt_42_epsilon_0, x = reduce_mean_42)[name = string("rsqrt_42")];
            tensor<fp16, [8, 8, 44]> mul_196 = mul(x = transpose_16, y = rsqrt_42)[name = string("mul_196")];
            tensor<fp16, [44]> mul_197_y_0 = const()[name = string("mul_197_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3745856)))];
            tensor<fp16, [8, 8, 44]> mul_197 = mul(x = mul_196, y = mul_197_y_0)[name = string("mul_197")];
            tensor<int32, [3]> slice_by_index_16_begin_0 = const()[name = string("slice_by_index_16_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_16_end_0 = const()[name = string("slice_by_index_16_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_16_end_mask_0 = const()[name = string("slice_by_index_16_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 8, 22]> slice_by_index_16 = slice_by_index(begin = slice_by_index_16_begin_0, end = slice_by_index_16_end_0, end_mask = slice_by_index_16_end_mask_0, x = mul_197)[name = string("slice_by_index_16")];
            tensor<int32, [3]> slice_by_index_17_begin_0 = const()[name = string("slice_by_index_17_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_17_end_0 = const()[name = string("slice_by_index_17_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_17_end_mask_0 = const()[name = string("slice_by_index_17_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 8, 22]> slice_by_index_17 = slice_by_index(begin = slice_by_index_17_begin_0, end = slice_by_index_17_end_0, end_mask = slice_by_index_17_end_mask_0, x = mul_197)[name = string("slice_by_index_17")];
            int32 concat_8_axis_0 = const()[name = string("concat_8_axis_0"), val = int32(-1)];
            bool concat_8_interleave_0 = const()[name = string("concat_8_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 8, 44]> concat_8 = concat(axis = concat_8_axis_0, interleave = concat_8_interleave_0, values = (slice_by_index_17, slice_by_index_16))[name = string("concat_8")];
            tensor<fp16, [44]> mul_198_y_0 = const()[name = string("mul_198_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 8, 44]> mul_198 = mul(x = concat_8, y = mul_198_y_0)[name = string("mul_198")];
            tensor<fp16, [8, 8, 44]> mul_199 = mul(x = mul_197, y = mul_11_y_0)[name = string("mul_199")];
            tensor<fp16, [8, 8, 44]> mul_200 = mul(x = mul_198, y = mul_12_y_0)[name = string("mul_200")];
            tensor<fp16, [8, 8, 44]> add_24 = add(x = mul_199, y = mul_200)[name = string("add_24")];
            tensor<fp16, [2, 8, 44]> transpose_17 = transpose(perm = transpose_17_perm_0, x = reshape_35)[name = string("transpose_46")];
            tensor<fp16, [2, 8, 44]> mul_201 = mul(x = transpose_17, y = transpose_17)[name = string("mul_201")];
            tensor<int32, [1]> reduce_mean_43_axes_0 = const()[name = string("reduce_mean_43_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_43_keep_dims_0 = const()[name = string("reduce_mean_43_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 8, 1]> reduce_mean_43 = reduce_mean(axes = reduce_mean_43_axes_0, keep_dims = reduce_mean_43_keep_dims_0, x = mul_201)[name = string("reduce_mean_43")];
            fp32 rsqrt_43_epsilon_0 = const()[name = string("rsqrt_43_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 8, 1]> rsqrt_43 = rsqrt(epsilon = rsqrt_43_epsilon_0, x = reduce_mean_43)[name = string("rsqrt_43")];
            tensor<fp16, [2, 8, 44]> mul_202 = mul(x = transpose_17, y = rsqrt_43)[name = string("mul_202")];
            tensor<fp16, [44]> mul_203_y_0 = const()[name = string("mul_203_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3746048)))];
            tensor<fp16, [2, 8, 44]> mul_203 = mul(x = mul_202, y = mul_203_y_0)[name = string("mul_203")];
            tensor<int32, [3]> slice_by_index_18_begin_0 = const()[name = string("slice_by_index_18_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_18_end_0 = const()[name = string("slice_by_index_18_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_18_end_mask_0 = const()[name = string("slice_by_index_18_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 8, 22]> slice_by_index_18 = slice_by_index(begin = slice_by_index_18_begin_0, end = slice_by_index_18_end_0, end_mask = slice_by_index_18_end_mask_0, x = mul_203)[name = string("slice_by_index_18")];
            tensor<int32, [3]> slice_by_index_19_begin_0 = const()[name = string("slice_by_index_19_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_19_end_0 = const()[name = string("slice_by_index_19_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_19_end_mask_0 = const()[name = string("slice_by_index_19_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 8, 22]> slice_by_index_19 = slice_by_index(begin = slice_by_index_19_begin_0, end = slice_by_index_19_end_0, end_mask = slice_by_index_19_end_mask_0, x = mul_203)[name = string("slice_by_index_19")];
            int32 concat_9_axis_0 = const()[name = string("concat_9_axis_0"), val = int32(-1)];
            bool concat_9_interleave_0 = const()[name = string("concat_9_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 8, 44]> concat_9 = concat(axis = concat_9_axis_0, interleave = concat_9_interleave_0, values = (slice_by_index_19, slice_by_index_18))[name = string("concat_9")];
            tensor<fp16, [44]> mul_204_y_0 = const()[name = string("mul_204_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 8, 44]> mul_204 = mul(x = concat_9, y = mul_204_y_0)[name = string("mul_204")];
            tensor<fp16, [2, 8, 44]> mul_205 = mul(x = mul_203, y = mul_11_y_0)[name = string("mul_205")];
            tensor<fp16, [2, 8, 44]> mul_206 = mul(x = mul_204, y = mul_12_y_0)[name = string("mul_206")];
            tensor<fp16, [2, 8, 44]> add_25 = add(x = mul_205, y = mul_206)[name = string("add_25")];
            tensor<int32, [4]> reshape_37_shape_0 = const()[name = string("reshape_37_shape_0"), val = tensor<int32, [4]>([2, 1, 8, 44])];
            tensor<fp16, [2, 1, 8, 44]> reshape_37 = reshape(shape = reshape_37_shape_0, x = add_25)[name = string("reshape_37")];
            tensor<int32, [4]> tile_8_reps_0 = const()[name = string("tile_8_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 8, 44]> tile_8 = tile(reps = tile_8_reps_0, x = reshape_37)[name = string("tile_8")];
            tensor<int32, [3]> reshape_38_shape_0 = const()[name = string("reshape_38_shape_0"), val = tensor<int32, [3]>([8, 8, 44])];
            tensor<fp16, [8, 8, 44]> reshape_38 = reshape(shape = reshape_38_shape_0, x = tile_8)[name = string("reshape_38")];
            tensor<int32, [4]> reshape_39_shape_0 = const()[name = string("reshape_39_shape_0"), val = tensor<int32, [4]>([2, 1, 8, 44])];
            tensor<fp16, [2, 8, 44]> transpose_18 = transpose(perm = transpose_18_perm_0, x = reshape_36)[name = string("transpose_45")];
            tensor<fp16, [2, 1, 8, 44]> reshape_39 = reshape(shape = reshape_39_shape_0, x = transpose_18)[name = string("reshape_39")];
            tensor<int32, [4]> tile_9_reps_0 = const()[name = string("tile_9_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 8, 44]> tile_9 = tile(reps = tile_9_reps_0, x = reshape_39)[name = string("tile_9")];
            tensor<int32, [3]> reshape_40_shape_0 = const()[name = string("reshape_40_shape_0"), val = tensor<int32, [3]>([8, 8, 44])];
            tensor<fp16, [8, 8, 44]> reshape_40 = reshape(shape = reshape_40_shape_0, x = tile_9)[name = string("reshape_40")];
            fp16 mul_207_y_0 = const()[name = string("mul_207_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 8, 44]> mul_207 = mul(x = add_24, y = mul_207_y_0)[name = string("mul_207")];
            bool matmul_8_transpose_y_0 = const()[name = string("matmul_8_transpose_y_0"), val = bool(true)];
            bool matmul_8_transpose_x_0 = const()[name = string("matmul_8_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 8, 8]> matmul_8 = matmul(transpose_x = matmul_8_transpose_x_0, transpose_y = matmul_8_transpose_y_0, x = mul_207, y = reshape_38)[name = string("matmul_8")];
            tensor<fp16, [8, 8, 8]> add_26 = add(x = matmul_8, y = reshape_1)[name = string("add_26")];
            int32 softmax_4_axis_0 = const()[name = string("softmax_4_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 8, 8]> softmax_4 = softmax(axis = softmax_4_axis_0, x = add_26)[name = string("softmax_4")];
            bool matmul_9_transpose_x_0 = const()[name = string("matmul_9_transpose_x_0"), val = bool(false)];
            bool matmul_9_transpose_y_0 = const()[name = string("matmul_9_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 8, 44]> matmul_9 = matmul(transpose_x = matmul_9_transpose_x_0, transpose_y = matmul_9_transpose_y_0, x = softmax_4, y = reshape_40)[name = string("matmul_9")];
            tensor<int32, [3]> transpose_19_perm_0 = const()[name = string("transpose_19_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_41_shape_0 = const()[name = string("reshape_41_shape_0"), val = tensor<int32, [2]>([8, 352])];
            tensor<fp16, [8, 8, 44]> transpose_19 = transpose(perm = transpose_19_perm_0, x = matmul_9)[name = string("transpose_44")];
            tensor<fp16, [8, 352]> reshape_41 = reshape(shape = reshape_41_shape_0, x = transpose_19)[name = string("reshape_41")];
            tensor<fp16, [8, 352]> mul_208 = mul(x = reshape_41, y = reshape_41)[name = string("mul_208")];
            tensor<int32, [1]> reduce_mean_44_axes_0 = const()[name = string("reduce_mean_44_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_44_keep_dims_0 = const()[name = string("reduce_mean_44_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_44 = reduce_mean(axes = reduce_mean_44_axes_0, keep_dims = reduce_mean_44_keep_dims_0, x = mul_208)[name = string("reduce_mean_44")];
            fp32 rsqrt_44_epsilon_0 = const()[name = string("rsqrt_44_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_44 = rsqrt(epsilon = rsqrt_44_epsilon_0, x = reduce_mean_44)[name = string("rsqrt_44")];
            tensor<fp16, [8, 352]> mul_209 = mul(x = reshape_41, y = rsqrt_44)[name = string("mul_209")];
            tensor<fp16, [352]> mul_210_y_0 = const()[name = string("mul_210_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3746240)))];
            tensor<fp16, [8, 352]> mul_210 = mul(x = mul_209, y = mul_210_y_0)[name = string("mul_210")];
            tensor<fp16, [352, 352]> tern_4_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3747008))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_4_o_weight_0_palettized")];
            tensor<fp16, [8, 352]> tern_4_o = linear(bias = linear_0_bias_0, weight = tern_4_o_weight_0_palettized, x = mul_210)[name = string("tern_4_o")];
            tensor<fp16, [352]> mul_211_y_0 = const()[name = string("mul_211_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3778048)))];
            tensor<fp16, [8, 352]> mul_211 = mul(x = tern_4_o, y = mul_211_y_0)[name = string("mul_211")];
            tensor<fp16, [8, 352]> add_27 = add(x = add_23, y = mul_211)[name = string("add_27")];
            tensor<fp16, [8, 352]> mul_212 = mul(x = add_27, y = add_27)[name = string("mul_212")];
            tensor<int32, [1]> reduce_mean_45_axes_0 = const()[name = string("reduce_mean_45_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_45_keep_dims_0 = const()[name = string("reduce_mean_45_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_45 = reduce_mean(axes = reduce_mean_45_axes_0, keep_dims = reduce_mean_45_keep_dims_0, x = mul_212)[name = string("reduce_mean_45")];
            fp32 rsqrt_45_epsilon_0 = const()[name = string("rsqrt_45_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_45 = rsqrt(epsilon = rsqrt_45_epsilon_0, x = reduce_mean_45)[name = string("rsqrt_45")];
            tensor<fp16, [8, 352]> mul_213 = mul(x = add_27, y = rsqrt_45)[name = string("mul_213")];
            tensor<fp16, [352]> mul_214_y_0 = const()[name = string("mul_214_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3778816)))];
            tensor<fp16, [8, 352]> mul_214 = mul(x = mul_213, y = mul_214_y_0)[name = string("mul_214")];
            tensor<fp16, [8, 352]> mul_215 = mul(x = mul_214, y = mul_214)[name = string("mul_215")];
            tensor<int32, [1]> reduce_mean_46_axes_0 = const()[name = string("reduce_mean_46_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_46_keep_dims_0 = const()[name = string("reduce_mean_46_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_46 = reduce_mean(axes = reduce_mean_46_axes_0, keep_dims = reduce_mean_46_keep_dims_0, x = mul_215)[name = string("reduce_mean_46")];
            fp32 rsqrt_46_epsilon_0 = const()[name = string("rsqrt_46_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_46 = rsqrt(epsilon = rsqrt_46_epsilon_0, x = reduce_mean_46)[name = string("rsqrt_46")];
            tensor<fp16, [8, 352]> mul_216 = mul(x = mul_214, y = rsqrt_46)[name = string("mul_216")];
            tensor<fp16, [352]> mul_217_y_0 = const()[name = string("mul_217_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3779584)))];
            tensor<fp16, [8, 352]> mul_217 = mul(x = mul_216, y = mul_217_y_0)[name = string("mul_217")];
            tensor<fp16, [960, 352]> tern_4_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3780352))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_4_w1_weight_0_palettized")];
            tensor<fp16, [8, 960]> tern_4_w1 = linear(bias = linear_4_bias_0, weight = tern_4_w1_weight_0_palettized, x = mul_217)[name = string("tern_4_w1")];
            tensor<fp16, [960]> mul_218_y_0 = const()[name = string("mul_218_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3864896)))];
            tensor<fp16, [8, 960]> mul_218 = mul(x = tern_4_w1, y = mul_218_y_0)[name = string("mul_218")];
            tensor<fp16, [352]> mul_221_y_0 = const()[name = string("mul_221_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3866880)))];
            tensor<fp16, [8, 352]> mul_221 = mul(x = mul_216, y = mul_221_y_0)[name = string("mul_221")];
            tensor<fp16, [960, 352]> tern_4_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3867648))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_4_w3_weight_0_palettized")];
            tensor<fp16, [8, 960]> tern_4_w3 = linear(bias = linear_4_bias_0, weight = tern_4_w3_weight_0_palettized, x = mul_221)[name = string("tern_4_w3")];
            tensor<fp16, [960]> mul_222_y_0 = const()[name = string("mul_222_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3952192)))];
            tensor<fp16, [8, 960]> mul_222 = mul(x = tern_4_w3, y = mul_222_y_0)[name = string("mul_222")];
            fp16 mul_223_y_0 = const()[name = string("mul_223_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [8, 960]> mul_223 = mul(x = mul_218, y = mul_223_y_0)[name = string("mul_223")];
            tensor<fp16, [8, 960]> tanh_4 = tanh(x = mul_223)[name = string("tanh_4")];
            fp16 mul_224_x_0 = const()[name = string("mul_224_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [8, 960]> mul_224 = mul(x = mul_224_x_0, y = tanh_4)[name = string("mul_224")];
            fp16 add_28_x_0 = const()[name = string("add_28_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [8, 960]> add_28 = add(x = add_28_x_0, y = mul_224)[name = string("add_28")];
            tensor<fp16, [8, 960]> mul_225 = mul(x = mul_218, y = add_28)[name = string("mul_225")];
            tensor<fp16, [8, 960]> mul_226 = mul(x = mul_225, y = mul_222)[name = string("mul_226")];
            tensor<fp16, [8, 960]> mul_227 = mul(x = mul_226, y = mul_226)[name = string("mul_227")];
            tensor<int32, [1]> reduce_mean_48_axes_0 = const()[name = string("reduce_mean_48_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_48_keep_dims_0 = const()[name = string("reduce_mean_48_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_48 = reduce_mean(axes = reduce_mean_48_axes_0, keep_dims = reduce_mean_48_keep_dims_0, x = mul_227)[name = string("reduce_mean_48")];
            fp32 rsqrt_48_epsilon_0 = const()[name = string("rsqrt_48_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_48 = rsqrt(epsilon = rsqrt_48_epsilon_0, x = reduce_mean_48)[name = string("rsqrt_48")];
            tensor<fp16, [8, 960]> mul_228 = mul(x = mul_226, y = rsqrt_48)[name = string("mul_228")];
            tensor<fp16, [960]> mul_229_y_0 = const()[name = string("mul_229_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3954176)))];
            tensor<fp16, [8, 960]> mul_229 = mul(x = mul_228, y = mul_229_y_0)[name = string("mul_229")];
            tensor<fp16, [352, 960]> tern_4_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(3956160))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_4_w2_weight_0_palettized")];
            tensor<fp16, [8, 352]> tern_4_w2 = linear(bias = linear_0_bias_0, weight = tern_4_w2_weight_0_palettized, x = mul_229)[name = string("tern_4_w2")];
            tensor<fp16, [352]> mul_230_y_0 = const()[name = string("mul_230_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4040704)))];
            tensor<fp16, [8, 352]> mul_230 = mul(x = tern_4_w2, y = mul_230_y_0)[name = string("mul_230")];
            tensor<fp16, [8, 352]> add_29 = add(x = add_27, y = mul_230)[name = string("add_29")];
            tensor<fp16, [8, 352]> mul_231 = mul(x = add_29, y = add_29)[name = string("mul_231")];
            tensor<int32, [1]> reduce_mean_49_axes_0 = const()[name = string("reduce_mean_49_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_49_keep_dims_0 = const()[name = string("reduce_mean_49_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_49 = reduce_mean(axes = reduce_mean_49_axes_0, keep_dims = reduce_mean_49_keep_dims_0, x = mul_231)[name = string("reduce_mean_49")];
            fp32 rsqrt_49_epsilon_0 = const()[name = string("rsqrt_49_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_49 = rsqrt(epsilon = rsqrt_49_epsilon_0, x = reduce_mean_49)[name = string("rsqrt_49")];
            tensor<fp16, [8, 352]> mul_232 = mul(x = add_29, y = rsqrt_49)[name = string("mul_232")];
            tensor<fp16, [352]> mul_233_y_0 = const()[name = string("mul_233_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4041472)))];
            tensor<fp16, [8, 352]> mul_233 = mul(x = mul_232, y = mul_233_y_0)[name = string("mul_233")];
            tensor<fp16, [8, 352]> mul_234 = mul(x = mul_233, y = mul_233)[name = string("mul_234")];
            tensor<int32, [1]> reduce_mean_50_axes_0 = const()[name = string("reduce_mean_50_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_50_keep_dims_0 = const()[name = string("reduce_mean_50_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_50 = reduce_mean(axes = reduce_mean_50_axes_0, keep_dims = reduce_mean_50_keep_dims_0, x = mul_234)[name = string("reduce_mean_50")];
            fp32 rsqrt_50_epsilon_0 = const()[name = string("rsqrt_50_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_50 = rsqrt(epsilon = rsqrt_50_epsilon_0, x = reduce_mean_50)[name = string("rsqrt_50")];
            tensor<fp16, [8, 352]> mul_235 = mul(x = mul_233, y = rsqrt_50)[name = string("mul_235")];
            tensor<fp16, [352]> mul_236_y_0 = const()[name = string("mul_236_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4042240)))];
            tensor<fp16, [8, 352]> mul_236 = mul(x = mul_235, y = mul_236_y_0)[name = string("mul_236")];
            tensor<fp16, [352, 352]> tern_5_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4043008))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_5_q_weight_0_palettized")];
            tensor<fp16, [8, 352]> tern_5_q = linear(bias = linear_0_bias_0, weight = tern_5_q_weight_0_palettized, x = mul_236)[name = string("tern_5_q")];
            tensor<fp16, [352]> mul_237_y_0 = const()[name = string("mul_237_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4074048)))];
            tensor<fp16, [8, 352]> mul_237 = mul(x = tern_5_q, y = mul_237_y_0)[name = string("mul_237")];
            tensor<int32, [3]> reshape_42_shape_0 = const()[name = string("reshape_42_shape_0"), val = tensor<int32, [3]>([8, 8, 44])];
            tensor<fp16, [8, 8, 44]> reshape_42 = reshape(shape = reshape_42_shape_0, x = mul_237)[name = string("reshape_42")];
            tensor<int32, [3]> transpose_20_perm_0 = const()[name = string("transpose_20_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_240_y_0 = const()[name = string("mul_240_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4074816)))];
            tensor<fp16, [8, 352]> mul_240 = mul(x = mul_235, y = mul_240_y_0)[name = string("mul_240")];
            tensor<fp16, [88, 352]> tern_5_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4075584))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_5_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_5_k_bias_0 = const()[name = string("tern_5_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [8, 88]> tern_5_k = linear(bias = tern_5_k_bias_0, weight = tern_5_k_weight_0_palettized, x = mul_240)[name = string("tern_5_k")];
            tensor<fp16, [88]> mul_241_y_0 = const()[name = string("mul_241_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4083392)))];
            tensor<fp16, [8, 88]> mul_241 = mul(x = tern_5_k, y = mul_241_y_0)[name = string("mul_241")];
            tensor<int32, [3]> reshape_43_shape_0 = const()[name = string("reshape_43_shape_0"), val = tensor<int32, [3]>([8, 2, 44])];
            tensor<fp16, [8, 2, 44]> reshape_43 = reshape(shape = reshape_43_shape_0, x = mul_241)[name = string("reshape_43")];
            tensor<int32, [3]> transpose_21_perm_0 = const()[name = string("transpose_21_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_244_y_0 = const()[name = string("mul_244_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4083648)))];
            tensor<fp16, [8, 352]> mul_244 = mul(x = mul_235, y = mul_244_y_0)[name = string("mul_244")];
            tensor<fp16, [88, 352]> tern_5_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4084416))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_5_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_5_v_bias_0 = const()[name = string("tern_5_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [8, 88]> tern_5_v = linear(bias = tern_5_v_bias_0, weight = tern_5_v_weight_0_palettized, x = mul_244)[name = string("tern_5_v")];
            tensor<fp16, [88]> mul_245_y_0 = const()[name = string("mul_245_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4092224)))];
            tensor<fp16, [8, 88]> mul_245 = mul(x = tern_5_v, y = mul_245_y_0)[name = string("mul_245")];
            tensor<int32, [3]> reshape_44_shape_0 = const()[name = string("reshape_44_shape_0"), val = tensor<int32, [3]>([8, 2, 44])];
            tensor<fp16, [8, 2, 44]> reshape_44 = reshape(shape = reshape_44_shape_0, x = mul_245)[name = string("reshape_44")];
            tensor<int32, [3]> transpose_22_perm_0 = const()[name = string("transpose_22_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 8, 44]> transpose_20 = transpose(perm = transpose_20_perm_0, x = reshape_42)[name = string("transpose_43")];
            tensor<fp16, [8, 8, 44]> mul_246 = mul(x = transpose_20, y = transpose_20)[name = string("mul_246")];
            tensor<int32, [1]> reduce_mean_53_axes_0 = const()[name = string("reduce_mean_53_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_53_keep_dims_0 = const()[name = string("reduce_mean_53_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 8, 1]> reduce_mean_53 = reduce_mean(axes = reduce_mean_53_axes_0, keep_dims = reduce_mean_53_keep_dims_0, x = mul_246)[name = string("reduce_mean_53")];
            fp32 rsqrt_53_epsilon_0 = const()[name = string("rsqrt_53_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 8, 1]> rsqrt_53 = rsqrt(epsilon = rsqrt_53_epsilon_0, x = reduce_mean_53)[name = string("rsqrt_53")];
            tensor<fp16, [8, 8, 44]> mul_247 = mul(x = transpose_20, y = rsqrt_53)[name = string("mul_247")];
            tensor<fp16, [44]> mul_248_y_0 = const()[name = string("mul_248_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4092480)))];
            tensor<fp16, [8, 8, 44]> mul_248 = mul(x = mul_247, y = mul_248_y_0)[name = string("mul_248")];
            tensor<int32, [3]> slice_by_index_20_begin_0 = const()[name = string("slice_by_index_20_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_20_end_0 = const()[name = string("slice_by_index_20_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_20_end_mask_0 = const()[name = string("slice_by_index_20_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 8, 22]> slice_by_index_20 = slice_by_index(begin = slice_by_index_20_begin_0, end = slice_by_index_20_end_0, end_mask = slice_by_index_20_end_mask_0, x = mul_248)[name = string("slice_by_index_20")];
            tensor<int32, [3]> slice_by_index_21_begin_0 = const()[name = string("slice_by_index_21_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_21_end_0 = const()[name = string("slice_by_index_21_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_21_end_mask_0 = const()[name = string("slice_by_index_21_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 8, 22]> slice_by_index_21 = slice_by_index(begin = slice_by_index_21_begin_0, end = slice_by_index_21_end_0, end_mask = slice_by_index_21_end_mask_0, x = mul_248)[name = string("slice_by_index_21")];
            int32 concat_10_axis_0 = const()[name = string("concat_10_axis_0"), val = int32(-1)];
            bool concat_10_interleave_0 = const()[name = string("concat_10_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 8, 44]> concat_10 = concat(axis = concat_10_axis_0, interleave = concat_10_interleave_0, values = (slice_by_index_21, slice_by_index_20))[name = string("concat_10")];
            tensor<fp16, [44]> mul_249_y_0 = const()[name = string("mul_249_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 8, 44]> mul_249 = mul(x = concat_10, y = mul_249_y_0)[name = string("mul_249")];
            tensor<fp16, [8, 8, 44]> mul_250 = mul(x = mul_248, y = mul_11_y_0)[name = string("mul_250")];
            tensor<fp16, [8, 8, 44]> mul_251 = mul(x = mul_249, y = mul_12_y_0)[name = string("mul_251")];
            tensor<fp16, [8, 8, 44]> add_30 = add(x = mul_250, y = mul_251)[name = string("add_30")];
            tensor<fp16, [2, 8, 44]> transpose_21 = transpose(perm = transpose_21_perm_0, x = reshape_43)[name = string("transpose_42")];
            tensor<fp16, [2, 8, 44]> mul_252 = mul(x = transpose_21, y = transpose_21)[name = string("mul_252")];
            tensor<int32, [1]> reduce_mean_54_axes_0 = const()[name = string("reduce_mean_54_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_54_keep_dims_0 = const()[name = string("reduce_mean_54_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 8, 1]> reduce_mean_54 = reduce_mean(axes = reduce_mean_54_axes_0, keep_dims = reduce_mean_54_keep_dims_0, x = mul_252)[name = string("reduce_mean_54")];
            fp32 rsqrt_54_epsilon_0 = const()[name = string("rsqrt_54_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 8, 1]> rsqrt_54 = rsqrt(epsilon = rsqrt_54_epsilon_0, x = reduce_mean_54)[name = string("rsqrt_54")];
            tensor<fp16, [2, 8, 44]> mul_253 = mul(x = transpose_21, y = rsqrt_54)[name = string("mul_253")];
            tensor<fp16, [44]> mul_254_y_0 = const()[name = string("mul_254_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4092672)))];
            tensor<fp16, [2, 8, 44]> mul_254 = mul(x = mul_253, y = mul_254_y_0)[name = string("mul_254")];
            tensor<int32, [3]> slice_by_index_22_begin_0 = const()[name = string("slice_by_index_22_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_22_end_0 = const()[name = string("slice_by_index_22_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_22_end_mask_0 = const()[name = string("slice_by_index_22_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 8, 22]> slice_by_index_22 = slice_by_index(begin = slice_by_index_22_begin_0, end = slice_by_index_22_end_0, end_mask = slice_by_index_22_end_mask_0, x = mul_254)[name = string("slice_by_index_22")];
            tensor<int32, [3]> slice_by_index_23_begin_0 = const()[name = string("slice_by_index_23_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_23_end_0 = const()[name = string("slice_by_index_23_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_23_end_mask_0 = const()[name = string("slice_by_index_23_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 8, 22]> slice_by_index_23 = slice_by_index(begin = slice_by_index_23_begin_0, end = slice_by_index_23_end_0, end_mask = slice_by_index_23_end_mask_0, x = mul_254)[name = string("slice_by_index_23")];
            int32 concat_11_axis_0 = const()[name = string("concat_11_axis_0"), val = int32(-1)];
            bool concat_11_interleave_0 = const()[name = string("concat_11_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 8, 44]> concat_11 = concat(axis = concat_11_axis_0, interleave = concat_11_interleave_0, values = (slice_by_index_23, slice_by_index_22))[name = string("concat_11")];
            tensor<fp16, [44]> mul_255_y_0 = const()[name = string("mul_255_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 8, 44]> mul_255 = mul(x = concat_11, y = mul_255_y_0)[name = string("mul_255")];
            tensor<fp16, [2, 8, 44]> mul_256 = mul(x = mul_254, y = mul_11_y_0)[name = string("mul_256")];
            tensor<fp16, [2, 8, 44]> mul_257 = mul(x = mul_255, y = mul_12_y_0)[name = string("mul_257")];
            tensor<fp16, [2, 8, 44]> add_31 = add(x = mul_256, y = mul_257)[name = string("add_31")];
            tensor<int32, [4]> reshape_45_shape_0 = const()[name = string("reshape_45_shape_0"), val = tensor<int32, [4]>([2, 1, 8, 44])];
            tensor<fp16, [2, 1, 8, 44]> reshape_45 = reshape(shape = reshape_45_shape_0, x = add_31)[name = string("reshape_45")];
            tensor<int32, [4]> tile_10_reps_0 = const()[name = string("tile_10_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 8, 44]> tile_10 = tile(reps = tile_10_reps_0, x = reshape_45)[name = string("tile_10")];
            tensor<int32, [3]> reshape_46_shape_0 = const()[name = string("reshape_46_shape_0"), val = tensor<int32, [3]>([8, 8, 44])];
            tensor<fp16, [8, 8, 44]> reshape_46 = reshape(shape = reshape_46_shape_0, x = tile_10)[name = string("reshape_46")];
            tensor<int32, [4]> reshape_47_shape_0 = const()[name = string("reshape_47_shape_0"), val = tensor<int32, [4]>([2, 1, 8, 44])];
            tensor<fp16, [2, 8, 44]> transpose_22 = transpose(perm = transpose_22_perm_0, x = reshape_44)[name = string("transpose_41")];
            tensor<fp16, [2, 1, 8, 44]> reshape_47 = reshape(shape = reshape_47_shape_0, x = transpose_22)[name = string("reshape_47")];
            tensor<int32, [4]> tile_11_reps_0 = const()[name = string("tile_11_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 8, 44]> tile_11 = tile(reps = tile_11_reps_0, x = reshape_47)[name = string("tile_11")];
            tensor<int32, [3]> reshape_48_shape_0 = const()[name = string("reshape_48_shape_0"), val = tensor<int32, [3]>([8, 8, 44])];
            tensor<fp16, [8, 8, 44]> reshape_48 = reshape(shape = reshape_48_shape_0, x = tile_11)[name = string("reshape_48")];
            fp16 mul_258_y_0 = const()[name = string("mul_258_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 8, 44]> mul_258 = mul(x = add_30, y = mul_258_y_0)[name = string("mul_258")];
            bool matmul_10_transpose_y_0 = const()[name = string("matmul_10_transpose_y_0"), val = bool(true)];
            bool matmul_10_transpose_x_0 = const()[name = string("matmul_10_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 8, 8]> matmul_10 = matmul(transpose_x = matmul_10_transpose_x_0, transpose_y = matmul_10_transpose_y_0, x = mul_258, y = reshape_46)[name = string("matmul_10")];
            tensor<fp16, [8, 8, 8]> add_32 = add(x = matmul_10, y = reshape_1)[name = string("add_32")];
            int32 softmax_5_axis_0 = const()[name = string("softmax_5_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 8, 8]> softmax_5 = softmax(axis = softmax_5_axis_0, x = add_32)[name = string("softmax_5")];
            bool matmul_11_transpose_x_0 = const()[name = string("matmul_11_transpose_x_0"), val = bool(false)];
            bool matmul_11_transpose_y_0 = const()[name = string("matmul_11_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 8, 44]> matmul_11 = matmul(transpose_x = matmul_11_transpose_x_0, transpose_y = matmul_11_transpose_y_0, x = softmax_5, y = reshape_48)[name = string("matmul_11")];
            tensor<int32, [3]> transpose_23_perm_0 = const()[name = string("transpose_23_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_49_shape_0 = const()[name = string("reshape_49_shape_0"), val = tensor<int32, [2]>([8, 352])];
            tensor<fp16, [8, 8, 44]> transpose_23 = transpose(perm = transpose_23_perm_0, x = matmul_11)[name = string("transpose_40")];
            tensor<fp16, [8, 352]> reshape_49 = reshape(shape = reshape_49_shape_0, x = transpose_23)[name = string("reshape_49")];
            tensor<fp16, [8, 352]> mul_259 = mul(x = reshape_49, y = reshape_49)[name = string("mul_259")];
            tensor<int32, [1]> reduce_mean_55_axes_0 = const()[name = string("reduce_mean_55_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_55_keep_dims_0 = const()[name = string("reduce_mean_55_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_55 = reduce_mean(axes = reduce_mean_55_axes_0, keep_dims = reduce_mean_55_keep_dims_0, x = mul_259)[name = string("reduce_mean_55")];
            fp32 rsqrt_55_epsilon_0 = const()[name = string("rsqrt_55_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_55 = rsqrt(epsilon = rsqrt_55_epsilon_0, x = reduce_mean_55)[name = string("rsqrt_55")];
            tensor<fp16, [8, 352]> mul_260 = mul(x = reshape_49, y = rsqrt_55)[name = string("mul_260")];
            tensor<fp16, [352]> mul_261_y_0 = const()[name = string("mul_261_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4092864)))];
            tensor<fp16, [8, 352]> mul_261 = mul(x = mul_260, y = mul_261_y_0)[name = string("mul_261")];
            tensor<fp16, [352, 352]> tern_5_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4093632))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_5_o_weight_0_palettized")];
            tensor<fp16, [8, 352]> tern_5_o = linear(bias = linear_0_bias_0, weight = tern_5_o_weight_0_palettized, x = mul_261)[name = string("tern_5_o")];
