program(1.3)
[buildInfo = dict<string, string>({{"coremlc-component-MIL", "3600.16.1"}, {"coremlc-version", "3600.25.1"}, {"coremltools-component-torch", "2.7.0"}, {"coremltools-source-dialect", "TorchScript"}, {"coremltools-version", "9.0"}})]
{
    func main<ios18>(tensor<fp32, [1, 128, 1501]> mel, tensor<int32, [1]> mel_length) {
            int32 var_32 = const()[name = string("op_32"), val = int32(-1)];
            tensor<int32, [3]> x_1_perm_0 = const()[name = string("x_1_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            string mel_to_fp16_dtype_0 = const()[name = string("mel_to_fp16_dtype_0"), val = string("fp16")];
            string var_89_to_fp16_dtype_0 = const()[name = string("op_89_to_fp16_dtype_0"), val = string("fp16")];
            fp16 var_90_promoted_to_fp16 = const()[name = string("op_90_promoted_to_fp16"), val = fp16(-0x1p+0)];
            tensor<fp16, [1]> mel_length_to_fp16 = cast(dtype = var_89_to_fp16_dtype_0, x = mel_length)[name = string("cast_229")];
            tensor<fp16, [1]> var_91_cast_fp16 = add(x = mel_length_to_fp16, y = var_90_promoted_to_fp16)[name = string("op_91_cast_fp16")];
            fp16 _inversed_93_y_0_to_fp16 = const()[name = string("_inversed_93_y_0_to_fp16"), val = fp16(0x1p-1)];
            tensor<fp16, [1]> _inversed_93_cast_fp16 = mul(x = var_91_cast_fp16, y = _inversed_93_y_0_to_fp16)[name = string("_inversed_93_cast_fp16")];
            fp16 var_94_to_fp16 = const()[name = string("op_94_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1]> lengths_1_cast_fp16 = add(x = _inversed_93_cast_fp16, y = var_94_to_fp16)[name = string("lengths_1_cast_fp16")];
            tensor<fp16, [1]> lengths_3_cast_fp16 = floor(x = lengths_1_cast_fp16)[name = string("lengths_3_cast_fp16")];
            fp16 var_98_promoted_to_fp16 = const()[name = string("op_98_promoted_to_fp16"), val = fp16(-0x1p+0)];
            tensor<fp16, [1]> var_99_cast_fp16 = add(x = lengths_3_cast_fp16, y = var_98_promoted_to_fp16)[name = string("op_99_cast_fp16")];
            fp16 _inversed_101_y_0_to_fp16 = const()[name = string("_inversed_101_y_0_to_fp16"), val = fp16(0x1p-1)];
            tensor<fp16, [1]> _inversed_101_cast_fp16 = mul(x = var_99_cast_fp16, y = _inversed_101_y_0_to_fp16)[name = string("_inversed_101_cast_fp16")];
            fp16 var_102_to_fp16 = const()[name = string("op_102_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1]> lengths_7_cast_fp16 = add(x = _inversed_101_cast_fp16, y = var_102_to_fp16)[name = string("lengths_7_cast_fp16")];
            tensor<fp16, [1]> lengths_9_cast_fp16 = floor(x = lengths_7_cast_fp16)[name = string("lengths_9_cast_fp16")];
            fp16 var_106_promoted_to_fp16 = const()[name = string("op_106_promoted_to_fp16"), val = fp16(-0x1p+0)];
            tensor<fp16, [1]> var_107_cast_fp16 = add(x = lengths_9_cast_fp16, y = var_106_promoted_to_fp16)[name = string("op_107_cast_fp16")];
            fp16 _inversed_109_y_0_to_fp16 = const()[name = string("_inversed_109_y_0_to_fp16"), val = fp16(0x1p-1)];
            tensor<fp16, [1]> _inversed_109_cast_fp16 = mul(x = var_107_cast_fp16, y = _inversed_109_y_0_to_fp16)[name = string("_inversed_109_cast_fp16")];
            fp16 var_110_to_fp16 = const()[name = string("op_110_to_fp16"), val = fp16(0x1p+0)];
            tensor<fp16, [1]> lengths_13_cast_fp16 = add(x = _inversed_109_cast_fp16, y = var_110_to_fp16)[name = string("lengths_13_cast_fp16")];
            tensor<fp16, [1]> lengths_cast_fp16 = floor(x = lengths_13_cast_fp16)[name = string("lengths_cast_fp16")];
            tensor<int32, [1]> input_1_axes_0 = const()[name = string("input_1_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1, 128, 1501]> mel_to_fp16 = cast(dtype = mel_to_fp16_dtype_0, x = mel)[name = string("cast_230")];
            tensor<fp16, [1, 1501, 128]> x_1_cast_fp16 = transpose(perm = x_1_perm_0, x = mel_to_fp16)[name = string("transpose_293")];
            tensor<fp16, [1, 1, 1501, 128]> input_1_cast_fp16 = expand_dims(axes = input_1_axes_0, x = x_1_cast_fp16)[name = string("input_1_cast_fp16")];
            string input_3_pad_type_0 = const()[name = string("input_3_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_3_pad_0 = const()[name = string("input_3_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_3_strides_0 = const()[name = string("input_3_strides_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [2]> input_3_dilations_0 = const()[name = string("input_3_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_3_groups_0 = const()[name = string("input_3_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1, 3, 3]> module_pre_encode_conv_0_weight_to_fp16 = const()[name = string("module_pre_encode_conv_0_weight_to_fp16"), val = tensor<fp16, [256, 1, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(64)))];
            tensor<fp16, [256]> module_pre_encode_conv_0_bias_to_fp16 = const()[name = string("module_pre_encode_conv_0_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4736)))];
            tensor<fp16, [1, 256, 751, 64]> input_3_cast_fp16 = conv(bias = module_pre_encode_conv_0_bias_to_fp16, dilations = input_3_dilations_0, groups = input_3_groups_0, pad = input_3_pad_0, pad_type = input_3_pad_type_0, strides = input_3_strides_0, weight = module_pre_encode_conv_0_weight_to_fp16, x = input_1_cast_fp16)[name = string("input_3_cast_fp16")];
            tensor<fp16, [1, 256, 751, 64]> input_5_cast_fp16 = relu(x = input_3_cast_fp16)[name = string("input_5_cast_fp16")];
            string input_7_pad_type_0 = const()[name = string("input_7_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_7_pad_0 = const()[name = string("input_7_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_7_strides_0 = const()[name = string("input_7_strides_0"), val = tensor<int32, [2]>([2, 2])];
            int32 input_7_groups_0 = const()[name = string("input_7_groups_0"), val = int32(256)];
            tensor<int32, [2]> input_7_dilations_0 = const()[name = string("input_7_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [256, 1, 3, 3]> module_pre_encode_conv_2_weight_to_fp16 = const()[name = string("module_pre_encode_conv_2_weight_to_fp16"), val = tensor<fp16, [256, 1, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5312)))];
            tensor<fp16, [256]> module_pre_encode_conv_2_bias_to_fp16 = const()[name = string("module_pre_encode_conv_2_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9984)))];
            tensor<fp16, [1, 256, 376, 32]> input_7_cast_fp16 = conv(bias = module_pre_encode_conv_2_bias_to_fp16, dilations = input_7_dilations_0, groups = input_7_groups_0, pad = input_7_pad_0, pad_type = input_7_pad_type_0, strides = input_7_strides_0, weight = module_pre_encode_conv_2_weight_to_fp16, x = input_5_cast_fp16)[name = string("input_7_cast_fp16")];
            string input_9_pad_type_0 = const()[name = string("input_9_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_9_strides_0 = const()[name = string("input_9_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_9_pad_0 = const()[name = string("input_9_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> input_9_dilations_0 = const()[name = string("input_9_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_9_groups_0 = const()[name = string("input_9_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1, 1]> module_pre_encode_conv_3_weight_to_fp16 = const()[name = string("module_pre_encode_conv_3_weight_to_fp16"), val = tensor<fp16, [256, 256, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10560)))];
            tensor<fp16, [256]> module_pre_encode_conv_3_bias_to_fp16 = const()[name = string("module_pre_encode_conv_3_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(141696)))];
            tensor<fp16, [1, 256, 376, 32]> input_9_cast_fp16 = conv(bias = module_pre_encode_conv_3_bias_to_fp16, dilations = input_9_dilations_0, groups = input_9_groups_0, pad = input_9_pad_0, pad_type = input_9_pad_type_0, strides = input_9_strides_0, weight = module_pre_encode_conv_3_weight_to_fp16, x = input_7_cast_fp16)[name = string("input_9_cast_fp16")];
            tensor<fp16, [1, 256, 376, 32]> input_11_cast_fp16 = relu(x = input_9_cast_fp16)[name = string("input_11_cast_fp16")];
            string input_13_pad_type_0 = const()[name = string("input_13_pad_type_0"), val = string("custom")];
            tensor<int32, [4]> input_13_pad_0 = const()[name = string("input_13_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_13_strides_0 = const()[name = string("input_13_strides_0"), val = tensor<int32, [2]>([2, 2])];
            int32 input_13_groups_0 = const()[name = string("input_13_groups_0"), val = int32(256)];
            tensor<int32, [2]> input_13_dilations_0 = const()[name = string("input_13_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [256, 1, 3, 3]> module_pre_encode_conv_5_weight_to_fp16 = const()[name = string("module_pre_encode_conv_5_weight_to_fp16"), val = tensor<fp16, [256, 1, 3, 3]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(142272)))];
            tensor<fp16, [256]> module_pre_encode_conv_5_bias_to_fp16 = const()[name = string("module_pre_encode_conv_5_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(146944)))];
            tensor<fp16, [1, 256, 188, 16]> input_13_cast_fp16 = conv(bias = module_pre_encode_conv_5_bias_to_fp16, dilations = input_13_dilations_0, groups = input_13_groups_0, pad = input_13_pad_0, pad_type = input_13_pad_type_0, strides = input_13_strides_0, weight = module_pre_encode_conv_5_weight_to_fp16, x = input_11_cast_fp16)[name = string("input_13_cast_fp16")];
            string input_15_pad_type_0 = const()[name = string("input_15_pad_type_0"), val = string("valid")];
            tensor<int32, [2]> input_15_strides_0 = const()[name = string("input_15_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_15_pad_0 = const()[name = string("input_15_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> input_15_dilations_0 = const()[name = string("input_15_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            int32 input_15_groups_0 = const()[name = string("input_15_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1, 1]> module_pre_encode_conv_6_weight_to_fp16 = const()[name = string("module_pre_encode_conv_6_weight_to_fp16"), val = tensor<fp16, [256, 256, 1, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(147520)))];
            tensor<fp16, [256]> module_pre_encode_conv_6_bias_to_fp16 = const()[name = string("module_pre_encode_conv_6_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(278656)))];
            tensor<fp16, [1, 256, 188, 16]> input_15_cast_fp16 = conv(bias = module_pre_encode_conv_6_bias_to_fp16, dilations = input_15_dilations_0, groups = input_15_groups_0, pad = input_15_pad_0, pad_type = input_15_pad_type_0, strides = input_15_strides_0, weight = module_pre_encode_conv_6_weight_to_fp16, x = input_13_cast_fp16)[name = string("input_15_cast_fp16")];
            tensor<fp16, [1, 256, 188, 16]> x_3_cast_fp16 = relu(x = input_15_cast_fp16)[name = string("x_3_cast_fp16")];
            tensor<int32, [4]> var_160_perm_0 = const()[name = string("op_160_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_161 = const()[name = string("op_161"), val = tensor<int32, [3]>([1, 188, -1])];
            tensor<fp16, [1, 188, 256, 16]> var_160_cast_fp16 = transpose(perm = var_160_perm_0, x = x_3_cast_fp16)[name = string("transpose_292")];
            tensor<fp16, [1, 188, 4096]> input_17_cast_fp16 = reshape(shape = var_161, x = var_160_cast_fp16)[name = string("input_17_cast_fp16")];
            tensor<fp16, [1024, 4096]> module_pre_encode_out_weight_to_fp16 = const()[name = string("module_pre_encode_out_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(279232)))];
            tensor<fp16, [1024]> module_pre_encode_out_bias_to_fp16 = const()[name = string("module_pre_encode_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8667904)))];
            tensor<fp16, [1, 188, 1024]> linear_0_cast_fp16 = linear(bias = module_pre_encode_out_bias_to_fp16, weight = module_pre_encode_out_weight_to_fp16, x = input_17_cast_fp16)[name = string("linear_0_cast_fp16")];
            tensor<int32, [1]> input_21_axes_0 = const()[name = string("input_21_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_fv_insert_ln_weight_to_fp16 = const()[name = string("module_fv_insert_ln_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8670016)))];
            tensor<fp16, [1024]> module_fv_insert_ln_bias_to_fp16 = const()[name = string("module_fv_insert_ln_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8672128)))];
            fp16 var_20_to_fp16 = const()[name = string("op_20_to_fp16"), val = fp16(0x1.5p-17)];
            tensor<fp16, [1, 188, 1024]> input_21_cast_fp16 = layer_norm(axes = input_21_axes_0, beta = module_fv_insert_ln_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_fv_insert_ln_weight_to_fp16, x = linear_0_cast_fp16)[name = string("input_21_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_fv_insert_down_weight_to_fp16 = const()[name = string("module_fv_insert_down_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8674240)))];
            tensor<fp16, [1024]> module_fv_insert_down_bias_to_fp16 = const()[name = string("module_fv_insert_down_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10771456)))];
            tensor<fp16, [1, 188, 1024]> linear_1_cast_fp16 = linear(bias = module_fv_insert_down_bias_to_fp16, weight = module_fv_insert_down_weight_to_fp16, x = input_21_cast_fp16)[name = string("linear_1_cast_fp16")];
            tensor<int32, [3]> input_23_perm_0 = const()[name = string("input_23_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            string var_187_pad_type_0 = const()[name = string("op_187_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> var_187_pad_0 = const()[name = string("op_187_pad_0"), val = tensor<int32, [2]>([7, 7])];
            int32 var_187_groups_0 = const()[name = string("op_187_groups_0"), val = int32(1024)];
            tensor<int32, [1]> var_187_strides_0 = const()[name = string("op_187_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> var_187_dilations_0 = const()[name = string("op_187_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 15]> module_fv_insert_mix_weight_to_fp16 = const()[name = string("module_fv_insert_mix_weight_to_fp16"), val = tensor<fp16, [1024, 1, 15]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10773568)))];
            tensor<fp16, [1024]> module_fv_insert_mix_bias_to_fp16 = const()[name = string("module_fv_insert_mix_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10804352)))];
            tensor<fp16, [1, 1024, 188]> input_23_cast_fp16 = transpose(perm = input_23_perm_0, x = linear_1_cast_fp16)[name = string("transpose_291")];
            tensor<fp16, [1, 1024, 188]> var_187_cast_fp16 = conv(bias = module_fv_insert_mix_bias_to_fp16, dilations = var_187_dilations_0, groups = var_187_groups_0, pad = var_187_pad_0, pad_type = var_187_pad_type_0, strides = var_187_strides_0, weight = module_fv_insert_mix_weight_to_fp16, x = input_23_cast_fp16)[name = string("op_187_cast_fp16")];
            string var_188_mode_0 = const()[name = string("op_188_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 1024, 188]> var_188_cast_fp16 = gelu(mode = var_188_mode_0, x = var_187_cast_fp16)[name = string("op_188_cast_fp16")];
            tensor<int32, [3]> input_25_perm_0 = const()[name = string("input_25_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1024, 1024]> module_fv_insert_up_weight_to_fp16 = const()[name = string("module_fv_insert_up_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10806464)))];
            tensor<fp16, [1024]> module_fv_insert_up_bias_to_fp16 = const()[name = string("module_fv_insert_up_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12903680)))];
            tensor<fp16, [1, 188, 1024]> input_25_cast_fp16 = transpose(perm = input_25_perm_0, x = var_188_cast_fp16)[name = string("transpose_290")];
            tensor<fp16, [1, 188, 1024]> linear_2_cast_fp16 = linear(bias = module_fv_insert_up_bias_to_fp16, weight = module_fv_insert_up_weight_to_fp16, x = input_25_cast_fp16)[name = string("linear_2_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> audio_signal_1_cast_fp16 = add(x = linear_0_cast_fp16, y = linear_2_cast_fp16)[name = string("audio_signal_1_cast_fp16")];
            string padding_length_dtype_0 = const()[name = string("padding_length_dtype_0"), val = string("int32")];
            tensor<int32, [1, 188]> expand_dims_0 = const()[name = string("expand_dims_0"), val = tensor<int32, [1, 188]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12905792)))];
            tensor<int32, [1]> var_224_axes_0 = const()[name = string("op_224_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<int32, [1]> encoder_length = cast(dtype = padding_length_dtype_0, x = lengths_cast_fp16)[name = string("cast_228")];
            tensor<int32, [1, 1]> var_224 = expand_dims(axes = var_224_axes_0, x = encoder_length)[name = string("op_224")];
            tensor<bool, [1, 188]> pad_mask_1 = less(x = expand_dims_0, y = var_224)[name = string("pad_mask_1")];
            tensor<int32, [1]> var_226_axes_0 = const()[name = string("op_226_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<bool, [1, 1, 188]> var_226 = expand_dims(axes = var_226_axes_0, x = pad_mask_1)[name = string("op_226")];
            tensor<int32, [3]> var_227 = const()[name = string("op_227"), val = tensor<int32, [3]>([1, 188, 1])];
            tensor<bool, [1, 188, 188]> pad_mask_for_att_mask_1 = tile(reps = var_227, x = var_226)[name = string("pad_mask_for_att_mask_1")];
            tensor<int32, [3]> var_229_perm_0 = const()[name = string("op_229_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, [1, 188, 188]> var_229 = transpose(perm = var_229_perm_0, x = pad_mask_for_att_mask_1)[name = string("transpose_289")];
            tensor<bool, [1, 188, 188]> pad_mask_for_att_mask = logical_and(x = pad_mask_for_att_mask_1, y = var_229)[name = string("pad_mask_for_att_mask")];
            tensor<bool, [1, 188, 188]> const_7 = const()[name = string("const_7"), val = tensor<bool, [1, 188, 188]>([[[true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, 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true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true], [true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, 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true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true]]])];
            tensor<bool, [1, 188, 188]> att_mask = logical_and(x = pad_mask_for_att_mask, y = const_7)[name = string("att_mask")];
            tensor<bool, [1, 188, 188]> mask_1 = logical_not(x = att_mask)[name = string("mask_1")];
            tensor<bool, [1, 188]> pad_mask = logical_not(x = pad_mask_1)[name = string("pad_mask")];
            tensor<int32, [1]> input_29_axes_0 = const()[name = string("input_29_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_0_norm_feed_forward1_weight_to_fp16 = const()[name = string("module_layers_0_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12906624)))];
            tensor<fp16, [1024]> module_layers_0_norm_feed_forward1_bias_to_fp16 = const()[name = string("module_layers_0_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12908736)))];
            tensor<fp16, [1, 188, 1024]> input_29_cast_fp16 = layer_norm(axes = input_29_axes_0, beta = module_layers_0_norm_feed_forward1_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_0_norm_feed_forward1_weight_to_fp16, x = audio_signal_1_cast_fp16)[name = string("input_29_cast_fp16")];
            tensor<fp16, [4096, 1024]> module_layers_0_feed_forward1_linear1_weight_to_fp16 = const()[name = string("module_layers_0_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12910848)))];
            tensor<fp16, [4096]> linear_3_bias_0_to_fp16 = const()[name = string("linear_3_bias_0_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21299520)))];
            tensor<fp16, [1, 188, 4096]> linear_3_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = module_layers_0_feed_forward1_linear1_weight_to_fp16, x = input_29_cast_fp16)[name = string("linear_3_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_33_cast_fp16 = silu(x = linear_3_cast_fp16)[name = string("input_33_cast_fp16")];
            tensor<fp16, [1024, 4096]> module_layers_0_feed_forward1_linear2_weight_to_fp16 = const()[name = string("module_layers_0_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21307776)))];
            tensor<fp16, [1024]> linear_4_bias_0_to_fp16 = const()[name = string("linear_4_bias_0_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29696448)))];
            tensor<fp16, [1, 188, 1024]> linear_4_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_0_feed_forward1_linear2_weight_to_fp16, x = input_33_cast_fp16)[name = string("linear_4_cast_fp16")];
            fp16 var_260_to_fp16 = const()[name = string("op_260_to_fp16"), val = fp16(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_261_cast_fp16 = mul(x = linear_4_cast_fp16, y = var_260_to_fp16)[name = string("op_261_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_39_cast_fp16 = add(x = audio_signal_1_cast_fp16, y = var_261_cast_fp16)[name = string("input_39_cast_fp16")];
            tensor<int32, [1]> query_1_axes_0 = const()[name = string("query_1_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_0_norm_self_att_weight_to_fp16 = const()[name = string("module_layers_0_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29698560)))];
            tensor<fp16, [1024]> module_layers_0_norm_self_att_bias_to_fp16 = const()[name = string("module_layers_0_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29700672)))];
            tensor<fp16, [1, 188, 1024]> query_1_cast_fp16 = layer_norm(axes = query_1_axes_0, beta = module_layers_0_norm_self_att_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_0_norm_self_att_weight_to_fp16, x = input_39_cast_fp16)[name = string("query_1_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_0_self_attn_linear_q_weight_to_fp16 = const()[name = string("module_layers_0_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29702784)))];
            tensor<fp16, [1, 188, 1024]> linear_5_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_0_self_attn_linear_q_weight_to_fp16, x = query_1_cast_fp16)[name = string("linear_5_cast_fp16")];
            tensor<int32, [4]> var_277 = const()[name = string("op_277"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_1_cast_fp16 = reshape(shape = var_277, x = linear_5_cast_fp16)[name = string("q_1_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_0_self_attn_linear_k_weight_to_fp16 = const()[name = string("module_layers_0_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(31800000)))];
            tensor<fp16, [1, 188, 1024]> linear_6_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_0_self_attn_linear_k_weight_to_fp16, x = query_1_cast_fp16)[name = string("linear_6_cast_fp16")];
            tensor<int32, [4]> var_281 = const()[name = string("op_281"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_1_cast_fp16 = reshape(shape = var_281, x = linear_6_cast_fp16)[name = string("k_1_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_0_self_attn_linear_v_weight_to_fp16 = const()[name = string("module_layers_0_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33897216)))];
            tensor<fp16, [1, 188, 1024]> linear_7_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_0_self_attn_linear_v_weight_to_fp16, x = query_1_cast_fp16)[name = string("linear_7_cast_fp16")];
            tensor<int32, [4]> var_285 = const()[name = string("op_285"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_1_cast_fp16 = reshape(shape = var_285, x = linear_7_cast_fp16)[name = string("v_1_cast_fp16")];
            tensor<int32, [4]> value_3_perm_0 = const()[name = string("value_3_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> module_layers_0_self_attn_pos_bias_u_to_fp16 = const()[name = string("module_layers_0_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(35994432)))];
            tensor<fp16, [1, 188, 8, 128]> var_297_cast_fp16 = add(x = q_1_cast_fp16, y = module_layers_0_self_attn_pos_bias_u_to_fp16)[name = string("op_297_cast_fp16")];
            tensor<fp16, [8, 128]> module_layers_0_self_attn_pos_bias_v_to_fp16 = const()[name = string("module_layers_0_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(35996544)))];
            tensor<fp16, [1, 188, 8, 128]> var_299_cast_fp16 = add(x = q_1_cast_fp16, y = module_layers_0_self_attn_pos_bias_v_to_fp16)[name = string("op_299_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_1_perm_0 = const()[name = string("q_with_bias_v_1_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            bool x_7_transpose_x_0 = const()[name = string("x_7_transpose_x_0"), val = bool(false)];
            bool x_7_transpose_y_0 = const()[name = string("x_7_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 128, 375]> var_301_to_fp16 = const()[name = string("op_301_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(35998656)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_1_cast_fp16 = transpose(perm = q_with_bias_v_1_perm_0, x = var_299_cast_fp16)[name = string("transpose_287")];
            tensor<fp16, [1, 8, 188, 375]> x_7_cast_fp16 = matmul(transpose_x = x_7_transpose_x_0, transpose_y = x_7_transpose_y_0, x = q_with_bias_v_1_cast_fp16, y = var_301_to_fp16)[name = string("x_7_cast_fp16")];
            tensor<int32, [8]> x_9_pad_0 = const()[name = string("x_9_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            string x_9_mode_0 = const()[name = string("x_9_mode_0"), val = string("constant")];