            tensor<fp16, [352]> mul_262_y_0 = const()[name = string("mul_262_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4124672)))];
            tensor<fp16, [8, 352]> mul_262 = mul(x = tern_5_o, y = mul_262_y_0)[name = string("mul_262")];
            tensor<fp16, [8, 352]> add_33 = add(x = add_29, y = mul_262)[name = string("add_33")];
            tensor<fp16, [8, 352]> mul_263 = mul(x = add_33, y = add_33)[name = string("mul_263")];
            tensor<int32, [1]> reduce_mean_56_axes_0 = const()[name = string("reduce_mean_56_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_56_keep_dims_0 = const()[name = string("reduce_mean_56_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_56 = reduce_mean(axes = reduce_mean_56_axes_0, keep_dims = reduce_mean_56_keep_dims_0, x = mul_263)[name = string("reduce_mean_56")];
            fp32 rsqrt_56_epsilon_0 = const()[name = string("rsqrt_56_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_56 = rsqrt(epsilon = rsqrt_56_epsilon_0, x = reduce_mean_56)[name = string("rsqrt_56")];
            tensor<fp16, [8, 352]> mul_264 = mul(x = add_33, y = rsqrt_56)[name = string("mul_264")];
            tensor<fp16, [352]> mul_265_y_0 = const()[name = string("mul_265_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4125440)))];
            tensor<fp16, [8, 352]> mul_265 = mul(x = mul_264, y = mul_265_y_0)[name = string("mul_265")];
            tensor<fp16, [8, 352]> mul_266 = mul(x = mul_265, y = mul_265)[name = string("mul_266")];
            tensor<int32, [1]> reduce_mean_57_axes_0 = const()[name = string("reduce_mean_57_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_57_keep_dims_0 = const()[name = string("reduce_mean_57_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_57 = reduce_mean(axes = reduce_mean_57_axes_0, keep_dims = reduce_mean_57_keep_dims_0, x = mul_266)[name = string("reduce_mean_57")];
            fp32 rsqrt_57_epsilon_0 = const()[name = string("rsqrt_57_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_57 = rsqrt(epsilon = rsqrt_57_epsilon_0, x = reduce_mean_57)[name = string("rsqrt_57")];
            tensor<fp16, [8, 352]> mul_267 = mul(x = mul_265, y = rsqrt_57)[name = string("mul_267")];
            tensor<fp16, [352]> mul_268_y_0 = const()[name = string("mul_268_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4126208)))];
            tensor<fp16, [8, 352]> mul_268 = mul(x = mul_267, y = mul_268_y_0)[name = string("mul_268")];
            tensor<fp16, [960, 352]> tern_5_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4126976))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_5_w1_weight_0_palettized")];
            tensor<fp16, [8, 960]> tern_5_w1 = linear(bias = linear_4_bias_0, weight = tern_5_w1_weight_0_palettized, x = mul_268)[name = string("tern_5_w1")];
            tensor<fp16, [960]> mul_269_y_0 = const()[name = string("mul_269_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4211520)))];
            tensor<fp16, [8, 960]> mul_269 = mul(x = tern_5_w1, y = mul_269_y_0)[name = string("mul_269")];
            tensor<fp16, [352]> mul_272_y_0 = const()[name = string("mul_272_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4213504)))];
            tensor<fp16, [8, 352]> mul_272 = mul(x = mul_267, y = mul_272_y_0)[name = string("mul_272")];
            tensor<fp16, [960, 352]> tern_5_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4214272))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_5_w3_weight_0_palettized")];
            tensor<fp16, [8, 960]> tern_5_w3 = linear(bias = linear_4_bias_0, weight = tern_5_w3_weight_0_palettized, x = mul_272)[name = string("tern_5_w3")];
            tensor<fp16, [960]> mul_273_y_0 = const()[name = string("mul_273_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4298816)))];
            tensor<fp16, [8, 960]> mul_273 = mul(x = tern_5_w3, y = mul_273_y_0)[name = string("mul_273")];
            fp16 mul_274_y_0 = const()[name = string("mul_274_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [8, 960]> mul_274 = mul(x = mul_269, y = mul_274_y_0)[name = string("mul_274")];
            tensor<fp16, [8, 960]> tanh_5 = tanh(x = mul_274)[name = string("tanh_5")];
            fp16 mul_275_x_0 = const()[name = string("mul_275_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [8, 960]> mul_275 = mul(x = mul_275_x_0, y = tanh_5)[name = string("mul_275")];
            fp16 add_34_x_0 = const()[name = string("add_34_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [8, 960]> add_34 = add(x = add_34_x_0, y = mul_275)[name = string("add_34")];
            tensor<fp16, [8, 960]> mul_276 = mul(x = mul_269, y = add_34)[name = string("mul_276")];
            tensor<fp16, [8, 960]> mul_277 = mul(x = mul_276, y = mul_273)[name = string("mul_277")];
            tensor<fp16, [8, 960]> mul_278 = mul(x = mul_277, y = mul_277)[name = string("mul_278")];
            tensor<int32, [1]> reduce_mean_59_axes_0 = const()[name = string("reduce_mean_59_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_59_keep_dims_0 = const()[name = string("reduce_mean_59_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_59 = reduce_mean(axes = reduce_mean_59_axes_0, keep_dims = reduce_mean_59_keep_dims_0, x = mul_278)[name = string("reduce_mean_59")];
            fp32 rsqrt_59_epsilon_0 = const()[name = string("rsqrt_59_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_59 = rsqrt(epsilon = rsqrt_59_epsilon_0, x = reduce_mean_59)[name = string("rsqrt_59")];
            tensor<fp16, [8, 960]> mul_279 = mul(x = mul_277, y = rsqrt_59)[name = string("mul_279")];
            tensor<fp16, [960]> mul_280_y_0 = const()[name = string("mul_280_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4300800)))];
            tensor<fp16, [8, 960]> mul_280 = mul(x = mul_279, y = mul_280_y_0)[name = string("mul_280")];
            tensor<fp16, [352, 960]> tern_5_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4302784))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_5_w2_weight_0_palettized")];
            tensor<fp16, [8, 352]> tern_5_w2 = linear(bias = linear_0_bias_0, weight = tern_5_w2_weight_0_palettized, x = mul_280)[name = string("tern_5_w2")];
            tensor<fp16, [352]> mul_281_y_0 = const()[name = string("mul_281_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4387328)))];
            tensor<fp16, [8, 352]> mul_281 = mul(x = tern_5_w2, y = mul_281_y_0)[name = string("mul_281")];
            tensor<fp16, [8, 352]> add_35 = add(x = add_33, y = mul_281)[name = string("add_35")];
            tensor<fp16, [8, 352]> mul_282 = mul(x = add_35, y = add_35)[name = string("mul_282")];
            tensor<int32, [1]> reduce_mean_60_axes_0 = const()[name = string("reduce_mean_60_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_60_keep_dims_0 = const()[name = string("reduce_mean_60_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_60 = reduce_mean(axes = reduce_mean_60_axes_0, keep_dims = reduce_mean_60_keep_dims_0, x = mul_282)[name = string("reduce_mean_60")];
            fp32 rsqrt_60_epsilon_0 = const()[name = string("rsqrt_60_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_60 = rsqrt(epsilon = rsqrt_60_epsilon_0, x = reduce_mean_60)[name = string("rsqrt_60")];
            tensor<fp16, [8, 352]> mul_283 = mul(x = add_35, y = rsqrt_60)[name = string("mul_283")];
            tensor<fp16, [352]> mul_284_y_0 = const()[name = string("mul_284_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4388096)))];
            tensor<fp16, [8, 352]> mul_284 = mul(x = mul_283, y = mul_284_y_0)[name = string("mul_284")];
            tensor<fp16, [8, 352]> mul_285 = mul(x = mul_284, y = mul_284)[name = string("mul_285")];
            tensor<int32, [1]> reduce_mean_61_axes_0 = const()[name = string("reduce_mean_61_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_61_keep_dims_0 = const()[name = string("reduce_mean_61_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_61 = reduce_mean(axes = reduce_mean_61_axes_0, keep_dims = reduce_mean_61_keep_dims_0, x = mul_285)[name = string("reduce_mean_61")];
            fp32 rsqrt_61_epsilon_0 = const()[name = string("rsqrt_61_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_61 = rsqrt(epsilon = rsqrt_61_epsilon_0, x = reduce_mean_61)[name = string("rsqrt_61")];
            tensor<fp16, [8, 352]> mul_286 = mul(x = mul_284, y = rsqrt_61)[name = string("mul_286")];
            tensor<fp16, [352]> mul_287_y_0 = const()[name = string("mul_287_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4388864)))];
            tensor<fp16, [8, 352]> mul_287 = mul(x = mul_286, y = mul_287_y_0)[name = string("mul_287")];
            tensor<fp16, [352, 352]> tern_6_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4389632))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_6_q_weight_0_palettized")];
            tensor<fp16, [8, 352]> tern_6_q = linear(bias = linear_0_bias_0, weight = tern_6_q_weight_0_palettized, x = mul_287)[name = string("tern_6_q")];
            tensor<fp16, [352]> mul_288_y_0 = const()[name = string("mul_288_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4420672)))];
            tensor<fp16, [8, 352]> mul_288 = mul(x = tern_6_q, y = mul_288_y_0)[name = string("mul_288")];
            tensor<int32, [3]> reshape_50_shape_0 = const()[name = string("reshape_50_shape_0"), val = tensor<int32, [3]>([8, 8, 44])];
            tensor<fp16, [8, 8, 44]> reshape_50 = reshape(shape = reshape_50_shape_0, x = mul_288)[name = string("reshape_50")];
            tensor<int32, [3]> transpose_24_perm_0 = const()[name = string("transpose_24_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_291_y_0 = const()[name = string("mul_291_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4421440)))];
            tensor<fp16, [8, 352]> mul_291 = mul(x = mul_286, y = mul_291_y_0)[name = string("mul_291")];
            tensor<fp16, [88, 352]> tern_6_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4422208))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_6_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_6_k_bias_0 = const()[name = string("tern_6_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [8, 88]> tern_6_k = linear(bias = tern_6_k_bias_0, weight = tern_6_k_weight_0_palettized, x = mul_291)[name = string("tern_6_k")];
            tensor<fp16, [88]> mul_292_y_0 = const()[name = string("mul_292_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4430016)))];
            tensor<fp16, [8, 88]> mul_292 = mul(x = tern_6_k, y = mul_292_y_0)[name = string("mul_292")];
            tensor<int32, [3]> reshape_51_shape_0 = const()[name = string("reshape_51_shape_0"), val = tensor<int32, [3]>([8, 2, 44])];
            tensor<fp16, [8, 2, 44]> reshape_51 = reshape(shape = reshape_51_shape_0, x = mul_292)[name = string("reshape_51")];
            tensor<int32, [3]> transpose_25_perm_0 = const()[name = string("transpose_25_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_295_y_0 = const()[name = string("mul_295_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4430272)))];
            tensor<fp16, [8, 352]> mul_295 = mul(x = mul_286, y = mul_295_y_0)[name = string("mul_295")];
            tensor<fp16, [88, 352]> tern_6_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4431040))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_6_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_6_v_bias_0 = const()[name = string("tern_6_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [8, 88]> tern_6_v = linear(bias = tern_6_v_bias_0, weight = tern_6_v_weight_0_palettized, x = mul_295)[name = string("tern_6_v")];
            tensor<fp16, [88]> mul_296_y_0 = const()[name = string("mul_296_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4438848)))];
            tensor<fp16, [8, 88]> mul_296 = mul(x = tern_6_v, y = mul_296_y_0)[name = string("mul_296")];
            tensor<int32, [3]> reshape_52_shape_0 = const()[name = string("reshape_52_shape_0"), val = tensor<int32, [3]>([8, 2, 44])];
            tensor<fp16, [8, 2, 44]> reshape_52 = reshape(shape = reshape_52_shape_0, x = mul_296)[name = string("reshape_52")];
            tensor<int32, [3]> transpose_26_perm_0 = const()[name = string("transpose_26_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 8, 44]> transpose_24 = transpose(perm = transpose_24_perm_0, x = reshape_50)[name = string("transpose_39")];
            tensor<fp16, [8, 8, 44]> mul_297 = mul(x = transpose_24, y = transpose_24)[name = string("mul_297")];
            tensor<int32, [1]> reduce_mean_64_axes_0 = const()[name = string("reduce_mean_64_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_64_keep_dims_0 = const()[name = string("reduce_mean_64_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 8, 1]> reduce_mean_64 = reduce_mean(axes = reduce_mean_64_axes_0, keep_dims = reduce_mean_64_keep_dims_0, x = mul_297)[name = string("reduce_mean_64")];
            fp32 rsqrt_64_epsilon_0 = const()[name = string("rsqrt_64_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 8, 1]> rsqrt_64 = rsqrt(epsilon = rsqrt_64_epsilon_0, x = reduce_mean_64)[name = string("rsqrt_64")];
            tensor<fp16, [8, 8, 44]> mul_298 = mul(x = transpose_24, y = rsqrt_64)[name = string("mul_298")];
            tensor<fp16, [44]> mul_299_y_0 = const()[name = string("mul_299_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4439104)))];
            tensor<fp16, [8, 8, 44]> mul_299 = mul(x = mul_298, y = mul_299_y_0)[name = string("mul_299")];
            tensor<int32, [3]> slice_by_index_24_begin_0 = const()[name = string("slice_by_index_24_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_24_end_0 = const()[name = string("slice_by_index_24_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_24_end_mask_0 = const()[name = string("slice_by_index_24_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 8, 22]> slice_by_index_24 = slice_by_index(begin = slice_by_index_24_begin_0, end = slice_by_index_24_end_0, end_mask = slice_by_index_24_end_mask_0, x = mul_299)[name = string("slice_by_index_24")];
            tensor<int32, [3]> slice_by_index_25_begin_0 = const()[name = string("slice_by_index_25_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_25_end_0 = const()[name = string("slice_by_index_25_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_25_end_mask_0 = const()[name = string("slice_by_index_25_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 8, 22]> slice_by_index_25 = slice_by_index(begin = slice_by_index_25_begin_0, end = slice_by_index_25_end_0, end_mask = slice_by_index_25_end_mask_0, x = mul_299)[name = string("slice_by_index_25")];
            int32 concat_12_axis_0 = const()[name = string("concat_12_axis_0"), val = int32(-1)];
            bool concat_12_interleave_0 = const()[name = string("concat_12_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 8, 44]> concat_12 = concat(axis = concat_12_axis_0, interleave = concat_12_interleave_0, values = (slice_by_index_25, slice_by_index_24))[name = string("concat_12")];
            tensor<fp16, [44]> mul_300_y_0 = const()[name = string("mul_300_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 8, 44]> mul_300 = mul(x = concat_12, y = mul_300_y_0)[name = string("mul_300")];
            tensor<fp16, [8, 8, 44]> mul_301 = mul(x = mul_299, y = mul_11_y_0)[name = string("mul_301")];
            tensor<fp16, [8, 8, 44]> mul_302 = mul(x = mul_300, y = mul_12_y_0)[name = string("mul_302")];
            tensor<fp16, [8, 8, 44]> add_36 = add(x = mul_301, y = mul_302)[name = string("add_36")];
            tensor<fp16, [2, 8, 44]> transpose_25 = transpose(perm = transpose_25_perm_0, x = reshape_51)[name = string("transpose_38")];
            tensor<fp16, [2, 8, 44]> mul_303 = mul(x = transpose_25, y = transpose_25)[name = string("mul_303")];
            tensor<int32, [1]> reduce_mean_65_axes_0 = const()[name = string("reduce_mean_65_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_65_keep_dims_0 = const()[name = string("reduce_mean_65_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 8, 1]> reduce_mean_65 = reduce_mean(axes = reduce_mean_65_axes_0, keep_dims = reduce_mean_65_keep_dims_0, x = mul_303)[name = string("reduce_mean_65")];
            fp32 rsqrt_65_epsilon_0 = const()[name = string("rsqrt_65_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 8, 1]> rsqrt_65 = rsqrt(epsilon = rsqrt_65_epsilon_0, x = reduce_mean_65)[name = string("rsqrt_65")];
            tensor<fp16, [2, 8, 44]> mul_304 = mul(x = transpose_25, y = rsqrt_65)[name = string("mul_304")];
            tensor<fp16, [44]> mul_305_y_0 = const()[name = string("mul_305_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4439296)))];
            tensor<fp16, [2, 8, 44]> mul_305 = mul(x = mul_304, y = mul_305_y_0)[name = string("mul_305")];
            tensor<int32, [3]> slice_by_index_26_begin_0 = const()[name = string("slice_by_index_26_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_26_end_0 = const()[name = string("slice_by_index_26_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_26_end_mask_0 = const()[name = string("slice_by_index_26_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 8, 22]> slice_by_index_26 = slice_by_index(begin = slice_by_index_26_begin_0, end = slice_by_index_26_end_0, end_mask = slice_by_index_26_end_mask_0, x = mul_305)[name = string("slice_by_index_26")];
            tensor<int32, [3]> slice_by_index_27_begin_0 = const()[name = string("slice_by_index_27_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_27_end_0 = const()[name = string("slice_by_index_27_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_27_end_mask_0 = const()[name = string("slice_by_index_27_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 8, 22]> slice_by_index_27 = slice_by_index(begin = slice_by_index_27_begin_0, end = slice_by_index_27_end_0, end_mask = slice_by_index_27_end_mask_0, x = mul_305)[name = string("slice_by_index_27")];
            int32 concat_13_axis_0 = const()[name = string("concat_13_axis_0"), val = int32(-1)];
            bool concat_13_interleave_0 = const()[name = string("concat_13_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 8, 44]> concat_13 = concat(axis = concat_13_axis_0, interleave = concat_13_interleave_0, values = (slice_by_index_27, slice_by_index_26))[name = string("concat_13")];
            tensor<fp16, [44]> mul_306_y_0 = const()[name = string("mul_306_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 8, 44]> mul_306 = mul(x = concat_13, y = mul_306_y_0)[name = string("mul_306")];
            tensor<fp16, [2, 8, 44]> mul_307 = mul(x = mul_305, y = mul_11_y_0)[name = string("mul_307")];
            tensor<fp16, [2, 8, 44]> mul_308 = mul(x = mul_306, y = mul_12_y_0)[name = string("mul_308")];
            tensor<fp16, [2, 8, 44]> add_37 = add(x = mul_307, y = mul_308)[name = string("add_37")];
            tensor<int32, [4]> reshape_53_shape_0 = const()[name = string("reshape_53_shape_0"), val = tensor<int32, [4]>([2, 1, 8, 44])];
            tensor<fp16, [2, 1, 8, 44]> reshape_53 = reshape(shape = reshape_53_shape_0, x = add_37)[name = string("reshape_53")];
            tensor<int32, [4]> tile_12_reps_0 = const()[name = string("tile_12_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 8, 44]> tile_12 = tile(reps = tile_12_reps_0, x = reshape_53)[name = string("tile_12")];
            tensor<int32, [3]> reshape_54_shape_0 = const()[name = string("reshape_54_shape_0"), val = tensor<int32, [3]>([8, 8, 44])];
            tensor<fp16, [8, 8, 44]> reshape_54 = reshape(shape = reshape_54_shape_0, x = tile_12)[name = string("reshape_54")];
            tensor<int32, [4]> reshape_55_shape_0 = const()[name = string("reshape_55_shape_0"), val = tensor<int32, [4]>([2, 1, 8, 44])];
            tensor<fp16, [2, 8, 44]> transpose_26 = transpose(perm = transpose_26_perm_0, x = reshape_52)[name = string("transpose_37")];
            tensor<fp16, [2, 1, 8, 44]> reshape_55 = reshape(shape = reshape_55_shape_0, x = transpose_26)[name = string("reshape_55")];
            tensor<int32, [4]> tile_13_reps_0 = const()[name = string("tile_13_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 8, 44]> tile_13 = tile(reps = tile_13_reps_0, x = reshape_55)[name = string("tile_13")];
            tensor<int32, [3]> reshape_56_shape_0 = const()[name = string("reshape_56_shape_0"), val = tensor<int32, [3]>([8, 8, 44])];
            tensor<fp16, [8, 8, 44]> reshape_56 = reshape(shape = reshape_56_shape_0, x = tile_13)[name = string("reshape_56")];
            fp16 mul_309_y_0 = const()[name = string("mul_309_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 8, 44]> mul_309 = mul(x = add_36, y = mul_309_y_0)[name = string("mul_309")];
            bool matmul_12_transpose_y_0 = const()[name = string("matmul_12_transpose_y_0"), val = bool(true)];
            bool matmul_12_transpose_x_0 = const()[name = string("matmul_12_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 8, 8]> matmul_12 = matmul(transpose_x = matmul_12_transpose_x_0, transpose_y = matmul_12_transpose_y_0, x = mul_309, y = reshape_54)[name = string("matmul_12")];
            tensor<fp16, [8, 8, 8]> add_38 = add(x = matmul_12, y = reshape_1)[name = string("add_38")];
            int32 softmax_6_axis_0 = const()[name = string("softmax_6_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 8, 8]> softmax_6 = softmax(axis = softmax_6_axis_0, x = add_38)[name = string("softmax_6")];
            bool matmul_13_transpose_x_0 = const()[name = string("matmul_13_transpose_x_0"), val = bool(false)];
            bool matmul_13_transpose_y_0 = const()[name = string("matmul_13_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 8, 44]> matmul_13 = matmul(transpose_x = matmul_13_transpose_x_0, transpose_y = matmul_13_transpose_y_0, x = softmax_6, y = reshape_56)[name = string("matmul_13")];
            tensor<int32, [3]> transpose_27_perm_0 = const()[name = string("transpose_27_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_57_shape_0 = const()[name = string("reshape_57_shape_0"), val = tensor<int32, [2]>([8, 352])];
            tensor<fp16, [8, 8, 44]> transpose_27 = transpose(perm = transpose_27_perm_0, x = matmul_13)[name = string("transpose_36")];
            tensor<fp16, [8, 352]> reshape_57 = reshape(shape = reshape_57_shape_0, x = transpose_27)[name = string("reshape_57")];
            tensor<fp16, [8, 352]> mul_310 = mul(x = reshape_57, y = reshape_57)[name = string("mul_310")];
            tensor<int32, [1]> reduce_mean_66_axes_0 = const()[name = string("reduce_mean_66_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_66_keep_dims_0 = const()[name = string("reduce_mean_66_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_66 = reduce_mean(axes = reduce_mean_66_axes_0, keep_dims = reduce_mean_66_keep_dims_0, x = mul_310)[name = string("reduce_mean_66")];
            fp32 rsqrt_66_epsilon_0 = const()[name = string("rsqrt_66_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_66 = rsqrt(epsilon = rsqrt_66_epsilon_0, x = reduce_mean_66)[name = string("rsqrt_66")];
            tensor<fp16, [8, 352]> mul_311 = mul(x = reshape_57, y = rsqrt_66)[name = string("mul_311")];
            tensor<fp16, [352]> mul_312_y_0 = const()[name = string("mul_312_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4439488)))];
            tensor<fp16, [8, 352]> mul_312 = mul(x = mul_311, y = mul_312_y_0)[name = string("mul_312")];
            tensor<fp16, [352, 352]> tern_6_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4440256))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_6_o_weight_0_palettized")];
            tensor<fp16, [8, 352]> tern_6_o = linear(bias = linear_0_bias_0, weight = tern_6_o_weight_0_palettized, x = mul_312)[name = string("tern_6_o")];
            tensor<fp16, [352]> mul_313_y_0 = const()[name = string("mul_313_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4471296)))];
            tensor<fp16, [8, 352]> mul_313 = mul(x = tern_6_o, y = mul_313_y_0)[name = string("mul_313")];
            tensor<fp16, [8, 352]> add_39 = add(x = add_35, y = mul_313)[name = string("add_39")];
            tensor<fp16, [8, 352]> mul_314 = mul(x = add_39, y = add_39)[name = string("mul_314")];
            tensor<int32, [1]> reduce_mean_67_axes_0 = const()[name = string("reduce_mean_67_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_67_keep_dims_0 = const()[name = string("reduce_mean_67_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_67 = reduce_mean(axes = reduce_mean_67_axes_0, keep_dims = reduce_mean_67_keep_dims_0, x = mul_314)[name = string("reduce_mean_67")];
            fp32 rsqrt_67_epsilon_0 = const()[name = string("rsqrt_67_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_67 = rsqrt(epsilon = rsqrt_67_epsilon_0, x = reduce_mean_67)[name = string("rsqrt_67")];
            tensor<fp16, [8, 352]> mul_315 = mul(x = add_39, y = rsqrt_67)[name = string("mul_315")];
            tensor<fp16, [352]> mul_316_y_0 = const()[name = string("mul_316_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4472064)))];
            tensor<fp16, [8, 352]> mul_316 = mul(x = mul_315, y = mul_316_y_0)[name = string("mul_316")];
            tensor<fp16, [8, 352]> mul_317 = mul(x = mul_316, y = mul_316)[name = string("mul_317")];
            tensor<int32, [1]> reduce_mean_68_axes_0 = const()[name = string("reduce_mean_68_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_68_keep_dims_0 = const()[name = string("reduce_mean_68_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_68 = reduce_mean(axes = reduce_mean_68_axes_0, keep_dims = reduce_mean_68_keep_dims_0, x = mul_317)[name = string("reduce_mean_68")];
            fp32 rsqrt_68_epsilon_0 = const()[name = string("rsqrt_68_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_68 = rsqrt(epsilon = rsqrt_68_epsilon_0, x = reduce_mean_68)[name = string("rsqrt_68")];
            tensor<fp16, [8, 352]> mul_318 = mul(x = mul_316, y = rsqrt_68)[name = string("mul_318")];
            tensor<fp16, [352]> mul_319_y_0 = const()[name = string("mul_319_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4472832)))];
            tensor<fp16, [8, 352]> mul_319 = mul(x = mul_318, y = mul_319_y_0)[name = string("mul_319")];
            tensor<fp16, [960, 352]> tern_6_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4473600))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_6_w1_weight_0_palettized")];
            tensor<fp16, [8, 960]> tern_6_w1 = linear(bias = linear_4_bias_0, weight = tern_6_w1_weight_0_palettized, x = mul_319)[name = string("tern_6_w1")];
            tensor<fp16, [960]> mul_320_y_0 = const()[name = string("mul_320_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4558144)))];
            tensor<fp16, [8, 960]> mul_320 = mul(x = tern_6_w1, y = mul_320_y_0)[name = string("mul_320")];
            tensor<fp16, [352]> mul_323_y_0 = const()[name = string("mul_323_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4560128)))];
            tensor<fp16, [8, 352]> mul_323 = mul(x = mul_318, y = mul_323_y_0)[name = string("mul_323")];
            tensor<fp16, [960, 352]> tern_6_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4560896))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_6_w3_weight_0_palettized")];
            tensor<fp16, [8, 960]> tern_6_w3 = linear(bias = linear_4_bias_0, weight = tern_6_w3_weight_0_palettized, x = mul_323)[name = string("tern_6_w3")];
            tensor<fp16, [960]> mul_324_y_0 = const()[name = string("mul_324_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4645440)))];
            tensor<fp16, [8, 960]> mul_324 = mul(x = tern_6_w3, y = mul_324_y_0)[name = string("mul_324")];
            fp16 mul_325_y_0 = const()[name = string("mul_325_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [8, 960]> mul_325 = mul(x = mul_320, y = mul_325_y_0)[name = string("mul_325")];
            tensor<fp16, [8, 960]> tanh_6 = tanh(x = mul_325)[name = string("tanh_6")];
            fp16 mul_326_x_0 = const()[name = string("mul_326_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [8, 960]> mul_326 = mul(x = mul_326_x_0, y = tanh_6)[name = string("mul_326")];
            fp16 add_40_x_0 = const()[name = string("add_40_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [8, 960]> add_40 = add(x = add_40_x_0, y = mul_326)[name = string("add_40")];
            tensor<fp16, [8, 960]> mul_327 = mul(x = mul_320, y = add_40)[name = string("mul_327")];
            tensor<fp16, [8, 960]> mul_328 = mul(x = mul_327, y = mul_324)[name = string("mul_328")];
            tensor<fp16, [8, 960]> mul_329 = mul(x = mul_328, y = mul_328)[name = string("mul_329")];
            tensor<int32, [1]> reduce_mean_70_axes_0 = const()[name = string("reduce_mean_70_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_70_keep_dims_0 = const()[name = string("reduce_mean_70_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_70 = reduce_mean(axes = reduce_mean_70_axes_0, keep_dims = reduce_mean_70_keep_dims_0, x = mul_329)[name = string("reduce_mean_70")];
            fp32 rsqrt_70_epsilon_0 = const()[name = string("rsqrt_70_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_70 = rsqrt(epsilon = rsqrt_70_epsilon_0, x = reduce_mean_70)[name = string("rsqrt_70")];
            tensor<fp16, [8, 960]> mul_330 = mul(x = mul_328, y = rsqrt_70)[name = string("mul_330")];
            tensor<fp16, [960]> mul_331_y_0 = const()[name = string("mul_331_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4647424)))];
            tensor<fp16, [8, 960]> mul_331 = mul(x = mul_330, y = mul_331_y_0)[name = string("mul_331")];
            tensor<fp16, [352, 960]> tern_6_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4649408))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_6_w2_weight_0_palettized")];
            tensor<fp16, [8, 352]> tern_6_w2 = linear(bias = linear_0_bias_0, weight = tern_6_w2_weight_0_palettized, x = mul_331)[name = string("tern_6_w2")];
            tensor<fp16, [352]> mul_332_y_0 = const()[name = string("mul_332_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4733952)))];
            tensor<fp16, [8, 352]> mul_332 = mul(x = tern_6_w2, y = mul_332_y_0)[name = string("mul_332")];
            tensor<fp16, [8, 352]> add_41 = add(x = add_39, y = mul_332)[name = string("add_41")];
            tensor<fp16, [8, 352]> mul_333 = mul(x = add_41, y = add_41)[name = string("mul_333")];
            tensor<int32, [1]> reduce_mean_71_axes_0 = const()[name = string("reduce_mean_71_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_71_keep_dims_0 = const()[name = string("reduce_mean_71_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_71 = reduce_mean(axes = reduce_mean_71_axes_0, keep_dims = reduce_mean_71_keep_dims_0, x = mul_333)[name = string("reduce_mean_71")];
            fp32 rsqrt_71_epsilon_0 = const()[name = string("rsqrt_71_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_71 = rsqrt(epsilon = rsqrt_71_epsilon_0, x = reduce_mean_71)[name = string("rsqrt_71")];
            tensor<fp16, [8, 352]> mul_334 = mul(x = add_41, y = rsqrt_71)[name = string("mul_334")];
            tensor<fp16, [352]> mul_335_y_0 = const()[name = string("mul_335_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4734720)))];
            tensor<fp16, [8, 352]> mul_335 = mul(x = mul_334, y = mul_335_y_0)[name = string("mul_335")];
            tensor<fp16, [8, 352]> mul_336 = mul(x = mul_335, y = mul_335)[name = string("mul_336")];
            tensor<int32, [1]> reduce_mean_72_axes_0 = const()[name = string("reduce_mean_72_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_72_keep_dims_0 = const()[name = string("reduce_mean_72_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_72 = reduce_mean(axes = reduce_mean_72_axes_0, keep_dims = reduce_mean_72_keep_dims_0, x = mul_336)[name = string("reduce_mean_72")];
            fp32 rsqrt_72_epsilon_0 = const()[name = string("rsqrt_72_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_72 = rsqrt(epsilon = rsqrt_72_epsilon_0, x = reduce_mean_72)[name = string("rsqrt_72")];
            tensor<fp16, [8, 352]> mul_337 = mul(x = mul_335, y = rsqrt_72)[name = string("mul_337")];
            tensor<fp16, [352]> mul_338_y_0 = const()[name = string("mul_338_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4735488)))];
            tensor<fp16, [8, 352]> mul_338 = mul(x = mul_337, y = mul_338_y_0)[name = string("mul_338")];
            tensor<fp16, [352, 352]> tern_7_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4736256))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_7_q_weight_0_palettized")];
            tensor<fp16, [8, 352]> tern_7_q = linear(bias = linear_0_bias_0, weight = tern_7_q_weight_0_palettized, x = mul_338)[name = string("tern_7_q")];
            tensor<fp16, [352]> mul_339_y_0 = const()[name = string("mul_339_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4767296)))];
            tensor<fp16, [8, 352]> mul_339 = mul(x = tern_7_q, y = mul_339_y_0)[name = string("mul_339")];
            tensor<int32, [3]> reshape_58_shape_0 = const()[name = string("reshape_58_shape_0"), val = tensor<int32, [3]>([8, 8, 44])];
            tensor<fp16, [8, 8, 44]> reshape_58 = reshape(shape = reshape_58_shape_0, x = mul_339)[name = string("reshape_58")];
            tensor<int32, [3]> transpose_28_perm_0 = const()[name = string("transpose_28_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_342_y_0 = const()[name = string("mul_342_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4768064)))];
            tensor<fp16, [8, 352]> mul_342 = mul(x = mul_337, y = mul_342_y_0)[name = string("mul_342")];
            tensor<fp16, [88, 352]> tern_7_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4768832))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_7_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_7_k_bias_0 = const()[name = string("tern_7_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [8, 88]> tern_7_k = linear(bias = tern_7_k_bias_0, weight = tern_7_k_weight_0_palettized, x = mul_342)[name = string("tern_7_k")];
            tensor<fp16, [88]> mul_343_y_0 = const()[name = string("mul_343_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4776640)))];
            tensor<fp16, [8, 88]> mul_343 = mul(x = tern_7_k, y = mul_343_y_0)[name = string("mul_343")];
            tensor<int32, [3]> reshape_59_shape_0 = const()[name = string("reshape_59_shape_0"), val = tensor<int32, [3]>([8, 2, 44])];