            fp16 const_14_to_fp16 = const()[name = string("const_14_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_9_cast_fp16 = pad(constant_val = const_14_to_fp16, mode = x_9_mode_0, pad = x_9_pad_0, x = x_7_cast_fp16)[name = string("x_9_cast_fp16")];
            tensor<int32, [4]> var_309 = const()[name = string("op_309"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_11_cast_fp16 = reshape(shape = var_309, x = x_9_cast_fp16)[name = string("x_11_cast_fp16")];
            tensor<int32, [4]> var_313_begin_0 = const()[name = string("op_313_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_313_end_0 = const()[name = string("op_313_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_313_end_mask_0 = const()[name = string("op_313_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_313_cast_fp16 = slice_by_index(begin = var_313_begin_0, end = var_313_end_0, end_mask = var_313_end_mask_0, x = x_11_cast_fp16)[name = string("op_313_cast_fp16")];
            tensor<int32, [4]> var_314 = const()[name = string("op_314"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_1_cast_fp16 = reshape(shape = var_314, x = var_313_cast_fp16)[name = string("matrix_bd_1_cast_fp16")];
            bool matrix_ac_1_transpose_x_0 = const()[name = string("matrix_ac_1_transpose_x_0"), val = bool(false)];
            bool matrix_ac_1_transpose_y_0 = const()[name = string("matrix_ac_1_transpose_y_0"), val = bool(false)];
            tensor<int32, [4]> transpose_72_perm_0 = const()[name = string("transpose_72_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_73_perm_0 = const()[name = string("transpose_73_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_73 = transpose(perm = transpose_73_perm_0, x = k_1_cast_fp16)[name = string("transpose_285")];
            tensor<fp16, [1, 8, 188, 128]> transpose_72 = transpose(perm = transpose_72_perm_0, x = var_297_cast_fp16)[name = string("transpose_286")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_1_cast_fp16 = matmul(transpose_x = matrix_ac_1_transpose_x_0, transpose_y = matrix_ac_1_transpose_y_0, x = transpose_72, y = transpose_73)[name = string("matrix_ac_1_cast_fp16")];
            tensor<int32, [4]> matrix_bd_3_begin_0 = const()[name = string("matrix_bd_3_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_3_end_0 = const()[name = string("matrix_bd_3_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_3_end_mask_0 = const()[name = string("matrix_bd_3_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_3_cast_fp16 = slice_by_index(begin = matrix_bd_3_begin_0, end = matrix_bd_3_end_0, end_mask = matrix_bd_3_end_mask_0, x = matrix_bd_1_cast_fp16)[name = string("matrix_bd_3_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_323_cast_fp16 = add(x = matrix_ac_1_cast_fp16, y = matrix_bd_3_cast_fp16)[name = string("op_323_cast_fp16")];
            fp16 _inversed_scores_1_y_0_to_fp16 = const()[name = string("_inversed_scores_1_y_0_to_fp16"), val = fp16(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_1_cast_fp16 = mul(x = var_323_cast_fp16, y = _inversed_scores_1_y_0_to_fp16)[name = string("_inversed_scores_1_cast_fp16")];
            tensor<int32, [1]> mask_3_axes_0 = const()[name = string("mask_3_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<bool, [1, 1, 188, 188]> mask_3 = expand_dims(axes = mask_3_axes_0, x = mask_1)[name = string("mask_3")];
            fp16 var_10_to_fp16 = const()[name = string("op_10_to_fp16"), val = fp16(-0x1.388p+13)];
            tensor<fp16, [1, 8, 188, 188]> scores_3_cast_fp16 = select(a = var_10_to_fp16, b = _inversed_scores_1_cast_fp16, cond = mask_3)[name = string("scores_3_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_329_cast_fp16 = softmax(axis = var_32, x = scores_3_cast_fp16)[name = string("op_329_cast_fp16")];
            fp16 var_9_to_fp16 = const()[name = string("op_9_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 8, 188, 188]> input_41_cast_fp16 = select(a = var_9_to_fp16, b = var_329_cast_fp16, cond = mask_3)[name = string("input_41_cast_fp16")];
            bool x_13_transpose_x_0 = const()[name = string("x_13_transpose_x_0"), val = bool(false)];
            bool x_13_transpose_y_0 = const()[name = string("x_13_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 188, 128]> value_3_cast_fp16 = transpose(perm = value_3_perm_0, x = v_1_cast_fp16)[name = string("transpose_288")];
            tensor<fp16, [1, 8, 188, 128]> x_13_cast_fp16 = matmul(transpose_x = x_13_transpose_x_0, transpose_y = x_13_transpose_y_0, x = input_41_cast_fp16, y = value_3_cast_fp16)[name = string("x_13_cast_fp16")];
            tensor<int32, [4]> var_333_perm_0 = const()[name = string("op_333_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_334 = const()[name = string("op_334"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_333_cast_fp16 = transpose(perm = var_333_perm_0, x = x_13_cast_fp16)[name = string("transpose_284")];
            tensor<fp16, [1, 188, 1024]> input_43_cast_fp16 = reshape(shape = var_334, x = var_333_cast_fp16)[name = string("input_43_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_0_self_attn_linear_out_weight_to_fp16 = const()[name = string("module_layers_0_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(36766720)))];
            tensor<fp16, [1, 188, 1024]> linear_9_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_0_self_attn_linear_out_weight_to_fp16, x = input_43_cast_fp16)[name = string("linear_9_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_47_cast_fp16 = add(x = input_39_cast_fp16, y = linear_9_cast_fp16)[name = string("input_47_cast_fp16")];
            tensor<int32, [1]> x_17_axes_0 = const()[name = string("x_17_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_0_norm_conv_weight_to_fp16 = const()[name = string("module_layers_0_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38863936)))];
            tensor<fp16, [1024]> module_layers_0_norm_conv_bias_to_fp16 = const()[name = string("module_layers_0_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38866048)))];
            tensor<fp16, [1, 188, 1024]> x_17_cast_fp16 = layer_norm(axes = x_17_axes_0, beta = module_layers_0_norm_conv_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_0_norm_conv_weight_to_fp16, x = input_47_cast_fp16)[name = string("x_17_cast_fp16")];
            tensor<int32, [3]> input_49_perm_0 = const()[name = string("input_49_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            string input_51_pad_type_0 = const()[name = string("input_51_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_51_strides_0 = const()[name = string("input_51_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_51_pad_0 = const()[name = string("input_51_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_51_dilations_0 = const()[name = string("input_51_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_51_groups_0 = const()[name = string("input_51_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 1024, 1]> module_layers_0_conv_pointwise_conv1_weight_to_fp16 = const()[name = string("module_layers_0_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(38868160)))];
            tensor<fp16, [1, 1024, 188]> input_49_cast_fp16 = transpose(perm = input_49_perm_0, x = x_17_cast_fp16)[name = string("transpose_283")];
            tensor<fp16, [1, 2048, 188]> input_51_cast_fp16 = conv(dilations = input_51_dilations_0, groups = input_51_groups_0, pad = input_51_pad_0, pad_type = input_51_pad_type_0, strides = input_51_strides_0, weight = module_layers_0_conv_pointwise_conv1_weight_to_fp16, x = input_49_cast_fp16)[name = string("input_51_cast_fp16")];
            int32 x_19_split_num_splits_0 = const()[name = string("x_19_split_num_splits_0"), val = int32(2)];
            int32 x_19_split_axis_0 = const()[name = string("x_19_split_axis_0"), val = int32(1)];
            tensor<fp16, [1, 1024, 188]> x_19_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_19_split_cast_fp16_1 = split(axis = x_19_split_axis_0, num_splits = x_19_split_num_splits_0, x = input_51_cast_fp16)[name = string("x_19_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_19_split_1_sigmoid_cast_fp16 = sigmoid(x = x_19_split_cast_fp16_1)[name = string("x_19_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_19_cast_fp16 = mul(x = x_19_split_cast_fp16_0, y = x_19_split_1_sigmoid_cast_fp16)[name = string("x_19_cast_fp16")];
            tensor<int32, [1]> var_356_axes_0 = const()[name = string("op_356_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<bool, [1, 1, 188]> var_356 = expand_dims(axes = var_356_axes_0, x = pad_mask)[name = string("op_356")];
            tensor<fp16, [1, 1024, 188]> input_53_cast_fp16 = select(a = var_9_to_fp16, b = x_19_cast_fp16, cond = var_356)[name = string("input_53_cast_fp16")];
            tensor<int32, [6]> input_55_pad_0 = const()[name = string("input_55_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            string input_55_mode_0 = const()[name = string("input_55_mode_0"), val = string("constant")];
            fp16 const_17_to_fp16 = const()[name = string("const_17_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_55_cast_fp16 = pad(constant_val = const_17_to_fp16, mode = input_55_mode_0, pad = input_55_pad_0, x = input_53_cast_fp16)[name = string("input_55_cast_fp16")];
            string input_57_pad_type_0 = const()[name = string("input_57_pad_type_0"), val = string("valid")];
            int32 input_57_groups_0 = const()[name = string("input_57_groups_0"), val = int32(1024)];
            tensor<int32, [1]> input_57_strides_0 = const()[name = string("input_57_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_57_pad_0 = const()[name = string("input_57_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_57_dilations_0 = const()[name = string("input_57_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_248_to_fp16 = const()[name = string("const_248_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(43062528)))];
            tensor<fp16, [1024]> const_249_to_fp16 = const()[name = string("const_249_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(43081024)))];
            tensor<fp16, [1, 1024, 188]> input_59_cast_fp16 = conv(bias = const_249_to_fp16, dilations = input_57_dilations_0, groups = input_57_groups_0, pad = input_57_pad_0, pad_type = input_57_pad_type_0, strides = input_57_strides_0, weight = const_248_to_fp16, x = input_55_cast_fp16)[name = string("input_59_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_61_cast_fp16 = silu(x = input_59_cast_fp16)[name = string("input_61_cast_fp16")];
            string x_21_pad_type_0 = const()[name = string("x_21_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> x_21_strides_0 = const()[name = string("x_21_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_21_pad_0 = const()[name = string("x_21_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_21_dilations_0 = const()[name = string("x_21_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 x_21_groups_0 = const()[name = string("x_21_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 1024, 1]> module_layers_0_conv_pointwise_conv2_weight_to_fp16 = const()[name = string("module_layers_0_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(43083136)))];
            tensor<fp16, [1, 1024, 188]> x_21_cast_fp16 = conv(dilations = x_21_dilations_0, groups = x_21_groups_0, pad = x_21_pad_0, pad_type = x_21_pad_type_0, strides = x_21_strides_0, weight = module_layers_0_conv_pointwise_conv2_weight_to_fp16, x = input_61_cast_fp16)[name = string("x_21_cast_fp16")];
            tensor<int32, [3]> input_63_perm_0 = const()[name = string("input_63_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_63_cast_fp16 = transpose(perm = input_63_perm_0, x = x_21_cast_fp16)[name = string("transpose_282")];
            tensor<fp16, [1, 188, 1024]> input_65_cast_fp16 = add(x = input_47_cast_fp16, y = input_63_cast_fp16)[name = string("input_65_cast_fp16")];
            tensor<int32, [1]> input_67_axes_0 = const()[name = string("input_67_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_0_norm_feed_forward2_weight_to_fp16 = const()[name = string("module_layers_0_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(45180352)))];
            tensor<fp16, [1024]> module_layers_0_norm_feed_forward2_bias_to_fp16 = const()[name = string("module_layers_0_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(45182464)))];
            tensor<fp16, [1, 188, 1024]> input_67_cast_fp16 = layer_norm(axes = input_67_axes_0, beta = module_layers_0_norm_feed_forward2_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_0_norm_feed_forward2_weight_to_fp16, x = input_65_cast_fp16)[name = string("input_67_cast_fp16")];
            tensor<fp16, [4096, 1024]> module_layers_0_feed_forward2_linear1_weight_to_fp16 = const()[name = string("module_layers_0_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(45184576)))];
            tensor<fp16, [1, 188, 4096]> linear_10_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = module_layers_0_feed_forward2_linear1_weight_to_fp16, x = input_67_cast_fp16)[name = string("linear_10_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_71_cast_fp16 = silu(x = linear_10_cast_fp16)[name = string("input_71_cast_fp16")];
            tensor<fp16, [1024, 4096]> module_layers_0_feed_forward2_linear2_weight_to_fp16 = const()[name = string("module_layers_0_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(53573248)))];
            tensor<fp16, [1, 188, 1024]> linear_11_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_0_feed_forward2_linear2_weight_to_fp16, x = input_71_cast_fp16)[name = string("linear_11_cast_fp16")];
            fp16 var_394_to_fp16 = const()[name = string("op_394_to_fp16"), val = fp16(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_395_cast_fp16 = mul(x = linear_11_cast_fp16, y = var_394_to_fp16)[name = string("op_395_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_77_cast_fp16 = add(x = input_65_cast_fp16, y = var_395_cast_fp16)[name = string("input_77_cast_fp16")];
            tensor<int32, [1]> input_79_axes_0 = const()[name = string("input_79_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_0_norm_out_weight_to_fp16 = const()[name = string("module_layers_0_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(61961920)))];
            tensor<fp16, [1024]> module_layers_0_norm_out_bias_to_fp16 = const()[name = string("module_layers_0_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(61964032)))];
            tensor<fp16, [1, 188, 1024]> input_79_cast_fp16 = layer_norm(axes = input_79_axes_0, beta = module_layers_0_norm_out_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_0_norm_out_weight_to_fp16, x = input_77_cast_fp16)[name = string("input_79_cast_fp16")];
            tensor<int32, [1]> input_81_axes_0 = const()[name = string("input_81_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_1_norm_feed_forward1_weight_to_fp16 = const()[name = string("module_layers_1_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(61966144)))];
            tensor<fp16, [1024]> module_layers_1_norm_feed_forward1_bias_to_fp16 = const()[name = string("module_layers_1_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(61968256)))];
            tensor<fp16, [1, 188, 1024]> input_81_cast_fp16 = layer_norm(axes = input_81_axes_0, beta = module_layers_1_norm_feed_forward1_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_1_norm_feed_forward1_weight_to_fp16, x = input_79_cast_fp16)[name = string("input_81_cast_fp16")];
            tensor<fp16, [4096, 1024]> module_layers_1_feed_forward1_linear1_weight_to_fp16 = const()[name = string("module_layers_1_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(61970368)))];
            tensor<fp16, [1, 188, 4096]> linear_12_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = module_layers_1_feed_forward1_linear1_weight_to_fp16, x = input_81_cast_fp16)[name = string("linear_12_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_85_cast_fp16 = silu(x = linear_12_cast_fp16)[name = string("input_85_cast_fp16")];
            tensor<fp16, [1024, 4096]> module_layers_1_feed_forward1_linear2_weight_to_fp16 = const()[name = string("module_layers_1_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(70359040)))];
            tensor<fp16, [1, 188, 1024]> linear_13_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_1_feed_forward1_linear2_weight_to_fp16, x = input_85_cast_fp16)[name = string("linear_13_cast_fp16")];
            fp16 var_423_to_fp16 = const()[name = string("op_423_to_fp16"), val = fp16(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_424_cast_fp16 = mul(x = linear_13_cast_fp16, y = var_423_to_fp16)[name = string("op_424_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_91_cast_fp16 = add(x = input_79_cast_fp16, y = var_424_cast_fp16)[name = string("input_91_cast_fp16")];
            tensor<int32, [1]> query_3_axes_0 = const()[name = string("query_3_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_1_norm_self_att_weight_to_fp16 = const()[name = string("module_layers_1_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(78747712)))];
            tensor<fp16, [1024]> module_layers_1_norm_self_att_bias_to_fp16 = const()[name = string("module_layers_1_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(78749824)))];
            tensor<fp16, [1, 188, 1024]> query_3_cast_fp16 = layer_norm(axes = query_3_axes_0, beta = module_layers_1_norm_self_att_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_1_norm_self_att_weight_to_fp16, x = input_91_cast_fp16)[name = string("query_3_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_1_self_attn_linear_q_weight_to_fp16 = const()[name = string("module_layers_1_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(78751936)))];
            tensor<fp16, [1, 188, 1024]> linear_14_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_1_self_attn_linear_q_weight_to_fp16, x = query_3_cast_fp16)[name = string("linear_14_cast_fp16")];
            tensor<int32, [4]> var_440 = const()[name = string("op_440"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_7_cast_fp16 = reshape(shape = var_440, x = linear_14_cast_fp16)[name = string("q_7_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_1_self_attn_linear_k_weight_to_fp16 = const()[name = string("module_layers_1_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(80849152)))];
            tensor<fp16, [1, 188, 1024]> linear_15_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_1_self_attn_linear_k_weight_to_fp16, x = query_3_cast_fp16)[name = string("linear_15_cast_fp16")];
            tensor<int32, [4]> var_444 = const()[name = string("op_444"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_5_cast_fp16 = reshape(shape = var_444, x = linear_15_cast_fp16)[name = string("k_5_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_1_self_attn_linear_v_weight_to_fp16 = const()[name = string("module_layers_1_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(82946368)))];
            tensor<fp16, [1, 188, 1024]> linear_16_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_1_self_attn_linear_v_weight_to_fp16, x = query_3_cast_fp16)[name = string("linear_16_cast_fp16")];
            tensor<int32, [4]> var_448 = const()[name = string("op_448"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_3_cast_fp16 = reshape(shape = var_448, x = linear_16_cast_fp16)[name = string("v_3_cast_fp16")];
            tensor<int32, [4]> value_5_perm_0 = const()[name = string("value_5_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> module_layers_1_self_attn_pos_bias_u_to_fp16 = const()[name = string("module_layers_1_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(85043584)))];
            tensor<fp16, [1, 188, 8, 128]> var_460_cast_fp16 = add(x = q_7_cast_fp16, y = module_layers_1_self_attn_pos_bias_u_to_fp16)[name = string("op_460_cast_fp16")];
            tensor<fp16, [8, 128]> module_layers_1_self_attn_pos_bias_v_to_fp16 = const()[name = string("module_layers_1_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(85045696)))];
            tensor<fp16, [1, 188, 8, 128]> var_462_cast_fp16 = add(x = q_7_cast_fp16, y = module_layers_1_self_attn_pos_bias_v_to_fp16)[name = string("op_462_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_3_perm_0 = const()[name = string("q_with_bias_v_3_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            bool x_29_transpose_x_0 = const()[name = string("x_29_transpose_x_0"), val = bool(false)];
            bool x_29_transpose_y_0 = const()[name = string("x_29_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 128, 375]> var_464_to_fp16 = const()[name = string("op_464_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(85047808)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_3_cast_fp16 = transpose(perm = q_with_bias_v_3_perm_0, x = var_462_cast_fp16)[name = string("transpose_280")];
            tensor<fp16, [1, 8, 188, 375]> x_29_cast_fp16 = matmul(transpose_x = x_29_transpose_x_0, transpose_y = x_29_transpose_y_0, x = q_with_bias_v_3_cast_fp16, y = var_464_to_fp16)[name = string("x_29_cast_fp16")];
            tensor<int32, [8]> x_31_pad_0 = const()[name = string("x_31_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            string x_31_mode_0 = const()[name = string("x_31_mode_0"), val = string("constant")];
            fp16 const_24_to_fp16 = const()[name = string("const_24_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_31_cast_fp16 = pad(constant_val = const_24_to_fp16, mode = x_31_mode_0, pad = x_31_pad_0, x = x_29_cast_fp16)[name = string("x_31_cast_fp16")];
            tensor<int32, [4]> var_472 = const()[name = string("op_472"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_33_cast_fp16 = reshape(shape = var_472, x = x_31_cast_fp16)[name = string("x_33_cast_fp16")];
            tensor<int32, [4]> var_476_begin_0 = const()[name = string("op_476_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_476_end_0 = const()[name = string("op_476_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_476_end_mask_0 = const()[name = string("op_476_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_476_cast_fp16 = slice_by_index(begin = var_476_begin_0, end = var_476_end_0, end_mask = var_476_end_mask_0, x = x_33_cast_fp16)[name = string("op_476_cast_fp16")];
            tensor<int32, [4]> var_477 = const()[name = string("op_477"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_5_cast_fp16 = reshape(shape = var_477, x = var_476_cast_fp16)[name = string("matrix_bd_5_cast_fp16")];
            bool matrix_ac_3_transpose_x_0 = const()[name = string("matrix_ac_3_transpose_x_0"), val = bool(false)];
            bool matrix_ac_3_transpose_y_0 = const()[name = string("matrix_ac_3_transpose_y_0"), val = bool(false)];
            tensor<int32, [4]> transpose_74_perm_0 = const()[name = string("transpose_74_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_75_perm_0 = const()[name = string("transpose_75_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_75 = transpose(perm = transpose_75_perm_0, x = k_5_cast_fp16)[name = string("transpose_278")];
            tensor<fp16, [1, 8, 188, 128]> transpose_74 = transpose(perm = transpose_74_perm_0, x = var_460_cast_fp16)[name = string("transpose_279")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_3_cast_fp16 = matmul(transpose_x = matrix_ac_3_transpose_x_0, transpose_y = matrix_ac_3_transpose_y_0, x = transpose_74, y = transpose_75)[name = string("matrix_ac_3_cast_fp16")];
            tensor<int32, [4]> matrix_bd_7_begin_0 = const()[name = string("matrix_bd_7_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_7_end_0 = const()[name = string("matrix_bd_7_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_7_end_mask_0 = const()[name = string("matrix_bd_7_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_7_cast_fp16 = slice_by_index(begin = matrix_bd_7_begin_0, end = matrix_bd_7_end_0, end_mask = matrix_bd_7_end_mask_0, x = matrix_bd_5_cast_fp16)[name = string("matrix_bd_7_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_486_cast_fp16 = add(x = matrix_ac_3_cast_fp16, y = matrix_bd_7_cast_fp16)[name = string("op_486_cast_fp16")];
            fp16 _inversed_scores_5_y_0_to_fp16 = const()[name = string("_inversed_scores_5_y_0_to_fp16"), val = fp16(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_5_cast_fp16 = mul(x = var_486_cast_fp16, y = _inversed_scores_5_y_0_to_fp16)[name = string("_inversed_scores_5_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_7_cast_fp16 = select(a = var_10_to_fp16, b = _inversed_scores_5_cast_fp16, cond = mask_3)[name = string("scores_7_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_492_cast_fp16 = softmax(axis = var_32, x = scores_7_cast_fp16)[name = string("op_492_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_93_cast_fp16 = select(a = var_9_to_fp16, b = var_492_cast_fp16, cond = mask_3)[name = string("input_93_cast_fp16")];
            bool x_35_transpose_x_0 = const()[name = string("x_35_transpose_x_0"), val = bool(false)];
            bool x_35_transpose_y_0 = const()[name = string("x_35_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 188, 128]> value_5_cast_fp16 = transpose(perm = value_5_perm_0, x = v_3_cast_fp16)[name = string("transpose_281")];
            tensor<fp16, [1, 8, 188, 128]> x_35_cast_fp16 = matmul(transpose_x = x_35_transpose_x_0, transpose_y = x_35_transpose_y_0, x = input_93_cast_fp16, y = value_5_cast_fp16)[name = string("x_35_cast_fp16")];
            tensor<int32, [4]> var_496_perm_0 = const()[name = string("op_496_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_497 = const()[name = string("op_497"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_496_cast_fp16 = transpose(perm = var_496_perm_0, x = x_35_cast_fp16)[name = string("transpose_277")];
            tensor<fp16, [1, 188, 1024]> input_95_cast_fp16 = reshape(shape = var_497, x = var_496_cast_fp16)[name = string("input_95_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_1_self_attn_linear_out_weight_to_fp16 = const()[name = string("module_layers_1_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(85815872)))];
            tensor<fp16, [1, 188, 1024]> linear_18_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_1_self_attn_linear_out_weight_to_fp16, x = input_95_cast_fp16)[name = string("linear_18_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_99_cast_fp16 = add(x = input_91_cast_fp16, y = linear_18_cast_fp16)[name = string("input_99_cast_fp16")];
            tensor<int32, [1]> x_39_axes_0 = const()[name = string("x_39_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_1_norm_conv_weight_to_fp16 = const()[name = string("module_layers_1_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(87913088)))];
            tensor<fp16, [1024]> module_layers_1_norm_conv_bias_to_fp16 = const()[name = string("module_layers_1_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(87915200)))];
            tensor<fp16, [1, 188, 1024]> x_39_cast_fp16 = layer_norm(axes = x_39_axes_0, beta = module_layers_1_norm_conv_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_1_norm_conv_weight_to_fp16, x = input_99_cast_fp16)[name = string("x_39_cast_fp16")];
            tensor<int32, [3]> input_101_perm_0 = const()[name = string("input_101_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            string input_103_pad_type_0 = const()[name = string("input_103_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_103_strides_0 = const()[name = string("input_103_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_103_pad_0 = const()[name = string("input_103_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_103_dilations_0 = const()[name = string("input_103_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_103_groups_0 = const()[name = string("input_103_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 1024, 1]> module_layers_1_conv_pointwise_conv1_weight_to_fp16 = const()[name = string("module_layers_1_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(87917312)))];
            tensor<fp16, [1, 1024, 188]> input_101_cast_fp16 = transpose(perm = input_101_perm_0, x = x_39_cast_fp16)[name = string("transpose_276")];
            tensor<fp16, [1, 2048, 188]> input_103_cast_fp16 = conv(dilations = input_103_dilations_0, groups = input_103_groups_0, pad = input_103_pad_0, pad_type = input_103_pad_type_0, strides = input_103_strides_0, weight = module_layers_1_conv_pointwise_conv1_weight_to_fp16, x = input_101_cast_fp16)[name = string("input_103_cast_fp16")];
            int32 x_41_split_num_splits_0 = const()[name = string("x_41_split_num_splits_0"), val = int32(2)];
            int32 x_41_split_axis_0 = const()[name = string("x_41_split_axis_0"), val = int32(1)];
            tensor<fp16, [1, 1024, 188]> x_41_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_41_split_cast_fp16_1 = split(axis = x_41_split_axis_0, num_splits = x_41_split_num_splits_0, x = input_103_cast_fp16)[name = string("x_41_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_41_split_1_sigmoid_cast_fp16 = sigmoid(x = x_41_split_cast_fp16_1)[name = string("x_41_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_41_cast_fp16 = mul(x = x_41_split_cast_fp16_0, y = x_41_split_1_sigmoid_cast_fp16)[name = string("x_41_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_105_cast_fp16 = select(a = var_9_to_fp16, b = x_41_cast_fp16, cond = var_356)[name = string("input_105_cast_fp16")];
            tensor<int32, [6]> input_107_pad_0 = const()[name = string("input_107_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            string input_107_mode_0 = const()[name = string("input_107_mode_0"), val = string("constant")];
            fp16 const_27_to_fp16 = const()[name = string("const_27_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_107_cast_fp16 = pad(constant_val = const_27_to_fp16, mode = input_107_mode_0, pad = input_107_pad_0, x = input_105_cast_fp16)[name = string("input_107_cast_fp16")];
            string input_109_pad_type_0 = const()[name = string("input_109_pad_type_0"), val = string("valid")];
            int32 input_109_groups_0 = const()[name = string("input_109_groups_0"), val = int32(1024)];
            tensor<int32, [1]> input_109_strides_0 = const()[name = string("input_109_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_109_pad_0 = const()[name = string("input_109_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_109_dilations_0 = const()[name = string("input_109_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_250_to_fp16 = const()[name = string("const_250_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(92111680)))];
            tensor<fp16, [1024]> const_251_to_fp16 = const()[name = string("const_251_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(92130176)))];
            tensor<fp16, [1, 1024, 188]> input_111_cast_fp16 = conv(bias = const_251_to_fp16, dilations = input_109_dilations_0, groups = input_109_groups_0, pad = input_109_pad_0, pad_type = input_109_pad_type_0, strides = input_109_strides_0, weight = const_250_to_fp16, x = input_107_cast_fp16)[name = string("input_111_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_113_cast_fp16 = silu(x = input_111_cast_fp16)[name = string("input_113_cast_fp16")];
            string x_43_pad_type_0 = const()[name = string("x_43_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> x_43_strides_0 = const()[name = string("x_43_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_43_pad_0 = const()[name = string("x_43_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_43_dilations_0 = const()[name = string("x_43_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 x_43_groups_0 = const()[name = string("x_43_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 1024, 1]> module_layers_1_conv_pointwise_conv2_weight_to_fp16 = const()[name = string("module_layers_1_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(92132288)))];
            tensor<fp16, [1, 1024, 188]> x_43_cast_fp16 = conv(dilations = x_43_dilations_0, groups = x_43_groups_0, pad = x_43_pad_0, pad_type = x_43_pad_type_0, strides = x_43_strides_0, weight = module_layers_1_conv_pointwise_conv2_weight_to_fp16, x = input_113_cast_fp16)[name = string("x_43_cast_fp16")];
            tensor<int32, [3]> input_115_perm_0 = const()[name = string("input_115_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_115_cast_fp16 = transpose(perm = input_115_perm_0, x = x_43_cast_fp16)[name = string("transpose_275")];
            tensor<fp16, [1, 188, 1024]> input_117_cast_fp16 = add(x = input_99_cast_fp16, y = input_115_cast_fp16)[name = string("input_117_cast_fp16")];
            tensor<int32, [1]> input_119_axes_0 = const()[name = string("input_119_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_1_norm_feed_forward2_weight_to_fp16 = const()[name = string("module_layers_1_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(94229504)))];
            tensor<fp16, [1024]> module_layers_1_norm_feed_forward2_bias_to_fp16 = const()[name = string("module_layers_1_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(94231616)))];
            tensor<fp16, [1, 188, 1024]> input_119_cast_fp16 = layer_norm(axes = input_119_axes_0, beta = module_layers_1_norm_feed_forward2_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_1_norm_feed_forward2_weight_to_fp16, x = input_117_cast_fp16)[name = string("input_119_cast_fp16")];
            tensor<fp16, [4096, 1024]> module_layers_1_feed_forward2_linear1_weight_to_fp16 = const()[name = string("module_layers_1_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(94233728)))];
            tensor<fp16, [1, 188, 4096]> linear_19_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = module_layers_1_feed_forward2_linear1_weight_to_fp16, x = input_119_cast_fp16)[name = string("linear_19_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_123_cast_fp16 = silu(x = linear_19_cast_fp16)[name = string("input_123_cast_fp16")];
            tensor<fp16, [1024, 4096]> module_layers_1_feed_forward2_linear2_weight_to_fp16 = const()[name = string("module_layers_1_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(102622400)))];
            tensor<fp16, [1, 188, 1024]> linear_20_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_1_feed_forward2_linear2_weight_to_fp16, x = input_123_cast_fp16)[name = string("linear_20_cast_fp16")];
            fp16 var_557_to_fp16 = const()[name = string("op_557_to_fp16"), val = fp16(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_558_cast_fp16 = mul(x = linear_20_cast_fp16, y = var_557_to_fp16)[name = string("op_558_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_129_cast_fp16 = add(x = input_117_cast_fp16, y = var_558_cast_fp16)[name = string("input_129_cast_fp16")];
            tensor<int32, [1]> input_131_axes_0 = const()[name = string("input_131_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_1_norm_out_weight_to_fp16 = const()[name = string("module_layers_1_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(111011072)))];
            tensor<fp16, [1024]> module_layers_1_norm_out_bias_to_fp16 = const()[name = string("module_layers_1_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(111013184)))];
            tensor<fp16, [1, 188, 1024]> input_131_cast_fp16 = layer_norm(axes = input_131_axes_0, beta = module_layers_1_norm_out_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_1_norm_out_weight_to_fp16, x = input_129_cast_fp16)[name = string("input_131_cast_fp16")];
            tensor<int32, [1]> input_133_axes_0 = const()[name = string("input_133_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_2_norm_feed_forward1_weight_to_fp16 = const()[name = string("module_layers_2_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(111015296)))];
            tensor<fp16, [1024]> module_layers_2_norm_feed_forward1_bias_to_fp16 = const()[name = string("module_layers_2_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(111017408)))];
            tensor<fp16, [1, 188, 1024]> input_133_cast_fp16 = layer_norm(axes = input_133_axes_0, beta = module_layers_2_norm_feed_forward1_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_2_norm_feed_forward1_weight_to_fp16, x = input_131_cast_fp16)[name = string("input_133_cast_fp16")];
            tensor<fp16, [4096, 1024]> module_layers_2_feed_forward1_linear1_weight_to_fp16 = const()[name = string("module_layers_2_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(111019520)))];
            tensor<fp16, [1, 188, 4096]> linear_21_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = module_layers_2_feed_forward1_linear1_weight_to_fp16, x = input_133_cast_fp16)[name = string("linear_21_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_137_cast_fp16 = silu(x = linear_21_cast_fp16)[name = string("input_137_cast_fp16")];
            tensor<fp16, [1024, 4096]> module_layers_2_feed_forward1_linear2_weight_to_fp16 = const()[name = string("module_layers_2_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(119408192)))];
            tensor<fp16, [1, 188, 1024]> linear_22_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_2_feed_forward1_linear2_weight_to_fp16, x = input_137_cast_fp16)[name = string("linear_22_cast_fp16")];
            fp16 var_586_to_fp16 = const()[name = string("op_586_to_fp16"), val = fp16(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_587_cast_fp16 = mul(x = linear_22_cast_fp16, y = var_586_to_fp16)[name = string("op_587_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_143_cast_fp16 = add(x = input_131_cast_fp16, y = var_587_cast_fp16)[name = string("input_143_cast_fp16")];
            tensor<int32, [1]> query_5_axes_0 = const()[name = string("query_5_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_2_norm_self_att_weight_to_fp16 = const()[name = string("module_layers_2_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(127796864)))];
            tensor<fp16, [1024]> module_layers_2_norm_self_att_bias_to_fp16 = const()[name = string("module_layers_2_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(127798976)))];
            tensor<fp16, [1, 188, 1024]> query_5_cast_fp16 = layer_norm(axes = query_5_axes_0, beta = module_layers_2_norm_self_att_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_2_norm_self_att_weight_to_fp16, x = input_143_cast_fp16)[name = string("query_5_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_2_self_attn_linear_q_weight_to_fp16 = const()[name = string("module_layers_2_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(127801088)))];
            tensor<fp16, [1, 188, 1024]> linear_23_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_2_self_attn_linear_q_weight_to_fp16, x = query_5_cast_fp16)[name = string("linear_23_cast_fp16")];
            tensor<int32, [4]> var_603 = const()[name = string("op_603"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_13_cast_fp16 = reshape(shape = var_603, x = linear_23_cast_fp16)[name = string("q_13_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_2_self_attn_linear_k_weight_to_fp16 = const()[name = string("module_layers_2_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(129898304)))];
            tensor<fp16, [1, 188, 1024]> linear_24_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_2_self_attn_linear_k_weight_to_fp16, x = query_5_cast_fp16)[name = string("linear_24_cast_fp16")];
            tensor<int32, [4]> var_607 = const()[name = string("op_607"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_9_cast_fp16 = reshape(shape = var_607, x = linear_24_cast_fp16)[name = string("k_9_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_2_self_attn_linear_v_weight_to_fp16 = const()[name = string("module_layers_2_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(131995520)))];
            tensor<fp16, [1, 188, 1024]> linear_25_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_2_self_attn_linear_v_weight_to_fp16, x = query_5_cast_fp16)[name = string("linear_25_cast_fp16")];
            tensor<int32, [4]> var_611 = const()[name = string("op_611"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_5_cast_fp16 = reshape(shape = var_611, x = linear_25_cast_fp16)[name = string("v_5_cast_fp16")];
            tensor<int32, [4]> value_7_perm_0 = const()[name = string("value_7_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> module_layers_2_self_attn_pos_bias_u_to_fp16 = const()[name = string("module_layers_2_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(134092736)))];
            tensor<fp16, [1, 188, 8, 128]> var_623_cast_fp16 = add(x = q_13_cast_fp16, y = module_layers_2_self_attn_pos_bias_u_to_fp16)[name = string("op_623_cast_fp16")];
            tensor<fp16, [8, 128]> module_layers_2_self_attn_pos_bias_v_to_fp16 = const()[name = string("module_layers_2_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(134094848)))];
            tensor<fp16, [1, 188, 8, 128]> var_625_cast_fp16 = add(x = q_13_cast_fp16, y = module_layers_2_self_attn_pos_bias_v_to_fp16)[name = string("op_625_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_5_perm_0 = const()[name = string("q_with_bias_v_5_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            bool x_51_transpose_x_0 = const()[name = string("x_51_transpose_x_0"), val = bool(false)];
            bool x_51_transpose_y_0 = const()[name = string("x_51_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 128, 375]> var_627_to_fp16 = const()[name = string("op_627_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(134096960)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_5_cast_fp16 = transpose(perm = q_with_bias_v_5_perm_0, x = var_625_cast_fp16)[name = string("transpose_273")];
            tensor<fp16, [1, 8, 188, 375]> x_51_cast_fp16 = matmul(transpose_x = x_51_transpose_x_0, transpose_y = x_51_transpose_y_0, x = q_with_bias_v_5_cast_fp16, y = var_627_to_fp16)[name = string("x_51_cast_fp16")];
            tensor<int32, [8]> x_53_pad_0 = const()[name = string("x_53_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            string x_53_mode_0 = const()[name = string("x_53_mode_0"), val = string("constant")];
            fp16 const_34_to_fp16 = const()[name = string("const_34_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_53_cast_fp16 = pad(constant_val = const_34_to_fp16, mode = x_53_mode_0, pad = x_53_pad_0, x = x_51_cast_fp16)[name = string("x_53_cast_fp16")];
            tensor<int32, [4]> var_635 = const()[name = string("op_635"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_55_cast_fp16 = reshape(shape = var_635, x = x_53_cast_fp16)[name = string("x_55_cast_fp16")];
            tensor<int32, [4]> var_639_begin_0 = const()[name = string("op_639_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_639_end_0 = const()[name = string("op_639_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_639_end_mask_0 = const()[name = string("op_639_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_639_cast_fp16 = slice_by_index(begin = var_639_begin_0, end = var_639_end_0, end_mask = var_639_end_mask_0, x = x_55_cast_fp16)[name = string("op_639_cast_fp16")];
            tensor<int32, [4]> var_640 = const()[name = string("op_640"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_9_cast_fp16 = reshape(shape = var_640, x = var_639_cast_fp16)[name = string("matrix_bd_9_cast_fp16")];
            bool matrix_ac_5_transpose_x_0 = const()[name = string("matrix_ac_5_transpose_x_0"), val = bool(false)];
            bool matrix_ac_5_transpose_y_0 = const()[name = string("matrix_ac_5_transpose_y_0"), val = bool(false)];
            tensor<int32, [4]> transpose_76_perm_0 = const()[name = string("transpose_76_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_77_perm_0 = const()[name = string("transpose_77_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_77 = transpose(perm = transpose_77_perm_0, x = k_9_cast_fp16)[name = string("transpose_271")];
            tensor<fp16, [1, 8, 188, 128]> transpose_76 = transpose(perm = transpose_76_perm_0, x = var_623_cast_fp16)[name = string("transpose_272")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_5_cast_fp16 = matmul(transpose_x = matrix_ac_5_transpose_x_0, transpose_y = matrix_ac_5_transpose_y_0, x = transpose_76, y = transpose_77)[name = string("matrix_ac_5_cast_fp16")];
            tensor<int32, [4]> matrix_bd_11_begin_0 = const()[name = string("matrix_bd_11_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_11_end_0 = const()[name = string("matrix_bd_11_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_11_end_mask_0 = const()[name = string("matrix_bd_11_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_11_cast_fp16 = slice_by_index(begin = matrix_bd_11_begin_0, end = matrix_bd_11_end_0, end_mask = matrix_bd_11_end_mask_0, x = matrix_bd_9_cast_fp16)[name = string("matrix_bd_11_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_649_cast_fp16 = add(x = matrix_ac_5_cast_fp16, y = matrix_bd_11_cast_fp16)[name = string("op_649_cast_fp16")];
            fp16 _inversed_scores_9_y_0_to_fp16 = const()[name = string("_inversed_scores_9_y_0_to_fp16"), val = fp16(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_9_cast_fp16 = mul(x = var_649_cast_fp16, y = _inversed_scores_9_y_0_to_fp16)[name = string("_inversed_scores_9_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_11_cast_fp16 = select(a = var_10_to_fp16, b = _inversed_scores_9_cast_fp16, cond = mask_3)[name = string("scores_11_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_655_cast_fp16 = softmax(axis = var_32, x = scores_11_cast_fp16)[name = string("op_655_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_145_cast_fp16 = select(a = var_9_to_fp16, b = var_655_cast_fp16, cond = mask_3)[name = string("input_145_cast_fp16")];
            bool x_57_transpose_x_0 = const()[name = string("x_57_transpose_x_0"), val = bool(false)];
            bool x_57_transpose_y_0 = const()[name = string("x_57_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 188, 128]> value_7_cast_fp16 = transpose(perm = value_7_perm_0, x = v_5_cast_fp16)[name = string("transpose_274")];
            tensor<fp16, [1, 8, 188, 128]> x_57_cast_fp16 = matmul(transpose_x = x_57_transpose_x_0, transpose_y = x_57_transpose_y_0, x = input_145_cast_fp16, y = value_7_cast_fp16)[name = string("x_57_cast_fp16")];
            tensor<int32, [4]> var_659_perm_0 = const()[name = string("op_659_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_660 = const()[name = string("op_660"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_659_cast_fp16 = transpose(perm = var_659_perm_0, x = x_57_cast_fp16)[name = string("transpose_270")];
            tensor<fp16, [1, 188, 1024]> input_147_cast_fp16 = reshape(shape = var_660, x = var_659_cast_fp16)[name = string("input_147_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_2_self_attn_linear_out_weight_to_fp16 = const()[name = string("module_layers_2_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(134865024)))];
            tensor<fp16, [1, 188, 1024]> linear_27_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_2_self_attn_linear_out_weight_to_fp16, x = input_147_cast_fp16)[name = string("linear_27_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_151_cast_fp16 = add(x = input_143_cast_fp16, y = linear_27_cast_fp16)[name = string("input_151_cast_fp16")];
            tensor<int32, [1]> x_61_axes_0 = const()[name = string("x_61_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_2_norm_conv_weight_to_fp16 = const()[name = string("module_layers_2_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(136962240)))];
            tensor<fp16, [1024]> module_layers_2_norm_conv_bias_to_fp16 = const()[name = string("module_layers_2_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(136964352)))];
            tensor<fp16, [1, 188, 1024]> x_61_cast_fp16 = layer_norm(axes = x_61_axes_0, beta = module_layers_2_norm_conv_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_2_norm_conv_weight_to_fp16, x = input_151_cast_fp16)[name = string("x_61_cast_fp16")];
            tensor<int32, [3]> input_153_perm_0 = const()[name = string("input_153_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            string input_155_pad_type_0 = const()[name = string("input_155_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_155_strides_0 = const()[name = string("input_155_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_155_pad_0 = const()[name = string("input_155_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_155_dilations_0 = const()[name = string("input_155_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_155_groups_0 = const()[name = string("input_155_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 1024, 1]> module_layers_2_conv_pointwise_conv1_weight_to_fp16 = const()[name = string("module_layers_2_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(136966464)))];
            tensor<fp16, [1, 1024, 188]> input_153_cast_fp16 = transpose(perm = input_153_perm_0, x = x_61_cast_fp16)[name = string("transpose_269")];
            tensor<fp16, [1, 2048, 188]> input_155_cast_fp16 = conv(dilations = input_155_dilations_0, groups = input_155_groups_0, pad = input_155_pad_0, pad_type = input_155_pad_type_0, strides = input_155_strides_0, weight = module_layers_2_conv_pointwise_conv1_weight_to_fp16, x = input_153_cast_fp16)[name = string("input_155_cast_fp16")];
            int32 x_63_split_num_splits_0 = const()[name = string("x_63_split_num_splits_0"), val = int32(2)];
            int32 x_63_split_axis_0 = const()[name = string("x_63_split_axis_0"), val = int32(1)];
            tensor<fp16, [1, 1024, 188]> x_63_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_63_split_cast_fp16_1 = split(axis = x_63_split_axis_0, num_splits = x_63_split_num_splits_0, x = input_155_cast_fp16)[name = string("x_63_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_63_split_1_sigmoid_cast_fp16 = sigmoid(x = x_63_split_cast_fp16_1)[name = string("x_63_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_63_cast_fp16 = mul(x = x_63_split_cast_fp16_0, y = x_63_split_1_sigmoid_cast_fp16)[name = string("x_63_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_157_cast_fp16 = select(a = var_9_to_fp16, b = x_63_cast_fp16, cond = var_356)[name = string("input_157_cast_fp16")];
            tensor<int32, [6]> input_159_pad_0 = const()[name = string("input_159_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            string input_159_mode_0 = const()[name = string("input_159_mode_0"), val = string("constant")];
            fp16 const_37_to_fp16 = const()[name = string("const_37_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_159_cast_fp16 = pad(constant_val = const_37_to_fp16, mode = input_159_mode_0, pad = input_159_pad_0, x = input_157_cast_fp16)[name = string("input_159_cast_fp16")];
            string input_161_pad_type_0 = const()[name = string("input_161_pad_type_0"), val = string("valid")];
            int32 input_161_groups_0 = const()[name = string("input_161_groups_0"), val = int32(1024)];
            tensor<int32, [1]> input_161_strides_0 = const()[name = string("input_161_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_161_pad_0 = const()[name = string("input_161_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_161_dilations_0 = const()[name = string("input_161_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_252_to_fp16 = const()[name = string("const_252_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(141160832)))];
            tensor<fp16, [1024]> const_253_to_fp16 = const()[name = string("const_253_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(141179328)))];
            tensor<fp16, [1, 1024, 188]> input_163_cast_fp16 = conv(bias = const_253_to_fp16, dilations = input_161_dilations_0, groups = input_161_groups_0, pad = input_161_pad_0, pad_type = input_161_pad_type_0, strides = input_161_strides_0, weight = const_252_to_fp16, x = input_159_cast_fp16)[name = string("input_163_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_165_cast_fp16 = silu(x = input_163_cast_fp16)[name = string("input_165_cast_fp16")];