            tensor<fp16, [8, 2, 44]> reshape_59 = reshape(shape = reshape_59_shape_0, x = mul_343)[name = string("reshape_59")];
            tensor<int32, [3]> transpose_29_perm_0 = const()[name = string("transpose_29_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_346_y_0 = const()[name = string("mul_346_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4776896)))];
            tensor<fp16, [8, 352]> mul_346 = mul(x = mul_337, y = mul_346_y_0)[name = string("mul_346")];
            tensor<fp16, [88, 352]> tern_7_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4777664))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_7_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_7_v_bias_0 = const()[name = string("tern_7_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [8, 88]> tern_7_v = linear(bias = tern_7_v_bias_0, weight = tern_7_v_weight_0_palettized, x = mul_346)[name = string("tern_7_v")];
            tensor<fp16, [88]> mul_347_y_0 = const()[name = string("mul_347_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4785472)))];
            tensor<fp16, [8, 88]> mul_347 = mul(x = tern_7_v, y = mul_347_y_0)[name = string("mul_347")];
            tensor<int32, [3]> reshape_60_shape_0 = const()[name = string("reshape_60_shape_0"), val = tensor<int32, [3]>([8, 2, 44])];
            tensor<fp16, [8, 2, 44]> reshape_60 = reshape(shape = reshape_60_shape_0, x = mul_347)[name = string("reshape_60")];
            tensor<int32, [3]> transpose_30_perm_0 = const()[name = string("transpose_30_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 8, 44]> transpose_28 = transpose(perm = transpose_28_perm_0, x = reshape_58)[name = string("transpose_35")];
            tensor<fp16, [8, 8, 44]> mul_348 = mul(x = transpose_28, y = transpose_28)[name = string("mul_348")];
            tensor<int32, [1]> reduce_mean_75_axes_0 = const()[name = string("reduce_mean_75_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_75_keep_dims_0 = const()[name = string("reduce_mean_75_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 8, 1]> reduce_mean_75 = reduce_mean(axes = reduce_mean_75_axes_0, keep_dims = reduce_mean_75_keep_dims_0, x = mul_348)[name = string("reduce_mean_75")];
            fp32 rsqrt_75_epsilon_0 = const()[name = string("rsqrt_75_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 8, 1]> rsqrt_75 = rsqrt(epsilon = rsqrt_75_epsilon_0, x = reduce_mean_75)[name = string("rsqrt_75")];
            tensor<fp16, [8, 8, 44]> mul_349 = mul(x = transpose_28, y = rsqrt_75)[name = string("mul_349")];
            tensor<fp16, [44]> mul_350_y_0 = const()[name = string("mul_350_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4785728)))];
            tensor<fp16, [8, 8, 44]> mul_350 = mul(x = mul_349, y = mul_350_y_0)[name = string("mul_350")];
            tensor<int32, [3]> slice_by_index_28_begin_0 = const()[name = string("slice_by_index_28_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_28_end_0 = const()[name = string("slice_by_index_28_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_28_end_mask_0 = const()[name = string("slice_by_index_28_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 8, 22]> slice_by_index_28 = slice_by_index(begin = slice_by_index_28_begin_0, end = slice_by_index_28_end_0, end_mask = slice_by_index_28_end_mask_0, x = mul_350)[name = string("slice_by_index_28")];
            tensor<int32, [3]> slice_by_index_29_begin_0 = const()[name = string("slice_by_index_29_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_29_end_0 = const()[name = string("slice_by_index_29_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_29_end_mask_0 = const()[name = string("slice_by_index_29_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 8, 22]> slice_by_index_29 = slice_by_index(begin = slice_by_index_29_begin_0, end = slice_by_index_29_end_0, end_mask = slice_by_index_29_end_mask_0, x = mul_350)[name = string("slice_by_index_29")];
            int32 concat_14_axis_0 = const()[name = string("concat_14_axis_0"), val = int32(-1)];
            bool concat_14_interleave_0 = const()[name = string("concat_14_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 8, 44]> concat_14 = concat(axis = concat_14_axis_0, interleave = concat_14_interleave_0, values = (slice_by_index_29, slice_by_index_28))[name = string("concat_14")];
            tensor<fp16, [44]> mul_351_y_0 = const()[name = string("mul_351_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 8, 44]> mul_351 = mul(x = concat_14, y = mul_351_y_0)[name = string("mul_351")];
            tensor<fp16, [8, 8, 44]> mul_352 = mul(x = mul_350, y = mul_11_y_0)[name = string("mul_352")];
            tensor<fp16, [8, 8, 44]> mul_353 = mul(x = mul_351, y = mul_12_y_0)[name = string("mul_353")];
            tensor<fp16, [8, 8, 44]> add_42 = add(x = mul_352, y = mul_353)[name = string("add_42")];
            tensor<fp16, [2, 8, 44]> transpose_29 = transpose(perm = transpose_29_perm_0, x = reshape_59)[name = string("transpose_34")];
            tensor<fp16, [2, 8, 44]> mul_354 = mul(x = transpose_29, y = transpose_29)[name = string("mul_354")];
            tensor<int32, [1]> reduce_mean_76_axes_0 = const()[name = string("reduce_mean_76_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_76_keep_dims_0 = const()[name = string("reduce_mean_76_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 8, 1]> reduce_mean_76 = reduce_mean(axes = reduce_mean_76_axes_0, keep_dims = reduce_mean_76_keep_dims_0, x = mul_354)[name = string("reduce_mean_76")];
            fp32 rsqrt_76_epsilon_0 = const()[name = string("rsqrt_76_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 8, 1]> rsqrt_76 = rsqrt(epsilon = rsqrt_76_epsilon_0, x = reduce_mean_76)[name = string("rsqrt_76")];
            tensor<fp16, [2, 8, 44]> mul_355 = mul(x = transpose_29, y = rsqrt_76)[name = string("mul_355")];
            tensor<fp16, [44]> mul_356_y_0 = const()[name = string("mul_356_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4785920)))];
            tensor<fp16, [2, 8, 44]> mul_356 = mul(x = mul_355, y = mul_356_y_0)[name = string("mul_356")];
            tensor<int32, [3]> slice_by_index_30_begin_0 = const()[name = string("slice_by_index_30_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_30_end_0 = const()[name = string("slice_by_index_30_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_30_end_mask_0 = const()[name = string("slice_by_index_30_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 8, 22]> slice_by_index_30 = slice_by_index(begin = slice_by_index_30_begin_0, end = slice_by_index_30_end_0, end_mask = slice_by_index_30_end_mask_0, x = mul_356)[name = string("slice_by_index_30")];
            tensor<int32, [3]> slice_by_index_31_begin_0 = const()[name = string("slice_by_index_31_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_31_end_0 = const()[name = string("slice_by_index_31_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_31_end_mask_0 = const()[name = string("slice_by_index_31_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 8, 22]> slice_by_index_31 = slice_by_index(begin = slice_by_index_31_begin_0, end = slice_by_index_31_end_0, end_mask = slice_by_index_31_end_mask_0, x = mul_356)[name = string("slice_by_index_31")];
            int32 concat_15_axis_0 = const()[name = string("concat_15_axis_0"), val = int32(-1)];
            bool concat_15_interleave_0 = const()[name = string("concat_15_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 8, 44]> concat_15 = concat(axis = concat_15_axis_0, interleave = concat_15_interleave_0, values = (slice_by_index_31, slice_by_index_30))[name = string("concat_15")];
            tensor<fp16, [44]> mul_357_y_0 = const()[name = string("mul_357_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 8, 44]> mul_357 = mul(x = concat_15, y = mul_357_y_0)[name = string("mul_357")];
            tensor<fp16, [2, 8, 44]> mul_358 = mul(x = mul_356, y = mul_11_y_0)[name = string("mul_358")];
            tensor<fp16, [2, 8, 44]> mul_359 = mul(x = mul_357, y = mul_12_y_0)[name = string("mul_359")];
            tensor<fp16, [2, 8, 44]> add_43 = add(x = mul_358, y = mul_359)[name = string("add_43")];
            tensor<int32, [4]> reshape_61_shape_0 = const()[name = string("reshape_61_shape_0"), val = tensor<int32, [4]>([2, 1, 8, 44])];
            tensor<fp16, [2, 1, 8, 44]> reshape_61 = reshape(shape = reshape_61_shape_0, x = add_43)[name = string("reshape_61")];
            tensor<int32, [4]> tile_14_reps_0 = const()[name = string("tile_14_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 8, 44]> tile_14 = tile(reps = tile_14_reps_0, x = reshape_61)[name = string("tile_14")];
            tensor<int32, [3]> reshape_62_shape_0 = const()[name = string("reshape_62_shape_0"), val = tensor<int32, [3]>([8, 8, 44])];
            tensor<fp16, [8, 8, 44]> reshape_62 = reshape(shape = reshape_62_shape_0, x = tile_14)[name = string("reshape_62")];
            tensor<int32, [4]> reshape_63_shape_0 = const()[name = string("reshape_63_shape_0"), val = tensor<int32, [4]>([2, 1, 8, 44])];
            tensor<fp16, [2, 8, 44]> transpose_30 = transpose(perm = transpose_30_perm_0, x = reshape_60)[name = string("transpose_33")];
            tensor<fp16, [2, 1, 8, 44]> reshape_63 = reshape(shape = reshape_63_shape_0, x = transpose_30)[name = string("reshape_63")];
            tensor<int32, [4]> tile_15_reps_0 = const()[name = string("tile_15_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 8, 44]> tile_15 = tile(reps = tile_15_reps_0, x = reshape_63)[name = string("tile_15")];
            tensor<int32, [3]> reshape_64_shape_0 = const()[name = string("reshape_64_shape_0"), val = tensor<int32, [3]>([8, 8, 44])];
            tensor<fp16, [8, 8, 44]> reshape_64 = reshape(shape = reshape_64_shape_0, x = tile_15)[name = string("reshape_64")];
            fp16 mul_360_y_0 = const()[name = string("mul_360_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 8, 44]> mul_360 = mul(x = add_42, y = mul_360_y_0)[name = string("mul_360")];
            bool matmul_14_transpose_y_0 = const()[name = string("matmul_14_transpose_y_0"), val = bool(true)];
            bool matmul_14_transpose_x_0 = const()[name = string("matmul_14_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 8, 8]> matmul_14 = matmul(transpose_x = matmul_14_transpose_x_0, transpose_y = matmul_14_transpose_y_0, x = mul_360, y = reshape_62)[name = string("matmul_14")];
            tensor<fp16, [8, 8, 8]> add_44 = add(x = matmul_14, y = reshape_1)[name = string("add_44")];
            int32 softmax_7_axis_0 = const()[name = string("softmax_7_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 8, 8]> softmax_7 = softmax(axis = softmax_7_axis_0, x = add_44)[name = string("softmax_7")];
            bool matmul_15_transpose_x_0 = const()[name = string("matmul_15_transpose_x_0"), val = bool(false)];
            bool matmul_15_transpose_y_0 = const()[name = string("matmul_15_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 8, 44]> matmul_15 = matmul(transpose_x = matmul_15_transpose_x_0, transpose_y = matmul_15_transpose_y_0, x = softmax_7, y = reshape_64)[name = string("matmul_15")];
            tensor<int32, [3]> transpose_31_perm_0 = const()[name = string("transpose_31_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_65_shape_0 = const()[name = string("reshape_65_shape_0"), val = tensor<int32, [2]>([8, 352])];
            tensor<fp16, [8, 8, 44]> transpose_31 = transpose(perm = transpose_31_perm_0, x = matmul_15)[name = string("transpose_32")];
            tensor<fp16, [8, 352]> reshape_65 = reshape(shape = reshape_65_shape_0, x = transpose_31)[name = string("reshape_65")];
            tensor<fp16, [8, 352]> mul_361 = mul(x = reshape_65, y = reshape_65)[name = string("mul_361")];
            tensor<int32, [1]> reduce_mean_77_axes_0 = const()[name = string("reduce_mean_77_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_77_keep_dims_0 = const()[name = string("reduce_mean_77_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_77 = reduce_mean(axes = reduce_mean_77_axes_0, keep_dims = reduce_mean_77_keep_dims_0, x = mul_361)[name = string("reduce_mean_77")];
            fp32 rsqrt_77_epsilon_0 = const()[name = string("rsqrt_77_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_77 = rsqrt(epsilon = rsqrt_77_epsilon_0, x = reduce_mean_77)[name = string("rsqrt_77")];
            tensor<fp16, [8, 352]> mul_362 = mul(x = reshape_65, y = rsqrt_77)[name = string("mul_362")];
            tensor<fp16, [352]> mul_363_y_0 = const()[name = string("mul_363_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4786112)))];
            tensor<fp16, [8, 352]> mul_363 = mul(x = mul_362, y = mul_363_y_0)[name = string("mul_363")];
            tensor<fp16, [352, 352]> tern_7_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4786880))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_7_o_weight_0_palettized")];
            tensor<fp16, [8, 352]> tern_7_o = linear(bias = linear_0_bias_0, weight = tern_7_o_weight_0_palettized, x = mul_363)[name = string("tern_7_o")];
            tensor<fp16, [352]> mul_364_y_0 = const()[name = string("mul_364_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4817920)))];
            tensor<fp16, [8, 352]> mul_364 = mul(x = tern_7_o, y = mul_364_y_0)[name = string("mul_364")];
            tensor<fp16, [8, 352]> add_45 = add(x = add_41, y = mul_364)[name = string("add_45")];
            tensor<fp16, [8, 352]> mul_365 = mul(x = add_45, y = add_45)[name = string("mul_365")];
            tensor<int32, [1]> reduce_mean_78_axes_0 = const()[name = string("reduce_mean_78_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_78_keep_dims_0 = const()[name = string("reduce_mean_78_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_78 = reduce_mean(axes = reduce_mean_78_axes_0, keep_dims = reduce_mean_78_keep_dims_0, x = mul_365)[name = string("reduce_mean_78")];
            fp32 rsqrt_78_epsilon_0 = const()[name = string("rsqrt_78_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_78 = rsqrt(epsilon = rsqrt_78_epsilon_0, x = reduce_mean_78)[name = string("rsqrt_78")];
            tensor<fp16, [8, 352]> mul_366 = mul(x = add_45, y = rsqrt_78)[name = string("mul_366")];
            tensor<fp16, [352]> mul_367_y_0 = const()[name = string("mul_367_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4818688)))];
            tensor<fp16, [8, 352]> mul_367 = mul(x = mul_366, y = mul_367_y_0)[name = string("mul_367")];
            tensor<fp16, [8, 352]> mul_368 = mul(x = mul_367, y = mul_367)[name = string("mul_368")];
            tensor<int32, [1]> reduce_mean_79_axes_0 = const()[name = string("reduce_mean_79_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_79_keep_dims_0 = const()[name = string("reduce_mean_79_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_79 = reduce_mean(axes = reduce_mean_79_axes_0, keep_dims = reduce_mean_79_keep_dims_0, x = mul_368)[name = string("reduce_mean_79")];
            fp32 rsqrt_79_epsilon_0 = const()[name = string("rsqrt_79_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_79 = rsqrt(epsilon = rsqrt_79_epsilon_0, x = reduce_mean_79)[name = string("rsqrt_79")];
            tensor<fp16, [8, 352]> mul_369 = mul(x = mul_367, y = rsqrt_79)[name = string("mul_369")];
            tensor<fp16, [352]> mul_370_y_0 = const()[name = string("mul_370_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4819456)))];
            tensor<fp16, [8, 352]> mul_370 = mul(x = mul_369, y = mul_370_y_0)[name = string("mul_370")];
            tensor<fp16, [960, 352]> tern_7_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4820224))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_7_w1_weight_0_palettized")];
            tensor<fp16, [8, 960]> tern_7_w1 = linear(bias = linear_4_bias_0, weight = tern_7_w1_weight_0_palettized, x = mul_370)[name = string("tern_7_w1")];
            tensor<fp16, [960]> mul_371_y_0 = const()[name = string("mul_371_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4904768)))];
            tensor<fp16, [8, 960]> mul_371 = mul(x = tern_7_w1, y = mul_371_y_0)[name = string("mul_371")];
            tensor<fp16, [352]> mul_374_y_0 = const()[name = string("mul_374_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4906752)))];
            tensor<fp16, [8, 352]> mul_374 = mul(x = mul_369, y = mul_374_y_0)[name = string("mul_374")];
            tensor<fp16, [960, 352]> tern_7_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4907520))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_7_w3_weight_0_palettized")];
            tensor<fp16, [8, 960]> tern_7_w3 = linear(bias = linear_4_bias_0, weight = tern_7_w3_weight_0_palettized, x = mul_374)[name = string("tern_7_w3")];
            tensor<fp16, [960]> mul_375_y_0 = const()[name = string("mul_375_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4992064)))];
            tensor<fp16, [8, 960]> mul_375 = mul(x = tern_7_w3, y = mul_375_y_0)[name = string("mul_375")];
            fp16 mul_376_y_0 = const()[name = string("mul_376_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [8, 960]> mul_376 = mul(x = mul_371, y = mul_376_y_0)[name = string("mul_376")];
            tensor<fp16, [8, 960]> tanh_7 = tanh(x = mul_376)[name = string("tanh_7")];
            fp16 mul_377_x_0 = const()[name = string("mul_377_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [8, 960]> mul_377 = mul(x = mul_377_x_0, y = tanh_7)[name = string("mul_377")];
            fp16 add_46_x_0 = const()[name = string("add_46_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [8, 960]> add_46 = add(x = add_46_x_0, y = mul_377)[name = string("add_46")];
            tensor<fp16, [8, 960]> mul_378 = mul(x = mul_371, y = add_46)[name = string("mul_378")];
            tensor<fp16, [8, 960]> mul_379 = mul(x = mul_378, y = mul_375)[name = string("mul_379")];
            tensor<fp16, [8, 960]> mul_380 = mul(x = mul_379, y = mul_379)[name = string("mul_380")];
            tensor<int32, [1]> reduce_mean_81_axes_0 = const()[name = string("reduce_mean_81_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_81_keep_dims_0 = const()[name = string("reduce_mean_81_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_81 = reduce_mean(axes = reduce_mean_81_axes_0, keep_dims = reduce_mean_81_keep_dims_0, x = mul_380)[name = string("reduce_mean_81")];
            fp32 rsqrt_81_epsilon_0 = const()[name = string("rsqrt_81_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_81 = rsqrt(epsilon = rsqrt_81_epsilon_0, x = reduce_mean_81)[name = string("rsqrt_81")];
            tensor<fp16, [8, 960]> mul_381 = mul(x = mul_379, y = rsqrt_81)[name = string("mul_381")];
            tensor<fp16, [960]> mul_382_y_0 = const()[name = string("mul_382_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4994048)))];
            tensor<fp16, [8, 960]> mul_382 = mul(x = mul_381, y = mul_382_y_0)[name = string("mul_382")];
            tensor<fp16, [352, 960]> tern_7_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4996032))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_7_w2_weight_0_palettized")];
            tensor<fp16, [8, 352]> tern_7_w2 = linear(bias = linear_0_bias_0, weight = tern_7_w2_weight_0_palettized, x = mul_382)[name = string("tern_7_w2")];
            tensor<fp16, [352]> mul_383_y_0 = const()[name = string("mul_383_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5080576)))];
            tensor<fp16, [8, 352]> mul_383 = mul(x = tern_7_w2, y = mul_383_y_0)[name = string("mul_383")];
            tensor<fp16, [8, 352]> add_47 = add(x = add_45, y = mul_383)[name = string("add_47")];
            tensor<fp16, [8, 352]> mul_384 = mul(x = add_47, y = add_47)[name = string("mul_384")];
            tensor<int32, [1]> reduce_mean_82_axes_0 = const()[name = string("reduce_mean_82_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_82_keep_dims_0 = const()[name = string("reduce_mean_82_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_82 = reduce_mean(axes = reduce_mean_82_axes_0, keep_dims = reduce_mean_82_keep_dims_0, x = mul_384)[name = string("reduce_mean_82")];
            fp32 rsqrt_82_epsilon_0 = const()[name = string("rsqrt_82_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_82 = rsqrt(epsilon = rsqrt_82_epsilon_0, x = reduce_mean_82)[name = string("rsqrt_82")];
            tensor<fp16, [8, 352]> mul_385 = mul(x = add_47, y = rsqrt_82)[name = string("mul_385")];
            tensor<fp16, [352]> mul_386_y_0 = const()[name = string("mul_386_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5081344)))];
            tensor<fp16, [8, 352]> mul_386 = mul(x = mul_385, y = mul_386_y_0)[name = string("mul_386")];
            tensor<fp16, [8, 352]> mul_387 = mul(x = mul_386, y = mul_386)[name = string("mul_387")];
            tensor<int32, [1]> reduce_mean_83_axes_0 = const()[name = string("reduce_mean_83_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_83_keep_dims_0 = const()[name = string("reduce_mean_83_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_83 = reduce_mean(axes = reduce_mean_83_axes_0, keep_dims = reduce_mean_83_keep_dims_0, x = mul_387)[name = string("reduce_mean_83")];
            fp32 rsqrt_83_epsilon_0 = const()[name = string("rsqrt_83_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_83 = rsqrt(epsilon = rsqrt_83_epsilon_0, x = reduce_mean_83)[name = string("rsqrt_83")];
            tensor<fp16, [8, 352]> mul_388 = mul(x = mul_386, y = rsqrt_83)[name = string("mul_388")];
            tensor<fp16, [352]> mul_389_y_0 = const()[name = string("mul_389_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5082112)))];
            tensor<fp16, [8, 352]> mul_389 = mul(x = mul_388, y = mul_389_y_0)[name = string("mul_389")];
            tensor<fp16, [352, 352]> tern_8_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5082880))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_8_q_weight_0_palettized")];
            tensor<fp16, [8, 352]> tern_8_q = linear(bias = linear_0_bias_0, weight = tern_8_q_weight_0_palettized, x = mul_389)[name = string("tern_8_q")];
            tensor<fp16, [352]> mul_390_y_0 = const()[name = string("mul_390_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5113920)))];
            tensor<fp16, [8, 352]> mul_390 = mul(x = tern_8_q, y = mul_390_y_0)[name = string("mul_390")];
            tensor<int32, [3]> reshape_66_shape_0 = const()[name = string("reshape_66_shape_0"), val = tensor<int32, [3]>([8, 8, 44])];
            tensor<fp16, [8, 8, 44]> reshape_66 = reshape(shape = reshape_66_shape_0, x = mul_390)[name = string("reshape_66")];
            tensor<int32, [3]> transpose_32_perm_0 = const()[name = string("transpose_32_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_393_y_0 = const()[name = string("mul_393_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5114688)))];
            tensor<fp16, [8, 352]> mul_393 = mul(x = mul_388, y = mul_393_y_0)[name = string("mul_393")];
            tensor<fp16, [88, 352]> tern_8_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5115456))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_8_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_8_k_bias_0 = const()[name = string("tern_8_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [8, 88]> tern_8_k = linear(bias = tern_8_k_bias_0, weight = tern_8_k_weight_0_palettized, x = mul_393)[name = string("tern_8_k")];
            tensor<fp16, [88]> mul_394_y_0 = const()[name = string("mul_394_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5123264)))];
            tensor<fp16, [8, 88]> mul_394 = mul(x = tern_8_k, y = mul_394_y_0)[name = string("mul_394")];
            tensor<int32, [3]> reshape_67_shape_0 = const()[name = string("reshape_67_shape_0"), val = tensor<int32, [3]>([8, 2, 44])];
            tensor<fp16, [8, 2, 44]> reshape_67 = reshape(shape = reshape_67_shape_0, x = mul_394)[name = string("reshape_67")];
            tensor<int32, [3]> transpose_33_perm_0 = const()[name = string("transpose_33_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_397_y_0 = const()[name = string("mul_397_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5123520)))];
            tensor<fp16, [8, 352]> mul_397 = mul(x = mul_388, y = mul_397_y_0)[name = string("mul_397")];
            tensor<fp16, [88, 352]> tern_8_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5124288))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_8_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_8_v_bias_0 = const()[name = string("tern_8_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [8, 88]> tern_8_v = linear(bias = tern_8_v_bias_0, weight = tern_8_v_weight_0_palettized, x = mul_397)[name = string("tern_8_v")];
            tensor<fp16, [88]> mul_398_y_0 = const()[name = string("mul_398_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5132096)))];
            tensor<fp16, [8, 88]> mul_398 = mul(x = tern_8_v, y = mul_398_y_0)[name = string("mul_398")];
            tensor<int32, [3]> reshape_68_shape_0 = const()[name = string("reshape_68_shape_0"), val = tensor<int32, [3]>([8, 2, 44])];
            tensor<fp16, [8, 2, 44]> reshape_68 = reshape(shape = reshape_68_shape_0, x = mul_398)[name = string("reshape_68")];
            tensor<int32, [3]> transpose_34_perm_0 = const()[name = string("transpose_34_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 8, 44]> transpose_32 = transpose(perm = transpose_32_perm_0, x = reshape_66)[name = string("transpose_31")];
            tensor<fp16, [8, 8, 44]> mul_399 = mul(x = transpose_32, y = transpose_32)[name = string("mul_399")];
            tensor<int32, [1]> reduce_mean_86_axes_0 = const()[name = string("reduce_mean_86_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_86_keep_dims_0 = const()[name = string("reduce_mean_86_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 8, 1]> reduce_mean_86 = reduce_mean(axes = reduce_mean_86_axes_0, keep_dims = reduce_mean_86_keep_dims_0, x = mul_399)[name = string("reduce_mean_86")];
            fp32 rsqrt_86_epsilon_0 = const()[name = string("rsqrt_86_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 8, 1]> rsqrt_86 = rsqrt(epsilon = rsqrt_86_epsilon_0, x = reduce_mean_86)[name = string("rsqrt_86")];
            tensor<fp16, [8, 8, 44]> mul_400 = mul(x = transpose_32, y = rsqrt_86)[name = string("mul_400")];
            tensor<fp16, [44]> mul_401_y_0 = const()[name = string("mul_401_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5132352)))];
            tensor<fp16, [8, 8, 44]> mul_401 = mul(x = mul_400, y = mul_401_y_0)[name = string("mul_401")];
            tensor<int32, [3]> slice_by_index_32_begin_0 = const()[name = string("slice_by_index_32_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_32_end_0 = const()[name = string("slice_by_index_32_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_32_end_mask_0 = const()[name = string("slice_by_index_32_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 8, 22]> slice_by_index_32 = slice_by_index(begin = slice_by_index_32_begin_0, end = slice_by_index_32_end_0, end_mask = slice_by_index_32_end_mask_0, x = mul_401)[name = string("slice_by_index_32")];
            tensor<int32, [3]> slice_by_index_33_begin_0 = const()[name = string("slice_by_index_33_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_33_end_0 = const()[name = string("slice_by_index_33_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_33_end_mask_0 = const()[name = string("slice_by_index_33_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 8, 22]> slice_by_index_33 = slice_by_index(begin = slice_by_index_33_begin_0, end = slice_by_index_33_end_0, end_mask = slice_by_index_33_end_mask_0, x = mul_401)[name = string("slice_by_index_33")];
            int32 concat_16_axis_0 = const()[name = string("concat_16_axis_0"), val = int32(-1)];
            bool concat_16_interleave_0 = const()[name = string("concat_16_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 8, 44]> concat_16 = concat(axis = concat_16_axis_0, interleave = concat_16_interleave_0, values = (slice_by_index_33, slice_by_index_32))[name = string("concat_16")];
            tensor<fp16, [44]> mul_402_y_0 = const()[name = string("mul_402_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 8, 44]> mul_402 = mul(x = concat_16, y = mul_402_y_0)[name = string("mul_402")];
            tensor<fp16, [8, 8, 44]> mul_403 = mul(x = mul_401, y = mul_11_y_0)[name = string("mul_403")];
            tensor<fp16, [8, 8, 44]> mul_404 = mul(x = mul_402, y = mul_12_y_0)[name = string("mul_404")];
            tensor<fp16, [8, 8, 44]> add_48 = add(x = mul_403, y = mul_404)[name = string("add_48")];
            tensor<fp16, [2, 8, 44]> transpose_33 = transpose(perm = transpose_33_perm_0, x = reshape_67)[name = string("transpose_30")];
            tensor<fp16, [2, 8, 44]> mul_405 = mul(x = transpose_33, y = transpose_33)[name = string("mul_405")];
            tensor<int32, [1]> reduce_mean_87_axes_0 = const()[name = string("reduce_mean_87_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_87_keep_dims_0 = const()[name = string("reduce_mean_87_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 8, 1]> reduce_mean_87 = reduce_mean(axes = reduce_mean_87_axes_0, keep_dims = reduce_mean_87_keep_dims_0, x = mul_405)[name = string("reduce_mean_87")];
            fp32 rsqrt_87_epsilon_0 = const()[name = string("rsqrt_87_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 8, 1]> rsqrt_87 = rsqrt(epsilon = rsqrt_87_epsilon_0, x = reduce_mean_87)[name = string("rsqrt_87")];
            tensor<fp16, [2, 8, 44]> mul_406 = mul(x = transpose_33, y = rsqrt_87)[name = string("mul_406")];
            tensor<fp16, [44]> mul_407_y_0 = const()[name = string("mul_407_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5132544)))];
            tensor<fp16, [2, 8, 44]> mul_407 = mul(x = mul_406, y = mul_407_y_0)[name = string("mul_407")];
            tensor<int32, [3]> slice_by_index_34_begin_0 = const()[name = string("slice_by_index_34_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_34_end_0 = const()[name = string("slice_by_index_34_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_34_end_mask_0 = const()[name = string("slice_by_index_34_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 8, 22]> slice_by_index_34 = slice_by_index(begin = slice_by_index_34_begin_0, end = slice_by_index_34_end_0, end_mask = slice_by_index_34_end_mask_0, x = mul_407)[name = string("slice_by_index_34")];
            tensor<int32, [3]> slice_by_index_35_begin_0 = const()[name = string("slice_by_index_35_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_35_end_0 = const()[name = string("slice_by_index_35_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_35_end_mask_0 = const()[name = string("slice_by_index_35_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 8, 22]> slice_by_index_35 = slice_by_index(begin = slice_by_index_35_begin_0, end = slice_by_index_35_end_0, end_mask = slice_by_index_35_end_mask_0, x = mul_407)[name = string("slice_by_index_35")];
            int32 concat_17_axis_0 = const()[name = string("concat_17_axis_0"), val = int32(-1)];
            bool concat_17_interleave_0 = const()[name = string("concat_17_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 8, 44]> concat_17 = concat(axis = concat_17_axis_0, interleave = concat_17_interleave_0, values = (slice_by_index_35, slice_by_index_34))[name = string("concat_17")];
            tensor<fp16, [44]> mul_408_y_0 = const()[name = string("mul_408_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 8, 44]> mul_408 = mul(x = concat_17, y = mul_408_y_0)[name = string("mul_408")];
            tensor<fp16, [2, 8, 44]> mul_409 = mul(x = mul_407, y = mul_11_y_0)[name = string("mul_409")];
            tensor<fp16, [2, 8, 44]> mul_410 = mul(x = mul_408, y = mul_12_y_0)[name = string("mul_410")];
            tensor<fp16, [2, 8, 44]> add_49 = add(x = mul_409, y = mul_410)[name = string("add_49")];
            tensor<int32, [4]> reshape_69_shape_0 = const()[name = string("reshape_69_shape_0"), val = tensor<int32, [4]>([2, 1, 8, 44])];
            tensor<fp16, [2, 1, 8, 44]> reshape_69 = reshape(shape = reshape_69_shape_0, x = add_49)[name = string("reshape_69")];
            tensor<int32, [4]> tile_16_reps_0 = const()[name = string("tile_16_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 8, 44]> tile_16 = tile(reps = tile_16_reps_0, x = reshape_69)[name = string("tile_16")];
            tensor<int32, [3]> reshape_70_shape_0 = const()[name = string("reshape_70_shape_0"), val = tensor<int32, [3]>([8, 8, 44])];
            tensor<fp16, [8, 8, 44]> reshape_70 = reshape(shape = reshape_70_shape_0, x = tile_16)[name = string("reshape_70")];
            tensor<int32, [4]> reshape_71_shape_0 = const()[name = string("reshape_71_shape_0"), val = tensor<int32, [4]>([2, 1, 8, 44])];
            tensor<fp16, [2, 8, 44]> transpose_34 = transpose(perm = transpose_34_perm_0, x = reshape_68)[name = string("transpose_29")];
            tensor<fp16, [2, 1, 8, 44]> reshape_71 = reshape(shape = reshape_71_shape_0, x = transpose_34)[name = string("reshape_71")];
            tensor<int32, [4]> tile_17_reps_0 = const()[name = string("tile_17_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 8, 44]> tile_17 = tile(reps = tile_17_reps_0, x = reshape_71)[name = string("tile_17")];
            tensor<int32, [3]> reshape_72_shape_0 = const()[name = string("reshape_72_shape_0"), val = tensor<int32, [3]>([8, 8, 44])];
            tensor<fp16, [8, 8, 44]> reshape_72 = reshape(shape = reshape_72_shape_0, x = tile_17)[name = string("reshape_72")];
            fp16 mul_411_y_0 = const()[name = string("mul_411_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 8, 44]> mul_411 = mul(x = add_48, y = mul_411_y_0)[name = string("mul_411")];
            bool matmul_16_transpose_y_0 = const()[name = string("matmul_16_transpose_y_0"), val = bool(true)];
            bool matmul_16_transpose_x_0 = const()[name = string("matmul_16_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 8, 8]> matmul_16 = matmul(transpose_x = matmul_16_transpose_x_0, transpose_y = matmul_16_transpose_y_0, x = mul_411, y = reshape_70)[name = string("matmul_16")];
            tensor<fp16, [8, 8, 8]> add_50 = add(x = matmul_16, y = reshape_1)[name = string("add_50")];
            int32 softmax_8_axis_0 = const()[name = string("softmax_8_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 8, 8]> softmax_8 = softmax(axis = softmax_8_axis_0, x = add_50)[name = string("softmax_8")];