            string x_65_pad_type_0 = const()[name = string("x_65_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> x_65_strides_0 = const()[name = string("x_65_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_65_pad_0 = const()[name = string("x_65_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_65_dilations_0 = const()[name = string("x_65_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 x_65_groups_0 = const()[name = string("x_65_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 1024, 1]> module_layers_2_conv_pointwise_conv2_weight_to_fp16 = const()[name = string("module_layers_2_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(141181440)))];
            tensor<fp16, [1, 1024, 188]> x_65_cast_fp16 = conv(dilations = x_65_dilations_0, groups = x_65_groups_0, pad = x_65_pad_0, pad_type = x_65_pad_type_0, strides = x_65_strides_0, weight = module_layers_2_conv_pointwise_conv2_weight_to_fp16, x = input_165_cast_fp16)[name = string("x_65_cast_fp16")];
            tensor<int32, [3]> input_167_perm_0 = const()[name = string("input_167_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_167_cast_fp16 = transpose(perm = input_167_perm_0, x = x_65_cast_fp16)[name = string("transpose_268")];
            tensor<fp16, [1, 188, 1024]> input_169_cast_fp16 = add(x = input_151_cast_fp16, y = input_167_cast_fp16)[name = string("input_169_cast_fp16")];
            tensor<int32, [1]> input_171_axes_0 = const()[name = string("input_171_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_2_norm_feed_forward2_weight_to_fp16 = const()[name = string("module_layers_2_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(143278656)))];
            tensor<fp16, [1024]> module_layers_2_norm_feed_forward2_bias_to_fp16 = const()[name = string("module_layers_2_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(143280768)))];
            tensor<fp16, [1, 188, 1024]> input_171_cast_fp16 = layer_norm(axes = input_171_axes_0, beta = module_layers_2_norm_feed_forward2_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_2_norm_feed_forward2_weight_to_fp16, x = input_169_cast_fp16)[name = string("input_171_cast_fp16")];
            tensor<fp16, [4096, 1024]> module_layers_2_feed_forward2_linear1_weight_to_fp16 = const()[name = string("module_layers_2_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(143282880)))];
            tensor<fp16, [1, 188, 4096]> linear_28_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = module_layers_2_feed_forward2_linear1_weight_to_fp16, x = input_171_cast_fp16)[name = string("linear_28_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_175_cast_fp16 = silu(x = linear_28_cast_fp16)[name = string("input_175_cast_fp16")];
            tensor<fp16, [1024, 4096]> module_layers_2_feed_forward2_linear2_weight_to_fp16 = const()[name = string("module_layers_2_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(151671552)))];
            tensor<fp16, [1, 188, 1024]> linear_29_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_2_feed_forward2_linear2_weight_to_fp16, x = input_175_cast_fp16)[name = string("linear_29_cast_fp16")];
            fp16 var_720_to_fp16 = const()[name = string("op_720_to_fp16"), val = fp16(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_721_cast_fp16 = mul(x = linear_29_cast_fp16, y = var_720_to_fp16)[name = string("op_721_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_181_cast_fp16 = add(x = input_169_cast_fp16, y = var_721_cast_fp16)[name = string("input_181_cast_fp16")];
            tensor<int32, [1]> input_183_axes_0 = const()[name = string("input_183_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_2_norm_out_weight_to_fp16 = const()[name = string("module_layers_2_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(160060224)))];
            tensor<fp16, [1024]> module_layers_2_norm_out_bias_to_fp16 = const()[name = string("module_layers_2_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(160062336)))];
            tensor<fp16, [1, 188, 1024]> input_183_cast_fp16 = layer_norm(axes = input_183_axes_0, beta = module_layers_2_norm_out_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_2_norm_out_weight_to_fp16, x = input_181_cast_fp16)[name = string("input_183_cast_fp16")];
            tensor<int32, [1]> input_185_axes_0 = const()[name = string("input_185_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_3_norm_feed_forward1_weight_to_fp16 = const()[name = string("module_layers_3_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(160064448)))];
            tensor<fp16, [1024]> module_layers_3_norm_feed_forward1_bias_to_fp16 = const()[name = string("module_layers_3_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(160066560)))];
            tensor<fp16, [1, 188, 1024]> input_185_cast_fp16 = layer_norm(axes = input_185_axes_0, beta = module_layers_3_norm_feed_forward1_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_3_norm_feed_forward1_weight_to_fp16, x = input_183_cast_fp16)[name = string("input_185_cast_fp16")];
            tensor<fp16, [4096, 1024]> module_layers_3_feed_forward1_linear1_weight_to_fp16 = const()[name = string("module_layers_3_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(160068672)))];
            tensor<fp16, [1, 188, 4096]> linear_30_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = module_layers_3_feed_forward1_linear1_weight_to_fp16, x = input_185_cast_fp16)[name = string("linear_30_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_189_cast_fp16 = silu(x = linear_30_cast_fp16)[name = string("input_189_cast_fp16")];
            tensor<fp16, [1024, 4096]> module_layers_3_feed_forward1_linear2_weight_to_fp16 = const()[name = string("module_layers_3_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(168457344)))];
            tensor<fp16, [1, 188, 1024]> linear_31_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_3_feed_forward1_linear2_weight_to_fp16, x = input_189_cast_fp16)[name = string("linear_31_cast_fp16")];
            fp16 var_749_to_fp16 = const()[name = string("op_749_to_fp16"), val = fp16(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_750_cast_fp16 = mul(x = linear_31_cast_fp16, y = var_749_to_fp16)[name = string("op_750_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_195_cast_fp16 = add(x = input_183_cast_fp16, y = var_750_cast_fp16)[name = string("input_195_cast_fp16")];
            tensor<int32, [1]> query_7_axes_0 = const()[name = string("query_7_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_3_norm_self_att_weight_to_fp16 = const()[name = string("module_layers_3_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(176846016)))];
            tensor<fp16, [1024]> module_layers_3_norm_self_att_bias_to_fp16 = const()[name = string("module_layers_3_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(176848128)))];
            tensor<fp16, [1, 188, 1024]> query_7_cast_fp16 = layer_norm(axes = query_7_axes_0, beta = module_layers_3_norm_self_att_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_3_norm_self_att_weight_to_fp16, x = input_195_cast_fp16)[name = string("query_7_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_3_self_attn_linear_q_weight_to_fp16 = const()[name = string("module_layers_3_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(176850240)))];
            tensor<fp16, [1, 188, 1024]> linear_32_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_3_self_attn_linear_q_weight_to_fp16, x = query_7_cast_fp16)[name = string("linear_32_cast_fp16")];
            tensor<int32, [4]> var_766 = const()[name = string("op_766"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_19_cast_fp16 = reshape(shape = var_766, x = linear_32_cast_fp16)[name = string("q_19_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_3_self_attn_linear_k_weight_to_fp16 = const()[name = string("module_layers_3_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(178947456)))];
            tensor<fp16, [1, 188, 1024]> linear_33_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_3_self_attn_linear_k_weight_to_fp16, x = query_7_cast_fp16)[name = string("linear_33_cast_fp16")];
            tensor<int32, [4]> var_770 = const()[name = string("op_770"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_13_cast_fp16 = reshape(shape = var_770, x = linear_33_cast_fp16)[name = string("k_13_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_3_self_attn_linear_v_weight_to_fp16 = const()[name = string("module_layers_3_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(181044672)))];
            tensor<fp16, [1, 188, 1024]> linear_34_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_3_self_attn_linear_v_weight_to_fp16, x = query_7_cast_fp16)[name = string("linear_34_cast_fp16")];
            tensor<int32, [4]> var_774 = const()[name = string("op_774"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_7_cast_fp16 = reshape(shape = var_774, x = linear_34_cast_fp16)[name = string("v_7_cast_fp16")];
            tensor<int32, [4]> value_9_perm_0 = const()[name = string("value_9_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> module_layers_3_self_attn_pos_bias_u_to_fp16 = const()[name = string("module_layers_3_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(183141888)))];
            tensor<fp16, [1, 188, 8, 128]> var_786_cast_fp16 = add(x = q_19_cast_fp16, y = module_layers_3_self_attn_pos_bias_u_to_fp16)[name = string("op_786_cast_fp16")];
            tensor<fp16, [8, 128]> module_layers_3_self_attn_pos_bias_v_to_fp16 = const()[name = string("module_layers_3_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(183144000)))];
            tensor<fp16, [1, 188, 8, 128]> var_788_cast_fp16 = add(x = q_19_cast_fp16, y = module_layers_3_self_attn_pos_bias_v_to_fp16)[name = string("op_788_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_7_perm_0 = const()[name = string("q_with_bias_v_7_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            bool x_73_transpose_x_0 = const()[name = string("x_73_transpose_x_0"), val = bool(false)];
            bool x_73_transpose_y_0 = const()[name = string("x_73_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 128, 375]> var_790_to_fp16 = const()[name = string("op_790_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(183146112)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_7_cast_fp16 = transpose(perm = q_with_bias_v_7_perm_0, x = var_788_cast_fp16)[name = string("transpose_266")];
            tensor<fp16, [1, 8, 188, 375]> x_73_cast_fp16 = matmul(transpose_x = x_73_transpose_x_0, transpose_y = x_73_transpose_y_0, x = q_with_bias_v_7_cast_fp16, y = var_790_to_fp16)[name = string("x_73_cast_fp16")];
            tensor<int32, [8]> x_75_pad_0 = const()[name = string("x_75_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            string x_75_mode_0 = const()[name = string("x_75_mode_0"), val = string("constant")];
            fp16 const_44_to_fp16 = const()[name = string("const_44_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_75_cast_fp16 = pad(constant_val = const_44_to_fp16, mode = x_75_mode_0, pad = x_75_pad_0, x = x_73_cast_fp16)[name = string("x_75_cast_fp16")];
            tensor<int32, [4]> var_798 = const()[name = string("op_798"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_77_cast_fp16 = reshape(shape = var_798, x = x_75_cast_fp16)[name = string("x_77_cast_fp16")];
            tensor<int32, [4]> var_802_begin_0 = const()[name = string("op_802_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_802_end_0 = const()[name = string("op_802_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_802_end_mask_0 = const()[name = string("op_802_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_802_cast_fp16 = slice_by_index(begin = var_802_begin_0, end = var_802_end_0, end_mask = var_802_end_mask_0, x = x_77_cast_fp16)[name = string("op_802_cast_fp16")];
            tensor<int32, [4]> var_803 = const()[name = string("op_803"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_13_cast_fp16 = reshape(shape = var_803, x = var_802_cast_fp16)[name = string("matrix_bd_13_cast_fp16")];
            bool matrix_ac_7_transpose_x_0 = const()[name = string("matrix_ac_7_transpose_x_0"), val = bool(false)];
            bool matrix_ac_7_transpose_y_0 = const()[name = string("matrix_ac_7_transpose_y_0"), val = bool(false)];
            tensor<int32, [4]> transpose_78_perm_0 = const()[name = string("transpose_78_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_79_perm_0 = const()[name = string("transpose_79_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_79 = transpose(perm = transpose_79_perm_0, x = k_13_cast_fp16)[name = string("transpose_264")];
            tensor<fp16, [1, 8, 188, 128]> transpose_78 = transpose(perm = transpose_78_perm_0, x = var_786_cast_fp16)[name = string("transpose_265")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_7_cast_fp16 = matmul(transpose_x = matrix_ac_7_transpose_x_0, transpose_y = matrix_ac_7_transpose_y_0, x = transpose_78, y = transpose_79)[name = string("matrix_ac_7_cast_fp16")];
            tensor<int32, [4]> matrix_bd_15_begin_0 = const()[name = string("matrix_bd_15_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_15_end_0 = const()[name = string("matrix_bd_15_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_15_end_mask_0 = const()[name = string("matrix_bd_15_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_15_cast_fp16 = slice_by_index(begin = matrix_bd_15_begin_0, end = matrix_bd_15_end_0, end_mask = matrix_bd_15_end_mask_0, x = matrix_bd_13_cast_fp16)[name = string("matrix_bd_15_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_812_cast_fp16 = add(x = matrix_ac_7_cast_fp16, y = matrix_bd_15_cast_fp16)[name = string("op_812_cast_fp16")];
            fp16 _inversed_scores_13_y_0_to_fp16 = const()[name = string("_inversed_scores_13_y_0_to_fp16"), val = fp16(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_13_cast_fp16 = mul(x = var_812_cast_fp16, y = _inversed_scores_13_y_0_to_fp16)[name = string("_inversed_scores_13_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_15_cast_fp16 = select(a = var_10_to_fp16, b = _inversed_scores_13_cast_fp16, cond = mask_3)[name = string("scores_15_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_818_cast_fp16 = softmax(axis = var_32, x = scores_15_cast_fp16)[name = string("op_818_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_197_cast_fp16 = select(a = var_9_to_fp16, b = var_818_cast_fp16, cond = mask_3)[name = string("input_197_cast_fp16")];
            bool x_79_transpose_x_0 = const()[name = string("x_79_transpose_x_0"), val = bool(false)];
            bool x_79_transpose_y_0 = const()[name = string("x_79_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 188, 128]> value_9_cast_fp16 = transpose(perm = value_9_perm_0, x = v_7_cast_fp16)[name = string("transpose_267")];
            tensor<fp16, [1, 8, 188, 128]> x_79_cast_fp16 = matmul(transpose_x = x_79_transpose_x_0, transpose_y = x_79_transpose_y_0, x = input_197_cast_fp16, y = value_9_cast_fp16)[name = string("x_79_cast_fp16")];
            tensor<int32, [4]> var_822_perm_0 = const()[name = string("op_822_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_823 = const()[name = string("op_823"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_822_cast_fp16 = transpose(perm = var_822_perm_0, x = x_79_cast_fp16)[name = string("transpose_263")];
            tensor<fp16, [1, 188, 1024]> input_199_cast_fp16 = reshape(shape = var_823, x = var_822_cast_fp16)[name = string("input_199_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_3_self_attn_linear_out_weight_to_fp16 = const()[name = string("module_layers_3_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(183914176)))];
            tensor<fp16, [1, 188, 1024]> linear_36_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_3_self_attn_linear_out_weight_to_fp16, x = input_199_cast_fp16)[name = string("linear_36_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_203_cast_fp16 = add(x = input_195_cast_fp16, y = linear_36_cast_fp16)[name = string("input_203_cast_fp16")];
            tensor<int32, [1]> x_83_axes_0 = const()[name = string("x_83_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_3_norm_conv_weight_to_fp16 = const()[name = string("module_layers_3_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(186011392)))];
            tensor<fp16, [1024]> module_layers_3_norm_conv_bias_to_fp16 = const()[name = string("module_layers_3_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(186013504)))];
            tensor<fp16, [1, 188, 1024]> x_83_cast_fp16 = layer_norm(axes = x_83_axes_0, beta = module_layers_3_norm_conv_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_3_norm_conv_weight_to_fp16, x = input_203_cast_fp16)[name = string("x_83_cast_fp16")];
            tensor<int32, [3]> input_205_perm_0 = const()[name = string("input_205_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            string input_207_pad_type_0 = const()[name = string("input_207_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_207_strides_0 = const()[name = string("input_207_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_207_pad_0 = const()[name = string("input_207_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_207_dilations_0 = const()[name = string("input_207_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_207_groups_0 = const()[name = string("input_207_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 1024, 1]> module_layers_3_conv_pointwise_conv1_weight_to_fp16 = const()[name = string("module_layers_3_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(186015616)))];
            tensor<fp16, [1, 1024, 188]> input_205_cast_fp16 = transpose(perm = input_205_perm_0, x = x_83_cast_fp16)[name = string("transpose_262")];
            tensor<fp16, [1, 2048, 188]> input_207_cast_fp16 = conv(dilations = input_207_dilations_0, groups = input_207_groups_0, pad = input_207_pad_0, pad_type = input_207_pad_type_0, strides = input_207_strides_0, weight = module_layers_3_conv_pointwise_conv1_weight_to_fp16, x = input_205_cast_fp16)[name = string("input_207_cast_fp16")];
            int32 x_85_split_num_splits_0 = const()[name = string("x_85_split_num_splits_0"), val = int32(2)];
            int32 x_85_split_axis_0 = const()[name = string("x_85_split_axis_0"), val = int32(1)];
            tensor<fp16, [1, 1024, 188]> x_85_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_85_split_cast_fp16_1 = split(axis = x_85_split_axis_0, num_splits = x_85_split_num_splits_0, x = input_207_cast_fp16)[name = string("x_85_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_85_split_1_sigmoid_cast_fp16 = sigmoid(x = x_85_split_cast_fp16_1)[name = string("x_85_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_85_cast_fp16 = mul(x = x_85_split_cast_fp16_0, y = x_85_split_1_sigmoid_cast_fp16)[name = string("x_85_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_209_cast_fp16 = select(a = var_9_to_fp16, b = x_85_cast_fp16, cond = var_356)[name = string("input_209_cast_fp16")];
            tensor<int32, [6]> input_211_pad_0 = const()[name = string("input_211_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            string input_211_mode_0 = const()[name = string("input_211_mode_0"), val = string("constant")];
            fp16 const_47_to_fp16 = const()[name = string("const_47_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_211_cast_fp16 = pad(constant_val = const_47_to_fp16, mode = input_211_mode_0, pad = input_211_pad_0, x = input_209_cast_fp16)[name = string("input_211_cast_fp16")];
            string input_213_pad_type_0 = const()[name = string("input_213_pad_type_0"), val = string("valid")];
            int32 input_213_groups_0 = const()[name = string("input_213_groups_0"), val = int32(1024)];
            tensor<int32, [1]> input_213_strides_0 = const()[name = string("input_213_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_213_pad_0 = const()[name = string("input_213_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_213_dilations_0 = const()[name = string("input_213_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_254_to_fp16 = const()[name = string("const_254_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(190209984)))];
            tensor<fp16, [1024]> const_255_to_fp16 = const()[name = string("const_255_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(190228480)))];
            tensor<fp16, [1, 1024, 188]> input_215_cast_fp16 = conv(bias = const_255_to_fp16, dilations = input_213_dilations_0, groups = input_213_groups_0, pad = input_213_pad_0, pad_type = input_213_pad_type_0, strides = input_213_strides_0, weight = const_254_to_fp16, x = input_211_cast_fp16)[name = string("input_215_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_217_cast_fp16 = silu(x = input_215_cast_fp16)[name = string("input_217_cast_fp16")];
            string x_87_pad_type_0 = const()[name = string("x_87_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> x_87_strides_0 = const()[name = string("x_87_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_87_pad_0 = const()[name = string("x_87_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_87_dilations_0 = const()[name = string("x_87_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 x_87_groups_0 = const()[name = string("x_87_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 1024, 1]> module_layers_3_conv_pointwise_conv2_weight_to_fp16 = const()[name = string("module_layers_3_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(190230592)))];
            tensor<fp16, [1, 1024, 188]> x_87_cast_fp16 = conv(dilations = x_87_dilations_0, groups = x_87_groups_0, pad = x_87_pad_0, pad_type = x_87_pad_type_0, strides = x_87_strides_0, weight = module_layers_3_conv_pointwise_conv2_weight_to_fp16, x = input_217_cast_fp16)[name = string("x_87_cast_fp16")];
            tensor<int32, [3]> input_219_perm_0 = const()[name = string("input_219_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_219_cast_fp16 = transpose(perm = input_219_perm_0, x = x_87_cast_fp16)[name = string("transpose_261")];
            tensor<fp16, [1, 188, 1024]> input_221_cast_fp16 = add(x = input_203_cast_fp16, y = input_219_cast_fp16)[name = string("input_221_cast_fp16")];
            tensor<int32, [1]> input_223_axes_0 = const()[name = string("input_223_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_3_norm_feed_forward2_weight_to_fp16 = const()[name = string("module_layers_3_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(192327808)))];
            tensor<fp16, [1024]> module_layers_3_norm_feed_forward2_bias_to_fp16 = const()[name = string("module_layers_3_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(192329920)))];
            tensor<fp16, [1, 188, 1024]> input_223_cast_fp16 = layer_norm(axes = input_223_axes_0, beta = module_layers_3_norm_feed_forward2_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_3_norm_feed_forward2_weight_to_fp16, x = input_221_cast_fp16)[name = string("input_223_cast_fp16")];
            tensor<fp16, [4096, 1024]> module_layers_3_feed_forward2_linear1_weight_to_fp16 = const()[name = string("module_layers_3_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(192332032)))];
            tensor<fp16, [1, 188, 4096]> linear_37_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = module_layers_3_feed_forward2_linear1_weight_to_fp16, x = input_223_cast_fp16)[name = string("linear_37_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_227_cast_fp16 = silu(x = linear_37_cast_fp16)[name = string("input_227_cast_fp16")];
            tensor<fp16, [1024, 4096]> module_layers_3_feed_forward2_linear2_weight_to_fp16 = const()[name = string("module_layers_3_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(200720704)))];
            tensor<fp16, [1, 188, 1024]> linear_38_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_3_feed_forward2_linear2_weight_to_fp16, x = input_227_cast_fp16)[name = string("linear_38_cast_fp16")];
            fp16 var_883_to_fp16 = const()[name = string("op_883_to_fp16"), val = fp16(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_884_cast_fp16 = mul(x = linear_38_cast_fp16, y = var_883_to_fp16)[name = string("op_884_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_233_cast_fp16 = add(x = input_221_cast_fp16, y = var_884_cast_fp16)[name = string("input_233_cast_fp16")];
            tensor<int32, [1]> input_235_axes_0 = const()[name = string("input_235_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_3_norm_out_weight_to_fp16 = const()[name = string("module_layers_3_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(209109376)))];
            tensor<fp16, [1024]> module_layers_3_norm_out_bias_to_fp16 = const()[name = string("module_layers_3_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(209111488)))];
            tensor<fp16, [1, 188, 1024]> input_235_cast_fp16 = layer_norm(axes = input_235_axes_0, beta = module_layers_3_norm_out_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_3_norm_out_weight_to_fp16, x = input_233_cast_fp16)[name = string("input_235_cast_fp16")];
            tensor<int32, [1]> input_237_axes_0 = const()[name = string("input_237_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_4_norm_feed_forward1_weight_to_fp16 = const()[name = string("module_layers_4_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(209113600)))];
            tensor<fp16, [1024]> module_layers_4_norm_feed_forward1_bias_to_fp16 = const()[name = string("module_layers_4_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(209115712)))];
            tensor<fp16, [1, 188, 1024]> input_237_cast_fp16 = layer_norm(axes = input_237_axes_0, beta = module_layers_4_norm_feed_forward1_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_4_norm_feed_forward1_weight_to_fp16, x = input_235_cast_fp16)[name = string("input_237_cast_fp16")];
            tensor<fp16, [4096, 1024]> module_layers_4_feed_forward1_linear1_weight_to_fp16 = const()[name = string("module_layers_4_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(209117824)))];
            tensor<fp16, [1, 188, 4096]> linear_39_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = module_layers_4_feed_forward1_linear1_weight_to_fp16, x = input_237_cast_fp16)[name = string("linear_39_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_241_cast_fp16 = silu(x = linear_39_cast_fp16)[name = string("input_241_cast_fp16")];
            tensor<fp16, [1024, 4096]> module_layers_4_feed_forward1_linear2_weight_to_fp16 = const()[name = string("module_layers_4_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(217506496)))];
            tensor<fp16, [1, 188, 1024]> linear_40_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_4_feed_forward1_linear2_weight_to_fp16, x = input_241_cast_fp16)[name = string("linear_40_cast_fp16")];
            fp16 var_912_to_fp16 = const()[name = string("op_912_to_fp16"), val = fp16(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_913_cast_fp16 = mul(x = linear_40_cast_fp16, y = var_912_to_fp16)[name = string("op_913_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_247_cast_fp16 = add(x = input_235_cast_fp16, y = var_913_cast_fp16)[name = string("input_247_cast_fp16")];
            tensor<int32, [1]> query_9_axes_0 = const()[name = string("query_9_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_4_norm_self_att_weight_to_fp16 = const()[name = string("module_layers_4_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(225895168)))];
            tensor<fp16, [1024]> module_layers_4_norm_self_att_bias_to_fp16 = const()[name = string("module_layers_4_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(225897280)))];
            tensor<fp16, [1, 188, 1024]> query_9_cast_fp16 = layer_norm(axes = query_9_axes_0, beta = module_layers_4_norm_self_att_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_4_norm_self_att_weight_to_fp16, x = input_247_cast_fp16)[name = string("query_9_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_4_self_attn_linear_q_weight_to_fp16 = const()[name = string("module_layers_4_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(225899392)))];
            tensor<fp16, [1, 188, 1024]> linear_41_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_4_self_attn_linear_q_weight_to_fp16, x = query_9_cast_fp16)[name = string("linear_41_cast_fp16")];
            tensor<int32, [4]> var_929 = const()[name = string("op_929"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_25_cast_fp16 = reshape(shape = var_929, x = linear_41_cast_fp16)[name = string("q_25_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_4_self_attn_linear_k_weight_to_fp16 = const()[name = string("module_layers_4_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(227996608)))];
            tensor<fp16, [1, 188, 1024]> linear_42_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_4_self_attn_linear_k_weight_to_fp16, x = query_9_cast_fp16)[name = string("linear_42_cast_fp16")];
            tensor<int32, [4]> var_933 = const()[name = string("op_933"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_17_cast_fp16 = reshape(shape = var_933, x = linear_42_cast_fp16)[name = string("k_17_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_4_self_attn_linear_v_weight_to_fp16 = const()[name = string("module_layers_4_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(230093824)))];
            tensor<fp16, [1, 188, 1024]> linear_43_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_4_self_attn_linear_v_weight_to_fp16, x = query_9_cast_fp16)[name = string("linear_43_cast_fp16")];
            tensor<int32, [4]> var_937 = const()[name = string("op_937"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_9_cast_fp16 = reshape(shape = var_937, x = linear_43_cast_fp16)[name = string("v_9_cast_fp16")];
            tensor<int32, [4]> value_11_perm_0 = const()[name = string("value_11_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> module_layers_4_self_attn_pos_bias_u_to_fp16 = const()[name = string("module_layers_4_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(232191040)))];
            tensor<fp16, [1, 188, 8, 128]> var_949_cast_fp16 = add(x = q_25_cast_fp16, y = module_layers_4_self_attn_pos_bias_u_to_fp16)[name = string("op_949_cast_fp16")];
            tensor<fp16, [8, 128]> module_layers_4_self_attn_pos_bias_v_to_fp16 = const()[name = string("module_layers_4_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(232193152)))];
            tensor<fp16, [1, 188, 8, 128]> var_951_cast_fp16 = add(x = q_25_cast_fp16, y = module_layers_4_self_attn_pos_bias_v_to_fp16)[name = string("op_951_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_9_perm_0 = const()[name = string("q_with_bias_v_9_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            bool x_95_transpose_x_0 = const()[name = string("x_95_transpose_x_0"), val = bool(false)];
            bool x_95_transpose_y_0 = const()[name = string("x_95_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 128, 375]> var_953_to_fp16 = const()[name = string("op_953_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(232195264)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_9_cast_fp16 = transpose(perm = q_with_bias_v_9_perm_0, x = var_951_cast_fp16)[name = string("transpose_259")];
            tensor<fp16, [1, 8, 188, 375]> x_95_cast_fp16 = matmul(transpose_x = x_95_transpose_x_0, transpose_y = x_95_transpose_y_0, x = q_with_bias_v_9_cast_fp16, y = var_953_to_fp16)[name = string("x_95_cast_fp16")];
            tensor<int32, [8]> x_97_pad_0 = const()[name = string("x_97_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            string x_97_mode_0 = const()[name = string("x_97_mode_0"), val = string("constant")];
            fp16 const_54_to_fp16 = const()[name = string("const_54_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_97_cast_fp16 = pad(constant_val = const_54_to_fp16, mode = x_97_mode_0, pad = x_97_pad_0, x = x_95_cast_fp16)[name = string("x_97_cast_fp16")];
            tensor<int32, [4]> var_961 = const()[name = string("op_961"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_99_cast_fp16 = reshape(shape = var_961, x = x_97_cast_fp16)[name = string("x_99_cast_fp16")];
            tensor<int32, [4]> var_965_begin_0 = const()[name = string("op_965_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_965_end_0 = const()[name = string("op_965_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_965_end_mask_0 = const()[name = string("op_965_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_965_cast_fp16 = slice_by_index(begin = var_965_begin_0, end = var_965_end_0, end_mask = var_965_end_mask_0, x = x_99_cast_fp16)[name = string("op_965_cast_fp16")];
            tensor<int32, [4]> var_966 = const()[name = string("op_966"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_17_cast_fp16 = reshape(shape = var_966, x = var_965_cast_fp16)[name = string("matrix_bd_17_cast_fp16")];
            bool matrix_ac_9_transpose_x_0 = const()[name = string("matrix_ac_9_transpose_x_0"), val = bool(false)];
            bool matrix_ac_9_transpose_y_0 = const()[name = string("matrix_ac_9_transpose_y_0"), val = bool(false)];
            tensor<int32, [4]> transpose_80_perm_0 = const()[name = string("transpose_80_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_81_perm_0 = const()[name = string("transpose_81_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_81 = transpose(perm = transpose_81_perm_0, x = k_17_cast_fp16)[name = string("transpose_257")];
            tensor<fp16, [1, 8, 188, 128]> transpose_80 = transpose(perm = transpose_80_perm_0, x = var_949_cast_fp16)[name = string("transpose_258")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_9_cast_fp16 = matmul(transpose_x = matrix_ac_9_transpose_x_0, transpose_y = matrix_ac_9_transpose_y_0, x = transpose_80, y = transpose_81)[name = string("matrix_ac_9_cast_fp16")];
            tensor<int32, [4]> matrix_bd_19_begin_0 = const()[name = string("matrix_bd_19_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_19_end_0 = const()[name = string("matrix_bd_19_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_19_end_mask_0 = const()[name = string("matrix_bd_19_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_19_cast_fp16 = slice_by_index(begin = matrix_bd_19_begin_0, end = matrix_bd_19_end_0, end_mask = matrix_bd_19_end_mask_0, x = matrix_bd_17_cast_fp16)[name = string("matrix_bd_19_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_975_cast_fp16 = add(x = matrix_ac_9_cast_fp16, y = matrix_bd_19_cast_fp16)[name = string("op_975_cast_fp16")];
            fp16 _inversed_scores_17_y_0_to_fp16 = const()[name = string("_inversed_scores_17_y_0_to_fp16"), val = fp16(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_17_cast_fp16 = mul(x = var_975_cast_fp16, y = _inversed_scores_17_y_0_to_fp16)[name = string("_inversed_scores_17_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_19_cast_fp16 = select(a = var_10_to_fp16, b = _inversed_scores_17_cast_fp16, cond = mask_3)[name = string("scores_19_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_981_cast_fp16 = softmax(axis = var_32, x = scores_19_cast_fp16)[name = string("op_981_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_249_cast_fp16 = select(a = var_9_to_fp16, b = var_981_cast_fp16, cond = mask_3)[name = string("input_249_cast_fp16")];
            bool x_101_transpose_x_0 = const()[name = string("x_101_transpose_x_0"), val = bool(false)];
            bool x_101_transpose_y_0 = const()[name = string("x_101_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 188, 128]> value_11_cast_fp16 = transpose(perm = value_11_perm_0, x = v_9_cast_fp16)[name = string("transpose_260")];
            tensor<fp16, [1, 8, 188, 128]> x_101_cast_fp16 = matmul(transpose_x = x_101_transpose_x_0, transpose_y = x_101_transpose_y_0, x = input_249_cast_fp16, y = value_11_cast_fp16)[name = string("x_101_cast_fp16")];
            tensor<int32, [4]> var_985_perm_0 = const()[name = string("op_985_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_986 = const()[name = string("op_986"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_985_cast_fp16 = transpose(perm = var_985_perm_0, x = x_101_cast_fp16)[name = string("transpose_256")];
            tensor<fp16, [1, 188, 1024]> input_251_cast_fp16 = reshape(shape = var_986, x = var_985_cast_fp16)[name = string("input_251_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_4_self_attn_linear_out_weight_to_fp16 = const()[name = string("module_layers_4_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(232963328)))];
            tensor<fp16, [1, 188, 1024]> linear_45_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_4_self_attn_linear_out_weight_to_fp16, x = input_251_cast_fp16)[name = string("linear_45_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_255_cast_fp16 = add(x = input_247_cast_fp16, y = linear_45_cast_fp16)[name = string("input_255_cast_fp16")];
            tensor<int32, [1]> x_105_axes_0 = const()[name = string("x_105_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_4_norm_conv_weight_to_fp16 = const()[name = string("module_layers_4_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(235060544)))];
            tensor<fp16, [1024]> module_layers_4_norm_conv_bias_to_fp16 = const()[name = string("module_layers_4_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(235062656)))];
            tensor<fp16, [1, 188, 1024]> x_105_cast_fp16 = layer_norm(axes = x_105_axes_0, beta = module_layers_4_norm_conv_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_4_norm_conv_weight_to_fp16, x = input_255_cast_fp16)[name = string("x_105_cast_fp16")];
            tensor<int32, [3]> input_257_perm_0 = const()[name = string("input_257_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            string input_259_pad_type_0 = const()[name = string("input_259_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_259_strides_0 = const()[name = string("input_259_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_259_pad_0 = const()[name = string("input_259_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_259_dilations_0 = const()[name = string("input_259_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_259_groups_0 = const()[name = string("input_259_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 1024, 1]> module_layers_4_conv_pointwise_conv1_weight_to_fp16 = const()[name = string("module_layers_4_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(235064768)))];
            tensor<fp16, [1, 1024, 188]> input_257_cast_fp16 = transpose(perm = input_257_perm_0, x = x_105_cast_fp16)[name = string("transpose_255")];
            tensor<fp16, [1, 2048, 188]> input_259_cast_fp16 = conv(dilations = input_259_dilations_0, groups = input_259_groups_0, pad = input_259_pad_0, pad_type = input_259_pad_type_0, strides = input_259_strides_0, weight = module_layers_4_conv_pointwise_conv1_weight_to_fp16, x = input_257_cast_fp16)[name = string("input_259_cast_fp16")];
            int32 x_107_split_num_splits_0 = const()[name = string("x_107_split_num_splits_0"), val = int32(2)];
            int32 x_107_split_axis_0 = const()[name = string("x_107_split_axis_0"), val = int32(1)];
            tensor<fp16, [1, 1024, 188]> x_107_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_107_split_cast_fp16_1 = split(axis = x_107_split_axis_0, num_splits = x_107_split_num_splits_0, x = input_259_cast_fp16)[name = string("x_107_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_107_split_1_sigmoid_cast_fp16 = sigmoid(x = x_107_split_cast_fp16_1)[name = string("x_107_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_107_cast_fp16 = mul(x = x_107_split_cast_fp16_0, y = x_107_split_1_sigmoid_cast_fp16)[name = string("x_107_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_261_cast_fp16 = select(a = var_9_to_fp16, b = x_107_cast_fp16, cond = var_356)[name = string("input_261_cast_fp16")];
            tensor<int32, [6]> input_263_pad_0 = const()[name = string("input_263_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            string input_263_mode_0 = const()[name = string("input_263_mode_0"), val = string("constant")];
            fp16 const_57_to_fp16 = const()[name = string("const_57_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_263_cast_fp16 = pad(constant_val = const_57_to_fp16, mode = input_263_mode_0, pad = input_263_pad_0, x = input_261_cast_fp16)[name = string("input_263_cast_fp16")];
            string input_265_pad_type_0 = const()[name = string("input_265_pad_type_0"), val = string("valid")];
            int32 input_265_groups_0 = const()[name = string("input_265_groups_0"), val = int32(1024)];
            tensor<int32, [1]> input_265_strides_0 = const()[name = string("input_265_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_265_pad_0 = const()[name = string("input_265_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_265_dilations_0 = const()[name = string("input_265_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_256_to_fp16 = const()[name = string("const_256_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(239259136)))];
            tensor<fp16, [1024]> const_257_to_fp16 = const()[name = string("const_257_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(239277632)))];
            tensor<fp16, [1, 1024, 188]> input_267_cast_fp16 = conv(bias = const_257_to_fp16, dilations = input_265_dilations_0, groups = input_265_groups_0, pad = input_265_pad_0, pad_type = input_265_pad_type_0, strides = input_265_strides_0, weight = const_256_to_fp16, x = input_263_cast_fp16)[name = string("input_267_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_269_cast_fp16 = silu(x = input_267_cast_fp16)[name = string("input_269_cast_fp16")];
            string x_109_pad_type_0 = const()[name = string("x_109_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> x_109_strides_0 = const()[name = string("x_109_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_109_pad_0 = const()[name = string("x_109_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_109_dilations_0 = const()[name = string("x_109_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 x_109_groups_0 = const()[name = string("x_109_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 1024, 1]> module_layers_4_conv_pointwise_conv2_weight_to_fp16 = const()[name = string("module_layers_4_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(239279744)))];
            tensor<fp16, [1, 1024, 188]> x_109_cast_fp16 = conv(dilations = x_109_dilations_0, groups = x_109_groups_0, pad = x_109_pad_0, pad_type = x_109_pad_type_0, strides = x_109_strides_0, weight = module_layers_4_conv_pointwise_conv2_weight_to_fp16, x = input_269_cast_fp16)[name = string("x_109_cast_fp16")];
            tensor<int32, [3]> input_271_perm_0 = const()[name = string("input_271_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_271_cast_fp16 = transpose(perm = input_271_perm_0, x = x_109_cast_fp16)[name = string("transpose_254")];
            tensor<fp16, [1, 188, 1024]> input_273_cast_fp16 = add(x = input_255_cast_fp16, y = input_271_cast_fp16)[name = string("input_273_cast_fp16")];
            tensor<int32, [1]> input_275_axes_0 = const()[name = string("input_275_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_4_norm_feed_forward2_weight_to_fp16 = const()[name = string("module_layers_4_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(241376960)))];
            tensor<fp16, [1024]> module_layers_4_norm_feed_forward2_bias_to_fp16 = const()[name = string("module_layers_4_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(241379072)))];
            tensor<fp16, [1, 188, 1024]> input_275_cast_fp16 = layer_norm(axes = input_275_axes_0, beta = module_layers_4_norm_feed_forward2_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_4_norm_feed_forward2_weight_to_fp16, x = input_273_cast_fp16)[name = string("input_275_cast_fp16")];
            tensor<fp16, [4096, 1024]> module_layers_4_feed_forward2_linear1_weight_to_fp16 = const()[name = string("module_layers_4_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(241381184)))];
            tensor<fp16, [1, 188, 4096]> linear_46_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = module_layers_4_feed_forward2_linear1_weight_to_fp16, x = input_275_cast_fp16)[name = string("linear_46_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_279_cast_fp16 = silu(x = linear_46_cast_fp16)[name = string("input_279_cast_fp16")];
            tensor<fp16, [1024, 4096]> module_layers_4_feed_forward2_linear2_weight_to_fp16 = const()[name = string("module_layers_4_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(249769856)))];
            tensor<fp16, [1, 188, 1024]> linear_47_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_4_feed_forward2_linear2_weight_to_fp16, x = input_279_cast_fp16)[name = string("linear_47_cast_fp16")];
            fp16 var_1046_to_fp16 = const()[name = string("op_1046_to_fp16"), val = fp16(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_1047_cast_fp16 = mul(x = linear_47_cast_fp16, y = var_1046_to_fp16)[name = string("op_1047_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_285_cast_fp16 = add(x = input_273_cast_fp16, y = var_1047_cast_fp16)[name = string("input_285_cast_fp16")];
            tensor<int32, [1]> input_287_axes_0 = const()[name = string("input_287_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_4_norm_out_weight_to_fp16 = const()[name = string("module_layers_4_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(258158528)))];
            tensor<fp16, [1024]> module_layers_4_norm_out_bias_to_fp16 = const()[name = string("module_layers_4_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(258160640)))];
            tensor<fp16, [1, 188, 1024]> input_287_cast_fp16 = layer_norm(axes = input_287_axes_0, beta = module_layers_4_norm_out_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_4_norm_out_weight_to_fp16, x = input_285_cast_fp16)[name = string("input_287_cast_fp16")];
            tensor<int32, [1]> input_289_axes_0 = const()[name = string("input_289_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_5_norm_feed_forward1_weight_to_fp16 = const()[name = string("module_layers_5_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(258162752)))];
            tensor<fp16, [1024]> module_layers_5_norm_feed_forward1_bias_to_fp16 = const()[name = string("module_layers_5_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(258164864)))];
            tensor<fp16, [1, 188, 1024]> input_289_cast_fp16 = layer_norm(axes = input_289_axes_0, beta = module_layers_5_norm_feed_forward1_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_5_norm_feed_forward1_weight_to_fp16, x = input_287_cast_fp16)[name = string("input_289_cast_fp16")];
            tensor<fp16, [4096, 1024]> module_layers_5_feed_forward1_linear1_weight_to_fp16 = const()[name = string("module_layers_5_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(258166976)))];
            tensor<fp16, [1, 188, 4096]> linear_48_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = module_layers_5_feed_forward1_linear1_weight_to_fp16, x = input_289_cast_fp16)[name = string("linear_48_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_293_cast_fp16 = silu(x = linear_48_cast_fp16)[name = string("input_293_cast_fp16")];
            tensor<fp16, [1024, 4096]> module_layers_5_feed_forward1_linear2_weight_to_fp16 = const()[name = string("module_layers_5_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(266555648)))];
            tensor<fp16, [1, 188, 1024]> linear_49_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_5_feed_forward1_linear2_weight_to_fp16, x = input_293_cast_fp16)[name = string("linear_49_cast_fp16")];
            fp16 var_1075_to_fp16 = const()[name = string("op_1075_to_fp16"), val = fp16(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_1076_cast_fp16 = mul(x = linear_49_cast_fp16, y = var_1075_to_fp16)[name = string("op_1076_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_299_cast_fp16 = add(x = input_287_cast_fp16, y = var_1076_cast_fp16)[name = string("input_299_cast_fp16")];
            tensor<int32, [1]> query_11_axes_0 = const()[name = string("query_11_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_5_norm_self_att_weight_to_fp16 = const()[name = string("module_layers_5_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(274944320)))];
            tensor<fp16, [1024]> module_layers_5_norm_self_att_bias_to_fp16 = const()[name = string("module_layers_5_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(274946432)))];
            tensor<fp16, [1, 188, 1024]> query_11_cast_fp16 = layer_norm(axes = query_11_axes_0, beta = module_layers_5_norm_self_att_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_5_norm_self_att_weight_to_fp16, x = input_299_cast_fp16)[name = string("query_11_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_5_self_attn_linear_q_weight_to_fp16 = const()[name = string("module_layers_5_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(274948544)))];
            tensor<fp16, [1, 188, 1024]> linear_50_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_5_self_attn_linear_q_weight_to_fp16, x = query_11_cast_fp16)[name = string("linear_50_cast_fp16")];
            tensor<int32, [4]> var_1092 = const()[name = string("op_1092"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_31_cast_fp16 = reshape(shape = var_1092, x = linear_50_cast_fp16)[name = string("q_31_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_5_self_attn_linear_k_weight_to_fp16 = const()[name = string("module_layers_5_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(277045760)))];
            tensor<fp16, [1, 188, 1024]> linear_51_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_5_self_attn_linear_k_weight_to_fp16, x = query_11_cast_fp16)[name = string("linear_51_cast_fp16")];
            tensor<int32, [4]> var_1096 = const()[name = string("op_1096"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_21_cast_fp16 = reshape(shape = var_1096, x = linear_51_cast_fp16)[name = string("k_21_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_5_self_attn_linear_v_weight_to_fp16 = const()[name = string("module_layers_5_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(279142976)))];
            tensor<fp16, [1, 188, 1024]> linear_52_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_5_self_attn_linear_v_weight_to_fp16, x = query_11_cast_fp16)[name = string("linear_52_cast_fp16")];
            tensor<int32, [4]> var_1100 = const()[name = string("op_1100"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_11_cast_fp16 = reshape(shape = var_1100, x = linear_52_cast_fp16)[name = string("v_11_cast_fp16")];
            tensor<int32, [4]> value_13_perm_0 = const()[name = string("value_13_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> module_layers_5_self_attn_pos_bias_u_to_fp16 = const()[name = string("module_layers_5_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(281240192)))];
            tensor<fp16, [1, 188, 8, 128]> var_1112_cast_fp16 = add(x = q_31_cast_fp16, y = module_layers_5_self_attn_pos_bias_u_to_fp16)[name = string("op_1112_cast_fp16")];
            tensor<fp16, [8, 128]> module_layers_5_self_attn_pos_bias_v_to_fp16 = const()[name = string("module_layers_5_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(281242304)))];
            tensor<fp16, [1, 188, 8, 128]> var_1114_cast_fp16 = add(x = q_31_cast_fp16, y = module_layers_5_self_attn_pos_bias_v_to_fp16)[name = string("op_1114_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_11_perm_0 = const()[name = string("q_with_bias_v_11_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            bool x_117_transpose_x_0 = const()[name = string("x_117_transpose_x_0"), val = bool(false)];