            bool matmul_17_transpose_x_0 = const()[name = string("matmul_17_transpose_x_0"), val = bool(false)];
            bool matmul_17_transpose_y_0 = const()[name = string("matmul_17_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 8, 44]> matmul_17 = matmul(transpose_x = matmul_17_transpose_x_0, transpose_y = matmul_17_transpose_y_0, x = softmax_8, y = reshape_72)[name = string("matmul_17")];
            tensor<int32, [3]> transpose_35_perm_0 = const()[name = string("transpose_35_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_73_shape_0 = const()[name = string("reshape_73_shape_0"), val = tensor<int32, [2]>([8, 352])];
            tensor<fp16, [8, 8, 44]> transpose_35 = transpose(perm = transpose_35_perm_0, x = matmul_17)[name = string("transpose_28")];
            tensor<fp16, [8, 352]> reshape_73 = reshape(shape = reshape_73_shape_0, x = transpose_35)[name = string("reshape_73")];
            tensor<fp16, [8, 352]> mul_412 = mul(x = reshape_73, y = reshape_73)[name = string("mul_412")];
            tensor<int32, [1]> reduce_mean_88_axes_0 = const()[name = string("reduce_mean_88_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_88_keep_dims_0 = const()[name = string("reduce_mean_88_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_88 = reduce_mean(axes = reduce_mean_88_axes_0, keep_dims = reduce_mean_88_keep_dims_0, x = mul_412)[name = string("reduce_mean_88")];
            fp32 rsqrt_88_epsilon_0 = const()[name = string("rsqrt_88_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_88 = rsqrt(epsilon = rsqrt_88_epsilon_0, x = reduce_mean_88)[name = string("rsqrt_88")];
            tensor<fp16, [8, 352]> mul_413 = mul(x = reshape_73, y = rsqrt_88)[name = string("mul_413")];
            tensor<fp16, [352]> mul_414_y_0 = const()[name = string("mul_414_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5132736)))];
            tensor<fp16, [8, 352]> mul_414 = mul(x = mul_413, y = mul_414_y_0)[name = string("mul_414")];
            tensor<fp16, [352, 352]> tern_8_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5133504))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_8_o_weight_0_palettized")];
            tensor<fp16, [8, 352]> tern_8_o = linear(bias = linear_0_bias_0, weight = tern_8_o_weight_0_palettized, x = mul_414)[name = string("tern_8_o")];
            tensor<fp16, [352]> mul_415_y_0 = const()[name = string("mul_415_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5164544)))];
            tensor<fp16, [8, 352]> mul_415 = mul(x = tern_8_o, y = mul_415_y_0)[name = string("mul_415")];
            tensor<fp16, [8, 352]> add_51 = add(x = add_47, y = mul_415)[name = string("add_51")];
            tensor<fp16, [8, 352]> mul_416 = mul(x = add_51, y = add_51)[name = string("mul_416")];
            tensor<int32, [1]> reduce_mean_89_axes_0 = const()[name = string("reduce_mean_89_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_89_keep_dims_0 = const()[name = string("reduce_mean_89_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_89 = reduce_mean(axes = reduce_mean_89_axes_0, keep_dims = reduce_mean_89_keep_dims_0, x = mul_416)[name = string("reduce_mean_89")];
            fp32 rsqrt_89_epsilon_0 = const()[name = string("rsqrt_89_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_89 = rsqrt(epsilon = rsqrt_89_epsilon_0, x = reduce_mean_89)[name = string("rsqrt_89")];
            tensor<fp16, [8, 352]> mul_417 = mul(x = add_51, y = rsqrt_89)[name = string("mul_417")];
            tensor<fp16, [352]> mul_418_y_0 = const()[name = string("mul_418_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5165312)))];
            tensor<fp16, [8, 352]> mul_418 = mul(x = mul_417, y = mul_418_y_0)[name = string("mul_418")];
            tensor<fp16, [8, 352]> mul_419 = mul(x = mul_418, y = mul_418)[name = string("mul_419")];
            tensor<int32, [1]> reduce_mean_90_axes_0 = const()[name = string("reduce_mean_90_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_90_keep_dims_0 = const()[name = string("reduce_mean_90_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_90 = reduce_mean(axes = reduce_mean_90_axes_0, keep_dims = reduce_mean_90_keep_dims_0, x = mul_419)[name = string("reduce_mean_90")];
            fp32 rsqrt_90_epsilon_0 = const()[name = string("rsqrt_90_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_90 = rsqrt(epsilon = rsqrt_90_epsilon_0, x = reduce_mean_90)[name = string("rsqrt_90")];
            tensor<fp16, [8, 352]> mul_420 = mul(x = mul_418, y = rsqrt_90)[name = string("mul_420")];
            tensor<fp16, [352]> mul_421_y_0 = const()[name = string("mul_421_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5166080)))];
            tensor<fp16, [8, 352]> mul_421 = mul(x = mul_420, y = mul_421_y_0)[name = string("mul_421")];
            tensor<fp16, [960, 352]> tern_8_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5166848))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_8_w1_weight_0_palettized")];
            tensor<fp16, [8, 960]> tern_8_w1 = linear(bias = linear_4_bias_0, weight = tern_8_w1_weight_0_palettized, x = mul_421)[name = string("tern_8_w1")];
            tensor<fp16, [960]> mul_422_y_0 = const()[name = string("mul_422_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5251392)))];
            tensor<fp16, [8, 960]> mul_422 = mul(x = tern_8_w1, y = mul_422_y_0)[name = string("mul_422")];
            tensor<fp16, [352]> mul_425_y_0 = const()[name = string("mul_425_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5253376)))];
            tensor<fp16, [8, 352]> mul_425 = mul(x = mul_420, y = mul_425_y_0)[name = string("mul_425")];
            tensor<fp16, [960, 352]> tern_8_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5254144))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_8_w3_weight_0_palettized")];
            tensor<fp16, [8, 960]> tern_8_w3 = linear(bias = linear_4_bias_0, weight = tern_8_w3_weight_0_palettized, x = mul_425)[name = string("tern_8_w3")];
            tensor<fp16, [960]> mul_426_y_0 = const()[name = string("mul_426_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5338688)))];
            tensor<fp16, [8, 960]> mul_426 = mul(x = tern_8_w3, y = mul_426_y_0)[name = string("mul_426")];
            fp16 mul_427_y_0 = const()[name = string("mul_427_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [8, 960]> mul_427 = mul(x = mul_422, y = mul_427_y_0)[name = string("mul_427")];
            tensor<fp16, [8, 960]> tanh_8 = tanh(x = mul_427)[name = string("tanh_8")];
            fp16 mul_428_x_0 = const()[name = string("mul_428_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [8, 960]> mul_428 = mul(x = mul_428_x_0, y = tanh_8)[name = string("mul_428")];
            fp16 add_52_x_0 = const()[name = string("add_52_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [8, 960]> add_52 = add(x = add_52_x_0, y = mul_428)[name = string("add_52")];
            tensor<fp16, [8, 960]> mul_429 = mul(x = mul_422, y = add_52)[name = string("mul_429")];
            tensor<fp16, [8, 960]> mul_430 = mul(x = mul_429, y = mul_426)[name = string("mul_430")];
            tensor<fp16, [8, 960]> mul_431 = mul(x = mul_430, y = mul_430)[name = string("mul_431")];
            tensor<int32, [1]> reduce_mean_92_axes_0 = const()[name = string("reduce_mean_92_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_92_keep_dims_0 = const()[name = string("reduce_mean_92_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_92 = reduce_mean(axes = reduce_mean_92_axes_0, keep_dims = reduce_mean_92_keep_dims_0, x = mul_431)[name = string("reduce_mean_92")];
            fp32 rsqrt_92_epsilon_0 = const()[name = string("rsqrt_92_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_92 = rsqrt(epsilon = rsqrt_92_epsilon_0, x = reduce_mean_92)[name = string("rsqrt_92")];
            tensor<fp16, [8, 960]> mul_432 = mul(x = mul_430, y = rsqrt_92)[name = string("mul_432")];
            tensor<fp16, [960]> mul_433_y_0 = const()[name = string("mul_433_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5340672)))];
            tensor<fp16, [8, 960]> mul_433 = mul(x = mul_432, y = mul_433_y_0)[name = string("mul_433")];
            tensor<fp16, [352, 960]> tern_8_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5342656))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_8_w2_weight_0_palettized")];
            tensor<fp16, [8, 352]> tern_8_w2 = linear(bias = linear_0_bias_0, weight = tern_8_w2_weight_0_palettized, x = mul_433)[name = string("tern_8_w2")];
            tensor<fp16, [352]> mul_434_y_0 = const()[name = string("mul_434_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5427200)))];
            tensor<fp16, [8, 352]> mul_434 = mul(x = tern_8_w2, y = mul_434_y_0)[name = string("mul_434")];
            tensor<fp16, [8, 352]> add_53 = add(x = add_51, y = mul_434)[name = string("add_53")];
            tensor<fp16, [8, 352]> mul_435 = mul(x = add_53, y = add_53)[name = string("mul_435")];
            tensor<int32, [1]> reduce_mean_93_axes_0 = const()[name = string("reduce_mean_93_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_93_keep_dims_0 = const()[name = string("reduce_mean_93_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_93 = reduce_mean(axes = reduce_mean_93_axes_0, keep_dims = reduce_mean_93_keep_dims_0, x = mul_435)[name = string("reduce_mean_93")];
            fp32 rsqrt_93_epsilon_0 = const()[name = string("rsqrt_93_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_93 = rsqrt(epsilon = rsqrt_93_epsilon_0, x = reduce_mean_93)[name = string("rsqrt_93")];
            tensor<fp16, [8, 352]> mul_436 = mul(x = add_53, y = rsqrt_93)[name = string("mul_436")];
            tensor<fp16, [352]> mul_437_y_0 = const()[name = string("mul_437_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5427968)))];
            tensor<fp16, [8, 352]> mul_437 = mul(x = mul_436, y = mul_437_y_0)[name = string("mul_437")];
            tensor<fp16, [8, 352]> mul_438 = mul(x = mul_437, y = mul_437)[name = string("mul_438")];
            tensor<int32, [1]> reduce_mean_94_axes_0 = const()[name = string("reduce_mean_94_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_94_keep_dims_0 = const()[name = string("reduce_mean_94_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_94 = reduce_mean(axes = reduce_mean_94_axes_0, keep_dims = reduce_mean_94_keep_dims_0, x = mul_438)[name = string("reduce_mean_94")];
            fp32 rsqrt_94_epsilon_0 = const()[name = string("rsqrt_94_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_94 = rsqrt(epsilon = rsqrt_94_epsilon_0, x = reduce_mean_94)[name = string("rsqrt_94")];
            tensor<fp16, [8, 352]> mul_439 = mul(x = mul_437, y = rsqrt_94)[name = string("mul_439")];
            tensor<fp16, [352]> mul_440_y_0 = const()[name = string("mul_440_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5428736)))];
            tensor<fp16, [8, 352]> mul_440 = mul(x = mul_439, y = mul_440_y_0)[name = string("mul_440")];
            tensor<fp16, [352, 352]> tern_9_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5429504))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_9_q_weight_0_palettized")];
            tensor<fp16, [8, 352]> tern_9_q = linear(bias = linear_0_bias_0, weight = tern_9_q_weight_0_palettized, x = mul_440)[name = string("tern_9_q")];
            tensor<fp16, [352]> mul_441_y_0 = const()[name = string("mul_441_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5460544)))];
            tensor<fp16, [8, 352]> mul_441 = mul(x = tern_9_q, y = mul_441_y_0)[name = string("mul_441")];
            tensor<int32, [3]> reshape_74_shape_0 = const()[name = string("reshape_74_shape_0"), val = tensor<int32, [3]>([8, 8, 44])];
            tensor<fp16, [8, 8, 44]> reshape_74 = reshape(shape = reshape_74_shape_0, x = mul_441)[name = string("reshape_74")];
            tensor<int32, [3]> transpose_36_perm_0 = const()[name = string("transpose_36_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_444_y_0 = const()[name = string("mul_444_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5461312)))];
            tensor<fp16, [8, 352]> mul_444 = mul(x = mul_439, y = mul_444_y_0)[name = string("mul_444")];
            tensor<fp16, [88, 352]> tern_9_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5462080))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_9_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_9_k_bias_0 = const()[name = string("tern_9_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [8, 88]> tern_9_k = linear(bias = tern_9_k_bias_0, weight = tern_9_k_weight_0_palettized, x = mul_444)[name = string("tern_9_k")];
            tensor<fp16, [88]> mul_445_y_0 = const()[name = string("mul_445_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5469888)))];
            tensor<fp16, [8, 88]> mul_445 = mul(x = tern_9_k, y = mul_445_y_0)[name = string("mul_445")];
            tensor<int32, [3]> reshape_75_shape_0 = const()[name = string("reshape_75_shape_0"), val = tensor<int32, [3]>([8, 2, 44])];
            tensor<fp16, [8, 2, 44]> reshape_75 = reshape(shape = reshape_75_shape_0, x = mul_445)[name = string("reshape_75")];
            tensor<int32, [3]> transpose_37_perm_0 = const()[name = string("transpose_37_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_448_y_0 = const()[name = string("mul_448_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5470144)))];
            tensor<fp16, [8, 352]> mul_448 = mul(x = mul_439, y = mul_448_y_0)[name = string("mul_448")];
            tensor<fp16, [88, 352]> tern_9_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5470912))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_9_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_9_v_bias_0 = const()[name = string("tern_9_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [8, 88]> tern_9_v = linear(bias = tern_9_v_bias_0, weight = tern_9_v_weight_0_palettized, x = mul_448)[name = string("tern_9_v")];
            tensor<fp16, [88]> mul_449_y_0 = const()[name = string("mul_449_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5478720)))];
            tensor<fp16, [8, 88]> mul_449 = mul(x = tern_9_v, y = mul_449_y_0)[name = string("mul_449")];
            tensor<int32, [3]> reshape_76_shape_0 = const()[name = string("reshape_76_shape_0"), val = tensor<int32, [3]>([8, 2, 44])];
            tensor<fp16, [8, 2, 44]> reshape_76 = reshape(shape = reshape_76_shape_0, x = mul_449)[name = string("reshape_76")];
            tensor<int32, [3]> transpose_38_perm_0 = const()[name = string("transpose_38_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 8, 44]> transpose_36 = transpose(perm = transpose_36_perm_0, x = reshape_74)[name = string("transpose_27")];
            tensor<fp16, [8, 8, 44]> mul_450 = mul(x = transpose_36, y = transpose_36)[name = string("mul_450")];
            tensor<int32, [1]> reduce_mean_97_axes_0 = const()[name = string("reduce_mean_97_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_97_keep_dims_0 = const()[name = string("reduce_mean_97_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 8, 1]> reduce_mean_97 = reduce_mean(axes = reduce_mean_97_axes_0, keep_dims = reduce_mean_97_keep_dims_0, x = mul_450)[name = string("reduce_mean_97")];
            fp32 rsqrt_97_epsilon_0 = const()[name = string("rsqrt_97_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 8, 1]> rsqrt_97 = rsqrt(epsilon = rsqrt_97_epsilon_0, x = reduce_mean_97)[name = string("rsqrt_97")];
            tensor<fp16, [8, 8, 44]> mul_451 = mul(x = transpose_36, y = rsqrt_97)[name = string("mul_451")];
            tensor<fp16, [44]> mul_452_y_0 = const()[name = string("mul_452_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5478976)))];
            tensor<fp16, [8, 8, 44]> mul_452 = mul(x = mul_451, y = mul_452_y_0)[name = string("mul_452")];
            tensor<int32, [3]> slice_by_index_36_begin_0 = const()[name = string("slice_by_index_36_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_36_end_0 = const()[name = string("slice_by_index_36_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_36_end_mask_0 = const()[name = string("slice_by_index_36_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 8, 22]> slice_by_index_36 = slice_by_index(begin = slice_by_index_36_begin_0, end = slice_by_index_36_end_0, end_mask = slice_by_index_36_end_mask_0, x = mul_452)[name = string("slice_by_index_36")];
            tensor<int32, [3]> slice_by_index_37_begin_0 = const()[name = string("slice_by_index_37_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_37_end_0 = const()[name = string("slice_by_index_37_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_37_end_mask_0 = const()[name = string("slice_by_index_37_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 8, 22]> slice_by_index_37 = slice_by_index(begin = slice_by_index_37_begin_0, end = slice_by_index_37_end_0, end_mask = slice_by_index_37_end_mask_0, x = mul_452)[name = string("slice_by_index_37")];
            int32 concat_18_axis_0 = const()[name = string("concat_18_axis_0"), val = int32(-1)];
            bool concat_18_interleave_0 = const()[name = string("concat_18_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 8, 44]> concat_18 = concat(axis = concat_18_axis_0, interleave = concat_18_interleave_0, values = (slice_by_index_37, slice_by_index_36))[name = string("concat_18")];
            tensor<fp16, [44]> mul_453_y_0 = const()[name = string("mul_453_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 8, 44]> mul_453 = mul(x = concat_18, y = mul_453_y_0)[name = string("mul_453")];
            tensor<fp16, [8, 8, 44]> mul_454 = mul(x = mul_452, y = mul_11_y_0)[name = string("mul_454")];
            tensor<fp16, [8, 8, 44]> mul_455 = mul(x = mul_453, y = mul_12_y_0)[name = string("mul_455")];
            tensor<fp16, [8, 8, 44]> add_54 = add(x = mul_454, y = mul_455)[name = string("add_54")];
            tensor<fp16, [2, 8, 44]> transpose_37 = transpose(perm = transpose_37_perm_0, x = reshape_75)[name = string("transpose_26")];
            tensor<fp16, [2, 8, 44]> mul_456 = mul(x = transpose_37, y = transpose_37)[name = string("mul_456")];
            tensor<int32, [1]> reduce_mean_98_axes_0 = const()[name = string("reduce_mean_98_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_98_keep_dims_0 = const()[name = string("reduce_mean_98_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 8, 1]> reduce_mean_98 = reduce_mean(axes = reduce_mean_98_axes_0, keep_dims = reduce_mean_98_keep_dims_0, x = mul_456)[name = string("reduce_mean_98")];
            fp32 rsqrt_98_epsilon_0 = const()[name = string("rsqrt_98_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 8, 1]> rsqrt_98 = rsqrt(epsilon = rsqrt_98_epsilon_0, x = reduce_mean_98)[name = string("rsqrt_98")];
            tensor<fp16, [2, 8, 44]> mul_457 = mul(x = transpose_37, y = rsqrt_98)[name = string("mul_457")];
            tensor<fp16, [44]> mul_458_y_0 = const()[name = string("mul_458_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5479168)))];
            tensor<fp16, [2, 8, 44]> mul_458 = mul(x = mul_457, y = mul_458_y_0)[name = string("mul_458")];
            tensor<int32, [3]> slice_by_index_38_begin_0 = const()[name = string("slice_by_index_38_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_38_end_0 = const()[name = string("slice_by_index_38_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_38_end_mask_0 = const()[name = string("slice_by_index_38_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 8, 22]> slice_by_index_38 = slice_by_index(begin = slice_by_index_38_begin_0, end = slice_by_index_38_end_0, end_mask = slice_by_index_38_end_mask_0, x = mul_458)[name = string("slice_by_index_38")];
            tensor<int32, [3]> slice_by_index_39_begin_0 = const()[name = string("slice_by_index_39_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_39_end_0 = const()[name = string("slice_by_index_39_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_39_end_mask_0 = const()[name = string("slice_by_index_39_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 8, 22]> slice_by_index_39 = slice_by_index(begin = slice_by_index_39_begin_0, end = slice_by_index_39_end_0, end_mask = slice_by_index_39_end_mask_0, x = mul_458)[name = string("slice_by_index_39")];
            int32 concat_19_axis_0 = const()[name = string("concat_19_axis_0"), val = int32(-1)];
            bool concat_19_interleave_0 = const()[name = string("concat_19_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 8, 44]> concat_19 = concat(axis = concat_19_axis_0, interleave = concat_19_interleave_0, values = (slice_by_index_39, slice_by_index_38))[name = string("concat_19")];
            tensor<fp16, [44]> mul_459_y_0 = const()[name = string("mul_459_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 8, 44]> mul_459 = mul(x = concat_19, y = mul_459_y_0)[name = string("mul_459")];
            tensor<fp16, [2, 8, 44]> mul_460 = mul(x = mul_458, y = mul_11_y_0)[name = string("mul_460")];
            tensor<fp16, [2, 8, 44]> mul_461 = mul(x = mul_459, y = mul_12_y_0)[name = string("mul_461")];
            tensor<fp16, [2, 8, 44]> add_55 = add(x = mul_460, y = mul_461)[name = string("add_55")];
            tensor<int32, [4]> reshape_77_shape_0 = const()[name = string("reshape_77_shape_0"), val = tensor<int32, [4]>([2, 1, 8, 44])];
            tensor<fp16, [2, 1, 8, 44]> reshape_77 = reshape(shape = reshape_77_shape_0, x = add_55)[name = string("reshape_77")];
            tensor<int32, [4]> tile_18_reps_0 = const()[name = string("tile_18_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 8, 44]> tile_18 = tile(reps = tile_18_reps_0, x = reshape_77)[name = string("tile_18")];
            tensor<int32, [3]> reshape_78_shape_0 = const()[name = string("reshape_78_shape_0"), val = tensor<int32, [3]>([8, 8, 44])];
            tensor<fp16, [8, 8, 44]> reshape_78 = reshape(shape = reshape_78_shape_0, x = tile_18)[name = string("reshape_78")];
            tensor<int32, [4]> reshape_79_shape_0 = const()[name = string("reshape_79_shape_0"), val = tensor<int32, [4]>([2, 1, 8, 44])];
            tensor<fp16, [2, 8, 44]> transpose_38 = transpose(perm = transpose_38_perm_0, x = reshape_76)[name = string("transpose_25")];
            tensor<fp16, [2, 1, 8, 44]> reshape_79 = reshape(shape = reshape_79_shape_0, x = transpose_38)[name = string("reshape_79")];
            tensor<int32, [4]> tile_19_reps_0 = const()[name = string("tile_19_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 8, 44]> tile_19 = tile(reps = tile_19_reps_0, x = reshape_79)[name = string("tile_19")];
            tensor<int32, [3]> reshape_80_shape_0 = const()[name = string("reshape_80_shape_0"), val = tensor<int32, [3]>([8, 8, 44])];
            tensor<fp16, [8, 8, 44]> reshape_80 = reshape(shape = reshape_80_shape_0, x = tile_19)[name = string("reshape_80")];
            fp16 mul_462_y_0 = const()[name = string("mul_462_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 8, 44]> mul_462 = mul(x = add_54, y = mul_462_y_0)[name = string("mul_462")];
            bool matmul_18_transpose_y_0 = const()[name = string("matmul_18_transpose_y_0"), val = bool(true)];
            bool matmul_18_transpose_x_0 = const()[name = string("matmul_18_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 8, 8]> matmul_18 = matmul(transpose_x = matmul_18_transpose_x_0, transpose_y = matmul_18_transpose_y_0, x = mul_462, y = reshape_78)[name = string("matmul_18")];
            tensor<fp16, [8, 8, 8]> add_56 = add(x = matmul_18, y = reshape_1)[name = string("add_56")];
            int32 softmax_9_axis_0 = const()[name = string("softmax_9_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 8, 8]> softmax_9 = softmax(axis = softmax_9_axis_0, x = add_56)[name = string("softmax_9")];
            bool matmul_19_transpose_x_0 = const()[name = string("matmul_19_transpose_x_0"), val = bool(false)];
            bool matmul_19_transpose_y_0 = const()[name = string("matmul_19_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 8, 44]> matmul_19 = matmul(transpose_x = matmul_19_transpose_x_0, transpose_y = matmul_19_transpose_y_0, x = softmax_9, y = reshape_80)[name = string("matmul_19")];
            tensor<int32, [3]> transpose_39_perm_0 = const()[name = string("transpose_39_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_81_shape_0 = const()[name = string("reshape_81_shape_0"), val = tensor<int32, [2]>([8, 352])];
            tensor<fp16, [8, 8, 44]> transpose_39 = transpose(perm = transpose_39_perm_0, x = matmul_19)[name = string("transpose_24")];
            tensor<fp16, [8, 352]> reshape_81 = reshape(shape = reshape_81_shape_0, x = transpose_39)[name = string("reshape_81")];
            tensor<fp16, [8, 352]> mul_463 = mul(x = reshape_81, y = reshape_81)[name = string("mul_463")];
            tensor<int32, [1]> reduce_mean_99_axes_0 = const()[name = string("reduce_mean_99_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_99_keep_dims_0 = const()[name = string("reduce_mean_99_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_99 = reduce_mean(axes = reduce_mean_99_axes_0, keep_dims = reduce_mean_99_keep_dims_0, x = mul_463)[name = string("reduce_mean_99")];
            fp32 rsqrt_99_epsilon_0 = const()[name = string("rsqrt_99_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_99 = rsqrt(epsilon = rsqrt_99_epsilon_0, x = reduce_mean_99)[name = string("rsqrt_99")];
            tensor<fp16, [8, 352]> mul_464 = mul(x = reshape_81, y = rsqrt_99)[name = string("mul_464")];
            tensor<fp16, [352]> mul_465_y_0 = const()[name = string("mul_465_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5479360)))];
            tensor<fp16, [8, 352]> mul_465 = mul(x = mul_464, y = mul_465_y_0)[name = string("mul_465")];
            tensor<fp16, [352, 352]> tern_9_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5480128))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_9_o_weight_0_palettized")];
            tensor<fp16, [8, 352]> tern_9_o = linear(bias = linear_0_bias_0, weight = tern_9_o_weight_0_palettized, x = mul_465)[name = string("tern_9_o")];
            tensor<fp16, [352]> mul_466_y_0 = const()[name = string("mul_466_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5511168)))];
            tensor<fp16, [8, 352]> mul_466 = mul(x = tern_9_o, y = mul_466_y_0)[name = string("mul_466")];
            tensor<fp16, [8, 352]> add_57 = add(x = add_53, y = mul_466)[name = string("add_57")];
            tensor<fp16, [8, 352]> mul_467 = mul(x = add_57, y = add_57)[name = string("mul_467")];
            tensor<int32, [1]> reduce_mean_100_axes_0 = const()[name = string("reduce_mean_100_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_100_keep_dims_0 = const()[name = string("reduce_mean_100_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_100 = reduce_mean(axes = reduce_mean_100_axes_0, keep_dims = reduce_mean_100_keep_dims_0, x = mul_467)[name = string("reduce_mean_100")];
            fp32 rsqrt_100_epsilon_0 = const()[name = string("rsqrt_100_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_100 = rsqrt(epsilon = rsqrt_100_epsilon_0, x = reduce_mean_100)[name = string("rsqrt_100")];
            tensor<fp16, [8, 352]> mul_468 = mul(x = add_57, y = rsqrt_100)[name = string("mul_468")];
            tensor<fp16, [352]> mul_469_y_0 = const()[name = string("mul_469_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5511936)))];
            tensor<fp16, [8, 352]> mul_469 = mul(x = mul_468, y = mul_469_y_0)[name = string("mul_469")];
            tensor<fp16, [8, 352]> mul_470 = mul(x = mul_469, y = mul_469)[name = string("mul_470")];
            tensor<int32, [1]> reduce_mean_101_axes_0 = const()[name = string("reduce_mean_101_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_101_keep_dims_0 = const()[name = string("reduce_mean_101_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_101 = reduce_mean(axes = reduce_mean_101_axes_0, keep_dims = reduce_mean_101_keep_dims_0, x = mul_470)[name = string("reduce_mean_101")];
            fp32 rsqrt_101_epsilon_0 = const()[name = string("rsqrt_101_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_101 = rsqrt(epsilon = rsqrt_101_epsilon_0, x = reduce_mean_101)[name = string("rsqrt_101")];
            tensor<fp16, [8, 352]> mul_471 = mul(x = mul_469, y = rsqrt_101)[name = string("mul_471")];
            tensor<fp16, [352]> mul_472_y_0 = const()[name = string("mul_472_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5512704)))];
            tensor<fp16, [8, 352]> mul_472 = mul(x = mul_471, y = mul_472_y_0)[name = string("mul_472")];
            tensor<fp16, [960, 352]> tern_9_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5513472))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_9_w1_weight_0_palettized")];
            tensor<fp16, [8, 960]> tern_9_w1 = linear(bias = linear_4_bias_0, weight = tern_9_w1_weight_0_palettized, x = mul_472)[name = string("tern_9_w1")];
            tensor<fp16, [960]> mul_473_y_0 = const()[name = string("mul_473_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5598016)))];
            tensor<fp16, [8, 960]> mul_473 = mul(x = tern_9_w1, y = mul_473_y_0)[name = string("mul_473")];
            tensor<fp16, [352]> mul_476_y_0 = const()[name = string("mul_476_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5600000)))];
            tensor<fp16, [8, 352]> mul_476 = mul(x = mul_471, y = mul_476_y_0)[name = string("mul_476")];
            tensor<fp16, [960, 352]> tern_9_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5600768))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_9_w3_weight_0_palettized")];
            tensor<fp16, [8, 960]> tern_9_w3 = linear(bias = linear_4_bias_0, weight = tern_9_w3_weight_0_palettized, x = mul_476)[name = string("tern_9_w3")];
            tensor<fp16, [960]> mul_477_y_0 = const()[name = string("mul_477_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5685312)))];
            tensor<fp16, [8, 960]> mul_477 = mul(x = tern_9_w3, y = mul_477_y_0)[name = string("mul_477")];
            fp16 mul_478_y_0 = const()[name = string("mul_478_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [8, 960]> mul_478 = mul(x = mul_473, y = mul_478_y_0)[name = string("mul_478")];
            tensor<fp16, [8, 960]> tanh_9 = tanh(x = mul_478)[name = string("tanh_9")];
            fp16 mul_479_x_0 = const()[name = string("mul_479_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [8, 960]> mul_479 = mul(x = mul_479_x_0, y = tanh_9)[name = string("mul_479")];
            fp16 add_58_x_0 = const()[name = string("add_58_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [8, 960]> add_58 = add(x = add_58_x_0, y = mul_479)[name = string("add_58")];
            tensor<fp16, [8, 960]> mul_480 = mul(x = mul_473, y = add_58)[name = string("mul_480")];
            tensor<fp16, [8, 960]> mul_481 = mul(x = mul_480, y = mul_477)[name = string("mul_481")];
            tensor<fp16, [8, 960]> mul_482 = mul(x = mul_481, y = mul_481)[name = string("mul_482")];
            tensor<int32, [1]> reduce_mean_103_axes_0 = const()[name = string("reduce_mean_103_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_103_keep_dims_0 = const()[name = string("reduce_mean_103_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_103 = reduce_mean(axes = reduce_mean_103_axes_0, keep_dims = reduce_mean_103_keep_dims_0, x = mul_482)[name = string("reduce_mean_103")];
            fp32 rsqrt_103_epsilon_0 = const()[name = string("rsqrt_103_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_103 = rsqrt(epsilon = rsqrt_103_epsilon_0, x = reduce_mean_103)[name = string("rsqrt_103")];
            tensor<fp16, [8, 960]> mul_483 = mul(x = mul_481, y = rsqrt_103)[name = string("mul_483")];
            tensor<fp16, [960]> mul_484_y_0 = const()[name = string("mul_484_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5687296)))];
            tensor<fp16, [8, 960]> mul_484 = mul(x = mul_483, y = mul_484_y_0)[name = string("mul_484")];
            tensor<fp16, [352, 960]> tern_9_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5689280))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_9_w2_weight_0_palettized")];
            tensor<fp16, [8, 352]> tern_9_w2 = linear(bias = linear_0_bias_0, weight = tern_9_w2_weight_0_palettized, x = mul_484)[name = string("tern_9_w2")];
            tensor<fp16, [352]> mul_485_y_0 = const()[name = string("mul_485_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5773824)))];
            tensor<fp16, [8, 352]> mul_485 = mul(x = tern_9_w2, y = mul_485_y_0)[name = string("mul_485")];
            tensor<fp16, [8, 352]> add_59 = add(x = add_57, y = mul_485)[name = string("add_59")];
            tensor<fp16, [8, 352]> mul_486 = mul(x = add_59, y = add_59)[name = string("mul_486")];
            tensor<int32, [1]> reduce_mean_104_axes_0 = const()[name = string("reduce_mean_104_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_104_keep_dims_0 = const()[name = string("reduce_mean_104_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_104 = reduce_mean(axes = reduce_mean_104_axes_0, keep_dims = reduce_mean_104_keep_dims_0, x = mul_486)[name = string("reduce_mean_104")];
            fp32 rsqrt_104_epsilon_0 = const()[name = string("rsqrt_104_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_104 = rsqrt(epsilon = rsqrt_104_epsilon_0, x = reduce_mean_104)[name = string("rsqrt_104")];
            tensor<fp16, [8, 352]> mul_487 = mul(x = add_59, y = rsqrt_104)[name = string("mul_487")];
            tensor<fp16, [352]> mul_488_y_0 = const()[name = string("mul_488_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5774592)))];
            tensor<fp16, [8, 352]> mul_488 = mul(x = mul_487, y = mul_488_y_0)[name = string("mul_488")];
            tensor<fp16, [8, 352]> mul_489 = mul(x = mul_488, y = mul_488)[name = string("mul_489")];
            tensor<int32, [1]> reduce_mean_105_axes_0 = const()[name = string("reduce_mean_105_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_105_keep_dims_0 = const()[name = string("reduce_mean_105_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_105 = reduce_mean(axes = reduce_mean_105_axes_0, keep_dims = reduce_mean_105_keep_dims_0, x = mul_489)[name = string("reduce_mean_105")];
            fp32 rsqrt_105_epsilon_0 = const()[name = string("rsqrt_105_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_105 = rsqrt(epsilon = rsqrt_105_epsilon_0, x = reduce_mean_105)[name = string("rsqrt_105")];