            bool x_117_transpose_y_0 = const()[name = string("x_117_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 128, 375]> var_1116_to_fp16 = const()[name = string("op_1116_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(281244416)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_11_cast_fp16 = transpose(perm = q_with_bias_v_11_perm_0, x = var_1114_cast_fp16)[name = string("transpose_252")];
            tensor<fp16, [1, 8, 188, 375]> x_117_cast_fp16 = matmul(transpose_x = x_117_transpose_x_0, transpose_y = x_117_transpose_y_0, x = q_with_bias_v_11_cast_fp16, y = var_1116_to_fp16)[name = string("x_117_cast_fp16")];
            tensor<int32, [8]> x_119_pad_0 = const()[name = string("x_119_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            string x_119_mode_0 = const()[name = string("x_119_mode_0"), val = string("constant")];
            fp16 const_64_to_fp16 = const()[name = string("const_64_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_119_cast_fp16 = pad(constant_val = const_64_to_fp16, mode = x_119_mode_0, pad = x_119_pad_0, x = x_117_cast_fp16)[name = string("x_119_cast_fp16")];
            tensor<int32, [4]> var_1124 = const()[name = string("op_1124"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_121_cast_fp16 = reshape(shape = var_1124, x = x_119_cast_fp16)[name = string("x_121_cast_fp16")];
            tensor<int32, [4]> var_1128_begin_0 = const()[name = string("op_1128_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_1128_end_0 = const()[name = string("op_1128_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_1128_end_mask_0 = const()[name = string("op_1128_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_1128_cast_fp16 = slice_by_index(begin = var_1128_begin_0, end = var_1128_end_0, end_mask = var_1128_end_mask_0, x = x_121_cast_fp16)[name = string("op_1128_cast_fp16")];
            tensor<int32, [4]> var_1129 = const()[name = string("op_1129"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_21_cast_fp16 = reshape(shape = var_1129, x = var_1128_cast_fp16)[name = string("matrix_bd_21_cast_fp16")];
            bool matrix_ac_11_transpose_x_0 = const()[name = string("matrix_ac_11_transpose_x_0"), val = bool(false)];
            bool matrix_ac_11_transpose_y_0 = const()[name = string("matrix_ac_11_transpose_y_0"), val = bool(false)];
            tensor<int32, [4]> transpose_82_perm_0 = const()[name = string("transpose_82_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_83_perm_0 = const()[name = string("transpose_83_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_83 = transpose(perm = transpose_83_perm_0, x = k_21_cast_fp16)[name = string("transpose_250")];
            tensor<fp16, [1, 8, 188, 128]> transpose_82 = transpose(perm = transpose_82_perm_0, x = var_1112_cast_fp16)[name = string("transpose_251")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_11_cast_fp16 = matmul(transpose_x = matrix_ac_11_transpose_x_0, transpose_y = matrix_ac_11_transpose_y_0, x = transpose_82, y = transpose_83)[name = string("matrix_ac_11_cast_fp16")];
            tensor<int32, [4]> matrix_bd_23_begin_0 = const()[name = string("matrix_bd_23_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_23_end_0 = const()[name = string("matrix_bd_23_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_23_end_mask_0 = const()[name = string("matrix_bd_23_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_23_cast_fp16 = slice_by_index(begin = matrix_bd_23_begin_0, end = matrix_bd_23_end_0, end_mask = matrix_bd_23_end_mask_0, x = matrix_bd_21_cast_fp16)[name = string("matrix_bd_23_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_1138_cast_fp16 = add(x = matrix_ac_11_cast_fp16, y = matrix_bd_23_cast_fp16)[name = string("op_1138_cast_fp16")];
            fp16 _inversed_scores_21_y_0_to_fp16 = const()[name = string("_inversed_scores_21_y_0_to_fp16"), val = fp16(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_21_cast_fp16 = mul(x = var_1138_cast_fp16, y = _inversed_scores_21_y_0_to_fp16)[name = string("_inversed_scores_21_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_23_cast_fp16 = select(a = var_10_to_fp16, b = _inversed_scores_21_cast_fp16, cond = mask_3)[name = string("scores_23_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_1144_cast_fp16 = softmax(axis = var_32, x = scores_23_cast_fp16)[name = string("op_1144_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_301_cast_fp16 = select(a = var_9_to_fp16, b = var_1144_cast_fp16, cond = mask_3)[name = string("input_301_cast_fp16")];
            bool x_123_transpose_x_0 = const()[name = string("x_123_transpose_x_0"), val = bool(false)];
            bool x_123_transpose_y_0 = const()[name = string("x_123_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 188, 128]> value_13_cast_fp16 = transpose(perm = value_13_perm_0, x = v_11_cast_fp16)[name = string("transpose_253")];
            tensor<fp16, [1, 8, 188, 128]> x_123_cast_fp16 = matmul(transpose_x = x_123_transpose_x_0, transpose_y = x_123_transpose_y_0, x = input_301_cast_fp16, y = value_13_cast_fp16)[name = string("x_123_cast_fp16")];
            tensor<int32, [4]> var_1148_perm_0 = const()[name = string("op_1148_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1149 = const()[name = string("op_1149"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_1148_cast_fp16 = transpose(perm = var_1148_perm_0, x = x_123_cast_fp16)[name = string("transpose_249")];
            tensor<fp16, [1, 188, 1024]> input_303_cast_fp16 = reshape(shape = var_1149, x = var_1148_cast_fp16)[name = string("input_303_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_5_self_attn_linear_out_weight_to_fp16 = const()[name = string("module_layers_5_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(282012480)))];
            tensor<fp16, [1, 188, 1024]> linear_54_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_5_self_attn_linear_out_weight_to_fp16, x = input_303_cast_fp16)[name = string("linear_54_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_307_cast_fp16 = add(x = input_299_cast_fp16, y = linear_54_cast_fp16)[name = string("input_307_cast_fp16")];
            tensor<int32, [1]> x_127_axes_0 = const()[name = string("x_127_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_5_norm_conv_weight_to_fp16 = const()[name = string("module_layers_5_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(284109696)))];
            tensor<fp16, [1024]> module_layers_5_norm_conv_bias_to_fp16 = const()[name = string("module_layers_5_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(284111808)))];
            tensor<fp16, [1, 188, 1024]> x_127_cast_fp16 = layer_norm(axes = x_127_axes_0, beta = module_layers_5_norm_conv_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_5_norm_conv_weight_to_fp16, x = input_307_cast_fp16)[name = string("x_127_cast_fp16")];
            tensor<int32, [3]> input_309_perm_0 = const()[name = string("input_309_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            string input_311_pad_type_0 = const()[name = string("input_311_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_311_strides_0 = const()[name = string("input_311_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_311_pad_0 = const()[name = string("input_311_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_311_dilations_0 = const()[name = string("input_311_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_311_groups_0 = const()[name = string("input_311_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 1024, 1]> module_layers_5_conv_pointwise_conv1_weight_to_fp16 = const()[name = string("module_layers_5_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(284113920)))];
            tensor<fp16, [1, 1024, 188]> input_309_cast_fp16 = transpose(perm = input_309_perm_0, x = x_127_cast_fp16)[name = string("transpose_248")];
            tensor<fp16, [1, 2048, 188]> input_311_cast_fp16 = conv(dilations = input_311_dilations_0, groups = input_311_groups_0, pad = input_311_pad_0, pad_type = input_311_pad_type_0, strides = input_311_strides_0, weight = module_layers_5_conv_pointwise_conv1_weight_to_fp16, x = input_309_cast_fp16)[name = string("input_311_cast_fp16")];
            int32 x_129_split_num_splits_0 = const()[name = string("x_129_split_num_splits_0"), val = int32(2)];
            int32 x_129_split_axis_0 = const()[name = string("x_129_split_axis_0"), val = int32(1)];
            tensor<fp16, [1, 1024, 188]> x_129_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_129_split_cast_fp16_1 = split(axis = x_129_split_axis_0, num_splits = x_129_split_num_splits_0, x = input_311_cast_fp16)[name = string("x_129_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_129_split_1_sigmoid_cast_fp16 = sigmoid(x = x_129_split_cast_fp16_1)[name = string("x_129_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_129_cast_fp16 = mul(x = x_129_split_cast_fp16_0, y = x_129_split_1_sigmoid_cast_fp16)[name = string("x_129_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_313_cast_fp16 = select(a = var_9_to_fp16, b = x_129_cast_fp16, cond = var_356)[name = string("input_313_cast_fp16")];
            tensor<int32, [6]> input_315_pad_0 = const()[name = string("input_315_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            string input_315_mode_0 = const()[name = string("input_315_mode_0"), val = string("constant")];
            fp16 const_67_to_fp16 = const()[name = string("const_67_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_315_cast_fp16 = pad(constant_val = const_67_to_fp16, mode = input_315_mode_0, pad = input_315_pad_0, x = input_313_cast_fp16)[name = string("input_315_cast_fp16")];
            string input_317_pad_type_0 = const()[name = string("input_317_pad_type_0"), val = string("valid")];
            int32 input_317_groups_0 = const()[name = string("input_317_groups_0"), val = int32(1024)];
            tensor<int32, [1]> input_317_strides_0 = const()[name = string("input_317_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_317_pad_0 = const()[name = string("input_317_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_317_dilations_0 = const()[name = string("input_317_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_258_to_fp16 = const()[name = string("const_258_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(288308288)))];
            tensor<fp16, [1024]> const_259_to_fp16 = const()[name = string("const_259_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(288326784)))];
            tensor<fp16, [1, 1024, 188]> input_319_cast_fp16 = conv(bias = const_259_to_fp16, dilations = input_317_dilations_0, groups = input_317_groups_0, pad = input_317_pad_0, pad_type = input_317_pad_type_0, strides = input_317_strides_0, weight = const_258_to_fp16, x = input_315_cast_fp16)[name = string("input_319_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_321_cast_fp16 = silu(x = input_319_cast_fp16)[name = string("input_321_cast_fp16")];
            string x_131_pad_type_0 = const()[name = string("x_131_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> x_131_strides_0 = const()[name = string("x_131_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_131_pad_0 = const()[name = string("x_131_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_131_dilations_0 = const()[name = string("x_131_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 x_131_groups_0 = const()[name = string("x_131_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 1024, 1]> module_layers_5_conv_pointwise_conv2_weight_to_fp16 = const()[name = string("module_layers_5_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(288328896)))];
            tensor<fp16, [1, 1024, 188]> x_131_cast_fp16 = conv(dilations = x_131_dilations_0, groups = x_131_groups_0, pad = x_131_pad_0, pad_type = x_131_pad_type_0, strides = x_131_strides_0, weight = module_layers_5_conv_pointwise_conv2_weight_to_fp16, x = input_321_cast_fp16)[name = string("x_131_cast_fp16")];
            tensor<int32, [3]> input_323_perm_0 = const()[name = string("input_323_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_323_cast_fp16 = transpose(perm = input_323_perm_0, x = x_131_cast_fp16)[name = string("transpose_247")];
            tensor<fp16, [1, 188, 1024]> input_325_cast_fp16 = add(x = input_307_cast_fp16, y = input_323_cast_fp16)[name = string("input_325_cast_fp16")];
            tensor<int32, [1]> input_327_axes_0 = const()[name = string("input_327_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_5_norm_feed_forward2_weight_to_fp16 = const()[name = string("module_layers_5_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(290426112)))];
            tensor<fp16, [1024]> module_layers_5_norm_feed_forward2_bias_to_fp16 = const()[name = string("module_layers_5_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(290428224)))];
            tensor<fp16, [1, 188, 1024]> input_327_cast_fp16 = layer_norm(axes = input_327_axes_0, beta = module_layers_5_norm_feed_forward2_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_5_norm_feed_forward2_weight_to_fp16, x = input_325_cast_fp16)[name = string("input_327_cast_fp16")];
            tensor<fp16, [4096, 1024]> module_layers_5_feed_forward2_linear1_weight_to_fp16 = const()[name = string("module_layers_5_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(290430336)))];
            tensor<fp16, [1, 188, 4096]> linear_55_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = module_layers_5_feed_forward2_linear1_weight_to_fp16, x = input_327_cast_fp16)[name = string("linear_55_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_331_cast_fp16 = silu(x = linear_55_cast_fp16)[name = string("input_331_cast_fp16")];
            tensor<fp16, [1024, 4096]> module_layers_5_feed_forward2_linear2_weight_to_fp16 = const()[name = string("module_layers_5_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(298819008)))];
            tensor<fp16, [1, 188, 1024]> linear_56_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_5_feed_forward2_linear2_weight_to_fp16, x = input_331_cast_fp16)[name = string("linear_56_cast_fp16")];
            fp16 var_1209_to_fp16 = const()[name = string("op_1209_to_fp16"), val = fp16(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_1210_cast_fp16 = mul(x = linear_56_cast_fp16, y = var_1209_to_fp16)[name = string("op_1210_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_337_cast_fp16 = add(x = input_325_cast_fp16, y = var_1210_cast_fp16)[name = string("input_337_cast_fp16")];
            tensor<int32, [1]> input_339_axes_0 = const()[name = string("input_339_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_5_norm_out_weight_to_fp16 = const()[name = string("module_layers_5_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(307207680)))];
            tensor<fp16, [1024]> module_layers_5_norm_out_bias_to_fp16 = const()[name = string("module_layers_5_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(307209792)))];
            tensor<fp16, [1, 188, 1024]> input_339_cast_fp16 = layer_norm(axes = input_339_axes_0, beta = module_layers_5_norm_out_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_5_norm_out_weight_to_fp16, x = input_337_cast_fp16)[name = string("input_339_cast_fp16")];
            tensor<int32, [1]> input_341_axes_0 = const()[name = string("input_341_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_6_norm_feed_forward1_weight_to_fp16 = const()[name = string("module_layers_6_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(307211904)))];
            tensor<fp16, [1024]> module_layers_6_norm_feed_forward1_bias_to_fp16 = const()[name = string("module_layers_6_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(307214016)))];
            tensor<fp16, [1, 188, 1024]> input_341_cast_fp16 = layer_norm(axes = input_341_axes_0, beta = module_layers_6_norm_feed_forward1_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_6_norm_feed_forward1_weight_to_fp16, x = input_339_cast_fp16)[name = string("input_341_cast_fp16")];
            tensor<fp16, [4096, 1024]> module_layers_6_feed_forward1_linear1_weight_to_fp16 = const()[name = string("module_layers_6_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(307216128)))];
            tensor<fp16, [1, 188, 4096]> linear_57_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = module_layers_6_feed_forward1_linear1_weight_to_fp16, x = input_341_cast_fp16)[name = string("linear_57_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_345_cast_fp16 = silu(x = linear_57_cast_fp16)[name = string("input_345_cast_fp16")];
            tensor<fp16, [1024, 4096]> module_layers_6_feed_forward1_linear2_weight_to_fp16 = const()[name = string("module_layers_6_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(315604800)))];
            tensor<fp16, [1, 188, 1024]> linear_58_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_6_feed_forward1_linear2_weight_to_fp16, x = input_345_cast_fp16)[name = string("linear_58_cast_fp16")];
            fp16 var_1238_to_fp16 = const()[name = string("op_1238_to_fp16"), val = fp16(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_1239_cast_fp16 = mul(x = linear_58_cast_fp16, y = var_1238_to_fp16)[name = string("op_1239_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_351_cast_fp16 = add(x = input_339_cast_fp16, y = var_1239_cast_fp16)[name = string("input_351_cast_fp16")];
            tensor<int32, [1]> query_13_axes_0 = const()[name = string("query_13_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_6_norm_self_att_weight_to_fp16 = const()[name = string("module_layers_6_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(323993472)))];
            tensor<fp16, [1024]> module_layers_6_norm_self_att_bias_to_fp16 = const()[name = string("module_layers_6_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(323995584)))];
            tensor<fp16, [1, 188, 1024]> query_13_cast_fp16 = layer_norm(axes = query_13_axes_0, beta = module_layers_6_norm_self_att_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_6_norm_self_att_weight_to_fp16, x = input_351_cast_fp16)[name = string("query_13_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_6_self_attn_linear_q_weight_to_fp16 = const()[name = string("module_layers_6_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(323997696)))];
            tensor<fp16, [1, 188, 1024]> linear_59_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_6_self_attn_linear_q_weight_to_fp16, x = query_13_cast_fp16)[name = string("linear_59_cast_fp16")];
            tensor<int32, [4]> var_1255 = const()[name = string("op_1255"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_37_cast_fp16 = reshape(shape = var_1255, x = linear_59_cast_fp16)[name = string("q_37_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_6_self_attn_linear_k_weight_to_fp16 = const()[name = string("module_layers_6_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(326094912)))];
            tensor<fp16, [1, 188, 1024]> linear_60_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_6_self_attn_linear_k_weight_to_fp16, x = query_13_cast_fp16)[name = string("linear_60_cast_fp16")];
            tensor<int32, [4]> var_1259 = const()[name = string("op_1259"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_25_cast_fp16 = reshape(shape = var_1259, x = linear_60_cast_fp16)[name = string("k_25_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_6_self_attn_linear_v_weight_to_fp16 = const()[name = string("module_layers_6_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(328192128)))];
            tensor<fp16, [1, 188, 1024]> linear_61_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_6_self_attn_linear_v_weight_to_fp16, x = query_13_cast_fp16)[name = string("linear_61_cast_fp16")];
            tensor<int32, [4]> var_1263 = const()[name = string("op_1263"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_13_cast_fp16 = reshape(shape = var_1263, x = linear_61_cast_fp16)[name = string("v_13_cast_fp16")];
            tensor<int32, [4]> value_15_perm_0 = const()[name = string("value_15_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> module_layers_6_self_attn_pos_bias_u_to_fp16 = const()[name = string("module_layers_6_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(330289344)))];
            tensor<fp16, [1, 188, 8, 128]> var_1275_cast_fp16 = add(x = q_37_cast_fp16, y = module_layers_6_self_attn_pos_bias_u_to_fp16)[name = string("op_1275_cast_fp16")];
            tensor<fp16, [8, 128]> module_layers_6_self_attn_pos_bias_v_to_fp16 = const()[name = string("module_layers_6_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(330291456)))];
            tensor<fp16, [1, 188, 8, 128]> var_1277_cast_fp16 = add(x = q_37_cast_fp16, y = module_layers_6_self_attn_pos_bias_v_to_fp16)[name = string("op_1277_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_13_perm_0 = const()[name = string("q_with_bias_v_13_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            bool x_139_transpose_x_0 = const()[name = string("x_139_transpose_x_0"), val = bool(false)];
            bool x_139_transpose_y_0 = const()[name = string("x_139_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 128, 375]> var_1279_to_fp16 = const()[name = string("op_1279_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(330293568)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_13_cast_fp16 = transpose(perm = q_with_bias_v_13_perm_0, x = var_1277_cast_fp16)[name = string("transpose_245")];
            tensor<fp16, [1, 8, 188, 375]> x_139_cast_fp16 = matmul(transpose_x = x_139_transpose_x_0, transpose_y = x_139_transpose_y_0, x = q_with_bias_v_13_cast_fp16, y = var_1279_to_fp16)[name = string("x_139_cast_fp16")];
            tensor<int32, [8]> x_141_pad_0 = const()[name = string("x_141_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            string x_141_mode_0 = const()[name = string("x_141_mode_0"), val = string("constant")];
            fp16 const_74_to_fp16 = const()[name = string("const_74_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_141_cast_fp16 = pad(constant_val = const_74_to_fp16, mode = x_141_mode_0, pad = x_141_pad_0, x = x_139_cast_fp16)[name = string("x_141_cast_fp16")];
            tensor<int32, [4]> var_1287 = const()[name = string("op_1287"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_143_cast_fp16 = reshape(shape = var_1287, x = x_141_cast_fp16)[name = string("x_143_cast_fp16")];
            tensor<int32, [4]> var_1291_begin_0 = const()[name = string("op_1291_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_1291_end_0 = const()[name = string("op_1291_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_1291_end_mask_0 = const()[name = string("op_1291_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_1291_cast_fp16 = slice_by_index(begin = var_1291_begin_0, end = var_1291_end_0, end_mask = var_1291_end_mask_0, x = x_143_cast_fp16)[name = string("op_1291_cast_fp16")];
            tensor<int32, [4]> var_1292 = const()[name = string("op_1292"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_25_cast_fp16 = reshape(shape = var_1292, x = var_1291_cast_fp16)[name = string("matrix_bd_25_cast_fp16")];
            bool matrix_ac_13_transpose_x_0 = const()[name = string("matrix_ac_13_transpose_x_0"), val = bool(false)];
            bool matrix_ac_13_transpose_y_0 = const()[name = string("matrix_ac_13_transpose_y_0"), val = bool(false)];
            tensor<int32, [4]> transpose_84_perm_0 = const()[name = string("transpose_84_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_85_perm_0 = const()[name = string("transpose_85_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_85 = transpose(perm = transpose_85_perm_0, x = k_25_cast_fp16)[name = string("transpose_243")];
            tensor<fp16, [1, 8, 188, 128]> transpose_84 = transpose(perm = transpose_84_perm_0, x = var_1275_cast_fp16)[name = string("transpose_244")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_13_cast_fp16 = matmul(transpose_x = matrix_ac_13_transpose_x_0, transpose_y = matrix_ac_13_transpose_y_0, x = transpose_84, y = transpose_85)[name = string("matrix_ac_13_cast_fp16")];
            tensor<int32, [4]> matrix_bd_27_begin_0 = const()[name = string("matrix_bd_27_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_27_end_0 = const()[name = string("matrix_bd_27_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_27_end_mask_0 = const()[name = string("matrix_bd_27_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_27_cast_fp16 = slice_by_index(begin = matrix_bd_27_begin_0, end = matrix_bd_27_end_0, end_mask = matrix_bd_27_end_mask_0, x = matrix_bd_25_cast_fp16)[name = string("matrix_bd_27_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_1301_cast_fp16 = add(x = matrix_ac_13_cast_fp16, y = matrix_bd_27_cast_fp16)[name = string("op_1301_cast_fp16")];
            fp16 _inversed_scores_25_y_0_to_fp16 = const()[name = string("_inversed_scores_25_y_0_to_fp16"), val = fp16(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_25_cast_fp16 = mul(x = var_1301_cast_fp16, y = _inversed_scores_25_y_0_to_fp16)[name = string("_inversed_scores_25_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_27_cast_fp16 = select(a = var_10_to_fp16, b = _inversed_scores_25_cast_fp16, cond = mask_3)[name = string("scores_27_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_1307_cast_fp16 = softmax(axis = var_32, x = scores_27_cast_fp16)[name = string("op_1307_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_353_cast_fp16 = select(a = var_9_to_fp16, b = var_1307_cast_fp16, cond = mask_3)[name = string("input_353_cast_fp16")];
            bool x_145_transpose_x_0 = const()[name = string("x_145_transpose_x_0"), val = bool(false)];
            bool x_145_transpose_y_0 = const()[name = string("x_145_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 188, 128]> value_15_cast_fp16 = transpose(perm = value_15_perm_0, x = v_13_cast_fp16)[name = string("transpose_246")];
            tensor<fp16, [1, 8, 188, 128]> x_145_cast_fp16 = matmul(transpose_x = x_145_transpose_x_0, transpose_y = x_145_transpose_y_0, x = input_353_cast_fp16, y = value_15_cast_fp16)[name = string("x_145_cast_fp16")];
            tensor<int32, [4]> var_1311_perm_0 = const()[name = string("op_1311_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1312 = const()[name = string("op_1312"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_1311_cast_fp16 = transpose(perm = var_1311_perm_0, x = x_145_cast_fp16)[name = string("transpose_242")];
            tensor<fp16, [1, 188, 1024]> input_355_cast_fp16 = reshape(shape = var_1312, x = var_1311_cast_fp16)[name = string("input_355_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_6_self_attn_linear_out_weight_to_fp16 = const()[name = string("module_layers_6_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(331061632)))];
            tensor<fp16, [1, 188, 1024]> linear_63_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_6_self_attn_linear_out_weight_to_fp16, x = input_355_cast_fp16)[name = string("linear_63_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_359_cast_fp16 = add(x = input_351_cast_fp16, y = linear_63_cast_fp16)[name = string("input_359_cast_fp16")];
            tensor<int32, [1]> x_149_axes_0 = const()[name = string("x_149_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_6_norm_conv_weight_to_fp16 = const()[name = string("module_layers_6_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(333158848)))];
            tensor<fp16, [1024]> module_layers_6_norm_conv_bias_to_fp16 = const()[name = string("module_layers_6_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(333160960)))];
            tensor<fp16, [1, 188, 1024]> x_149_cast_fp16 = layer_norm(axes = x_149_axes_0, beta = module_layers_6_norm_conv_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_6_norm_conv_weight_to_fp16, x = input_359_cast_fp16)[name = string("x_149_cast_fp16")];
            tensor<int32, [3]> input_361_perm_0 = const()[name = string("input_361_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            string input_363_pad_type_0 = const()[name = string("input_363_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_363_strides_0 = const()[name = string("input_363_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_363_pad_0 = const()[name = string("input_363_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_363_dilations_0 = const()[name = string("input_363_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_363_groups_0 = const()[name = string("input_363_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 1024, 1]> module_layers_6_conv_pointwise_conv1_weight_to_fp16 = const()[name = string("module_layers_6_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(333163072)))];
            tensor<fp16, [1, 1024, 188]> input_361_cast_fp16 = transpose(perm = input_361_perm_0, x = x_149_cast_fp16)[name = string("transpose_241")];
            tensor<fp16, [1, 2048, 188]> input_363_cast_fp16 = conv(dilations = input_363_dilations_0, groups = input_363_groups_0, pad = input_363_pad_0, pad_type = input_363_pad_type_0, strides = input_363_strides_0, weight = module_layers_6_conv_pointwise_conv1_weight_to_fp16, x = input_361_cast_fp16)[name = string("input_363_cast_fp16")];
            int32 x_151_split_num_splits_0 = const()[name = string("x_151_split_num_splits_0"), val = int32(2)];
            int32 x_151_split_axis_0 = const()[name = string("x_151_split_axis_0"), val = int32(1)];
            tensor<fp16, [1, 1024, 188]> x_151_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_151_split_cast_fp16_1 = split(axis = x_151_split_axis_0, num_splits = x_151_split_num_splits_0, x = input_363_cast_fp16)[name = string("x_151_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_151_split_1_sigmoid_cast_fp16 = sigmoid(x = x_151_split_cast_fp16_1)[name = string("x_151_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_151_cast_fp16 = mul(x = x_151_split_cast_fp16_0, y = x_151_split_1_sigmoid_cast_fp16)[name = string("x_151_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_365_cast_fp16 = select(a = var_9_to_fp16, b = x_151_cast_fp16, cond = var_356)[name = string("input_365_cast_fp16")];
            tensor<int32, [6]> input_367_pad_0 = const()[name = string("input_367_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            string input_367_mode_0 = const()[name = string("input_367_mode_0"), val = string("constant")];
            fp16 const_77_to_fp16 = const()[name = string("const_77_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_367_cast_fp16 = pad(constant_val = const_77_to_fp16, mode = input_367_mode_0, pad = input_367_pad_0, x = input_365_cast_fp16)[name = string("input_367_cast_fp16")];
            string input_369_pad_type_0 = const()[name = string("input_369_pad_type_0"), val = string("valid")];
            int32 input_369_groups_0 = const()[name = string("input_369_groups_0"), val = int32(1024)];
            tensor<int32, [1]> input_369_strides_0 = const()[name = string("input_369_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_369_pad_0 = const()[name = string("input_369_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_369_dilations_0 = const()[name = string("input_369_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_260_to_fp16 = const()[name = string("const_260_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(337357440)))];
            tensor<fp16, [1024]> const_261_to_fp16 = const()[name = string("const_261_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(337375936)))];
            tensor<fp16, [1, 1024, 188]> input_371_cast_fp16 = conv(bias = const_261_to_fp16, dilations = input_369_dilations_0, groups = input_369_groups_0, pad = input_369_pad_0, pad_type = input_369_pad_type_0, strides = input_369_strides_0, weight = const_260_to_fp16, x = input_367_cast_fp16)[name = string("input_371_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_373_cast_fp16 = silu(x = input_371_cast_fp16)[name = string("input_373_cast_fp16")];
            string x_153_pad_type_0 = const()[name = string("x_153_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> x_153_strides_0 = const()[name = string("x_153_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_153_pad_0 = const()[name = string("x_153_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_153_dilations_0 = const()[name = string("x_153_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 x_153_groups_0 = const()[name = string("x_153_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 1024, 1]> module_layers_6_conv_pointwise_conv2_weight_to_fp16 = const()[name = string("module_layers_6_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(337378048)))];
            tensor<fp16, [1, 1024, 188]> x_153_cast_fp16 = conv(dilations = x_153_dilations_0, groups = x_153_groups_0, pad = x_153_pad_0, pad_type = x_153_pad_type_0, strides = x_153_strides_0, weight = module_layers_6_conv_pointwise_conv2_weight_to_fp16, x = input_373_cast_fp16)[name = string("x_153_cast_fp16")];
            tensor<int32, [3]> input_375_perm_0 = const()[name = string("input_375_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_375_cast_fp16 = transpose(perm = input_375_perm_0, x = x_153_cast_fp16)[name = string("transpose_240")];
            tensor<fp16, [1, 188, 1024]> input_377_cast_fp16 = add(x = input_359_cast_fp16, y = input_375_cast_fp16)[name = string("input_377_cast_fp16")];
            tensor<int32, [1]> input_379_axes_0 = const()[name = string("input_379_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_6_norm_feed_forward2_weight_to_fp16 = const()[name = string("module_layers_6_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(339475264)))];
            tensor<fp16, [1024]> module_layers_6_norm_feed_forward2_bias_to_fp16 = const()[name = string("module_layers_6_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(339477376)))];
            tensor<fp16, [1, 188, 1024]> input_379_cast_fp16 = layer_norm(axes = input_379_axes_0, beta = module_layers_6_norm_feed_forward2_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_6_norm_feed_forward2_weight_to_fp16, x = input_377_cast_fp16)[name = string("input_379_cast_fp16")];
            tensor<fp16, [4096, 1024]> module_layers_6_feed_forward2_linear1_weight_to_fp16 = const()[name = string("module_layers_6_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(339479488)))];
            tensor<fp16, [1, 188, 4096]> linear_64_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = module_layers_6_feed_forward2_linear1_weight_to_fp16, x = input_379_cast_fp16)[name = string("linear_64_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_383_cast_fp16 = silu(x = linear_64_cast_fp16)[name = string("input_383_cast_fp16")];
            tensor<fp16, [1024, 4096]> module_layers_6_feed_forward2_linear2_weight_to_fp16 = const()[name = string("module_layers_6_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(347868160)))];
            tensor<fp16, [1, 188, 1024]> linear_65_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_6_feed_forward2_linear2_weight_to_fp16, x = input_383_cast_fp16)[name = string("linear_65_cast_fp16")];
            fp16 var_1372_to_fp16 = const()[name = string("op_1372_to_fp16"), val = fp16(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_1373_cast_fp16 = mul(x = linear_65_cast_fp16, y = var_1372_to_fp16)[name = string("op_1373_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_389_cast_fp16 = add(x = input_377_cast_fp16, y = var_1373_cast_fp16)[name = string("input_389_cast_fp16")];
            tensor<int32, [1]> input_391_axes_0 = const()[name = string("input_391_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_6_norm_out_weight_to_fp16 = const()[name = string("module_layers_6_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(356256832)))];
            tensor<fp16, [1024]> module_layers_6_norm_out_bias_to_fp16 = const()[name = string("module_layers_6_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(356258944)))];
            tensor<fp16, [1, 188, 1024]> input_391_cast_fp16 = layer_norm(axes = input_391_axes_0, beta = module_layers_6_norm_out_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_6_norm_out_weight_to_fp16, x = input_389_cast_fp16)[name = string("input_391_cast_fp16")];
            tensor<int32, [1]> input_393_axes_0 = const()[name = string("input_393_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_7_norm_feed_forward1_weight_to_fp16 = const()[name = string("module_layers_7_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(356261056)))];
            tensor<fp16, [1024]> module_layers_7_norm_feed_forward1_bias_to_fp16 = const()[name = string("module_layers_7_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(356263168)))];
            tensor<fp16, [1, 188, 1024]> input_393_cast_fp16 = layer_norm(axes = input_393_axes_0, beta = module_layers_7_norm_feed_forward1_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_7_norm_feed_forward1_weight_to_fp16, x = input_391_cast_fp16)[name = string("input_393_cast_fp16")];
            tensor<fp16, [4096, 1024]> module_layers_7_feed_forward1_linear1_weight_to_fp16 = const()[name = string("module_layers_7_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(356265280)))];
            tensor<fp16, [1, 188, 4096]> linear_66_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = module_layers_7_feed_forward1_linear1_weight_to_fp16, x = input_393_cast_fp16)[name = string("linear_66_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_397_cast_fp16 = silu(x = linear_66_cast_fp16)[name = string("input_397_cast_fp16")];
            tensor<fp16, [1024, 4096]> module_layers_7_feed_forward1_linear2_weight_to_fp16 = const()[name = string("module_layers_7_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(364653952)))];
            tensor<fp16, [1, 188, 1024]> linear_67_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_7_feed_forward1_linear2_weight_to_fp16, x = input_397_cast_fp16)[name = string("linear_67_cast_fp16")];
            fp16 var_1401_to_fp16 = const()[name = string("op_1401_to_fp16"), val = fp16(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_1402_cast_fp16 = mul(x = linear_67_cast_fp16, y = var_1401_to_fp16)[name = string("op_1402_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_403_cast_fp16 = add(x = input_391_cast_fp16, y = var_1402_cast_fp16)[name = string("input_403_cast_fp16")];
            tensor<int32, [1]> query_15_axes_0 = const()[name = string("query_15_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_7_norm_self_att_weight_to_fp16 = const()[name = string("module_layers_7_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(373042624)))];
            tensor<fp16, [1024]> module_layers_7_norm_self_att_bias_to_fp16 = const()[name = string("module_layers_7_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(373044736)))];
            tensor<fp16, [1, 188, 1024]> query_15_cast_fp16 = layer_norm(axes = query_15_axes_0, beta = module_layers_7_norm_self_att_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_7_norm_self_att_weight_to_fp16, x = input_403_cast_fp16)[name = string("query_15_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_7_self_attn_linear_q_weight_to_fp16 = const()[name = string("module_layers_7_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(373046848)))];
            tensor<fp16, [1, 188, 1024]> linear_68_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_7_self_attn_linear_q_weight_to_fp16, x = query_15_cast_fp16)[name = string("linear_68_cast_fp16")];
            tensor<int32, [4]> var_1418 = const()[name = string("op_1418"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_43_cast_fp16 = reshape(shape = var_1418, x = linear_68_cast_fp16)[name = string("q_43_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_7_self_attn_linear_k_weight_to_fp16 = const()[name = string("module_layers_7_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(375144064)))];
            tensor<fp16, [1, 188, 1024]> linear_69_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_7_self_attn_linear_k_weight_to_fp16, x = query_15_cast_fp16)[name = string("linear_69_cast_fp16")];
            tensor<int32, [4]> var_1422 = const()[name = string("op_1422"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_29_cast_fp16 = reshape(shape = var_1422, x = linear_69_cast_fp16)[name = string("k_29_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_7_self_attn_linear_v_weight_to_fp16 = const()[name = string("module_layers_7_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(377241280)))];
            tensor<fp16, [1, 188, 1024]> linear_70_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_7_self_attn_linear_v_weight_to_fp16, x = query_15_cast_fp16)[name = string("linear_70_cast_fp16")];
            tensor<int32, [4]> var_1426 = const()[name = string("op_1426"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_15_cast_fp16 = reshape(shape = var_1426, x = linear_70_cast_fp16)[name = string("v_15_cast_fp16")];
            tensor<int32, [4]> value_17_perm_0 = const()[name = string("value_17_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> module_layers_7_self_attn_pos_bias_u_to_fp16 = const()[name = string("module_layers_7_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(379338496)))];
            tensor<fp16, [1, 188, 8, 128]> var_1438_cast_fp16 = add(x = q_43_cast_fp16, y = module_layers_7_self_attn_pos_bias_u_to_fp16)[name = string("op_1438_cast_fp16")];
            tensor<fp16, [8, 128]> module_layers_7_self_attn_pos_bias_v_to_fp16 = const()[name = string("module_layers_7_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(379340608)))];
            tensor<fp16, [1, 188, 8, 128]> var_1440_cast_fp16 = add(x = q_43_cast_fp16, y = module_layers_7_self_attn_pos_bias_v_to_fp16)[name = string("op_1440_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_15_perm_0 = const()[name = string("q_with_bias_v_15_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            bool x_161_transpose_x_0 = const()[name = string("x_161_transpose_x_0"), val = bool(false)];
            bool x_161_transpose_y_0 = const()[name = string("x_161_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 128, 375]> var_1442_to_fp16 = const()[name = string("op_1442_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(379342720)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_15_cast_fp16 = transpose(perm = q_with_bias_v_15_perm_0, x = var_1440_cast_fp16)[name = string("transpose_238")];
            tensor<fp16, [1, 8, 188, 375]> x_161_cast_fp16 = matmul(transpose_x = x_161_transpose_x_0, transpose_y = x_161_transpose_y_0, x = q_with_bias_v_15_cast_fp16, y = var_1442_to_fp16)[name = string("x_161_cast_fp16")];
            tensor<int32, [8]> x_163_pad_0 = const()[name = string("x_163_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            string x_163_mode_0 = const()[name = string("x_163_mode_0"), val = string("constant")];
            fp16 const_84_to_fp16 = const()[name = string("const_84_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_163_cast_fp16 = pad(constant_val = const_84_to_fp16, mode = x_163_mode_0, pad = x_163_pad_0, x = x_161_cast_fp16)[name = string("x_163_cast_fp16")];
            tensor<int32, [4]> var_1450 = const()[name = string("op_1450"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_165_cast_fp16 = reshape(shape = var_1450, x = x_163_cast_fp16)[name = string("x_165_cast_fp16")];
            tensor<int32, [4]> var_1454_begin_0 = const()[name = string("op_1454_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_1454_end_0 = const()[name = string("op_1454_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_1454_end_mask_0 = const()[name = string("op_1454_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_1454_cast_fp16 = slice_by_index(begin = var_1454_begin_0, end = var_1454_end_0, end_mask = var_1454_end_mask_0, x = x_165_cast_fp16)[name = string("op_1454_cast_fp16")];
            tensor<int32, [4]> var_1455 = const()[name = string("op_1455"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_29_cast_fp16 = reshape(shape = var_1455, x = var_1454_cast_fp16)[name = string("matrix_bd_29_cast_fp16")];
            bool matrix_ac_15_transpose_x_0 = const()[name = string("matrix_ac_15_transpose_x_0"), val = bool(false)];
            bool matrix_ac_15_transpose_y_0 = const()[name = string("matrix_ac_15_transpose_y_0"), val = bool(false)];
            tensor<int32, [4]> transpose_86_perm_0 = const()[name = string("transpose_86_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_87_perm_0 = const()[name = string("transpose_87_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_87 = transpose(perm = transpose_87_perm_0, x = k_29_cast_fp16)[name = string("transpose_236")];
            tensor<fp16, [1, 8, 188, 128]> transpose_86 = transpose(perm = transpose_86_perm_0, x = var_1438_cast_fp16)[name = string("transpose_237")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_15_cast_fp16 = matmul(transpose_x = matrix_ac_15_transpose_x_0, transpose_y = matrix_ac_15_transpose_y_0, x = transpose_86, y = transpose_87)[name = string("matrix_ac_15_cast_fp16")];
            tensor<int32, [4]> matrix_bd_31_begin_0 = const()[name = string("matrix_bd_31_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_31_end_0 = const()[name = string("matrix_bd_31_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_31_end_mask_0 = const()[name = string("matrix_bd_31_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_31_cast_fp16 = slice_by_index(begin = matrix_bd_31_begin_0, end = matrix_bd_31_end_0, end_mask = matrix_bd_31_end_mask_0, x = matrix_bd_29_cast_fp16)[name = string("matrix_bd_31_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_1464_cast_fp16 = add(x = matrix_ac_15_cast_fp16, y = matrix_bd_31_cast_fp16)[name = string("op_1464_cast_fp16")];
            fp16 _inversed_scores_29_y_0_to_fp16 = const()[name = string("_inversed_scores_29_y_0_to_fp16"), val = fp16(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_29_cast_fp16 = mul(x = var_1464_cast_fp16, y = _inversed_scores_29_y_0_to_fp16)[name = string("_inversed_scores_29_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_31_cast_fp16 = select(a = var_10_to_fp16, b = _inversed_scores_29_cast_fp16, cond = mask_3)[name = string("scores_31_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_1470_cast_fp16 = softmax(axis = var_32, x = scores_31_cast_fp16)[name = string("op_1470_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_405_cast_fp16 = select(a = var_9_to_fp16, b = var_1470_cast_fp16, cond = mask_3)[name = string("input_405_cast_fp16")];
            bool x_167_transpose_x_0 = const()[name = string("x_167_transpose_x_0"), val = bool(false)];
            bool x_167_transpose_y_0 = const()[name = string("x_167_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 188, 128]> value_17_cast_fp16 = transpose(perm = value_17_perm_0, x = v_15_cast_fp16)[name = string("transpose_239")];
            tensor<fp16, [1, 8, 188, 128]> x_167_cast_fp16 = matmul(transpose_x = x_167_transpose_x_0, transpose_y = x_167_transpose_y_0, x = input_405_cast_fp16, y = value_17_cast_fp16)[name = string("x_167_cast_fp16")];
            tensor<int32, [4]> var_1474_perm_0 = const()[name = string("op_1474_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1475 = const()[name = string("op_1475"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_1474_cast_fp16 = transpose(perm = var_1474_perm_0, x = x_167_cast_fp16)[name = string("transpose_235")];
            tensor<fp16, [1, 188, 1024]> input_407_cast_fp16 = reshape(shape = var_1475, x = var_1474_cast_fp16)[name = string("input_407_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_7_self_attn_linear_out_weight_to_fp16 = const()[name = string("module_layers_7_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(380110784)))];
            tensor<fp16, [1, 188, 1024]> linear_72_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_7_self_attn_linear_out_weight_to_fp16, x = input_407_cast_fp16)[name = string("linear_72_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_411_cast_fp16 = add(x = input_403_cast_fp16, y = linear_72_cast_fp16)[name = string("input_411_cast_fp16")];
            tensor<int32, [1]> x_171_axes_0 = const()[name = string("x_171_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_7_norm_conv_weight_to_fp16 = const()[name = string("module_layers_7_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(382208000)))];
            tensor<fp16, [1024]> module_layers_7_norm_conv_bias_to_fp16 = const()[name = string("module_layers_7_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(382210112)))];
            tensor<fp16, [1, 188, 1024]> x_171_cast_fp16 = layer_norm(axes = x_171_axes_0, beta = module_layers_7_norm_conv_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_7_norm_conv_weight_to_fp16, x = input_411_cast_fp16)[name = string("x_171_cast_fp16")];
            tensor<int32, [3]> input_413_perm_0 = const()[name = string("input_413_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            string input_415_pad_type_0 = const()[name = string("input_415_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_415_strides_0 = const()[name = string("input_415_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_415_pad_0 = const()[name = string("input_415_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_415_dilations_0 = const()[name = string("input_415_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_415_groups_0 = const()[name = string("input_415_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 1024, 1]> module_layers_7_conv_pointwise_conv1_weight_to_fp16 = const()[name = string("module_layers_7_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(382212224)))];
            tensor<fp16, [1, 1024, 188]> input_413_cast_fp16 = transpose(perm = input_413_perm_0, x = x_171_cast_fp16)[name = string("transpose_234")];
            tensor<fp16, [1, 2048, 188]> input_415_cast_fp16 = conv(dilations = input_415_dilations_0, groups = input_415_groups_0, pad = input_415_pad_0, pad_type = input_415_pad_type_0, strides = input_415_strides_0, weight = module_layers_7_conv_pointwise_conv1_weight_to_fp16, x = input_413_cast_fp16)[name = string("input_415_cast_fp16")];
            int32 x_173_split_num_splits_0 = const()[name = string("x_173_split_num_splits_0"), val = int32(2)];
            int32 x_173_split_axis_0 = const()[name = string("x_173_split_axis_0"), val = int32(1)];
            tensor<fp16, [1, 1024, 188]> x_173_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_173_split_cast_fp16_1 = split(axis = x_173_split_axis_0, num_splits = x_173_split_num_splits_0, x = input_415_cast_fp16)[name = string("x_173_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_173_split_1_sigmoid_cast_fp16 = sigmoid(x = x_173_split_cast_fp16_1)[name = string("x_173_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_173_cast_fp16 = mul(x = x_173_split_cast_fp16_0, y = x_173_split_1_sigmoid_cast_fp16)[name = string("x_173_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_417_cast_fp16 = select(a = var_9_to_fp16, b = x_173_cast_fp16, cond = var_356)[name = string("input_417_cast_fp16")];
            tensor<int32, [6]> input_419_pad_0 = const()[name = string("input_419_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            string input_419_mode_0 = const()[name = string("input_419_mode_0"), val = string("constant")];
            fp16 const_87_to_fp16 = const()[name = string("const_87_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_419_cast_fp16 = pad(constant_val = const_87_to_fp16, mode = input_419_mode_0, pad = input_419_pad_0, x = input_417_cast_fp16)[name = string("input_419_cast_fp16")];