            tensor<fp16, [8, 352]> mul_490 = mul(x = mul_488, y = rsqrt_105)[name = string("mul_490")];
            tensor<fp16, [352]> mul_491_y_0 = const()[name = string("mul_491_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5775360)))];
            tensor<fp16, [8, 352]> mul_491 = mul(x = mul_490, y = mul_491_y_0)[name = string("mul_491")];
            tensor<fp16, [352, 352]> tern_10_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5776128))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_10_q_weight_0_palettized")];
            tensor<fp16, [8, 352]> tern_10_q = linear(bias = linear_0_bias_0, weight = tern_10_q_weight_0_palettized, x = mul_491)[name = string("tern_10_q")];
            tensor<fp16, [352]> mul_492_y_0 = const()[name = string("mul_492_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5807168)))];
            tensor<fp16, [8, 352]> mul_492 = mul(x = tern_10_q, y = mul_492_y_0)[name = string("mul_492")];
            tensor<int32, [3]> reshape_82_shape_0 = const()[name = string("reshape_82_shape_0"), val = tensor<int32, [3]>([8, 8, 44])];
            tensor<fp16, [8, 8, 44]> reshape_82 = reshape(shape = reshape_82_shape_0, x = mul_492)[name = string("reshape_82")];
            tensor<int32, [3]> transpose_40_perm_0 = const()[name = string("transpose_40_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_495_y_0 = const()[name = string("mul_495_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5807936)))];
            tensor<fp16, [8, 352]> mul_495 = mul(x = mul_490, y = mul_495_y_0)[name = string("mul_495")];
            tensor<fp16, [88, 352]> tern_10_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5808704))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_10_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_10_k_bias_0 = const()[name = string("tern_10_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [8, 88]> tern_10_k = linear(bias = tern_10_k_bias_0, weight = tern_10_k_weight_0_palettized, x = mul_495)[name = string("tern_10_k")];
            tensor<fp16, [88]> mul_496_y_0 = const()[name = string("mul_496_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5816512)))];
            tensor<fp16, [8, 88]> mul_496 = mul(x = tern_10_k, y = mul_496_y_0)[name = string("mul_496")];
            tensor<int32, [3]> reshape_83_shape_0 = const()[name = string("reshape_83_shape_0"), val = tensor<int32, [3]>([8, 2, 44])];
            tensor<fp16, [8, 2, 44]> reshape_83 = reshape(shape = reshape_83_shape_0, x = mul_496)[name = string("reshape_83")];
            tensor<int32, [3]> transpose_41_perm_0 = const()[name = string("transpose_41_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_499_y_0 = const()[name = string("mul_499_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5816768)))];
            tensor<fp16, [8, 352]> mul_499 = mul(x = mul_490, y = mul_499_y_0)[name = string("mul_499")];
            tensor<fp16, [88, 352]> tern_10_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5817536))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_10_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_10_v_bias_0 = const()[name = string("tern_10_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [8, 88]> tern_10_v = linear(bias = tern_10_v_bias_0, weight = tern_10_v_weight_0_palettized, x = mul_499)[name = string("tern_10_v")];
            tensor<fp16, [88]> mul_500_y_0 = const()[name = string("mul_500_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5825344)))];
            tensor<fp16, [8, 88]> mul_500 = mul(x = tern_10_v, y = mul_500_y_0)[name = string("mul_500")];
            tensor<int32, [3]> reshape_84_shape_0 = const()[name = string("reshape_84_shape_0"), val = tensor<int32, [3]>([8, 2, 44])];
            tensor<fp16, [8, 2, 44]> reshape_84 = reshape(shape = reshape_84_shape_0, x = mul_500)[name = string("reshape_84")];
            tensor<int32, [3]> transpose_42_perm_0 = const()[name = string("transpose_42_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 8, 44]> transpose_40 = transpose(perm = transpose_40_perm_0, x = reshape_82)[name = string("transpose_23")];
            tensor<fp16, [8, 8, 44]> mul_501 = mul(x = transpose_40, y = transpose_40)[name = string("mul_501")];
            tensor<int32, [1]> reduce_mean_108_axes_0 = const()[name = string("reduce_mean_108_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_108_keep_dims_0 = const()[name = string("reduce_mean_108_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 8, 1]> reduce_mean_108 = reduce_mean(axes = reduce_mean_108_axes_0, keep_dims = reduce_mean_108_keep_dims_0, x = mul_501)[name = string("reduce_mean_108")];
            fp32 rsqrt_108_epsilon_0 = const()[name = string("rsqrt_108_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 8, 1]> rsqrt_108 = rsqrt(epsilon = rsqrt_108_epsilon_0, x = reduce_mean_108)[name = string("rsqrt_108")];
            tensor<fp16, [8, 8, 44]> mul_502 = mul(x = transpose_40, y = rsqrt_108)[name = string("mul_502")];
            tensor<fp16, [44]> mul_503_y_0 = const()[name = string("mul_503_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5825600)))];
            tensor<fp16, [8, 8, 44]> mul_503 = mul(x = mul_502, y = mul_503_y_0)[name = string("mul_503")];
            tensor<int32, [3]> slice_by_index_40_begin_0 = const()[name = string("slice_by_index_40_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_40_end_0 = const()[name = string("slice_by_index_40_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_40_end_mask_0 = const()[name = string("slice_by_index_40_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 8, 22]> slice_by_index_40 = slice_by_index(begin = slice_by_index_40_begin_0, end = slice_by_index_40_end_0, end_mask = slice_by_index_40_end_mask_0, x = mul_503)[name = string("slice_by_index_40")];
            tensor<int32, [3]> slice_by_index_41_begin_0 = const()[name = string("slice_by_index_41_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_41_end_0 = const()[name = string("slice_by_index_41_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_41_end_mask_0 = const()[name = string("slice_by_index_41_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 8, 22]> slice_by_index_41 = slice_by_index(begin = slice_by_index_41_begin_0, end = slice_by_index_41_end_0, end_mask = slice_by_index_41_end_mask_0, x = mul_503)[name = string("slice_by_index_41")];
            int32 concat_20_axis_0 = const()[name = string("concat_20_axis_0"), val = int32(-1)];
            bool concat_20_interleave_0 = const()[name = string("concat_20_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 8, 44]> concat_20 = concat(axis = concat_20_axis_0, interleave = concat_20_interleave_0, values = (slice_by_index_41, slice_by_index_40))[name = string("concat_20")];
            tensor<fp16, [44]> mul_504_y_0 = const()[name = string("mul_504_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 8, 44]> mul_504 = mul(x = concat_20, y = mul_504_y_0)[name = string("mul_504")];
            tensor<fp16, [8, 8, 44]> mul_505 = mul(x = mul_503, y = mul_11_y_0)[name = string("mul_505")];
            tensor<fp16, [8, 8, 44]> mul_506 = mul(x = mul_504, y = mul_12_y_0)[name = string("mul_506")];
            tensor<fp16, [8, 8, 44]> add_60 = add(x = mul_505, y = mul_506)[name = string("add_60")];
            tensor<fp16, [2, 8, 44]> transpose_41 = transpose(perm = transpose_41_perm_0, x = reshape_83)[name = string("transpose_22")];
            tensor<fp16, [2, 8, 44]> mul_507 = mul(x = transpose_41, y = transpose_41)[name = string("mul_507")];
            tensor<int32, [1]> reduce_mean_109_axes_0 = const()[name = string("reduce_mean_109_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_109_keep_dims_0 = const()[name = string("reduce_mean_109_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 8, 1]> reduce_mean_109 = reduce_mean(axes = reduce_mean_109_axes_0, keep_dims = reduce_mean_109_keep_dims_0, x = mul_507)[name = string("reduce_mean_109")];
            fp32 rsqrt_109_epsilon_0 = const()[name = string("rsqrt_109_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 8, 1]> rsqrt_109 = rsqrt(epsilon = rsqrt_109_epsilon_0, x = reduce_mean_109)[name = string("rsqrt_109")];
            tensor<fp16, [2, 8, 44]> mul_508 = mul(x = transpose_41, y = rsqrt_109)[name = string("mul_508")];
            tensor<fp16, [44]> mul_509_y_0 = const()[name = string("mul_509_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5825792)))];
            tensor<fp16, [2, 8, 44]> mul_509 = mul(x = mul_508, y = mul_509_y_0)[name = string("mul_509")];
            tensor<int32, [3]> slice_by_index_42_begin_0 = const()[name = string("slice_by_index_42_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_42_end_0 = const()[name = string("slice_by_index_42_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_42_end_mask_0 = const()[name = string("slice_by_index_42_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 8, 22]> slice_by_index_42 = slice_by_index(begin = slice_by_index_42_begin_0, end = slice_by_index_42_end_0, end_mask = slice_by_index_42_end_mask_0, x = mul_509)[name = string("slice_by_index_42")];
            tensor<int32, [3]> slice_by_index_43_begin_0 = const()[name = string("slice_by_index_43_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_43_end_0 = const()[name = string("slice_by_index_43_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_43_end_mask_0 = const()[name = string("slice_by_index_43_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 8, 22]> slice_by_index_43 = slice_by_index(begin = slice_by_index_43_begin_0, end = slice_by_index_43_end_0, end_mask = slice_by_index_43_end_mask_0, x = mul_509)[name = string("slice_by_index_43")];
            int32 concat_21_axis_0 = const()[name = string("concat_21_axis_0"), val = int32(-1)];
            bool concat_21_interleave_0 = const()[name = string("concat_21_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 8, 44]> concat_21 = concat(axis = concat_21_axis_0, interleave = concat_21_interleave_0, values = (slice_by_index_43, slice_by_index_42))[name = string("concat_21")];
            tensor<fp16, [44]> mul_510_y_0 = const()[name = string("mul_510_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 8, 44]> mul_510 = mul(x = concat_21, y = mul_510_y_0)[name = string("mul_510")];
            tensor<fp16, [2, 8, 44]> mul_511 = mul(x = mul_509, y = mul_11_y_0)[name = string("mul_511")];
            tensor<fp16, [2, 8, 44]> mul_512 = mul(x = mul_510, y = mul_12_y_0)[name = string("mul_512")];
            tensor<fp16, [2, 8, 44]> add_61 = add(x = mul_511, y = mul_512)[name = string("add_61")];
            tensor<int32, [4]> reshape_85_shape_0 = const()[name = string("reshape_85_shape_0"), val = tensor<int32, [4]>([2, 1, 8, 44])];
            tensor<fp16, [2, 1, 8, 44]> reshape_85 = reshape(shape = reshape_85_shape_0, x = add_61)[name = string("reshape_85")];
            tensor<int32, [4]> tile_20_reps_0 = const()[name = string("tile_20_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 8, 44]> tile_20 = tile(reps = tile_20_reps_0, x = reshape_85)[name = string("tile_20")];
            tensor<int32, [3]> reshape_86_shape_0 = const()[name = string("reshape_86_shape_0"), val = tensor<int32, [3]>([8, 8, 44])];
            tensor<fp16, [8, 8, 44]> reshape_86 = reshape(shape = reshape_86_shape_0, x = tile_20)[name = string("reshape_86")];
            tensor<int32, [4]> reshape_87_shape_0 = const()[name = string("reshape_87_shape_0"), val = tensor<int32, [4]>([2, 1, 8, 44])];
            tensor<fp16, [2, 8, 44]> transpose_42 = transpose(perm = transpose_42_perm_0, x = reshape_84)[name = string("transpose_21")];
            tensor<fp16, [2, 1, 8, 44]> reshape_87 = reshape(shape = reshape_87_shape_0, x = transpose_42)[name = string("reshape_87")];
            tensor<int32, [4]> tile_21_reps_0 = const()[name = string("tile_21_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 8, 44]> tile_21 = tile(reps = tile_21_reps_0, x = reshape_87)[name = string("tile_21")];
            tensor<int32, [3]> reshape_88_shape_0 = const()[name = string("reshape_88_shape_0"), val = tensor<int32, [3]>([8, 8, 44])];
            tensor<fp16, [8, 8, 44]> reshape_88 = reshape(shape = reshape_88_shape_0, x = tile_21)[name = string("reshape_88")];
            fp16 mul_513_y_0 = const()[name = string("mul_513_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 8, 44]> mul_513 = mul(x = add_60, y = mul_513_y_0)[name = string("mul_513")];
            bool matmul_20_transpose_y_0 = const()[name = string("matmul_20_transpose_y_0"), val = bool(true)];
            bool matmul_20_transpose_x_0 = const()[name = string("matmul_20_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 8, 8]> matmul_20 = matmul(transpose_x = matmul_20_transpose_x_0, transpose_y = matmul_20_transpose_y_0, x = mul_513, y = reshape_86)[name = string("matmul_20")];
            tensor<fp16, [8, 8, 8]> add_62 = add(x = matmul_20, y = reshape_1)[name = string("add_62")];
            int32 softmax_10_axis_0 = const()[name = string("softmax_10_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 8, 8]> softmax_10 = softmax(axis = softmax_10_axis_0, x = add_62)[name = string("softmax_10")];
            bool matmul_21_transpose_x_0 = const()[name = string("matmul_21_transpose_x_0"), val = bool(false)];
            bool matmul_21_transpose_y_0 = const()[name = string("matmul_21_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 8, 44]> matmul_21 = matmul(transpose_x = matmul_21_transpose_x_0, transpose_y = matmul_21_transpose_y_0, x = softmax_10, y = reshape_88)[name = string("matmul_21")];
            tensor<int32, [3]> transpose_43_perm_0 = const()[name = string("transpose_43_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_89_shape_0 = const()[name = string("reshape_89_shape_0"), val = tensor<int32, [2]>([8, 352])];
            tensor<fp16, [8, 8, 44]> transpose_43 = transpose(perm = transpose_43_perm_0, x = matmul_21)[name = string("transpose_20")];
            tensor<fp16, [8, 352]> reshape_89 = reshape(shape = reshape_89_shape_0, x = transpose_43)[name = string("reshape_89")];
            tensor<fp16, [8, 352]> mul_514 = mul(x = reshape_89, y = reshape_89)[name = string("mul_514")];
            tensor<int32, [1]> reduce_mean_110_axes_0 = const()[name = string("reduce_mean_110_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_110_keep_dims_0 = const()[name = string("reduce_mean_110_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_110 = reduce_mean(axes = reduce_mean_110_axes_0, keep_dims = reduce_mean_110_keep_dims_0, x = mul_514)[name = string("reduce_mean_110")];
            fp32 rsqrt_110_epsilon_0 = const()[name = string("rsqrt_110_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_110 = rsqrt(epsilon = rsqrt_110_epsilon_0, x = reduce_mean_110)[name = string("rsqrt_110")];
            tensor<fp16, [8, 352]> mul_515 = mul(x = reshape_89, y = rsqrt_110)[name = string("mul_515")];
            tensor<fp16, [352]> mul_516_y_0 = const()[name = string("mul_516_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5825984)))];
            tensor<fp16, [8, 352]> mul_516 = mul(x = mul_515, y = mul_516_y_0)[name = string("mul_516")];
            tensor<fp16, [352, 352]> tern_10_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5826752))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_10_o_weight_0_palettized")];
            tensor<fp16, [8, 352]> tern_10_o = linear(bias = linear_0_bias_0, weight = tern_10_o_weight_0_palettized, x = mul_516)[name = string("tern_10_o")];
            tensor<fp16, [352]> mul_517_y_0 = const()[name = string("mul_517_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5857792)))];
            tensor<fp16, [8, 352]> mul_517 = mul(x = tern_10_o, y = mul_517_y_0)[name = string("mul_517")];
            tensor<fp16, [8, 352]> add_63 = add(x = add_59, y = mul_517)[name = string("add_63")];
            tensor<fp16, [8, 352]> mul_518 = mul(x = add_63, y = add_63)[name = string("mul_518")];
            tensor<int32, [1]> reduce_mean_111_axes_0 = const()[name = string("reduce_mean_111_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_111_keep_dims_0 = const()[name = string("reduce_mean_111_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_111 = reduce_mean(axes = reduce_mean_111_axes_0, keep_dims = reduce_mean_111_keep_dims_0, x = mul_518)[name = string("reduce_mean_111")];
            fp32 rsqrt_111_epsilon_0 = const()[name = string("rsqrt_111_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_111 = rsqrt(epsilon = rsqrt_111_epsilon_0, x = reduce_mean_111)[name = string("rsqrt_111")];
            tensor<fp16, [8, 352]> mul_519 = mul(x = add_63, y = rsqrt_111)[name = string("mul_519")];
            tensor<fp16, [352]> mul_520_y_0 = const()[name = string("mul_520_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5858560)))];
            tensor<fp16, [8, 352]> mul_520 = mul(x = mul_519, y = mul_520_y_0)[name = string("mul_520")];
            tensor<fp16, [8, 352]> mul_521 = mul(x = mul_520, y = mul_520)[name = string("mul_521")];
            tensor<int32, [1]> reduce_mean_112_axes_0 = const()[name = string("reduce_mean_112_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_112_keep_dims_0 = const()[name = string("reduce_mean_112_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_112 = reduce_mean(axes = reduce_mean_112_axes_0, keep_dims = reduce_mean_112_keep_dims_0, x = mul_521)[name = string("reduce_mean_112")];
            fp32 rsqrt_112_epsilon_0 = const()[name = string("rsqrt_112_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_112 = rsqrt(epsilon = rsqrt_112_epsilon_0, x = reduce_mean_112)[name = string("rsqrt_112")];
            tensor<fp16, [8, 352]> mul_522 = mul(x = mul_520, y = rsqrt_112)[name = string("mul_522")];
            tensor<fp16, [352]> mul_523_y_0 = const()[name = string("mul_523_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5859328)))];
            tensor<fp16, [8, 352]> mul_523 = mul(x = mul_522, y = mul_523_y_0)[name = string("mul_523")];
            tensor<fp16, [960, 352]> tern_10_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5860096))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_10_w1_weight_0_palettized")];
            tensor<fp16, [8, 960]> tern_10_w1 = linear(bias = linear_4_bias_0, weight = tern_10_w1_weight_0_palettized, x = mul_523)[name = string("tern_10_w1")];
            tensor<fp16, [960]> mul_524_y_0 = const()[name = string("mul_524_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5944640)))];
            tensor<fp16, [8, 960]> mul_524 = mul(x = tern_10_w1, y = mul_524_y_0)[name = string("mul_524")];
            tensor<fp16, [352]> mul_527_y_0 = const()[name = string("mul_527_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5946624)))];
            tensor<fp16, [8, 352]> mul_527 = mul(x = mul_522, y = mul_527_y_0)[name = string("mul_527")];
            tensor<fp16, [960, 352]> tern_10_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5947392))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_10_w3_weight_0_palettized")];
            tensor<fp16, [8, 960]> tern_10_w3 = linear(bias = linear_4_bias_0, weight = tern_10_w3_weight_0_palettized, x = mul_527)[name = string("tern_10_w3")];
            tensor<fp16, [960]> mul_528_y_0 = const()[name = string("mul_528_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6031936)))];
            tensor<fp16, [8, 960]> mul_528 = mul(x = tern_10_w3, y = mul_528_y_0)[name = string("mul_528")];
            fp16 mul_529_y_0 = const()[name = string("mul_529_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [8, 960]> mul_529 = mul(x = mul_524, y = mul_529_y_0)[name = string("mul_529")];
            tensor<fp16, [8, 960]> tanh_10 = tanh(x = mul_529)[name = string("tanh_10")];
            fp16 mul_530_x_0 = const()[name = string("mul_530_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [8, 960]> mul_530 = mul(x = mul_530_x_0, y = tanh_10)[name = string("mul_530")];
            fp16 add_64_x_0 = const()[name = string("add_64_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [8, 960]> add_64 = add(x = add_64_x_0, y = mul_530)[name = string("add_64")];
            tensor<fp16, [8, 960]> mul_531 = mul(x = mul_524, y = add_64)[name = string("mul_531")];
            tensor<fp16, [8, 960]> mul_532 = mul(x = mul_531, y = mul_528)[name = string("mul_532")];
            tensor<fp16, [8, 960]> mul_533 = mul(x = mul_532, y = mul_532)[name = string("mul_533")];
            tensor<int32, [1]> reduce_mean_114_axes_0 = const()[name = string("reduce_mean_114_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_114_keep_dims_0 = const()[name = string("reduce_mean_114_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_114 = reduce_mean(axes = reduce_mean_114_axes_0, keep_dims = reduce_mean_114_keep_dims_0, x = mul_533)[name = string("reduce_mean_114")];
            fp32 rsqrt_114_epsilon_0 = const()[name = string("rsqrt_114_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_114 = rsqrt(epsilon = rsqrt_114_epsilon_0, x = reduce_mean_114)[name = string("rsqrt_114")];
            tensor<fp16, [8, 960]> mul_534 = mul(x = mul_532, y = rsqrt_114)[name = string("mul_534")];
            tensor<fp16, [960]> mul_535_y_0 = const()[name = string("mul_535_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6033920)))];
            tensor<fp16, [8, 960]> mul_535 = mul(x = mul_534, y = mul_535_y_0)[name = string("mul_535")];
            tensor<fp16, [352, 960]> tern_10_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6035904))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_10_w2_weight_0_palettized")];
            tensor<fp16, [8, 352]> tern_10_w2 = linear(bias = linear_0_bias_0, weight = tern_10_w2_weight_0_palettized, x = mul_535)[name = string("tern_10_w2")];
            tensor<fp16, [352]> mul_536_y_0 = const()[name = string("mul_536_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6120448)))];
            tensor<fp16, [8, 352]> mul_536 = mul(x = tern_10_w2, y = mul_536_y_0)[name = string("mul_536")];
            tensor<fp16, [8, 352]> add_65 = add(x = add_63, y = mul_536)[name = string("add_65")];
            tensor<fp16, [8, 352]> mul_537 = mul(x = add_65, y = add_65)[name = string("mul_537")];
            tensor<int32, [1]> reduce_mean_115_axes_0 = const()[name = string("reduce_mean_115_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_115_keep_dims_0 = const()[name = string("reduce_mean_115_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_115 = reduce_mean(axes = reduce_mean_115_axes_0, keep_dims = reduce_mean_115_keep_dims_0, x = mul_537)[name = string("reduce_mean_115")];
            fp32 rsqrt_115_epsilon_0 = const()[name = string("rsqrt_115_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_115 = rsqrt(epsilon = rsqrt_115_epsilon_0, x = reduce_mean_115)[name = string("rsqrt_115")];
            tensor<fp16, [8, 352]> mul_538 = mul(x = add_65, y = rsqrt_115)[name = string("mul_538")];
            tensor<fp16, [352]> mul_539_y_0 = const()[name = string("mul_539_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6121216)))];
            tensor<fp16, [8, 352]> mul_539 = mul(x = mul_538, y = mul_539_y_0)[name = string("mul_539")];
            tensor<fp16, [8, 352]> mul_540 = mul(x = mul_539, y = mul_539)[name = string("mul_540")];
            tensor<int32, [1]> reduce_mean_116_axes_0 = const()[name = string("reduce_mean_116_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_116_keep_dims_0 = const()[name = string("reduce_mean_116_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_116 = reduce_mean(axes = reduce_mean_116_axes_0, keep_dims = reduce_mean_116_keep_dims_0, x = mul_540)[name = string("reduce_mean_116")];
            fp32 rsqrt_116_epsilon_0 = const()[name = string("rsqrt_116_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_116 = rsqrt(epsilon = rsqrt_116_epsilon_0, x = reduce_mean_116)[name = string("rsqrt_116")];
            tensor<fp16, [8, 352]> mul_541 = mul(x = mul_539, y = rsqrt_116)[name = string("mul_541")];
            tensor<fp16, [352]> mul_542_y_0 = const()[name = string("mul_542_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6121984)))];
            tensor<fp16, [8, 352]> mul_542 = mul(x = mul_541, y = mul_542_y_0)[name = string("mul_542")];
            tensor<fp16, [352, 352]> tern_11_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6122752))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_11_q_weight_0_palettized")];
            tensor<fp16, [8, 352]> tern_11_q = linear(bias = linear_0_bias_0, weight = tern_11_q_weight_0_palettized, x = mul_542)[name = string("tern_11_q")];
            tensor<fp16, [352]> mul_543_y_0 = const()[name = string("mul_543_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6153792)))];
            tensor<fp16, [8, 352]> mul_543 = mul(x = tern_11_q, y = mul_543_y_0)[name = string("mul_543")];
            tensor<int32, [3]> reshape_90_shape_0 = const()[name = string("reshape_90_shape_0"), val = tensor<int32, [3]>([8, 8, 44])];
            tensor<fp16, [8, 8, 44]> reshape_90 = reshape(shape = reshape_90_shape_0, x = mul_543)[name = string("reshape_90")];
            tensor<int32, [3]> transpose_44_perm_0 = const()[name = string("transpose_44_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_546_y_0 = const()[name = string("mul_546_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6154560)))];
            tensor<fp16, [8, 352]> mul_546 = mul(x = mul_541, y = mul_546_y_0)[name = string("mul_546")];
            tensor<fp16, [88, 352]> tern_11_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6155328))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_11_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_11_k_bias_0 = const()[name = string("tern_11_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [8, 88]> tern_11_k = linear(bias = tern_11_k_bias_0, weight = tern_11_k_weight_0_palettized, x = mul_546)[name = string("tern_11_k")];
            tensor<fp16, [88]> mul_547_y_0 = const()[name = string("mul_547_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6163136)))];
            tensor<fp16, [8, 88]> mul_547 = mul(x = tern_11_k, y = mul_547_y_0)[name = string("mul_547")];
            tensor<int32, [3]> reshape_91_shape_0 = const()[name = string("reshape_91_shape_0"), val = tensor<int32, [3]>([8, 2, 44])];
            tensor<fp16, [8, 2, 44]> reshape_91 = reshape(shape = reshape_91_shape_0, x = mul_547)[name = string("reshape_91")];
            tensor<int32, [3]> transpose_45_perm_0 = const()[name = string("transpose_45_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_550_y_0 = const()[name = string("mul_550_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6163392)))];
            tensor<fp16, [8, 352]> mul_550 = mul(x = mul_541, y = mul_550_y_0)[name = string("mul_550")];
            tensor<fp16, [88, 352]> tern_11_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6164160))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_11_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_11_v_bias_0 = const()[name = string("tern_11_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [8, 88]> tern_11_v = linear(bias = tern_11_v_bias_0, weight = tern_11_v_weight_0_palettized, x = mul_550)[name = string("tern_11_v")];
            tensor<fp16, [88]> mul_551_y_0 = const()[name = string("mul_551_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6171968)))];
            tensor<fp16, [8, 88]> mul_551 = mul(x = tern_11_v, y = mul_551_y_0)[name = string("mul_551")];
            tensor<int32, [3]> reshape_92_shape_0 = const()[name = string("reshape_92_shape_0"), val = tensor<int32, [3]>([8, 2, 44])];
            tensor<fp16, [8, 2, 44]> reshape_92 = reshape(shape = reshape_92_shape_0, x = mul_551)[name = string("reshape_92")];
            tensor<int32, [3]> transpose_46_perm_0 = const()[name = string("transpose_46_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 8, 44]> transpose_44 = transpose(perm = transpose_44_perm_0, x = reshape_90)[name = string("transpose_19")];
            tensor<fp16, [8, 8, 44]> mul_552 = mul(x = transpose_44, y = transpose_44)[name = string("mul_552")];
            tensor<int32, [1]> reduce_mean_119_axes_0 = const()[name = string("reduce_mean_119_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_119_keep_dims_0 = const()[name = string("reduce_mean_119_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 8, 1]> reduce_mean_119 = reduce_mean(axes = reduce_mean_119_axes_0, keep_dims = reduce_mean_119_keep_dims_0, x = mul_552)[name = string("reduce_mean_119")];
            fp32 rsqrt_119_epsilon_0 = const()[name = string("rsqrt_119_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 8, 1]> rsqrt_119 = rsqrt(epsilon = rsqrt_119_epsilon_0, x = reduce_mean_119)[name = string("rsqrt_119")];
            tensor<fp16, [8, 8, 44]> mul_553 = mul(x = transpose_44, y = rsqrt_119)[name = string("mul_553")];
            tensor<fp16, [44]> mul_554_y_0 = const()[name = string("mul_554_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6172224)))];
            tensor<fp16, [8, 8, 44]> mul_554 = mul(x = mul_553, y = mul_554_y_0)[name = string("mul_554")];
            tensor<int32, [3]> slice_by_index_44_begin_0 = const()[name = string("slice_by_index_44_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_44_end_0 = const()[name = string("slice_by_index_44_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_44_end_mask_0 = const()[name = string("slice_by_index_44_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 8, 22]> slice_by_index_44 = slice_by_index(begin = slice_by_index_44_begin_0, end = slice_by_index_44_end_0, end_mask = slice_by_index_44_end_mask_0, x = mul_554)[name = string("slice_by_index_44")];
            tensor<int32, [3]> slice_by_index_45_begin_0 = const()[name = string("slice_by_index_45_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_45_end_0 = const()[name = string("slice_by_index_45_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_45_end_mask_0 = const()[name = string("slice_by_index_45_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 8, 22]> slice_by_index_45 = slice_by_index(begin = slice_by_index_45_begin_0, end = slice_by_index_45_end_0, end_mask = slice_by_index_45_end_mask_0, x = mul_554)[name = string("slice_by_index_45")];
            int32 concat_22_axis_0 = const()[name = string("concat_22_axis_0"), val = int32(-1)];
            bool concat_22_interleave_0 = const()[name = string("concat_22_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 8, 44]> concat_22 = concat(axis = concat_22_axis_0, interleave = concat_22_interleave_0, values = (slice_by_index_45, slice_by_index_44))[name = string("concat_22")];
            tensor<fp16, [44]> mul_555_y_0 = const()[name = string("mul_555_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 8, 44]> mul_555 = mul(x = concat_22, y = mul_555_y_0)[name = string("mul_555")];
            tensor<fp16, [8, 8, 44]> mul_556 = mul(x = mul_554, y = mul_11_y_0)[name = string("mul_556")];
            tensor<fp16, [8, 8, 44]> mul_557 = mul(x = mul_555, y = mul_12_y_0)[name = string("mul_557")];
            tensor<fp16, [8, 8, 44]> add_66 = add(x = mul_556, y = mul_557)[name = string("add_66")];
            tensor<fp16, [2, 8, 44]> transpose_45 = transpose(perm = transpose_45_perm_0, x = reshape_91)[name = string("transpose_18")];
            tensor<fp16, [2, 8, 44]> mul_558 = mul(x = transpose_45, y = transpose_45)[name = string("mul_558")];
            tensor<int32, [1]> reduce_mean_120_axes_0 = const()[name = string("reduce_mean_120_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_120_keep_dims_0 = const()[name = string("reduce_mean_120_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 8, 1]> reduce_mean_120 = reduce_mean(axes = reduce_mean_120_axes_0, keep_dims = reduce_mean_120_keep_dims_0, x = mul_558)[name = string("reduce_mean_120")];
            fp32 rsqrt_120_epsilon_0 = const()[name = string("rsqrt_120_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 8, 1]> rsqrt_120 = rsqrt(epsilon = rsqrt_120_epsilon_0, x = reduce_mean_120)[name = string("rsqrt_120")];
            tensor<fp16, [2, 8, 44]> mul_559 = mul(x = transpose_45, y = rsqrt_120)[name = string("mul_559")];
            tensor<fp16, [44]> mul_560_y_0 = const()[name = string("mul_560_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6172416)))];
            tensor<fp16, [2, 8, 44]> mul_560 = mul(x = mul_559, y = mul_560_y_0)[name = string("mul_560")];
            tensor<int32, [3]> slice_by_index_46_begin_0 = const()[name = string("slice_by_index_46_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_46_end_0 = const()[name = string("slice_by_index_46_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_46_end_mask_0 = const()[name = string("slice_by_index_46_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 8, 22]> slice_by_index_46 = slice_by_index(begin = slice_by_index_46_begin_0, end = slice_by_index_46_end_0, end_mask = slice_by_index_46_end_mask_0, x = mul_560)[name = string("slice_by_index_46")];
            tensor<int32, [3]> slice_by_index_47_begin_0 = const()[name = string("slice_by_index_47_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_47_end_0 = const()[name = string("slice_by_index_47_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_47_end_mask_0 = const()[name = string("slice_by_index_47_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 8, 22]> slice_by_index_47 = slice_by_index(begin = slice_by_index_47_begin_0, end = slice_by_index_47_end_0, end_mask = slice_by_index_47_end_mask_0, x = mul_560)[name = string("slice_by_index_47")];
            int32 concat_23_axis_0 = const()[name = string("concat_23_axis_0"), val = int32(-1)];
            bool concat_23_interleave_0 = const()[name = string("concat_23_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 8, 44]> concat_23 = concat(axis = concat_23_axis_0, interleave = concat_23_interleave_0, values = (slice_by_index_47, slice_by_index_46))[name = string("concat_23")];
            tensor<fp16, [44]> mul_561_y_0 = const()[name = string("mul_561_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 8, 44]> mul_561 = mul(x = concat_23, y = mul_561_y_0)[name = string("mul_561")];
            tensor<fp16, [2, 8, 44]> mul_562 = mul(x = mul_560, y = mul_11_y_0)[name = string("mul_562")];
            tensor<fp16, [2, 8, 44]> mul_563 = mul(x = mul_561, y = mul_12_y_0)[name = string("mul_563")];
            tensor<fp16, [2, 8, 44]> add_67 = add(x = mul_562, y = mul_563)[name = string("add_67")];
            tensor<int32, [4]> reshape_93_shape_0 = const()[name = string("reshape_93_shape_0"), val = tensor<int32, [4]>([2, 1, 8, 44])];
            tensor<fp16, [2, 1, 8, 44]> reshape_93 = reshape(shape = reshape_93_shape_0, x = add_67)[name = string("reshape_93")];
            tensor<int32, [4]> tile_22_reps_0 = const()[name = string("tile_22_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 8, 44]> tile_22 = tile(reps = tile_22_reps_0, x = reshape_93)[name = string("tile_22")];
            tensor<int32, [3]> reshape_94_shape_0 = const()[name = string("reshape_94_shape_0"), val = tensor<int32, [3]>([8, 8, 44])];
            tensor<fp16, [8, 8, 44]> reshape_94 = reshape(shape = reshape_94_shape_0, x = tile_22)[name = string("reshape_94")];
            tensor<int32, [4]> reshape_95_shape_0 = const()[name = string("reshape_95_shape_0"), val = tensor<int32, [4]>([2, 1, 8, 44])];
            tensor<fp16, [2, 8, 44]> transpose_46 = transpose(perm = transpose_46_perm_0, x = reshape_92)[name = string("transpose_17")];
            tensor<fp16, [2, 1, 8, 44]> reshape_95 = reshape(shape = reshape_95_shape_0, x = transpose_46)[name = string("reshape_95")];
            tensor<int32, [4]> tile_23_reps_0 = const()[name = string("tile_23_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 8, 44]> tile_23 = tile(reps = tile_23_reps_0, x = reshape_95)[name = string("tile_23")];
            tensor<int32, [3]> reshape_96_shape_0 = const()[name = string("reshape_96_shape_0"), val = tensor<int32, [3]>([8, 8, 44])];
            tensor<fp16, [8, 8, 44]> reshape_96 = reshape(shape = reshape_96_shape_0, x = tile_23)[name = string("reshape_96")];
            fp16 mul_564_y_0 = const()[name = string("mul_564_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 8, 44]> mul_564 = mul(x = add_66, y = mul_564_y_0)[name = string("mul_564")];
            bool matmul_22_transpose_y_0 = const()[name = string("matmul_22_transpose_y_0"), val = bool(true)];
            bool matmul_22_transpose_x_0 = const()[name = string("matmul_22_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 8, 8]> matmul_22 = matmul(transpose_x = matmul_22_transpose_x_0, transpose_y = matmul_22_transpose_y_0, x = mul_564, y = reshape_94)[name = string("matmul_22")];
            tensor<fp16, [8, 8, 8]> add_68 = add(x = matmul_22, y = reshape_1)[name = string("add_68")];
            int32 softmax_11_axis_0 = const()[name = string("softmax_11_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 8, 8]> softmax_11 = softmax(axis = softmax_11_axis_0, x = add_68)[name = string("softmax_11")];
            bool matmul_23_transpose_x_0 = const()[name = string("matmul_23_transpose_x_0"), val = bool(false)];
            bool matmul_23_transpose_y_0 = const()[name = string("matmul_23_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 8, 44]> matmul_23 = matmul(transpose_x = matmul_23_transpose_x_0, transpose_y = matmul_23_transpose_y_0, x = softmax_11, y = reshape_96)[name = string("matmul_23")];
            tensor<int32, [3]> transpose_47_perm_0 = const()[name = string("transpose_47_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_97_shape_0 = const()[name = string("reshape_97_shape_0"), val = tensor<int32, [2]>([8, 352])];
            tensor<fp16, [8, 8, 44]> transpose_47 = transpose(perm = transpose_47_perm_0, x = matmul_23)[name = string("transpose_16")];
            tensor<fp16, [8, 352]> reshape_97 = reshape(shape = reshape_97_shape_0, x = transpose_47)[name = string("reshape_97")];
            tensor<fp16, [8, 352]> mul_565 = mul(x = reshape_97, y = reshape_97)[name = string("mul_565")];
            tensor<int32, [1]> reduce_mean_121_axes_0 = const()[name = string("reduce_mean_121_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_121_keep_dims_0 = const()[name = string("reduce_mean_121_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_121 = reduce_mean(axes = reduce_mean_121_axes_0, keep_dims = reduce_mean_121_keep_dims_0, x = mul_565)[name = string("reduce_mean_121")];
            fp32 rsqrt_121_epsilon_0 = const()[name = string("rsqrt_121_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_121 = rsqrt(epsilon = rsqrt_121_epsilon_0, x = reduce_mean_121)[name = string("rsqrt_121")];
            tensor<fp16, [8, 352]> mul_566 = mul(x = reshape_97, y = rsqrt_121)[name = string("mul_566")];
            tensor<fp16, [352]> mul_567_y_0 = const()[name = string("mul_567_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6172608)))];
            tensor<fp16, [8, 352]> mul_567 = mul(x = mul_566, y = mul_567_y_0)[name = string("mul_567")];
            tensor<fp16, [352, 352]> tern_11_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6173376))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_11_o_weight_0_palettized")];
            tensor<fp16, [8, 352]> tern_11_o = linear(bias = linear_0_bias_0, weight = tern_11_o_weight_0_palettized, x = mul_567)[name = string("tern_11_o")];
            tensor<fp16, [352]> mul_568_y_0 = const()[name = string("mul_568_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6204416)))];
            tensor<fp16, [8, 352]> mul_568 = mul(x = tern_11_o, y = mul_568_y_0)[name = string("mul_568")];
            tensor<fp16, [8, 352]> add_69 = add(x = add_65, y = mul_568)[name = string("add_69")];
            tensor<fp16, [8, 352]> mul_569 = mul(x = add_69, y = add_69)[name = string("mul_569")];
            tensor<int32, [1]> reduce_mean_122_axes_0 = const()[name = string("reduce_mean_122_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_122_keep_dims_0 = const()[name = string("reduce_mean_122_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_122 = reduce_mean(axes = reduce_mean_122_axes_0, keep_dims = reduce_mean_122_keep_dims_0, x = mul_569)[name = string("reduce_mean_122")];
            fp32 rsqrt_122_epsilon_0 = const()[name = string("rsqrt_122_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_122 = rsqrt(epsilon = rsqrt_122_epsilon_0, x = reduce_mean_122)[name = string("rsqrt_122")];
            tensor<fp16, [8, 352]> mul_570 = mul(x = add_69, y = rsqrt_122)[name = string("mul_570")];
            tensor<fp16, [352]> mul_571_y_0 = const()[name = string("mul_571_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6205184)))];
            tensor<fp16, [8, 352]> mul_571 = mul(x = mul_570, y = mul_571_y_0)[name = string("mul_571")];
            tensor<fp16, [8, 352]> mul_572 = mul(x = mul_571, y = mul_571)[name = string("mul_572")];
            tensor<int32, [1]> reduce_mean_123_axes_0 = const()[name = string("reduce_mean_123_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_123_keep_dims_0 = const()[name = string("reduce_mean_123_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_123 = reduce_mean(axes = reduce_mean_123_axes_0, keep_dims = reduce_mean_123_keep_dims_0, x = mul_572)[name = string("reduce_mean_123")];
            fp32 rsqrt_123_epsilon_0 = const()[name = string("rsqrt_123_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_123 = rsqrt(epsilon = rsqrt_123_epsilon_0, x = reduce_mean_123)[name = string("rsqrt_123")];
            tensor<fp16, [8, 352]> mul_573 = mul(x = mul_571, y = rsqrt_123)[name = string("mul_573")];
            tensor<fp16, [352]> mul_574_y_0 = const()[name = string("mul_574_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6205952)))];
            tensor<fp16, [8, 352]> mul_574 = mul(x = mul_573, y = mul_574_y_0)[name = string("mul_574")];
            tensor<fp16, [960, 352]> tern_11_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6206720))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_11_w1_weight_0_palettized")];
            tensor<fp16, [8, 960]> tern_11_w1 = linear(bias = linear_4_bias_0, weight = tern_11_w1_weight_0_palettized, x = mul_574)[name = string("tern_11_w1")];
            tensor<fp16, [960]> mul_575_y_0 = const()[name = string("mul_575_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6291264)))];
            tensor<fp16, [8, 960]> mul_575 = mul(x = tern_11_w1, y = mul_575_y_0)[name = string("mul_575")];
            tensor<fp16, [352]> mul_578_y_0 = const()[name = string("mul_578_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6293248)))];
            tensor<fp16, [8, 352]> mul_578 = mul(x = mul_573, y = mul_578_y_0)[name = string("mul_578")];
            tensor<fp16, [960, 352]> tern_11_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6294016))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_11_w3_weight_0_palettized")];
            tensor<fp16, [8, 960]> tern_11_w3 = linear(bias = linear_4_bias_0, weight = tern_11_w3_weight_0_palettized, x = mul_578)[name = string("tern_11_w3")];
            tensor<fp16, [960]> mul_579_y_0 = const()[name = string("mul_579_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6378560)))];
            tensor<fp16, [8, 960]> mul_579 = mul(x = tern_11_w3, y = mul_579_y_0)[name = string("mul_579")];
            fp16 mul_580_y_0 = const()[name = string("mul_580_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [8, 960]> mul_580 = mul(x = mul_575, y = mul_580_y_0)[name = string("mul_580")];
            tensor<fp16, [8, 960]> tanh_11 = tanh(x = mul_580)[name = string("tanh_11")];
            fp16 mul_581_x_0 = const()[name = string("mul_581_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [8, 960]> mul_581 = mul(x = mul_581_x_0, y = tanh_11)[name = string("mul_581")];
            fp16 add_70_x_0 = const()[name = string("add_70_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [8, 960]> add_70 = add(x = add_70_x_0, y = mul_581)[name = string("add_70")];
            tensor<fp16, [8, 960]> mul_582 = mul(x = mul_575, y = add_70)[name = string("mul_582")];
            tensor<fp16, [8, 960]> mul_583 = mul(x = mul_582, y = mul_579)[name = string("mul_583")];
            tensor<fp16, [8, 960]> mul_584 = mul(x = mul_583, y = mul_583)[name = string("mul_584")];
            tensor<int32, [1]> reduce_mean_125_axes_0 = const()[name = string("reduce_mean_125_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_125_keep_dims_0 = const()[name = string("reduce_mean_125_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_125 = reduce_mean(axes = reduce_mean_125_axes_0, keep_dims = reduce_mean_125_keep_dims_0, x = mul_584)[name = string("reduce_mean_125")];
            fp32 rsqrt_125_epsilon_0 = const()[name = string("rsqrt_125_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_125 = rsqrt(epsilon = rsqrt_125_epsilon_0, x = reduce_mean_125)[name = string("rsqrt_125")];
            tensor<fp16, [8, 960]> mul_585 = mul(x = mul_583, y = rsqrt_125)[name = string("mul_585")];
            tensor<fp16, [960]> mul_586_y_0 = const()[name = string("mul_586_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6380544)))];
            tensor<fp16, [8, 960]> mul_586 = mul(x = mul_585, y = mul_586_y_0)[name = string("mul_586")];
            tensor<fp16, [352, 960]> tern_11_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6382528))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_11_w2_weight_0_palettized")];
            tensor<fp16, [8, 352]> tern_11_w2 = linear(bias = linear_0_bias_0, weight = tern_11_w2_weight_0_palettized, x = mul_586)[name = string("tern_11_w2")];
            tensor<fp16, [352]> mul_587_y_0 = const()[name = string("mul_587_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6467072)))];
            tensor<fp16, [8, 352]> mul_587 = mul(x = tern_11_w2, y = mul_587_y_0)[name = string("mul_587")];
            tensor<fp16, [8, 352]> add_71 = add(x = add_69, y = mul_587)[name = string("add_71")];
            tensor<fp16, [8, 352]> mul_588 = mul(x = add_71, y = add_71)[name = string("mul_588")];
            tensor<int32, [1]> reduce_mean_126_axes_0 = const()[name = string("reduce_mean_126_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_126_keep_dims_0 = const()[name = string("reduce_mean_126_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_126 = reduce_mean(axes = reduce_mean_126_axes_0, keep_dims = reduce_mean_126_keep_dims_0, x = mul_588)[name = string("reduce_mean_126")];
            fp32 rsqrt_126_epsilon_0 = const()[name = string("rsqrt_126_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_126 = rsqrt(epsilon = rsqrt_126_epsilon_0, x = reduce_mean_126)[name = string("rsqrt_126")];
            tensor<fp16, [8, 352]> mul_589 = mul(x = add_71, y = rsqrt_126)[name = string("mul_589")];
            tensor<fp16, [352]> mul_590_y_0 = const()[name = string("mul_590_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6467840)))];
            tensor<fp16, [8, 352]> mul_590 = mul(x = mul_589, y = mul_590_y_0)[name = string("mul_590")];
            tensor<fp16, [8, 352]> mul_591 = mul(x = mul_590, y = mul_590)[name = string("mul_591")];
            tensor<int32, [1]> reduce_mean_127_axes_0 = const()[name = string("reduce_mean_127_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_127_keep_dims_0 = const()[name = string("reduce_mean_127_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_127 = reduce_mean(axes = reduce_mean_127_axes_0, keep_dims = reduce_mean_127_keep_dims_0, x = mul_591)[name = string("reduce_mean_127")];
            fp32 rsqrt_127_epsilon_0 = const()[name = string("rsqrt_127_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_127 = rsqrt(epsilon = rsqrt_127_epsilon_0, x = reduce_mean_127)[name = string("rsqrt_127")];
            tensor<fp16, [8, 352]> mul_592 = mul(x = mul_590, y = rsqrt_127)[name = string("mul_592")];
            tensor<fp16, [352]> mul_593_y_0 = const()[name = string("mul_593_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6468608)))];
            tensor<fp16, [8, 352]> mul_593 = mul(x = mul_592, y = mul_593_y_0)[name = string("mul_593")];
            tensor<fp16, [352, 352]> tern_12_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6469376))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_12_q_weight_0_palettized")];
            tensor<fp16, [8, 352]> tern_12_q = linear(bias = linear_0_bias_0, weight = tern_12_q_weight_0_palettized, x = mul_593)[name = string("tern_12_q")];
            tensor<fp16, [352]> mul_594_y_0 = const()[name = string("mul_594_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6500416)))];
            tensor<fp16, [8, 352]> mul_594 = mul(x = tern_12_q, y = mul_594_y_0)[name = string("mul_594")];
            tensor<int32, [3]> reshape_98_shape_0 = const()[name = string("reshape_98_shape_0"), val = tensor<int32, [3]>([8, 8, 44])];
            tensor<fp16, [8, 8, 44]> reshape_98 = reshape(shape = reshape_98_shape_0, x = mul_594)[name = string("reshape_98")];
            tensor<int32, [3]> transpose_48_perm_0 = const()[name = string("transpose_48_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_597_y_0 = const()[name = string("mul_597_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6501184)))];
            tensor<fp16, [8, 352]> mul_597 = mul(x = mul_592, y = mul_597_y_0)[name = string("mul_597")];
            tensor<fp16, [88, 352]> tern_12_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6501952))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_12_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_12_k_bias_0 = const()[name = string("tern_12_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [8, 88]> tern_12_k = linear(bias = tern_12_k_bias_0, weight = tern_12_k_weight_0_palettized, x = mul_597)[name = string("tern_12_k")];
            tensor<fp16, [88]> mul_598_y_0 = const()[name = string("mul_598_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6509760)))];
            tensor<fp16, [8, 88]> mul_598 = mul(x = tern_12_k, y = mul_598_y_0)[name = string("mul_598")];
            tensor<int32, [3]> reshape_99_shape_0 = const()[name = string("reshape_99_shape_0"), val = tensor<int32, [3]>([8, 2, 44])];
            tensor<fp16, [8, 2, 44]> reshape_99 = reshape(shape = reshape_99_shape_0, x = mul_598)[name = string("reshape_99")];
            tensor<int32, [3]> transpose_49_perm_0 = const()[name = string("transpose_49_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_601_y_0 = const()[name = string("mul_601_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6510016)))];
            tensor<fp16, [8, 352]> mul_601 = mul(x = mul_592, y = mul_601_y_0)[name = string("mul_601")];
            tensor<fp16, [88, 352]> tern_12_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6510784))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_12_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_12_v_bias_0 = const()[name = string("tern_12_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [8, 88]> tern_12_v = linear(bias = tern_12_v_bias_0, weight = tern_12_v_weight_0_palettized, x = mul_601)[name = string("tern_12_v")];
            tensor<fp16, [88]> mul_602_y_0 = const()[name = string("mul_602_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6518592)))];
            tensor<fp16, [8, 88]> mul_602 = mul(x = tern_12_v, y = mul_602_y_0)[name = string("mul_602")];
            tensor<int32, [3]> reshape_100_shape_0 = const()[name = string("reshape_100_shape_0"), val = tensor<int32, [3]>([8, 2, 44])];
            tensor<fp16, [8, 2, 44]> reshape_100 = reshape(shape = reshape_100_shape_0, x = mul_602)[name = string("reshape_100")];
            tensor<int32, [3]> transpose_50_perm_0 = const()[name = string("transpose_50_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 8, 44]> transpose_48 = transpose(perm = transpose_48_perm_0, x = reshape_98)[name = string("transpose_15")];
            tensor<fp16, [8, 8, 44]> mul_603 = mul(x = transpose_48, y = transpose_48)[name = string("mul_603")];
            tensor<int32, [1]> reduce_mean_130_axes_0 = const()[name = string("reduce_mean_130_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_130_keep_dims_0 = const()[name = string("reduce_mean_130_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 8, 1]> reduce_mean_130 = reduce_mean(axes = reduce_mean_130_axes_0, keep_dims = reduce_mean_130_keep_dims_0, x = mul_603)[name = string("reduce_mean_130")];
            fp32 rsqrt_130_epsilon_0 = const()[name = string("rsqrt_130_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 8, 1]> rsqrt_130 = rsqrt(epsilon = rsqrt_130_epsilon_0, x = reduce_mean_130)[name = string("rsqrt_130")];
            tensor<fp16, [8, 8, 44]> mul_604 = mul(x = transpose_48, y = rsqrt_130)[name = string("mul_604")];
            tensor<fp16, [44]> mul_605_y_0 = const()[name = string("mul_605_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6518848)))];
            tensor<fp16, [8, 8, 44]> mul_605 = mul(x = mul_604, y = mul_605_y_0)[name = string("mul_605")];
            tensor<int32, [3]> slice_by_index_48_begin_0 = const()[name = string("slice_by_index_48_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_48_end_0 = const()[name = string("slice_by_index_48_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_48_end_mask_0 = const()[name = string("slice_by_index_48_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 8, 22]> slice_by_index_48 = slice_by_index(begin = slice_by_index_48_begin_0, end = slice_by_index_48_end_0, end_mask = slice_by_index_48_end_mask_0, x = mul_605)[name = string("slice_by_index_48")];
            tensor<int32, [3]> slice_by_index_49_begin_0 = const()[name = string("slice_by_index_49_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_49_end_0 = const()[name = string("slice_by_index_49_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_49_end_mask_0 = const()[name = string("slice_by_index_49_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 8, 22]> slice_by_index_49 = slice_by_index(begin = slice_by_index_49_begin_0, end = slice_by_index_49_end_0, end_mask = slice_by_index_49_end_mask_0, x = mul_605)[name = string("slice_by_index_49")];
            int32 concat_24_axis_0 = const()[name = string("concat_24_axis_0"), val = int32(-1)];
            bool concat_24_interleave_0 = const()[name = string("concat_24_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 8, 44]> concat_24 = concat(axis = concat_24_axis_0, interleave = concat_24_interleave_0, values = (slice_by_index_49, slice_by_index_48))[name = string("concat_24")];
            tensor<fp16, [44]> mul_606_y_0 = const()[name = string("mul_606_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 8, 44]> mul_606 = mul(x = concat_24, y = mul_606_y_0)[name = string("mul_606")];
            tensor<fp16, [8, 8, 44]> mul_607 = mul(x = mul_605, y = mul_11_y_0)[name = string("mul_607")];
            tensor<fp16, [8, 8, 44]> mul_608 = mul(x = mul_606, y = mul_12_y_0)[name = string("mul_608")];
            tensor<fp16, [8, 8, 44]> add_72 = add(x = mul_607, y = mul_608)[name = string("add_72")];
            tensor<fp16, [2, 8, 44]> transpose_49 = transpose(perm = transpose_49_perm_0, x = reshape_99)[name = string("transpose_14")];
            tensor<fp16, [2, 8, 44]> mul_609 = mul(x = transpose_49, y = transpose_49)[name = string("mul_609")];
            tensor<int32, [1]> reduce_mean_131_axes_0 = const()[name = string("reduce_mean_131_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_131_keep_dims_0 = const()[name = string("reduce_mean_131_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 8, 1]> reduce_mean_131 = reduce_mean(axes = reduce_mean_131_axes_0, keep_dims = reduce_mean_131_keep_dims_0, x = mul_609)[name = string("reduce_mean_131")];
            fp32 rsqrt_131_epsilon_0 = const()[name = string("rsqrt_131_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 8, 1]> rsqrt_131 = rsqrt(epsilon = rsqrt_131_epsilon_0, x = reduce_mean_131)[name = string("rsqrt_131")];
            tensor<fp16, [2, 8, 44]> mul_610 = mul(x = transpose_49, y = rsqrt_131)[name = string("mul_610")];
            tensor<fp16, [44]> mul_611_y_0 = const()[name = string("mul_611_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6519040)))];
            tensor<fp16, [2, 8, 44]> mul_611 = mul(x = mul_610, y = mul_611_y_0)[name = string("mul_611")];
            tensor<int32, [3]> slice_by_index_50_begin_0 = const()[name = string("slice_by_index_50_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_50_end_0 = const()[name = string("slice_by_index_50_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_50_end_mask_0 = const()[name = string("slice_by_index_50_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 8, 22]> slice_by_index_50 = slice_by_index(begin = slice_by_index_50_begin_0, end = slice_by_index_50_end_0, end_mask = slice_by_index_50_end_mask_0, x = mul_611)[name = string("slice_by_index_50")];
            tensor<int32, [3]> slice_by_index_51_begin_0 = const()[name = string("slice_by_index_51_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_51_end_0 = const()[name = string("slice_by_index_51_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_51_end_mask_0 = const()[name = string("slice_by_index_51_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 8, 22]> slice_by_index_51 = slice_by_index(begin = slice_by_index_51_begin_0, end = slice_by_index_51_end_0, end_mask = slice_by_index_51_end_mask_0, x = mul_611)[name = string("slice_by_index_51")];
            int32 concat_25_axis_0 = const()[name = string("concat_25_axis_0"), val = int32(-1)];
            bool concat_25_interleave_0 = const()[name = string("concat_25_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 8, 44]> concat_25 = concat(axis = concat_25_axis_0, interleave = concat_25_interleave_0, values = (slice_by_index_51, slice_by_index_50))[name = string("concat_25")];
            tensor<fp16, [44]> mul_612_y_0 = const()[name = string("mul_612_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 8, 44]> mul_612 = mul(x = concat_25, y = mul_612_y_0)[name = string("mul_612")];
            tensor<fp16, [2, 8, 44]> mul_613 = mul(x = mul_611, y = mul_11_y_0)[name = string("mul_613")];
            tensor<fp16, [2, 8, 44]> mul_614 = mul(x = mul_612, y = mul_12_y_0)[name = string("mul_614")];
            tensor<fp16, [2, 8, 44]> add_73 = add(x = mul_613, y = mul_614)[name = string("add_73")];
            tensor<int32, [4]> reshape_101_shape_0 = const()[name = string("reshape_101_shape_0"), val = tensor<int32, [4]>([2, 1, 8, 44])];
            tensor<fp16, [2, 1, 8, 44]> reshape_101 = reshape(shape = reshape_101_shape_0, x = add_73)[name = string("reshape_101")];
            tensor<int32, [4]> tile_24_reps_0 = const()[name = string("tile_24_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 8, 44]> tile_24 = tile(reps = tile_24_reps_0, x = reshape_101)[name = string("tile_24")];
            tensor<int32, [3]> reshape_102_shape_0 = const()[name = string("reshape_102_shape_0"), val = tensor<int32, [3]>([8, 8, 44])];
            tensor<fp16, [8, 8, 44]> reshape_102 = reshape(shape = reshape_102_shape_0, x = tile_24)[name = string("reshape_102")];
            tensor<int32, [4]> reshape_103_shape_0 = const()[name = string("reshape_103_shape_0"), val = tensor<int32, [4]>([2, 1, 8, 44])];
            tensor<fp16, [2, 8, 44]> transpose_50 = transpose(perm = transpose_50_perm_0, x = reshape_100)[name = string("transpose_13")];
            tensor<fp16, [2, 1, 8, 44]> reshape_103 = reshape(shape = reshape_103_shape_0, x = transpose_50)[name = string("reshape_103")];
            tensor<int32, [4]> tile_25_reps_0 = const()[name = string("tile_25_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 8, 44]> tile_25 = tile(reps = tile_25_reps_0, x = reshape_103)[name = string("tile_25")];
            tensor<int32, [3]> reshape_104_shape_0 = const()[name = string("reshape_104_shape_0"), val = tensor<int32, [3]>([8, 8, 44])];
            tensor<fp16, [8, 8, 44]> reshape_104 = reshape(shape = reshape_104_shape_0, x = tile_25)[name = string("reshape_104")];
            fp16 mul_615_y_0 = const()[name = string("mul_615_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 8, 44]> mul_615 = mul(x = add_72, y = mul_615_y_0)[name = string("mul_615")];
            bool matmul_24_transpose_y_0 = const()[name = string("matmul_24_transpose_y_0"), val = bool(true)];
            bool matmul_24_transpose_x_0 = const()[name = string("matmul_24_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 8, 8]> matmul_24 = matmul(transpose_x = matmul_24_transpose_x_0, transpose_y = matmul_24_transpose_y_0, x = mul_615, y = reshape_102)[name = string("matmul_24")];
            tensor<fp16, [8, 8, 8]> add_74 = add(x = matmul_24, y = reshape_1)[name = string("add_74")];
            int32 softmax_12_axis_0 = const()[name = string("softmax_12_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 8, 8]> softmax_12 = softmax(axis = softmax_12_axis_0, x = add_74)[name = string("softmax_12")];
            bool matmul_25_transpose_x_0 = const()[name = string("matmul_25_transpose_x_0"), val = bool(false)];
            bool matmul_25_transpose_y_0 = const()[name = string("matmul_25_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 8, 44]> matmul_25 = matmul(transpose_x = matmul_25_transpose_x_0, transpose_y = matmul_25_transpose_y_0, x = softmax_12, y = reshape_104)[name = string("matmul_25")];
            tensor<int32, [3]> transpose_51_perm_0 = const()[name = string("transpose_51_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_105_shape_0 = const()[name = string("reshape_105_shape_0"), val = tensor<int32, [2]>([8, 352])];
            tensor<fp16, [8, 8, 44]> transpose_51 = transpose(perm = transpose_51_perm_0, x = matmul_25)[name = string("transpose_12")];
            tensor<fp16, [8, 352]> reshape_105 = reshape(shape = reshape_105_shape_0, x = transpose_51)[name = string("reshape_105")];
            tensor<fp16, [8, 352]> mul_616 = mul(x = reshape_105, y = reshape_105)[name = string("mul_616")];
            tensor<int32, [1]> reduce_mean_132_axes_0 = const()[name = string("reduce_mean_132_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_132_keep_dims_0 = const()[name = string("reduce_mean_132_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_132 = reduce_mean(axes = reduce_mean_132_axes_0, keep_dims = reduce_mean_132_keep_dims_0, x = mul_616)[name = string("reduce_mean_132")];
            fp32 rsqrt_132_epsilon_0 = const()[name = string("rsqrt_132_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_132 = rsqrt(epsilon = rsqrt_132_epsilon_0, x = reduce_mean_132)[name = string("rsqrt_132")];
            tensor<fp16, [8, 352]> mul_617 = mul(x = reshape_105, y = rsqrt_132)[name = string("mul_617")];
            tensor<fp16, [352]> mul_618_y_0 = const()[name = string("mul_618_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6519232)))];
            tensor<fp16, [8, 352]> mul_618 = mul(x = mul_617, y = mul_618_y_0)[name = string("mul_618")];
            tensor<fp16, [352, 352]> tern_12_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6520000))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_12_o_weight_0_palettized")];
            tensor<fp16, [8, 352]> tern_12_o = linear(bias = linear_0_bias_0, weight = tern_12_o_weight_0_palettized, x = mul_618)[name = string("tern_12_o")];
            tensor<fp16, [352]> mul_619_y_0 = const()[name = string("mul_619_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6551040)))];
            tensor<fp16, [8, 352]> mul_619 = mul(x = tern_12_o, y = mul_619_y_0)[name = string("mul_619")];
            tensor<fp16, [8, 352]> add_75 = add(x = add_71, y = mul_619)[name = string("add_75")];
            tensor<fp16, [8, 352]> mul_620 = mul(x = add_75, y = add_75)[name = string("mul_620")];
            tensor<int32, [1]> reduce_mean_133_axes_0 = const()[name = string("reduce_mean_133_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_133_keep_dims_0 = const()[name = string("reduce_mean_133_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_133 = reduce_mean(axes = reduce_mean_133_axes_0, keep_dims = reduce_mean_133_keep_dims_0, x = mul_620)[name = string("reduce_mean_133")];
            fp32 rsqrt_133_epsilon_0 = const()[name = string("rsqrt_133_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_133 = rsqrt(epsilon = rsqrt_133_epsilon_0, x = reduce_mean_133)[name = string("rsqrt_133")];
            tensor<fp16, [8, 352]> mul_621 = mul(x = add_75, y = rsqrt_133)[name = string("mul_621")];
            tensor<fp16, [352]> mul_622_y_0 = const()[name = string("mul_622_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6551808)))];
            tensor<fp16, [8, 352]> mul_622 = mul(x = mul_621, y = mul_622_y_0)[name = string("mul_622")];
            tensor<fp16, [8, 352]> mul_623 = mul(x = mul_622, y = mul_622)[name = string("mul_623")];
            tensor<int32, [1]> reduce_mean_134_axes_0 = const()[name = string("reduce_mean_134_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_134_keep_dims_0 = const()[name = string("reduce_mean_134_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_134 = reduce_mean(axes = reduce_mean_134_axes_0, keep_dims = reduce_mean_134_keep_dims_0, x = mul_623)[name = string("reduce_mean_134")];
            fp32 rsqrt_134_epsilon_0 = const()[name = string("rsqrt_134_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_134 = rsqrt(epsilon = rsqrt_134_epsilon_0, x = reduce_mean_134)[name = string("rsqrt_134")];
            tensor<fp16, [8, 352]> mul_624 = mul(x = mul_622, y = rsqrt_134)[name = string("mul_624")];
            tensor<fp16, [352]> mul_625_y_0 = const()[name = string("mul_625_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6552576)))];
            tensor<fp16, [8, 352]> mul_625 = mul(x = mul_624, y = mul_625_y_0)[name = string("mul_625")];
            tensor<fp16, [960, 352]> tern_12_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6553344))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_12_w1_weight_0_palettized")];
            tensor<fp16, [8, 960]> tern_12_w1 = linear(bias = linear_4_bias_0, weight = tern_12_w1_weight_0_palettized, x = mul_625)[name = string("tern_12_w1")];
            tensor<fp16, [960]> mul_626_y_0 = const()[name = string("mul_626_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6637888)))];
            tensor<fp16, [8, 960]> mul_626 = mul(x = tern_12_w1, y = mul_626_y_0)[name = string("mul_626")];
            tensor<fp16, [352]> mul_629_y_0 = const()[name = string("mul_629_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6639872)))];
            tensor<fp16, [8, 352]> mul_629 = mul(x = mul_624, y = mul_629_y_0)[name = string("mul_629")];
            tensor<fp16, [960, 352]> tern_12_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6640640))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_12_w3_weight_0_palettized")];
            tensor<fp16, [8, 960]> tern_12_w3 = linear(bias = linear_4_bias_0, weight = tern_12_w3_weight_0_palettized, x = mul_629)[name = string("tern_12_w3")];
            tensor<fp16, [960]> mul_630_y_0 = const()[name = string("mul_630_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6725184)))];
            tensor<fp16, [8, 960]> mul_630 = mul(x = tern_12_w3, y = mul_630_y_0)[name = string("mul_630")];
            fp16 mul_631_y_0 = const()[name = string("mul_631_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [8, 960]> mul_631 = mul(x = mul_626, y = mul_631_y_0)[name = string("mul_631")];
            tensor<fp16, [8, 960]> tanh_12 = tanh(x = mul_631)[name = string("tanh_12")];
            fp16 mul_632_x_0 = const()[name = string("mul_632_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [8, 960]> mul_632 = mul(x = mul_632_x_0, y = tanh_12)[name = string("mul_632")];
            fp16 add_76_x_0 = const()[name = string("add_76_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [8, 960]> add_76 = add(x = add_76_x_0, y = mul_632)[name = string("add_76")];
            tensor<fp16, [8, 960]> mul_633 = mul(x = mul_626, y = add_76)[name = string("mul_633")];
            tensor<fp16, [8, 960]> mul_634 = mul(x = mul_633, y = mul_630)[name = string("mul_634")];
            tensor<fp16, [8, 960]> mul_635 = mul(x = mul_634, y = mul_634)[name = string("mul_635")];
            tensor<int32, [1]> reduce_mean_136_axes_0 = const()[name = string("reduce_mean_136_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_136_keep_dims_0 = const()[name = string("reduce_mean_136_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_136 = reduce_mean(axes = reduce_mean_136_axes_0, keep_dims = reduce_mean_136_keep_dims_0, x = mul_635)[name = string("reduce_mean_136")];
            fp32 rsqrt_136_epsilon_0 = const()[name = string("rsqrt_136_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_136 = rsqrt(epsilon = rsqrt_136_epsilon_0, x = reduce_mean_136)[name = string("rsqrt_136")];
            tensor<fp16, [8, 960]> mul_636 = mul(x = mul_634, y = rsqrt_136)[name = string("mul_636")];
            tensor<fp16, [960]> mul_637_y_0 = const()[name = string("mul_637_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6727168)))];
            tensor<fp16, [8, 960]> mul_637 = mul(x = mul_636, y = mul_637_y_0)[name = string("mul_637")];
            tensor<fp16, [352, 960]> tern_12_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6729152))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_12_w2_weight_0_palettized")];
            tensor<fp16, [8, 352]> tern_12_w2 = linear(bias = linear_0_bias_0, weight = tern_12_w2_weight_0_palettized, x = mul_637)[name = string("tern_12_w2")];
            tensor<fp16, [352]> mul_638_y_0 = const()[name = string("mul_638_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6813696)))];
            tensor<fp16, [8, 352]> mul_638 = mul(x = tern_12_w2, y = mul_638_y_0)[name = string("mul_638")];
            tensor<fp16, [8, 352]> add_77 = add(x = add_75, y = mul_638)[name = string("add_77")];
            tensor<fp16, [8, 352]> mul_639 = mul(x = add_77, y = add_77)[name = string("mul_639")];
            tensor<int32, [1]> reduce_mean_137_axes_0 = const()[name = string("reduce_mean_137_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_137_keep_dims_0 = const()[name = string("reduce_mean_137_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_137 = reduce_mean(axes = reduce_mean_137_axes_0, keep_dims = reduce_mean_137_keep_dims_0, x = mul_639)[name = string("reduce_mean_137")];
            fp32 rsqrt_137_epsilon_0 = const()[name = string("rsqrt_137_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_137 = rsqrt(epsilon = rsqrt_137_epsilon_0, x = reduce_mean_137)[name = string("rsqrt_137")];
            tensor<fp16, [8, 352]> mul_640 = mul(x = add_77, y = rsqrt_137)[name = string("mul_640")];
            tensor<fp16, [352]> mul_641_y_0 = const()[name = string("mul_641_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6814464)))];
            tensor<fp16, [8, 352]> mul_641 = mul(x = mul_640, y = mul_641_y_0)[name = string("mul_641")];
            tensor<fp16, [8, 352]> mul_642 = mul(x = mul_641, y = mul_641)[name = string("mul_642")];
            tensor<int32, [1]> reduce_mean_138_axes_0 = const()[name = string("reduce_mean_138_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_138_keep_dims_0 = const()[name = string("reduce_mean_138_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_138 = reduce_mean(axes = reduce_mean_138_axes_0, keep_dims = reduce_mean_138_keep_dims_0, x = mul_642)[name = string("reduce_mean_138")];
            fp32 rsqrt_138_epsilon_0 = const()[name = string("rsqrt_138_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_138 = rsqrt(epsilon = rsqrt_138_epsilon_0, x = reduce_mean_138)[name = string("rsqrt_138")];
            tensor<fp16, [8, 352]> mul_643 = mul(x = mul_641, y = rsqrt_138)[name = string("mul_643")];
            tensor<fp16, [352]> mul_644_y_0 = const()[name = string("mul_644_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6815232)))];
            tensor<fp16, [8, 352]> mul_644 = mul(x = mul_643, y = mul_644_y_0)[name = string("mul_644")];
            tensor<fp16, [352, 352]> tern_13_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6816000))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_13_q_weight_0_palettized")];
            tensor<fp16, [8, 352]> tern_13_q = linear(bias = linear_0_bias_0, weight = tern_13_q_weight_0_palettized, x = mul_644)[name = string("tern_13_q")];
            tensor<fp16, [352]> mul_645_y_0 = const()[name = string("mul_645_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6847040)))];
            tensor<fp16, [8, 352]> mul_645 = mul(x = tern_13_q, y = mul_645_y_0)[name = string("mul_645")];
            tensor<int32, [3]> reshape_106_shape_0 = const()[name = string("reshape_106_shape_0"), val = tensor<int32, [3]>([8, 8, 44])];
            tensor<fp16, [8, 8, 44]> reshape_106 = reshape(shape = reshape_106_shape_0, x = mul_645)[name = string("reshape_106")];
            tensor<int32, [3]> transpose_52_perm_0 = const()[name = string("transpose_52_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_648_y_0 = const()[name = string("mul_648_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6847808)))];
            tensor<fp16, [8, 352]> mul_648 = mul(x = mul_643, y = mul_648_y_0)[name = string("mul_648")];
            tensor<fp16, [88, 352]> tern_13_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6848576))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_13_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_13_k_bias_0 = const()[name = string("tern_13_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [8, 88]> tern_13_k = linear(bias = tern_13_k_bias_0, weight = tern_13_k_weight_0_palettized, x = mul_648)[name = string("tern_13_k")];
            tensor<fp16, [88]> mul_649_y_0 = const()[name = string("mul_649_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6856384)))];
            tensor<fp16, [8, 88]> mul_649 = mul(x = tern_13_k, y = mul_649_y_0)[name = string("mul_649")];
            tensor<int32, [3]> reshape_107_shape_0 = const()[name = string("reshape_107_shape_0"), val = tensor<int32, [3]>([8, 2, 44])];
            tensor<fp16, [8, 2, 44]> reshape_107 = reshape(shape = reshape_107_shape_0, x = mul_649)[name = string("reshape_107")];
            tensor<int32, [3]> transpose_53_perm_0 = const()[name = string("transpose_53_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_652_y_0 = const()[name = string("mul_652_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6856640)))];
            tensor<fp16, [8, 352]> mul_652 = mul(x = mul_643, y = mul_652_y_0)[name = string("mul_652")];
            tensor<fp16, [88, 352]> tern_13_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6857408))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_13_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_13_v_bias_0 = const()[name = string("tern_13_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [8, 88]> tern_13_v = linear(bias = tern_13_v_bias_0, weight = tern_13_v_weight_0_palettized, x = mul_652)[name = string("tern_13_v")];
            tensor<fp16, [88]> mul_653_y_0 = const()[name = string("mul_653_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6865216)))];
            tensor<fp16, [8, 88]> mul_653 = mul(x = tern_13_v, y = mul_653_y_0)[name = string("mul_653")];
            tensor<int32, [3]> reshape_108_shape_0 = const()[name = string("reshape_108_shape_0"), val = tensor<int32, [3]>([8, 2, 44])];
            tensor<fp16, [8, 2, 44]> reshape_108 = reshape(shape = reshape_108_shape_0, x = mul_653)[name = string("reshape_108")];
            tensor<int32, [3]> transpose_54_perm_0 = const()[name = string("transpose_54_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 8, 44]> transpose_52 = transpose(perm = transpose_52_perm_0, x = reshape_106)[name = string("transpose_11")];
            tensor<fp16, [8, 8, 44]> mul_654 = mul(x = transpose_52, y = transpose_52)[name = string("mul_654")];
            tensor<int32, [1]> reduce_mean_141_axes_0 = const()[name = string("reduce_mean_141_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_141_keep_dims_0 = const()[name = string("reduce_mean_141_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 8, 1]> reduce_mean_141 = reduce_mean(axes = reduce_mean_141_axes_0, keep_dims = reduce_mean_141_keep_dims_0, x = mul_654)[name = string("reduce_mean_141")];
            fp32 rsqrt_141_epsilon_0 = const()[name = string("rsqrt_141_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 8, 1]> rsqrt_141 = rsqrt(epsilon = rsqrt_141_epsilon_0, x = reduce_mean_141)[name = string("rsqrt_141")];
            tensor<fp16, [8, 8, 44]> mul_655 = mul(x = transpose_52, y = rsqrt_141)[name = string("mul_655")];
            tensor<fp16, [44]> mul_656_y_0 = const()[name = string("mul_656_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6865472)))];
            tensor<fp16, [8, 8, 44]> mul_656 = mul(x = mul_655, y = mul_656_y_0)[name = string("mul_656")];
            tensor<int32, [3]> slice_by_index_52_begin_0 = const()[name = string("slice_by_index_52_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_52_end_0 = const()[name = string("slice_by_index_52_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_52_end_mask_0 = const()[name = string("slice_by_index_52_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 8, 22]> slice_by_index_52 = slice_by_index(begin = slice_by_index_52_begin_0, end = slice_by_index_52_end_0, end_mask = slice_by_index_52_end_mask_0, x = mul_656)[name = string("slice_by_index_52")];
            tensor<int32, [3]> slice_by_index_53_begin_0 = const()[name = string("slice_by_index_53_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_53_end_0 = const()[name = string("slice_by_index_53_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_53_end_mask_0 = const()[name = string("slice_by_index_53_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 8, 22]> slice_by_index_53 = slice_by_index(begin = slice_by_index_53_begin_0, end = slice_by_index_53_end_0, end_mask = slice_by_index_53_end_mask_0, x = mul_656)[name = string("slice_by_index_53")];
            int32 concat_26_axis_0 = const()[name = string("concat_26_axis_0"), val = int32(-1)];
            bool concat_26_interleave_0 = const()[name = string("concat_26_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 8, 44]> concat_26 = concat(axis = concat_26_axis_0, interleave = concat_26_interleave_0, values = (slice_by_index_53, slice_by_index_52))[name = string("concat_26")];
            tensor<fp16, [44]> mul_657_y_0 = const()[name = string("mul_657_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 8, 44]> mul_657 = mul(x = concat_26, y = mul_657_y_0)[name = string("mul_657")];
            tensor<fp16, [8, 8, 44]> mul_658 = mul(x = mul_656, y = mul_11_y_0)[name = string("mul_658")];
            tensor<fp16, [8, 8, 44]> mul_659 = mul(x = mul_657, y = mul_12_y_0)[name = string("mul_659")];
            tensor<fp16, [8, 8, 44]> add_78 = add(x = mul_658, y = mul_659)[name = string("add_78")];
            tensor<fp16, [2, 8, 44]> transpose_53 = transpose(perm = transpose_53_perm_0, x = reshape_107)[name = string("transpose_10")];
            tensor<fp16, [2, 8, 44]> mul_660 = mul(x = transpose_53, y = transpose_53)[name = string("mul_660")];
            tensor<int32, [1]> reduce_mean_142_axes_0 = const()[name = string("reduce_mean_142_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_142_keep_dims_0 = const()[name = string("reduce_mean_142_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 8, 1]> reduce_mean_142 = reduce_mean(axes = reduce_mean_142_axes_0, keep_dims = reduce_mean_142_keep_dims_0, x = mul_660)[name = string("reduce_mean_142")];
            fp32 rsqrt_142_epsilon_0 = const()[name = string("rsqrt_142_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 8, 1]> rsqrt_142 = rsqrt(epsilon = rsqrt_142_epsilon_0, x = reduce_mean_142)[name = string("rsqrt_142")];
            tensor<fp16, [2, 8, 44]> mul_661 = mul(x = transpose_53, y = rsqrt_142)[name = string("mul_661")];
            tensor<fp16, [44]> mul_662_y_0 = const()[name = string("mul_662_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6865664)))];
            tensor<fp16, [2, 8, 44]> mul_662 = mul(x = mul_661, y = mul_662_y_0)[name = string("mul_662")];
            tensor<int32, [3]> slice_by_index_54_begin_0 = const()[name = string("slice_by_index_54_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_54_end_0 = const()[name = string("slice_by_index_54_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_54_end_mask_0 = const()[name = string("slice_by_index_54_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 8, 22]> slice_by_index_54 = slice_by_index(begin = slice_by_index_54_begin_0, end = slice_by_index_54_end_0, end_mask = slice_by_index_54_end_mask_0, x = mul_662)[name = string("slice_by_index_54")];
            tensor<int32, [3]> slice_by_index_55_begin_0 = const()[name = string("slice_by_index_55_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_55_end_0 = const()[name = string("slice_by_index_55_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_55_end_mask_0 = const()[name = string("slice_by_index_55_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 8, 22]> slice_by_index_55 = slice_by_index(begin = slice_by_index_55_begin_0, end = slice_by_index_55_end_0, end_mask = slice_by_index_55_end_mask_0, x = mul_662)[name = string("slice_by_index_55")];
            int32 concat_27_axis_0 = const()[name = string("concat_27_axis_0"), val = int32(-1)];
            bool concat_27_interleave_0 = const()[name = string("concat_27_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 8, 44]> concat_27 = concat(axis = concat_27_axis_0, interleave = concat_27_interleave_0, values = (slice_by_index_55, slice_by_index_54))[name = string("concat_27")];
            tensor<fp16, [44]> mul_663_y_0 = const()[name = string("mul_663_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 8, 44]> mul_663 = mul(x = concat_27, y = mul_663_y_0)[name = string("mul_663")];
            tensor<fp16, [2, 8, 44]> mul_664 = mul(x = mul_662, y = mul_11_y_0)[name = string("mul_664")];
            tensor<fp16, [2, 8, 44]> mul_665 = mul(x = mul_663, y = mul_12_y_0)[name = string("mul_665")];
            tensor<fp16, [2, 8, 44]> add_79 = add(x = mul_664, y = mul_665)[name = string("add_79")];
            tensor<int32, [4]> reshape_109_shape_0 = const()[name = string("reshape_109_shape_0"), val = tensor<int32, [4]>([2, 1, 8, 44])];
            tensor<fp16, [2, 1, 8, 44]> reshape_109 = reshape(shape = reshape_109_shape_0, x = add_79)[name = string("reshape_109")];
            tensor<int32, [4]> tile_26_reps_0 = const()[name = string("tile_26_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 8, 44]> tile_26 = tile(reps = tile_26_reps_0, x = reshape_109)[name = string("tile_26")];
            tensor<int32, [3]> reshape_110_shape_0 = const()[name = string("reshape_110_shape_0"), val = tensor<int32, [3]>([8, 8, 44])];
            tensor<fp16, [8, 8, 44]> reshape_110 = reshape(shape = reshape_110_shape_0, x = tile_26)[name = string("reshape_110")];
            tensor<int32, [4]> reshape_111_shape_0 = const()[name = string("reshape_111_shape_0"), val = tensor<int32, [4]>([2, 1, 8, 44])];
            tensor<fp16, [2, 8, 44]> transpose_54 = transpose(perm = transpose_54_perm_0, x = reshape_108)[name = string("transpose_9")];
            tensor<fp16, [2, 1, 8, 44]> reshape_111 = reshape(shape = reshape_111_shape_0, x = transpose_54)[name = string("reshape_111")];
            tensor<int32, [4]> tile_27_reps_0 = const()[name = string("tile_27_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 8, 44]> tile_27 = tile(reps = tile_27_reps_0, x = reshape_111)[name = string("tile_27")];
            tensor<int32, [3]> reshape_112_shape_0 = const()[name = string("reshape_112_shape_0"), val = tensor<int32, [3]>([8, 8, 44])];
            tensor<fp16, [8, 8, 44]> reshape_112 = reshape(shape = reshape_112_shape_0, x = tile_27)[name = string("reshape_112")];
            fp16 mul_666_y_0 = const()[name = string("mul_666_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 8, 44]> mul_666 = mul(x = add_78, y = mul_666_y_0)[name = string("mul_666")];
            bool matmul_26_transpose_y_0 = const()[name = string("matmul_26_transpose_y_0"), val = bool(true)];
            bool matmul_26_transpose_x_0 = const()[name = string("matmul_26_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 8, 8]> matmul_26 = matmul(transpose_x = matmul_26_transpose_x_0, transpose_y = matmul_26_transpose_y_0, x = mul_666, y = reshape_110)[name = string("matmul_26")];
            tensor<fp16, [8, 8, 8]> add_80 = add(x = matmul_26, y = reshape_1)[name = string("add_80")];
            int32 softmax_13_axis_0 = const()[name = string("softmax_13_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 8, 8]> softmax_13 = softmax(axis = softmax_13_axis_0, x = add_80)[name = string("softmax_13")];
            bool matmul_27_transpose_x_0 = const()[name = string("matmul_27_transpose_x_0"), val = bool(false)];
            bool matmul_27_transpose_y_0 = const()[name = string("matmul_27_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 8, 44]> matmul_27 = matmul(transpose_x = matmul_27_transpose_x_0, transpose_y = matmul_27_transpose_y_0, x = softmax_13, y = reshape_112)[name = string("matmul_27")];
            tensor<int32, [3]> transpose_55_perm_0 = const()[name = string("transpose_55_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_113_shape_0 = const()[name = string("reshape_113_shape_0"), val = tensor<int32, [2]>([8, 352])];
            tensor<fp16, [8, 8, 44]> transpose_55 = transpose(perm = transpose_55_perm_0, x = matmul_27)[name = string("transpose_8")];
            tensor<fp16, [8, 352]> reshape_113 = reshape(shape = reshape_113_shape_0, x = transpose_55)[name = string("reshape_113")];
            tensor<fp16, [8, 352]> mul_667 = mul(x = reshape_113, y = reshape_113)[name = string("mul_667")];
            tensor<int32, [1]> reduce_mean_143_axes_0 = const()[name = string("reduce_mean_143_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_143_keep_dims_0 = const()[name = string("reduce_mean_143_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_143 = reduce_mean(axes = reduce_mean_143_axes_0, keep_dims = reduce_mean_143_keep_dims_0, x = mul_667)[name = string("reduce_mean_143")];
            fp32 rsqrt_143_epsilon_0 = const()[name = string("rsqrt_143_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_143 = rsqrt(epsilon = rsqrt_143_epsilon_0, x = reduce_mean_143)[name = string("rsqrt_143")];
            tensor<fp16, [8, 352]> mul_668 = mul(x = reshape_113, y = rsqrt_143)[name = string("mul_668")];
            tensor<fp16, [352]> mul_669_y_0 = const()[name = string("mul_669_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6865856)))];
            tensor<fp16, [8, 352]> mul_669 = mul(x = mul_668, y = mul_669_y_0)[name = string("mul_669")];
            tensor<fp16, [352, 352]> tern_13_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6866624))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_13_o_weight_0_palettized")];
            tensor<fp16, [8, 352]> tern_13_o = linear(bias = linear_0_bias_0, weight = tern_13_o_weight_0_palettized, x = mul_669)[name = string("tern_13_o")];
            tensor<fp16, [352]> mul_670_y_0 = const()[name = string("mul_670_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6897664)))];
            tensor<fp16, [8, 352]> mul_670 = mul(x = tern_13_o, y = mul_670_y_0)[name = string("mul_670")];
            tensor<fp16, [8, 352]> add_81 = add(x = add_77, y = mul_670)[name = string("add_81")];
            tensor<fp16, [8, 352]> mul_671 = mul(x = add_81, y = add_81)[name = string("mul_671")];
            tensor<int32, [1]> reduce_mean_144_axes_0 = const()[name = string("reduce_mean_144_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_144_keep_dims_0 = const()[name = string("reduce_mean_144_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_144 = reduce_mean(axes = reduce_mean_144_axes_0, keep_dims = reduce_mean_144_keep_dims_0, x = mul_671)[name = string("reduce_mean_144")];
            fp32 rsqrt_144_epsilon_0 = const()[name = string("rsqrt_144_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_144 = rsqrt(epsilon = rsqrt_144_epsilon_0, x = reduce_mean_144)[name = string("rsqrt_144")];
            tensor<fp16, [8, 352]> mul_672 = mul(x = add_81, y = rsqrt_144)[name = string("mul_672")];
            tensor<fp16, [352]> mul_673_y_0 = const()[name = string("mul_673_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6898432)))];
            tensor<fp16, [8, 352]> mul_673 = mul(x = mul_672, y = mul_673_y_0)[name = string("mul_673")];
            tensor<fp16, [8, 352]> mul_674 = mul(x = mul_673, y = mul_673)[name = string("mul_674")];
            tensor<int32, [1]> reduce_mean_145_axes_0 = const()[name = string("reduce_mean_145_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_145_keep_dims_0 = const()[name = string("reduce_mean_145_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_145 = reduce_mean(axes = reduce_mean_145_axes_0, keep_dims = reduce_mean_145_keep_dims_0, x = mul_674)[name = string("reduce_mean_145")];
            fp32 rsqrt_145_epsilon_0 = const()[name = string("rsqrt_145_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_145 = rsqrt(epsilon = rsqrt_145_epsilon_0, x = reduce_mean_145)[name = string("rsqrt_145")];
            tensor<fp16, [8, 352]> mul_675 = mul(x = mul_673, y = rsqrt_145)[name = string("mul_675")];
            tensor<fp16, [352]> mul_676_y_0 = const()[name = string("mul_676_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6899200)))];
            tensor<fp16, [8, 352]> mul_676 = mul(x = mul_675, y = mul_676_y_0)[name = string("mul_676")];
            tensor<fp16, [960, 352]> tern_13_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6899968))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_13_w1_weight_0_palettized")];
            tensor<fp16, [8, 960]> tern_13_w1 = linear(bias = linear_4_bias_0, weight = tern_13_w1_weight_0_palettized, x = mul_676)[name = string("tern_13_w1")];
            tensor<fp16, [960]> mul_677_y_0 = const()[name = string("mul_677_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6984512)))];
            tensor<fp16, [8, 960]> mul_677 = mul(x = tern_13_w1, y = mul_677_y_0)[name = string("mul_677")];
            tensor<fp16, [352]> mul_680_y_0 = const()[name = string("mul_680_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6986496)))];
            tensor<fp16, [8, 352]> mul_680 = mul(x = mul_675, y = mul_680_y_0)[name = string("mul_680")];
            tensor<fp16, [960, 352]> tern_13_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6987264))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_13_w3_weight_0_palettized")];
            tensor<fp16, [8, 960]> tern_13_w3 = linear(bias = linear_4_bias_0, weight = tern_13_w3_weight_0_palettized, x = mul_680)[name = string("tern_13_w3")];
            tensor<fp16, [960]> mul_681_y_0 = const()[name = string("mul_681_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7071808)))];
            tensor<fp16, [8, 960]> mul_681 = mul(x = tern_13_w3, y = mul_681_y_0)[name = string("mul_681")];
            fp16 mul_682_y_0 = const()[name = string("mul_682_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [8, 960]> mul_682 = mul(x = mul_677, y = mul_682_y_0)[name = string("mul_682")];
            tensor<fp16, [8, 960]> tanh_13 = tanh(x = mul_682)[name = string("tanh_13")];
            fp16 mul_683_x_0 = const()[name = string("mul_683_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [8, 960]> mul_683 = mul(x = mul_683_x_0, y = tanh_13)[name = string("mul_683")];
            fp16 add_82_x_0 = const()[name = string("add_82_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [8, 960]> add_82 = add(x = add_82_x_0, y = mul_683)[name = string("add_82")];
            tensor<fp16, [8, 960]> mul_684 = mul(x = mul_677, y = add_82)[name = string("mul_684")];
            tensor<fp16, [8, 960]> mul_685 = mul(x = mul_684, y = mul_681)[name = string("mul_685")];
            tensor<fp16, [8, 960]> mul_686 = mul(x = mul_685, y = mul_685)[name = string("mul_686")];
            tensor<int32, [1]> reduce_mean_147_axes_0 = const()[name = string("reduce_mean_147_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_147_keep_dims_0 = const()[name = string("reduce_mean_147_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_147 = reduce_mean(axes = reduce_mean_147_axes_0, keep_dims = reduce_mean_147_keep_dims_0, x = mul_686)[name = string("reduce_mean_147")];
            fp32 rsqrt_147_epsilon_0 = const()[name = string("rsqrt_147_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_147 = rsqrt(epsilon = rsqrt_147_epsilon_0, x = reduce_mean_147)[name = string("rsqrt_147")];
            tensor<fp16, [8, 960]> mul_687 = mul(x = mul_685, y = rsqrt_147)[name = string("mul_687")];
            tensor<fp16, [960]> mul_688_y_0 = const()[name = string("mul_688_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7073792)))];
            tensor<fp16, [8, 960]> mul_688 = mul(x = mul_687, y = mul_688_y_0)[name = string("mul_688")];
            tensor<fp16, [352, 960]> tern_13_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7075776))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_13_w2_weight_0_palettized")];
            tensor<fp16, [8, 352]> tern_13_w2 = linear(bias = linear_0_bias_0, weight = tern_13_w2_weight_0_palettized, x = mul_688)[name = string("tern_13_w2")];
            tensor<fp16, [352]> mul_689_y_0 = const()[name = string("mul_689_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7160320)))];
            tensor<fp16, [8, 352]> mul_689 = mul(x = tern_13_w2, y = mul_689_y_0)[name = string("mul_689")];
            tensor<fp16, [8, 352]> add_83 = add(x = add_81, y = mul_689)[name = string("add_83")];
            tensor<fp16, [8, 352]> mul_690 = mul(x = add_83, y = add_83)[name = string("mul_690")];
            tensor<int32, [1]> reduce_mean_148_axes_0 = const()[name = string("reduce_mean_148_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_148_keep_dims_0 = const()[name = string("reduce_mean_148_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_148 = reduce_mean(axes = reduce_mean_148_axes_0, keep_dims = reduce_mean_148_keep_dims_0, x = mul_690)[name = string("reduce_mean_148")];
            fp32 rsqrt_148_epsilon_0 = const()[name = string("rsqrt_148_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_148 = rsqrt(epsilon = rsqrt_148_epsilon_0, x = reduce_mean_148)[name = string("rsqrt_148")];
            tensor<fp16, [8, 352]> mul_691 = mul(x = add_83, y = rsqrt_148)[name = string("mul_691")];
            tensor<fp16, [352]> mul_692_y_0 = const()[name = string("mul_692_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7161088)))];
            tensor<fp16, [8, 352]> mul_692 = mul(x = mul_691, y = mul_692_y_0)[name = string("mul_692")];
            tensor<fp16, [8, 352]> mul_693 = mul(x = mul_692, y = mul_692)[name = string("mul_693")];
            tensor<int32, [1]> reduce_mean_149_axes_0 = const()[name = string("reduce_mean_149_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_149_keep_dims_0 = const()[name = string("reduce_mean_149_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_149 = reduce_mean(axes = reduce_mean_149_axes_0, keep_dims = reduce_mean_149_keep_dims_0, x = mul_693)[name = string("reduce_mean_149")];
            fp32 rsqrt_149_epsilon_0 = const()[name = string("rsqrt_149_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_149 = rsqrt(epsilon = rsqrt_149_epsilon_0, x = reduce_mean_149)[name = string("rsqrt_149")];
            tensor<fp16, [8, 352]> mul_694 = mul(x = mul_692, y = rsqrt_149)[name = string("mul_694")];
            tensor<fp16, [352]> mul_695_y_0 = const()[name = string("mul_695_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7161856)))];
            tensor<fp16, [8, 352]> mul_695 = mul(x = mul_694, y = mul_695_y_0)[name = string("mul_695")];
            tensor<fp16, [352, 352]> tern_14_q_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7162624))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_14_q_weight_0_palettized")];
            tensor<fp16, [8, 352]> tern_14_q = linear(bias = linear_0_bias_0, weight = tern_14_q_weight_0_palettized, x = mul_695)[name = string("tern_14_q")];
            tensor<fp16, [352]> mul_696_y_0 = const()[name = string("mul_696_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7193664)))];
            tensor<fp16, [8, 352]> mul_696 = mul(x = tern_14_q, y = mul_696_y_0)[name = string("mul_696")];
            tensor<int32, [3]> reshape_114_shape_0 = const()[name = string("reshape_114_shape_0"), val = tensor<int32, [3]>([8, 8, 44])];
            tensor<fp16, [8, 8, 44]> reshape_114 = reshape(shape = reshape_114_shape_0, x = mul_696)[name = string("reshape_114")];
            tensor<int32, [3]> transpose_56_perm_0 = const()[name = string("transpose_56_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_699_y_0 = const()[name = string("mul_699_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7194432)))];
            tensor<fp16, [8, 352]> mul_699 = mul(x = mul_694, y = mul_699_y_0)[name = string("mul_699")];
            tensor<fp16, [88, 352]> tern_14_k_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7195200))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_14_k_weight_0_palettized")];
            tensor<fp16, [88]> tern_14_k_bias_0 = const()[name = string("tern_14_k_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [8, 88]> tern_14_k = linear(bias = tern_14_k_bias_0, weight = tern_14_k_weight_0_palettized, x = mul_699)[name = string("tern_14_k")];
            tensor<fp16, [88]> mul_700_y_0 = const()[name = string("mul_700_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7203008)))];
            tensor<fp16, [8, 88]> mul_700 = mul(x = tern_14_k, y = mul_700_y_0)[name = string("mul_700")];
            tensor<int32, [3]> reshape_115_shape_0 = const()[name = string("reshape_115_shape_0"), val = tensor<int32, [3]>([8, 2, 44])];
            tensor<fp16, [8, 2, 44]> reshape_115 = reshape(shape = reshape_115_shape_0, x = mul_700)[name = string("reshape_115")];
            tensor<int32, [3]> transpose_57_perm_0 = const()[name = string("transpose_57_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [352]> mul_703_y_0 = const()[name = string("mul_703_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7203264)))];
            tensor<fp16, [8, 352]> mul_703 = mul(x = mul_694, y = mul_703_y_0)[name = string("mul_703")];
            tensor<fp16, [88, 352]> tern_14_v_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7204032))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_14_v_weight_0_palettized")];
            tensor<fp16, [88]> tern_14_v_bias_0 = const()[name = string("tern_14_v_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [8, 88]> tern_14_v = linear(bias = tern_14_v_bias_0, weight = tern_14_v_weight_0_palettized, x = mul_703)[name = string("tern_14_v")];
            tensor<fp16, [88]> mul_704_y_0 = const()[name = string("mul_704_y_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7211840)))];
            tensor<fp16, [8, 88]> mul_704 = mul(x = tern_14_v, y = mul_704_y_0)[name = string("mul_704")];
            tensor<int32, [3]> reshape_116_shape_0 = const()[name = string("reshape_116_shape_0"), val = tensor<int32, [3]>([8, 2, 44])];
            tensor<fp16, [8, 2, 44]> reshape_116 = reshape(shape = reshape_116_shape_0, x = mul_704)[name = string("reshape_116")];
            tensor<int32, [3]> transpose_58_perm_0 = const()[name = string("transpose_58_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 8, 44]> transpose_56 = transpose(perm = transpose_56_perm_0, x = reshape_114)[name = string("transpose_7")];
            tensor<fp16, [8, 8, 44]> mul_705 = mul(x = transpose_56, y = transpose_56)[name = string("mul_705")];
            tensor<int32, [1]> reduce_mean_152_axes_0 = const()[name = string("reduce_mean_152_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_152_keep_dims_0 = const()[name = string("reduce_mean_152_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 8, 1]> reduce_mean_152 = reduce_mean(axes = reduce_mean_152_axes_0, keep_dims = reduce_mean_152_keep_dims_0, x = mul_705)[name = string("reduce_mean_152")];
            fp32 rsqrt_152_epsilon_0 = const()[name = string("rsqrt_152_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 8, 1]> rsqrt_152 = rsqrt(epsilon = rsqrt_152_epsilon_0, x = reduce_mean_152)[name = string("rsqrt_152")];
            tensor<fp16, [8, 8, 44]> mul_706 = mul(x = transpose_56, y = rsqrt_152)[name = string("mul_706")];
            tensor<fp16, [44]> mul_707_y_0 = const()[name = string("mul_707_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7212096)))];
            tensor<fp16, [8, 8, 44]> mul_707 = mul(x = mul_706, y = mul_707_y_0)[name = string("mul_707")];
            tensor<int32, [3]> slice_by_index_56_begin_0 = const()[name = string("slice_by_index_56_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_56_end_0 = const()[name = string("slice_by_index_56_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_56_end_mask_0 = const()[name = string("slice_by_index_56_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 8, 22]> slice_by_index_56 = slice_by_index(begin = slice_by_index_56_begin_0, end = slice_by_index_56_end_0, end_mask = slice_by_index_56_end_mask_0, x = mul_707)[name = string("slice_by_index_56")];
            tensor<int32, [3]> slice_by_index_57_begin_0 = const()[name = string("slice_by_index_57_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_57_end_0 = const()[name = string("slice_by_index_57_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_57_end_mask_0 = const()[name = string("slice_by_index_57_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 8, 22]> slice_by_index_57 = slice_by_index(begin = slice_by_index_57_begin_0, end = slice_by_index_57_end_0, end_mask = slice_by_index_57_end_mask_0, x = mul_707)[name = string("slice_by_index_57")];
            int32 concat_28_axis_0 = const()[name = string("concat_28_axis_0"), val = int32(-1)];
            bool concat_28_interleave_0 = const()[name = string("concat_28_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 8, 44]> concat_28 = concat(axis = concat_28_axis_0, interleave = concat_28_interleave_0, values = (slice_by_index_57, slice_by_index_56))[name = string("concat_28")];
            tensor<fp16, [44]> mul_708_y_0 = const()[name = string("mul_708_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 8, 44]> mul_708 = mul(x = concat_28, y = mul_708_y_0)[name = string("mul_708")];
            tensor<fp16, [8, 8, 44]> mul_709 = mul(x = mul_707, y = mul_11_y_0)[name = string("mul_709")];
            tensor<fp16, [8, 8, 44]> mul_710 = mul(x = mul_708, y = mul_12_y_0)[name = string("mul_710")];
            tensor<fp16, [8, 8, 44]> add_84 = add(x = mul_709, y = mul_710)[name = string("add_84")];
            tensor<fp16, [2, 8, 44]> transpose_57 = transpose(perm = transpose_57_perm_0, x = reshape_115)[name = string("transpose_6")];
            tensor<fp16, [2, 8, 44]> mul_711 = mul(x = transpose_57, y = transpose_57)[name = string("mul_711")];
            tensor<int32, [1]> reduce_mean_153_axes_0 = const()[name = string("reduce_mean_153_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_153_keep_dims_0 = const()[name = string("reduce_mean_153_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 8, 1]> reduce_mean_153 = reduce_mean(axes = reduce_mean_153_axes_0, keep_dims = reduce_mean_153_keep_dims_0, x = mul_711)[name = string("reduce_mean_153")];
            fp32 rsqrt_153_epsilon_0 = const()[name = string("rsqrt_153_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 8, 1]> rsqrt_153 = rsqrt(epsilon = rsqrt_153_epsilon_0, x = reduce_mean_153)[name = string("rsqrt_153")];
            tensor<fp16, [2, 8, 44]> mul_712 = mul(x = transpose_57, y = rsqrt_153)[name = string("mul_712")];
            tensor<fp16, [44]> mul_713_y_0 = const()[name = string("mul_713_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7212288)))];
            tensor<fp16, [2, 8, 44]> mul_713 = mul(x = mul_712, y = mul_713_y_0)[name = string("mul_713")];
            tensor<int32, [3]> slice_by_index_58_begin_0 = const()[name = string("slice_by_index_58_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_58_end_0 = const()[name = string("slice_by_index_58_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_58_end_mask_0 = const()[name = string("slice_by_index_58_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 8, 22]> slice_by_index_58 = slice_by_index(begin = slice_by_index_58_begin_0, end = slice_by_index_58_end_0, end_mask = slice_by_index_58_end_mask_0, x = mul_713)[name = string("slice_by_index_58")];
            tensor<int32, [3]> slice_by_index_59_begin_0 = const()[name = string("slice_by_index_59_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_59_end_0 = const()[name = string("slice_by_index_59_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_59_end_mask_0 = const()[name = string("slice_by_index_59_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 8, 22]> slice_by_index_59 = slice_by_index(begin = slice_by_index_59_begin_0, end = slice_by_index_59_end_0, end_mask = slice_by_index_59_end_mask_0, x = mul_713)[name = string("slice_by_index_59")];
            int32 concat_29_axis_0 = const()[name = string("concat_29_axis_0"), val = int32(-1)];
            bool concat_29_interleave_0 = const()[name = string("concat_29_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 8, 44]> concat_29 = concat(axis = concat_29_axis_0, interleave = concat_29_interleave_0, values = (slice_by_index_59, slice_by_index_58))[name = string("concat_29")];
            tensor<fp16, [44]> mul_714_y_0 = const()[name = string("mul_714_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 8, 44]> mul_714 = mul(x = concat_29, y = mul_714_y_0)[name = string("mul_714")];
            tensor<fp16, [2, 8, 44]> mul_715 = mul(x = mul_713, y = mul_11_y_0)[name = string("mul_715")];
            tensor<fp16, [2, 8, 44]> mul_716 = mul(x = mul_714, y = mul_12_y_0)[name = string("mul_716")];
            tensor<fp16, [2, 8, 44]> add_85 = add(x = mul_715, y = mul_716)[name = string("add_85")];
            tensor<int32, [4]> reshape_117_shape_0 = const()[name = string("reshape_117_shape_0"), val = tensor<int32, [4]>([2, 1, 8, 44])];
            tensor<fp16, [2, 1, 8, 44]> reshape_117 = reshape(shape = reshape_117_shape_0, x = add_85)[name = string("reshape_117")];
            tensor<int32, [4]> tile_28_reps_0 = const()[name = string("tile_28_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 8, 44]> tile_28 = tile(reps = tile_28_reps_0, x = reshape_117)[name = string("tile_28")];
            tensor<int32, [3]> reshape_118_shape_0 = const()[name = string("reshape_118_shape_0"), val = tensor<int32, [3]>([8, 8, 44])];
            tensor<fp16, [8, 8, 44]> reshape_118 = reshape(shape = reshape_118_shape_0, x = tile_28)[name = string("reshape_118")];
            tensor<int32, [4]> reshape_119_shape_0 = const()[name = string("reshape_119_shape_0"), val = tensor<int32, [4]>([2, 1, 8, 44])];
            tensor<fp16, [2, 8, 44]> transpose_58 = transpose(perm = transpose_58_perm_0, x = reshape_116)[name = string("transpose_5")];
            tensor<fp16, [2, 1, 8, 44]> reshape_119 = reshape(shape = reshape_119_shape_0, x = transpose_58)[name = string("reshape_119")];
            tensor<int32, [4]> tile_29_reps_0 = const()[name = string("tile_29_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 8, 44]> tile_29 = tile(reps = tile_29_reps_0, x = reshape_119)[name = string("tile_29")];
            tensor<int32, [3]> reshape_120_shape_0 = const()[name = string("reshape_120_shape_0"), val = tensor<int32, [3]>([8, 8, 44])];
            tensor<fp16, [8, 8, 44]> reshape_120 = reshape(shape = reshape_120_shape_0, x = tile_29)[name = string("reshape_120")];
            fp16 mul_717_y_0 = const()[name = string("mul_717_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 8, 44]> mul_717 = mul(x = add_84, y = mul_717_y_0)[name = string("mul_717")];
            bool matmul_28_transpose_y_0 = const()[name = string("matmul_28_transpose_y_0"), val = bool(true)];
            bool matmul_28_transpose_x_0 = const()[name = string("matmul_28_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 8, 8]> matmul_28 = matmul(transpose_x = matmul_28_transpose_x_0, transpose_y = matmul_28_transpose_y_0, x = mul_717, y = reshape_118)[name = string("matmul_28")];
            tensor<fp16, [8, 8, 8]> add_86 = add(x = matmul_28, y = reshape_1)[name = string("add_86")];
            int32 softmax_14_axis_0 = const()[name = string("softmax_14_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 8, 8]> softmax_14 = softmax(axis = softmax_14_axis_0, x = add_86)[name = string("softmax_14")];
            bool matmul_29_transpose_x_0 = const()[name = string("matmul_29_transpose_x_0"), val = bool(false)];
            bool matmul_29_transpose_y_0 = const()[name = string("matmul_29_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 8, 44]> matmul_29 = matmul(transpose_x = matmul_29_transpose_x_0, transpose_y = matmul_29_transpose_y_0, x = softmax_14, y = reshape_120)[name = string("matmul_29")];
            tensor<int32, [3]> transpose_59_perm_0 = const()[name = string("transpose_59_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_121_shape_0 = const()[name = string("reshape_121_shape_0"), val = tensor<int32, [2]>([8, 352])];
            tensor<fp16, [8, 8, 44]> transpose_59 = transpose(perm = transpose_59_perm_0, x = matmul_29)[name = string("transpose_4")];
            tensor<fp16, [8, 352]> reshape_121 = reshape(shape = reshape_121_shape_0, x = transpose_59)[name = string("reshape_121")];
            tensor<fp16, [8, 352]> mul_718 = mul(x = reshape_121, y = reshape_121)[name = string("mul_718")];
            tensor<int32, [1]> reduce_mean_154_axes_0 = const()[name = string("reduce_mean_154_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_154_keep_dims_0 = const()[name = string("reduce_mean_154_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_154 = reduce_mean(axes = reduce_mean_154_axes_0, keep_dims = reduce_mean_154_keep_dims_0, x = mul_718)[name = string("reduce_mean_154")];
            fp32 rsqrt_154_epsilon_0 = const()[name = string("rsqrt_154_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_154 = rsqrt(epsilon = rsqrt_154_epsilon_0, x = reduce_mean_154)[name = string("rsqrt_154")];
            tensor<fp16, [8, 352]> mul_719 = mul(x = reshape_121, y = rsqrt_154)[name = string("mul_719")];
            tensor<fp16, [352]> mul_720_y_0 = const()[name = string("mul_720_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7212480)))];
            tensor<fp16, [8, 352]> mul_720 = mul(x = mul_719, y = mul_720_y_0)[name = string("mul_720")];
            tensor<fp16, [352, 352]> tern_14_o_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7213248))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_14_o_weight_0_palettized")];
            tensor<fp16, [8, 352]> tern_14_o = linear(bias = linear_0_bias_0, weight = tern_14_o_weight_0_palettized, x = mul_720)[name = string("tern_14_o")];
            tensor<fp16, [352]> mul_721_y_0 = const()[name = string("mul_721_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7244288)))];
            tensor<fp16, [8, 352]> mul_721 = mul(x = tern_14_o, y = mul_721_y_0)[name = string("mul_721")];
            tensor<fp16, [8, 352]> add_87 = add(x = add_83, y = mul_721)[name = string("add_87")];
            tensor<fp16, [8, 352]> mul_722 = mul(x = add_87, y = add_87)[name = string("mul_722")];
            tensor<int32, [1]> reduce_mean_155_axes_0 = const()[name = string("reduce_mean_155_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_155_keep_dims_0 = const()[name = string("reduce_mean_155_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_155 = reduce_mean(axes = reduce_mean_155_axes_0, keep_dims = reduce_mean_155_keep_dims_0, x = mul_722)[name = string("reduce_mean_155")];
            fp32 rsqrt_155_epsilon_0 = const()[name = string("rsqrt_155_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_155 = rsqrt(epsilon = rsqrt_155_epsilon_0, x = reduce_mean_155)[name = string("rsqrt_155")];
            tensor<fp16, [8, 352]> mul_723 = mul(x = add_87, y = rsqrt_155)[name = string("mul_723")];
            tensor<fp16, [352]> mul_724_y_0 = const()[name = string("mul_724_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7245056)))];
            tensor<fp16, [8, 352]> mul_724 = mul(x = mul_723, y = mul_724_y_0)[name = string("mul_724")];
            tensor<fp16, [8, 352]> mul_725 = mul(x = mul_724, y = mul_724)[name = string("mul_725")];
            tensor<int32, [1]> reduce_mean_156_axes_0 = const()[name = string("reduce_mean_156_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_156_keep_dims_0 = const()[name = string("reduce_mean_156_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_156 = reduce_mean(axes = reduce_mean_156_axes_0, keep_dims = reduce_mean_156_keep_dims_0, x = mul_725)[name = string("reduce_mean_156")];
            fp32 rsqrt_156_epsilon_0 = const()[name = string("rsqrt_156_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_156 = rsqrt(epsilon = rsqrt_156_epsilon_0, x = reduce_mean_156)[name = string("rsqrt_156")];
            tensor<fp16, [8, 352]> mul_726 = mul(x = mul_724, y = rsqrt_156)[name = string("mul_726")];
            tensor<fp16, [352]> mul_727_y_0 = const()[name = string("mul_727_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7245824)))];
            tensor<fp16, [8, 352]> mul_727 = mul(x = mul_726, y = mul_727_y_0)[name = string("mul_727")];
            tensor<fp16, [960, 352]> tern_14_w1_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7246592))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_14_w1_weight_0_palettized")];
            tensor<fp16, [8, 960]> tern_14_w1 = linear(bias = linear_4_bias_0, weight = tern_14_w1_weight_0_palettized, x = mul_727)[name = string("tern_14_w1")];
            tensor<fp16, [960]> mul_728_y_0 = const()[name = string("mul_728_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7331136)))];
            tensor<fp16, [8, 960]> mul_728 = mul(x = tern_14_w1, y = mul_728_y_0)[name = string("mul_728")];
            tensor<fp16, [352]> mul_731_y_0 = const()[name = string("mul_731_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7333120)))];
            tensor<fp16, [8, 352]> mul_731 = mul(x = mul_726, y = mul_731_y_0)[name = string("mul_731")];
            tensor<fp16, [960, 352]> tern_14_w3_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7333888))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_14_w3_weight_0_palettized")];
            tensor<fp16, [8, 960]> tern_14_w3 = linear(bias = linear_4_bias_0, weight = tern_14_w3_weight_0_palettized, x = mul_731)[name = string("tern_14_w3")];
            tensor<fp16, [960]> mul_732_y_0 = const()[name = string("mul_732_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7418432)))];
            tensor<fp16, [8, 960]> mul_732 = mul(x = tern_14_w3, y = mul_732_y_0)[name = string("mul_732")];
            fp16 mul_733_y_0 = const()[name = string("mul_733_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [8, 960]> mul_733 = mul(x = mul_728, y = mul_733_y_0)[name = string("mul_733")];
            tensor<fp16, [8, 960]> tanh_14 = tanh(x = mul_733)[name = string("tanh_14")];
            fp16 mul_734_x_0 = const()[name = string("mul_734_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [8, 960]> mul_734 = mul(x = mul_734_x_0, y = tanh_14)[name = string("mul_734")];
            fp16 add_88_x_0 = const()[name = string("add_88_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [8, 960]> add_88 = add(x = add_88_x_0, y = mul_734)[name = string("add_88")];
            tensor<fp16, [8, 960]> mul_735 = mul(x = mul_728, y = add_88)[name = string("mul_735")];
            tensor<fp16, [8, 960]> mul_736 = mul(x = mul_735, y = mul_732)[name = string("mul_736")];
            tensor<fp16, [8, 960]> mul_737 = mul(x = mul_736, y = mul_736)[name = string("mul_737")];
            tensor<int32, [1]> reduce_mean_158_axes_0 = const()[name = string("reduce_mean_158_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_158_keep_dims_0 = const()[name = string("reduce_mean_158_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_158 = reduce_mean(axes = reduce_mean_158_axes_0, keep_dims = reduce_mean_158_keep_dims_0, x = mul_737)[name = string("reduce_mean_158")];
            fp32 rsqrt_158_epsilon_0 = const()[name = string("rsqrt_158_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_158 = rsqrt(epsilon = rsqrt_158_epsilon_0, x = reduce_mean_158)[name = string("rsqrt_158")];
            tensor<fp16, [8, 960]> mul_738 = mul(x = mul_736, y = rsqrt_158)[name = string("mul_738")];
            tensor<fp16, [960]> mul_739_y_0 = const()[name = string("mul_739_y_0"), val = tensor<fp16, [960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7420416)))];
            tensor<fp16, [8, 960]> mul_739 = mul(x = mul_738, y = mul_739_y_0)[name = string("mul_739")];
            tensor<fp16, [352, 960]> tern_14_w2_weight_0_palettized = constexpr_lut_to_dense(indices = tensor<uint2, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7422400))), lut = tensor<fp16, [1, 1, 4, 1]>([[[[-0x1p+0], [0x0p+0], [0x1p+0], [0x0p+0]]]]))[name = string("tern_14_w2_weight_0_palettized")];
            tensor<fp16, [8, 352]> tern_14_w2 = linear(bias = linear_0_bias_0, weight = tern_14_w2_weight_0_palettized, x = mul_739)[name = string("tern_14_w2")];
            tensor<fp16, [352]> mul_740_y_0 = const()[name = string("mul_740_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7506944)))];
            tensor<fp16, [8, 352]> mul_740 = mul(x = tern_14_w2, y = mul_740_y_0)[name = string("mul_740")];
            tensor<fp16, [8, 352]> add_89 = add(x = add_87, y = mul_740)[name = string("add_89")];
            tensor<fp16, [8, 352]> mul_741 = mul(x = add_89, y = add_89)[name = string("mul_741")];
            tensor<int32, [1]> reduce_mean_159_axes_0 = const()[name = string("reduce_mean_159_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_159_keep_dims_0 = const()[name = string("reduce_mean_159_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_159 = reduce_mean(axes = reduce_mean_159_axes_0, keep_dims = reduce_mean_159_keep_dims_0, x = mul_741)[name = string("reduce_mean_159")];
            fp32 rsqrt_159_epsilon_0 = const()[name = string("rsqrt_159_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_159 = rsqrt(epsilon = rsqrt_159_epsilon_0, x = reduce_mean_159)[name = string("rsqrt_159")];
            tensor<fp16, [8, 352]> mul_742 = mul(x = add_89, y = rsqrt_159)[name = string("mul_742")];
            tensor<fp16, [352]> mul_743_y_0 = const()[name = string("mul_743_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7507712)))];
            tensor<fp16, [8, 352]> mul_743 = mul(x = mul_742, y = mul_743_y_0)[name = string("mul_743")];
            tensor<fp16, [352, 352]> linear_7_weight_0 = const()[name = string("linear_7_weight_0"), val = tensor<fp16, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7508480)))];
            tensor<fp16, [8, 352]> linear_7 = linear(bias = linear_0_bias_0, weight = linear_7_weight_0, x = mul_743)[name = string("linear_7")];
            tensor<int32, [3]> reshape_122_shape_0 = const()[name = string("reshape_122_shape_0"), val = tensor<int32, [3]>([8, 8, 44])];
            tensor<fp16, [8, 8, 44]> reshape_122 = reshape(shape = reshape_122_shape_0, x = linear_7)[name = string("reshape_122")];
            tensor<int32, [3]> transpose_60_perm_0 = const()[name = string("transpose_60_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [88, 352]> linear_8_weight_0 = const()[name = string("linear_8_weight_0"), val = tensor<fp16, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7756352)))];
            tensor<fp16, [88]> linear_8_bias_0 = const()[name = string("linear_8_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [8, 88]> linear_8 = linear(bias = linear_8_bias_0, weight = linear_8_weight_0, x = mul_743)[name = string("linear_8")];
            tensor<int32, [3]> reshape_123_shape_0 = const()[name = string("reshape_123_shape_0"), val = tensor<int32, [3]>([8, 2, 44])];
            tensor<fp16, [8, 2, 44]> reshape_123 = reshape(shape = reshape_123_shape_0, x = linear_8)[name = string("reshape_123")];
            tensor<int32, [3]> transpose_61_perm_0 = const()[name = string("transpose_61_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [88, 352]> linear_9_weight_0 = const()[name = string("linear_9_weight_0"), val = tensor<fp16, [88, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7818368)))];
            tensor<fp16, [88]> linear_9_bias_0 = const()[name = string("linear_9_bias_0"), val = tensor<fp16, [88]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(312256)))];
            tensor<fp16, [8, 88]> linear_9 = linear(bias = linear_9_bias_0, weight = linear_9_weight_0, x = mul_743)[name = string("linear_9")];
            tensor<int32, [3]> reshape_124_shape_0 = const()[name = string("reshape_124_shape_0"), val = tensor<int32, [3]>([8, 2, 44])];
            tensor<fp16, [8, 2, 44]> reshape_124 = reshape(shape = reshape_124_shape_0, x = linear_9)[name = string("reshape_124")];
            tensor<int32, [3]> transpose_62_perm_0 = const()[name = string("transpose_62_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<fp16, [8, 8, 44]> transpose_60 = transpose(perm = transpose_60_perm_0, x = reshape_122)[name = string("transpose_3")];
            tensor<fp16, [8, 8, 44]> mul_744 = mul(x = transpose_60, y = transpose_60)[name = string("mul_744")];
            tensor<int32, [1]> reduce_mean_160_axes_0 = const()[name = string("reduce_mean_160_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_160_keep_dims_0 = const()[name = string("reduce_mean_160_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 8, 1]> reduce_mean_160 = reduce_mean(axes = reduce_mean_160_axes_0, keep_dims = reduce_mean_160_keep_dims_0, x = mul_744)[name = string("reduce_mean_160")];
            fp32 rsqrt_160_epsilon_0 = const()[name = string("rsqrt_160_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 8, 1]> rsqrt_160 = rsqrt(epsilon = rsqrt_160_epsilon_0, x = reduce_mean_160)[name = string("rsqrt_160")];
            tensor<fp16, [8, 8, 44]> mul_745 = mul(x = transpose_60, y = rsqrt_160)[name = string("mul_745")];
            tensor<fp16, [44]> mul_746_y_0 = const()[name = string("mul_746_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7880384)))];
            tensor<fp16, [8, 8, 44]> mul_746 = mul(x = mul_745, y = mul_746_y_0)[name = string("mul_746")];
            tensor<int32, [3]> slice_by_index_60_begin_0 = const()[name = string("slice_by_index_60_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_60_end_0 = const()[name = string("slice_by_index_60_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_60_end_mask_0 = const()[name = string("slice_by_index_60_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [8, 8, 22]> slice_by_index_60 = slice_by_index(begin = slice_by_index_60_begin_0, end = slice_by_index_60_end_0, end_mask = slice_by_index_60_end_mask_0, x = mul_746)[name = string("slice_by_index_60")];
            tensor<int32, [3]> slice_by_index_61_begin_0 = const()[name = string("slice_by_index_61_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_61_end_0 = const()[name = string("slice_by_index_61_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_61_end_mask_0 = const()[name = string("slice_by_index_61_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [8, 8, 22]> slice_by_index_61 = slice_by_index(begin = slice_by_index_61_begin_0, end = slice_by_index_61_end_0, end_mask = slice_by_index_61_end_mask_0, x = mul_746)[name = string("slice_by_index_61")];
            int32 concat_30_axis_0 = const()[name = string("concat_30_axis_0"), val = int32(-1)];
            bool concat_30_interleave_0 = const()[name = string("concat_30_interleave_0"), val = bool(false)];
            tensor<fp16, [8, 8, 44]> concat_30 = concat(axis = concat_30_axis_0, interleave = concat_30_interleave_0, values = (slice_by_index_61, slice_by_index_60))[name = string("concat_30")];
            tensor<fp16, [44]> mul_747_y_0 = const()[name = string("mul_747_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [8, 8, 44]> mul_747 = mul(x = concat_30, y = mul_747_y_0)[name = string("mul_747")];
            tensor<fp16, [8, 8, 44]> mul_748 = mul(x = mul_746, y = mul_11_y_0)[name = string("mul_748")];
            tensor<fp16, [8, 8, 44]> mul_749 = mul(x = mul_747, y = mul_12_y_0)[name = string("mul_749")];
            tensor<fp16, [8, 8, 44]> add_90 = add(x = mul_748, y = mul_749)[name = string("add_90")];
            tensor<fp16, [2, 8, 44]> transpose_61 = transpose(perm = transpose_61_perm_0, x = reshape_123)[name = string("transpose_2")];
            tensor<fp16, [2, 8, 44]> mul_750 = mul(x = transpose_61, y = transpose_61)[name = string("mul_750")];
            tensor<int32, [1]> reduce_mean_161_axes_0 = const()[name = string("reduce_mean_161_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_161_keep_dims_0 = const()[name = string("reduce_mean_161_keep_dims_0"), val = bool(true)];
            tensor<fp16, [2, 8, 1]> reduce_mean_161 = reduce_mean(axes = reduce_mean_161_axes_0, keep_dims = reduce_mean_161_keep_dims_0, x = mul_750)[name = string("reduce_mean_161")];
            fp32 rsqrt_161_epsilon_0 = const()[name = string("rsqrt_161_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [2, 8, 1]> rsqrt_161 = rsqrt(epsilon = rsqrt_161_epsilon_0, x = reduce_mean_161)[name = string("rsqrt_161")];
            tensor<fp16, [2, 8, 44]> mul_751 = mul(x = transpose_61, y = rsqrt_161)[name = string("mul_751")];
            tensor<fp16, [44]> mul_752_y_0 = const()[name = string("mul_752_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7880576)))];
            tensor<fp16, [2, 8, 44]> mul_752 = mul(x = mul_751, y = mul_752_y_0)[name = string("mul_752")];
            tensor<int32, [3]> slice_by_index_62_begin_0 = const()[name = string("slice_by_index_62_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_62_end_0 = const()[name = string("slice_by_index_62_end_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<bool, [3]> slice_by_index_62_end_mask_0 = const()[name = string("slice_by_index_62_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp16, [2, 8, 22]> slice_by_index_62 = slice_by_index(begin = slice_by_index_62_begin_0, end = slice_by_index_62_end_0, end_mask = slice_by_index_62_end_mask_0, x = mul_752)[name = string("slice_by_index_62")];
            tensor<int32, [3]> slice_by_index_63_begin_0 = const()[name = string("slice_by_index_63_begin_0"), val = tensor<int32, [3]>([0, 0, 22])];
            tensor<int32, [3]> slice_by_index_63_end_0 = const()[name = string("slice_by_index_63_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_63_end_mask_0 = const()[name = string("slice_by_index_63_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp16, [2, 8, 22]> slice_by_index_63 = slice_by_index(begin = slice_by_index_63_begin_0, end = slice_by_index_63_end_0, end_mask = slice_by_index_63_end_mask_0, x = mul_752)[name = string("slice_by_index_63")];
            int32 concat_31_axis_0 = const()[name = string("concat_31_axis_0"), val = int32(-1)];
            bool concat_31_interleave_0 = const()[name = string("concat_31_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 8, 44]> concat_31 = concat(axis = concat_31_axis_0, interleave = concat_31_interleave_0, values = (slice_by_index_63, slice_by_index_62))[name = string("concat_31")];
            tensor<fp16, [44]> mul_753_y_0 = const()[name = string("mul_753_y_0"), val = tensor<fp16, [44]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(374720)))];
            tensor<fp16, [2, 8, 44]> mul_753 = mul(x = concat_31, y = mul_753_y_0)[name = string("mul_753")];
            tensor<fp16, [2, 8, 44]> mul_754 = mul(x = mul_752, y = mul_11_y_0)[name = string("mul_754")];
            tensor<fp16, [2, 8, 44]> mul_755 = mul(x = mul_753, y = mul_12_y_0)[name = string("mul_755")];
            tensor<fp16, [2, 8, 44]> add_91 = add(x = mul_754, y = mul_755)[name = string("add_91")];
            tensor<int32, [4]> reshape_125_shape_0 = const()[name = string("reshape_125_shape_0"), val = tensor<int32, [4]>([2, 1, 8, 44])];
            tensor<fp16, [2, 1, 8, 44]> reshape_125 = reshape(shape = reshape_125_shape_0, x = add_91)[name = string("reshape_125")];
            tensor<int32, [4]> tile_30_reps_0 = const()[name = string("tile_30_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 8, 44]> tile_30 = tile(reps = tile_30_reps_0, x = reshape_125)[name = string("tile_30")];
            tensor<int32, [3]> reshape_126_shape_0 = const()[name = string("reshape_126_shape_0"), val = tensor<int32, [3]>([8, 8, 44])];
            tensor<fp16, [8, 8, 44]> reshape_126 = reshape(shape = reshape_126_shape_0, x = tile_30)[name = string("reshape_126")];
            tensor<int32, [4]> reshape_127_shape_0 = const()[name = string("reshape_127_shape_0"), val = tensor<int32, [4]>([2, 1, 8, 44])];
            tensor<fp16, [2, 8, 44]> transpose_62 = transpose(perm = transpose_62_perm_0, x = reshape_124)[name = string("transpose_1")];
            tensor<fp16, [2, 1, 8, 44]> reshape_127 = reshape(shape = reshape_127_shape_0, x = transpose_62)[name = string("reshape_127")];
            tensor<int32, [4]> tile_31_reps_0 = const()[name = string("tile_31_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<fp16, [2, 4, 8, 44]> tile_31 = tile(reps = tile_31_reps_0, x = reshape_127)[name = string("tile_31")];
            tensor<int32, [3]> reshape_128_shape_0 = const()[name = string("reshape_128_shape_0"), val = tensor<int32, [3]>([8, 8, 44])];
            tensor<fp16, [8, 8, 44]> reshape_128 = reshape(shape = reshape_128_shape_0, x = tile_31)[name = string("reshape_128")];
            fp16 mul_756_y_0 = const()[name = string("mul_756_y_0"), val = fp16(0x1.34cp-3)];
            tensor<fp16, [8, 8, 44]> mul_756 = mul(x = add_90, y = mul_756_y_0)[name = string("mul_756")];
            bool matmul_30_transpose_y_0 = const()[name = string("matmul_30_transpose_y_0"), val = bool(true)];
            bool matmul_30_transpose_x_0 = const()[name = string("matmul_30_transpose_x_0"), val = bool(false)];
            tensor<fp16, [8, 8, 8]> matmul_30 = matmul(transpose_x = matmul_30_transpose_x_0, transpose_y = matmul_30_transpose_y_0, x = mul_756, y = reshape_126)[name = string("matmul_30")];
            tensor<fp16, [8, 8, 8]> add_92 = add(x = matmul_30, y = reshape_1)[name = string("add_92")];
            int32 softmax_15_axis_0 = const()[name = string("softmax_15_axis_0"), val = int32(-1)];
            tensor<fp16, [8, 8, 8]> softmax_15 = softmax(axis = softmax_15_axis_0, x = add_92)[name = string("softmax_15")];
            bool matmul_31_transpose_x_0 = const()[name = string("matmul_31_transpose_x_0"), val = bool(false)];
            bool matmul_31_transpose_y_0 = const()[name = string("matmul_31_transpose_y_0"), val = bool(false)];
            tensor<fp16, [8, 8, 44]> matmul_31 = matmul(transpose_x = matmul_31_transpose_x_0, transpose_y = matmul_31_transpose_y_0, x = softmax_15, y = reshape_128)[name = string("matmul_31")];
            tensor<int32, [3]> transpose_63_perm_0 = const()[name = string("transpose_63_perm_0"), val = tensor<int32, [3]>([1, 0, 2])];
            tensor<int32, [2]> reshape_129_shape_0 = const()[name = string("reshape_129_shape_0"), val = tensor<int32, [2]>([8, 352])];
            tensor<fp16, [8, 8, 44]> transpose_63 = transpose(perm = transpose_63_perm_0, x = matmul_31)[name = string("transpose_0")];
            tensor<fp16, [8, 352]> reshape_129 = reshape(shape = reshape_129_shape_0, x = transpose_63)[name = string("reshape_129")];
            tensor<fp16, [352, 352]> linear_10_weight_0 = const()[name = string("linear_10_weight_0"), val = tensor<fp16, [352, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7880768)))];
            tensor<fp16, [8, 352]> linear_10 = linear(bias = linear_0_bias_0, weight = linear_10_weight_0, x = reshape_129)[name = string("linear_10")];
            tensor<fp16, [8, 352]> add_93 = add(x = add_89, y = linear_10)[name = string("add_93")];
            tensor<fp16, [8, 352]> mul_757 = mul(x = add_93, y = add_93)[name = string("mul_757")];
            tensor<int32, [1]> reduce_mean_162_axes_0 = const()[name = string("reduce_mean_162_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_162_keep_dims_0 = const()[name = string("reduce_mean_162_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_162 = reduce_mean(axes = reduce_mean_162_axes_0, keep_dims = reduce_mean_162_keep_dims_0, x = mul_757)[name = string("reduce_mean_162")];
            fp32 rsqrt_162_epsilon_0 = const()[name = string("rsqrt_162_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_162 = rsqrt(epsilon = rsqrt_162_epsilon_0, x = reduce_mean_162)[name = string("rsqrt_162")];
            tensor<fp16, [8, 352]> mul_758 = mul(x = add_93, y = rsqrt_162)[name = string("mul_758")];
            tensor<fp16, [352]> mul_759_y_0 = const()[name = string("mul_759_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8128640)))];
            tensor<fp16, [8, 352]> mul_759 = mul(x = mul_758, y = mul_759_y_0)[name = string("mul_759")];
            tensor<fp16, [960, 352]> linear_11_weight_0 = const()[name = string("linear_11_weight_0"), val = tensor<fp16, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8129408)))];
            tensor<fp16, [8, 960]> linear_11 = linear(bias = linear_4_bias_0, weight = linear_11_weight_0, x = mul_759)[name = string("linear_11")];
            tensor<fp16, [960, 352]> linear_12_weight_0 = const()[name = string("linear_12_weight_0"), val = tensor<fp16, [960, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8805312)))];
            tensor<fp16, [8, 960]> linear_12 = linear(bias = linear_4_bias_0, weight = linear_12_weight_0, x = mul_759)[name = string("linear_12")];
            fp16 mul_760_y_0 = const()[name = string("mul_760_y_0"), val = fp16(0x1p-1)];
            tensor<fp16, [8, 960]> mul_760 = mul(x = linear_11, y = mul_760_y_0)[name = string("mul_760")];
            tensor<fp16, [8, 960]> tanh_15 = tanh(x = mul_760)[name = string("tanh_15")];
            fp16 mul_761_x_0 = const()[name = string("mul_761_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [8, 960]> mul_761 = mul(x = mul_761_x_0, y = tanh_15)[name = string("mul_761")];
            fp16 add_94_x_0 = const()[name = string("add_94_x_0"), val = fp16(0x1p-1)];
            tensor<fp16, [8, 960]> add_94 = add(x = add_94_x_0, y = mul_761)[name = string("add_94")];
            tensor<fp16, [8, 960]> mul_762 = mul(x = linear_11, y = add_94)[name = string("mul_762")];
            tensor<fp16, [8, 960]> mul_763 = mul(x = mul_762, y = linear_12)[name = string("mul_763")];
            tensor<fp16, [352, 960]> linear_13_weight_0 = const()[name = string("linear_13_weight_0"), val = tensor<fp16, [352, 960]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9481216)))];
            tensor<fp16, [8, 352]> linear_13 = linear(bias = linear_0_bias_0, weight = linear_13_weight_0, x = mul_763)[name = string("linear_13")];
            tensor<fp16, [8, 352]> add_95 = add(x = add_93, y = linear_13)[name = string("add_95")];
            tensor<fp16, [8, 352]> mul_764 = mul(x = add_95, y = add_95)[name = string("mul_764")];
            tensor<int32, [1]> reduce_mean_163_axes_0 = const()[name = string("reduce_mean_163_axes_0"), val = tensor<int32, [1]>([-1])];
            bool reduce_mean_163_keep_dims_0 = const()[name = string("reduce_mean_163_keep_dims_0"), val = bool(true)];
            tensor<fp16, [8, 1]> reduce_mean_163 = reduce_mean(axes = reduce_mean_163_axes_0, keep_dims = reduce_mean_163_keep_dims_0, x = mul_764)[name = string("reduce_mean_163")];
            fp32 rsqrt_163_epsilon_0 = const()[name = string("rsqrt_163_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp16, [8, 1]> rsqrt_163 = rsqrt(epsilon = rsqrt_163_epsilon_0, x = reduce_mean_163)[name = string("rsqrt_163")];
            tensor<fp16, [8, 352]> mul_765 = mul(x = add_95, y = rsqrt_163)[name = string("mul_765")];
            tensor<fp16, [352]> mul_766_y_0 = const()[name = string("mul_766_y_0"), val = tensor<fp16, [352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10157120)))];
            tensor<fp16, [8, 352]> mul_766 = mul(x = mul_765, y = mul_766_y_0)[name = string("mul_766")];
            tensor<fp16, [8342, 352]> linear_14_weight_0 = const()[name = string("linear_14_weight_0"), val = tensor<fp16, [8342, 352]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10157888)))];
            tensor<fp16, [8342]> linear_14_bias_0 = const()[name = string("linear_14_bias_0"), val = tensor<fp16, [8342]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16030720)))];
            tensor<fp16, [8, 8342]> linear_14 = linear(bias = linear_14_bias_0, weight = linear_14_weight_0, x = mul_766)[name = string("linear_14")];
            tensor<int32, [3]> logits_shape_0 = const()[name = string("logits_shape_0"), val = tensor<int32, [3]>([1, 8, 8342])];
            tensor<fp16, [1, 8, 8342]> logits = reshape(shape = logits_shape_0, x = linear_14)[name = string("logits")];
        } -> (logits);
}