            string input_421_pad_type_0 = const()[name = string("input_421_pad_type_0"), val = string("valid")];
            int32 input_421_groups_0 = const()[name = string("input_421_groups_0"), val = int32(1024)];
            tensor<int32, [1]> input_421_strides_0 = const()[name = string("input_421_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_421_pad_0 = const()[name = string("input_421_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_421_dilations_0 = const()[name = string("input_421_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_262_to_fp16 = const()[name = string("const_262_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(386406592)))];
            tensor<fp16, [1024]> const_263_to_fp16 = const()[name = string("const_263_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(386425088)))];
            tensor<fp16, [1, 1024, 188]> input_423_cast_fp16 = conv(bias = const_263_to_fp16, dilations = input_421_dilations_0, groups = input_421_groups_0, pad = input_421_pad_0, pad_type = input_421_pad_type_0, strides = input_421_strides_0, weight = const_262_to_fp16, x = input_419_cast_fp16)[name = string("input_423_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_425_cast_fp16 = silu(x = input_423_cast_fp16)[name = string("input_425_cast_fp16")];
            string x_175_pad_type_0 = const()[name = string("x_175_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> x_175_strides_0 = const()[name = string("x_175_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_175_pad_0 = const()[name = string("x_175_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_175_dilations_0 = const()[name = string("x_175_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 x_175_groups_0 = const()[name = string("x_175_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 1024, 1]> module_layers_7_conv_pointwise_conv2_weight_to_fp16 = const()[name = string("module_layers_7_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(386427200)))];
            tensor<fp16, [1, 1024, 188]> x_175_cast_fp16 = conv(dilations = x_175_dilations_0, groups = x_175_groups_0, pad = x_175_pad_0, pad_type = x_175_pad_type_0, strides = x_175_strides_0, weight = module_layers_7_conv_pointwise_conv2_weight_to_fp16, x = input_425_cast_fp16)[name = string("x_175_cast_fp16")];
            tensor<int32, [3]> input_427_perm_0 = const()[name = string("input_427_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_427_cast_fp16 = transpose(perm = input_427_perm_0, x = x_175_cast_fp16)[name = string("transpose_233")];
            tensor<fp16, [1, 188, 1024]> input_429_cast_fp16 = add(x = input_411_cast_fp16, y = input_427_cast_fp16)[name = string("input_429_cast_fp16")];
            tensor<int32, [1]> input_431_axes_0 = const()[name = string("input_431_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_7_norm_feed_forward2_weight_to_fp16 = const()[name = string("module_layers_7_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(388524416)))];
            tensor<fp16, [1024]> module_layers_7_norm_feed_forward2_bias_to_fp16 = const()[name = string("module_layers_7_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(388526528)))];
            tensor<fp16, [1, 188, 1024]> input_431_cast_fp16 = layer_norm(axes = input_431_axes_0, beta = module_layers_7_norm_feed_forward2_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_7_norm_feed_forward2_weight_to_fp16, x = input_429_cast_fp16)[name = string("input_431_cast_fp16")];
            tensor<fp16, [4096, 1024]> module_layers_7_feed_forward2_linear1_weight_to_fp16 = const()[name = string("module_layers_7_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(388528640)))];
            tensor<fp16, [1, 188, 4096]> linear_73_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = module_layers_7_feed_forward2_linear1_weight_to_fp16, x = input_431_cast_fp16)[name = string("linear_73_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_435_cast_fp16 = silu(x = linear_73_cast_fp16)[name = string("input_435_cast_fp16")];
            tensor<fp16, [1024, 4096]> module_layers_7_feed_forward2_linear2_weight_to_fp16 = const()[name = string("module_layers_7_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(396917312)))];
            tensor<fp16, [1, 188, 1024]> linear_74_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_7_feed_forward2_linear2_weight_to_fp16, x = input_435_cast_fp16)[name = string("linear_74_cast_fp16")];
            fp16 var_1535_to_fp16 = const()[name = string("op_1535_to_fp16"), val = fp16(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_1536_cast_fp16 = mul(x = linear_74_cast_fp16, y = var_1535_to_fp16)[name = string("op_1536_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_441_cast_fp16 = add(x = input_429_cast_fp16, y = var_1536_cast_fp16)[name = string("input_441_cast_fp16")];
            tensor<int32, [1]> input_443_axes_0 = const()[name = string("input_443_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_7_norm_out_weight_to_fp16 = const()[name = string("module_layers_7_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(405305984)))];
            tensor<fp16, [1024]> module_layers_7_norm_out_bias_to_fp16 = const()[name = string("module_layers_7_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(405308096)))];
            tensor<fp16, [1, 188, 1024]> input_443_cast_fp16 = layer_norm(axes = input_443_axes_0, beta = module_layers_7_norm_out_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_7_norm_out_weight_to_fp16, x = input_441_cast_fp16)[name = string("input_443_cast_fp16")];
            tensor<int32, [1]> input_445_axes_0 = const()[name = string("input_445_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_8_norm_feed_forward1_weight_to_fp16 = const()[name = string("module_layers_8_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(405310208)))];
            tensor<fp16, [1024]> module_layers_8_norm_feed_forward1_bias_to_fp16 = const()[name = string("module_layers_8_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(405312320)))];
            tensor<fp16, [1, 188, 1024]> input_445_cast_fp16 = layer_norm(axes = input_445_axes_0, beta = module_layers_8_norm_feed_forward1_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_8_norm_feed_forward1_weight_to_fp16, x = input_443_cast_fp16)[name = string("input_445_cast_fp16")];
            tensor<fp16, [4096, 1024]> module_layers_8_feed_forward1_linear1_weight_to_fp16 = const()[name = string("module_layers_8_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(405314432)))];
            tensor<fp16, [1, 188, 4096]> linear_75_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = module_layers_8_feed_forward1_linear1_weight_to_fp16, x = input_445_cast_fp16)[name = string("linear_75_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_449_cast_fp16 = silu(x = linear_75_cast_fp16)[name = string("input_449_cast_fp16")];
            tensor<fp16, [1024, 4096]> module_layers_8_feed_forward1_linear2_weight_to_fp16 = const()[name = string("module_layers_8_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(413703104)))];
            tensor<fp16, [1, 188, 1024]> linear_76_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_8_feed_forward1_linear2_weight_to_fp16, x = input_449_cast_fp16)[name = string("linear_76_cast_fp16")];
            fp16 var_1564_to_fp16 = const()[name = string("op_1564_to_fp16"), val = fp16(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_1565_cast_fp16 = mul(x = linear_76_cast_fp16, y = var_1564_to_fp16)[name = string("op_1565_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_455_cast_fp16 = add(x = input_443_cast_fp16, y = var_1565_cast_fp16)[name = string("input_455_cast_fp16")];
            tensor<int32, [1]> query_17_axes_0 = const()[name = string("query_17_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_8_norm_self_att_weight_to_fp16 = const()[name = string("module_layers_8_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(422091776)))];
            tensor<fp16, [1024]> module_layers_8_norm_self_att_bias_to_fp16 = const()[name = string("module_layers_8_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(422093888)))];
            tensor<fp16, [1, 188, 1024]> query_17_cast_fp16 = layer_norm(axes = query_17_axes_0, beta = module_layers_8_norm_self_att_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_8_norm_self_att_weight_to_fp16, x = input_455_cast_fp16)[name = string("query_17_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_8_self_attn_linear_q_weight_to_fp16 = const()[name = string("module_layers_8_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(422096000)))];
            tensor<fp16, [1, 188, 1024]> linear_77_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_8_self_attn_linear_q_weight_to_fp16, x = query_17_cast_fp16)[name = string("linear_77_cast_fp16")];
            tensor<int32, [4]> var_1581 = const()[name = string("op_1581"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_49_cast_fp16 = reshape(shape = var_1581, x = linear_77_cast_fp16)[name = string("q_49_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_8_self_attn_linear_k_weight_to_fp16 = const()[name = string("module_layers_8_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(424193216)))];
            tensor<fp16, [1, 188, 1024]> linear_78_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_8_self_attn_linear_k_weight_to_fp16, x = query_17_cast_fp16)[name = string("linear_78_cast_fp16")];
            tensor<int32, [4]> var_1585 = const()[name = string("op_1585"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_33_cast_fp16 = reshape(shape = var_1585, x = linear_78_cast_fp16)[name = string("k_33_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_8_self_attn_linear_v_weight_to_fp16 = const()[name = string("module_layers_8_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(426290432)))];
            tensor<fp16, [1, 188, 1024]> linear_79_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_8_self_attn_linear_v_weight_to_fp16, x = query_17_cast_fp16)[name = string("linear_79_cast_fp16")];
            tensor<int32, [4]> var_1589 = const()[name = string("op_1589"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_17_cast_fp16 = reshape(shape = var_1589, x = linear_79_cast_fp16)[name = string("v_17_cast_fp16")];
            tensor<int32, [4]> value_19_perm_0 = const()[name = string("value_19_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> module_layers_8_self_attn_pos_bias_u_to_fp16 = const()[name = string("module_layers_8_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(428387648)))];
            tensor<fp16, [1, 188, 8, 128]> var_1601_cast_fp16 = add(x = q_49_cast_fp16, y = module_layers_8_self_attn_pos_bias_u_to_fp16)[name = string("op_1601_cast_fp16")];
            tensor<fp16, [8, 128]> module_layers_8_self_attn_pos_bias_v_to_fp16 = const()[name = string("module_layers_8_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(428389760)))];
            tensor<fp16, [1, 188, 8, 128]> var_1603_cast_fp16 = add(x = q_49_cast_fp16, y = module_layers_8_self_attn_pos_bias_v_to_fp16)[name = string("op_1603_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_17_perm_0 = const()[name = string("q_with_bias_v_17_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            bool x_183_transpose_x_0 = const()[name = string("x_183_transpose_x_0"), val = bool(false)];
            bool x_183_transpose_y_0 = const()[name = string("x_183_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 128, 375]> var_1605_to_fp16 = const()[name = string("op_1605_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(428391872)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_17_cast_fp16 = transpose(perm = q_with_bias_v_17_perm_0, x = var_1603_cast_fp16)[name = string("transpose_231")];
            tensor<fp16, [1, 8, 188, 375]> x_183_cast_fp16 = matmul(transpose_x = x_183_transpose_x_0, transpose_y = x_183_transpose_y_0, x = q_with_bias_v_17_cast_fp16, y = var_1605_to_fp16)[name = string("x_183_cast_fp16")];
            tensor<int32, [8]> x_185_pad_0 = const()[name = string("x_185_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            string x_185_mode_0 = const()[name = string("x_185_mode_0"), val = string("constant")];
            fp16 const_94_to_fp16 = const()[name = string("const_94_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_185_cast_fp16 = pad(constant_val = const_94_to_fp16, mode = x_185_mode_0, pad = x_185_pad_0, x = x_183_cast_fp16)[name = string("x_185_cast_fp16")];
            tensor<int32, [4]> var_1613 = const()[name = string("op_1613"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_187_cast_fp16 = reshape(shape = var_1613, x = x_185_cast_fp16)[name = string("x_187_cast_fp16")];
            tensor<int32, [4]> var_1617_begin_0 = const()[name = string("op_1617_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_1617_end_0 = const()[name = string("op_1617_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_1617_end_mask_0 = const()[name = string("op_1617_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_1617_cast_fp16 = slice_by_index(begin = var_1617_begin_0, end = var_1617_end_0, end_mask = var_1617_end_mask_0, x = x_187_cast_fp16)[name = string("op_1617_cast_fp16")];
            tensor<int32, [4]> var_1618 = const()[name = string("op_1618"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_33_cast_fp16 = reshape(shape = var_1618, x = var_1617_cast_fp16)[name = string("matrix_bd_33_cast_fp16")];
            bool matrix_ac_17_transpose_x_0 = const()[name = string("matrix_ac_17_transpose_x_0"), val = bool(false)];
            bool matrix_ac_17_transpose_y_0 = const()[name = string("matrix_ac_17_transpose_y_0"), val = bool(false)];
            tensor<int32, [4]> transpose_88_perm_0 = const()[name = string("transpose_88_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_89_perm_0 = const()[name = string("transpose_89_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_89 = transpose(perm = transpose_89_perm_0, x = k_33_cast_fp16)[name = string("transpose_229")];
            tensor<fp16, [1, 8, 188, 128]> transpose_88 = transpose(perm = transpose_88_perm_0, x = var_1601_cast_fp16)[name = string("transpose_230")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_17_cast_fp16 = matmul(transpose_x = matrix_ac_17_transpose_x_0, transpose_y = matrix_ac_17_transpose_y_0, x = transpose_88, y = transpose_89)[name = string("matrix_ac_17_cast_fp16")];
            tensor<int32, [4]> matrix_bd_35_begin_0 = const()[name = string("matrix_bd_35_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_35_end_0 = const()[name = string("matrix_bd_35_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_35_end_mask_0 = const()[name = string("matrix_bd_35_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_35_cast_fp16 = slice_by_index(begin = matrix_bd_35_begin_0, end = matrix_bd_35_end_0, end_mask = matrix_bd_35_end_mask_0, x = matrix_bd_33_cast_fp16)[name = string("matrix_bd_35_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_1627_cast_fp16 = add(x = matrix_ac_17_cast_fp16, y = matrix_bd_35_cast_fp16)[name = string("op_1627_cast_fp16")];
            fp16 _inversed_scores_33_y_0_to_fp16 = const()[name = string("_inversed_scores_33_y_0_to_fp16"), val = fp16(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_33_cast_fp16 = mul(x = var_1627_cast_fp16, y = _inversed_scores_33_y_0_to_fp16)[name = string("_inversed_scores_33_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_35_cast_fp16 = select(a = var_10_to_fp16, b = _inversed_scores_33_cast_fp16, cond = mask_3)[name = string("scores_35_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_1633_cast_fp16 = softmax(axis = var_32, x = scores_35_cast_fp16)[name = string("op_1633_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_457_cast_fp16 = select(a = var_9_to_fp16, b = var_1633_cast_fp16, cond = mask_3)[name = string("input_457_cast_fp16")];
            bool x_189_transpose_x_0 = const()[name = string("x_189_transpose_x_0"), val = bool(false)];
            bool x_189_transpose_y_0 = const()[name = string("x_189_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 188, 128]> value_19_cast_fp16 = transpose(perm = value_19_perm_0, x = v_17_cast_fp16)[name = string("transpose_232")];
            tensor<fp16, [1, 8, 188, 128]> x_189_cast_fp16 = matmul(transpose_x = x_189_transpose_x_0, transpose_y = x_189_transpose_y_0, x = input_457_cast_fp16, y = value_19_cast_fp16)[name = string("x_189_cast_fp16")];
            tensor<int32, [4]> var_1637_perm_0 = const()[name = string("op_1637_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1638 = const()[name = string("op_1638"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_1637_cast_fp16 = transpose(perm = var_1637_perm_0, x = x_189_cast_fp16)[name = string("transpose_228")];
            tensor<fp16, [1, 188, 1024]> input_459_cast_fp16 = reshape(shape = var_1638, x = var_1637_cast_fp16)[name = string("input_459_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_8_self_attn_linear_out_weight_to_fp16 = const()[name = string("module_layers_8_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(429159936)))];
            tensor<fp16, [1, 188, 1024]> linear_81_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_8_self_attn_linear_out_weight_to_fp16, x = input_459_cast_fp16)[name = string("linear_81_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_463_cast_fp16 = add(x = input_455_cast_fp16, y = linear_81_cast_fp16)[name = string("input_463_cast_fp16")];
            tensor<int32, [1]> x_193_axes_0 = const()[name = string("x_193_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_8_norm_conv_weight_to_fp16 = const()[name = string("module_layers_8_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(431257152)))];
            tensor<fp16, [1024]> module_layers_8_norm_conv_bias_to_fp16 = const()[name = string("module_layers_8_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(431259264)))];
            tensor<fp16, [1, 188, 1024]> x_193_cast_fp16 = layer_norm(axes = x_193_axes_0, beta = module_layers_8_norm_conv_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_8_norm_conv_weight_to_fp16, x = input_463_cast_fp16)[name = string("x_193_cast_fp16")];
            tensor<int32, [3]> input_465_perm_0 = const()[name = string("input_465_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            string input_467_pad_type_0 = const()[name = string("input_467_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_467_strides_0 = const()[name = string("input_467_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_467_pad_0 = const()[name = string("input_467_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_467_dilations_0 = const()[name = string("input_467_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_467_groups_0 = const()[name = string("input_467_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 1024, 1]> module_layers_8_conv_pointwise_conv1_weight_to_fp16 = const()[name = string("module_layers_8_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(431261376)))];
            tensor<fp16, [1, 1024, 188]> input_465_cast_fp16 = transpose(perm = input_465_perm_0, x = x_193_cast_fp16)[name = string("transpose_227")];
            tensor<fp16, [1, 2048, 188]> input_467_cast_fp16 = conv(dilations = input_467_dilations_0, groups = input_467_groups_0, pad = input_467_pad_0, pad_type = input_467_pad_type_0, strides = input_467_strides_0, weight = module_layers_8_conv_pointwise_conv1_weight_to_fp16, x = input_465_cast_fp16)[name = string("input_467_cast_fp16")];
            int32 x_195_split_num_splits_0 = const()[name = string("x_195_split_num_splits_0"), val = int32(2)];
            int32 x_195_split_axis_0 = const()[name = string("x_195_split_axis_0"), val = int32(1)];
            tensor<fp16, [1, 1024, 188]> x_195_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_195_split_cast_fp16_1 = split(axis = x_195_split_axis_0, num_splits = x_195_split_num_splits_0, x = input_467_cast_fp16)[name = string("x_195_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_195_split_1_sigmoid_cast_fp16 = sigmoid(x = x_195_split_cast_fp16_1)[name = string("x_195_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_195_cast_fp16 = mul(x = x_195_split_cast_fp16_0, y = x_195_split_1_sigmoid_cast_fp16)[name = string("x_195_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_469_cast_fp16 = select(a = var_9_to_fp16, b = x_195_cast_fp16, cond = var_356)[name = string("input_469_cast_fp16")];
            tensor<int32, [6]> input_471_pad_0 = const()[name = string("input_471_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            string input_471_mode_0 = const()[name = string("input_471_mode_0"), val = string("constant")];
            fp16 const_97_to_fp16 = const()[name = string("const_97_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_471_cast_fp16 = pad(constant_val = const_97_to_fp16, mode = input_471_mode_0, pad = input_471_pad_0, x = input_469_cast_fp16)[name = string("input_471_cast_fp16")];
            string input_473_pad_type_0 = const()[name = string("input_473_pad_type_0"), val = string("valid")];
            int32 input_473_groups_0 = const()[name = string("input_473_groups_0"), val = int32(1024)];
            tensor<int32, [1]> input_473_strides_0 = const()[name = string("input_473_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_473_pad_0 = const()[name = string("input_473_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_473_dilations_0 = const()[name = string("input_473_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_264_to_fp16 = const()[name = string("const_264_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(435455744)))];
            tensor<fp16, [1024]> const_265_to_fp16 = const()[name = string("const_265_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(435474240)))];
            tensor<fp16, [1, 1024, 188]> input_475_cast_fp16 = conv(bias = const_265_to_fp16, dilations = input_473_dilations_0, groups = input_473_groups_0, pad = input_473_pad_0, pad_type = input_473_pad_type_0, strides = input_473_strides_0, weight = const_264_to_fp16, x = input_471_cast_fp16)[name = string("input_475_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_477_cast_fp16 = silu(x = input_475_cast_fp16)[name = string("input_477_cast_fp16")];
            string x_197_pad_type_0 = const()[name = string("x_197_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> x_197_strides_0 = const()[name = string("x_197_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_197_pad_0 = const()[name = string("x_197_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_197_dilations_0 = const()[name = string("x_197_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 x_197_groups_0 = const()[name = string("x_197_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 1024, 1]> module_layers_8_conv_pointwise_conv2_weight_to_fp16 = const()[name = string("module_layers_8_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(435476352)))];
            tensor<fp16, [1, 1024, 188]> x_197_cast_fp16 = conv(dilations = x_197_dilations_0, groups = x_197_groups_0, pad = x_197_pad_0, pad_type = x_197_pad_type_0, strides = x_197_strides_0, weight = module_layers_8_conv_pointwise_conv2_weight_to_fp16, x = input_477_cast_fp16)[name = string("x_197_cast_fp16")];
            tensor<int32, [3]> input_479_perm_0 = const()[name = string("input_479_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_479_cast_fp16 = transpose(perm = input_479_perm_0, x = x_197_cast_fp16)[name = string("transpose_226")];
            tensor<fp16, [1, 188, 1024]> input_481_cast_fp16 = add(x = input_463_cast_fp16, y = input_479_cast_fp16)[name = string("input_481_cast_fp16")];
            tensor<int32, [1]> input_483_axes_0 = const()[name = string("input_483_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_8_norm_feed_forward2_weight_to_fp16 = const()[name = string("module_layers_8_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(437573568)))];
            tensor<fp16, [1024]> module_layers_8_norm_feed_forward2_bias_to_fp16 = const()[name = string("module_layers_8_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(437575680)))];
            tensor<fp16, [1, 188, 1024]> input_483_cast_fp16 = layer_norm(axes = input_483_axes_0, beta = module_layers_8_norm_feed_forward2_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_8_norm_feed_forward2_weight_to_fp16, x = input_481_cast_fp16)[name = string("input_483_cast_fp16")];
            tensor<fp16, [4096, 1024]> module_layers_8_feed_forward2_linear1_weight_to_fp16 = const()[name = string("module_layers_8_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(437577792)))];
            tensor<fp16, [1, 188, 4096]> linear_82_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = module_layers_8_feed_forward2_linear1_weight_to_fp16, x = input_483_cast_fp16)[name = string("linear_82_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_487_cast_fp16 = silu(x = linear_82_cast_fp16)[name = string("input_487_cast_fp16")];
            tensor<fp16, [1024, 4096]> module_layers_8_feed_forward2_linear2_weight_to_fp16 = const()[name = string("module_layers_8_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(445966464)))];
            tensor<fp16, [1, 188, 1024]> linear_83_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_8_feed_forward2_linear2_weight_to_fp16, x = input_487_cast_fp16)[name = string("linear_83_cast_fp16")];
            fp16 var_1698_to_fp16 = const()[name = string("op_1698_to_fp16"), val = fp16(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_1699_cast_fp16 = mul(x = linear_83_cast_fp16, y = var_1698_to_fp16)[name = string("op_1699_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_493_cast_fp16 = add(x = input_481_cast_fp16, y = var_1699_cast_fp16)[name = string("input_493_cast_fp16")];
            tensor<int32, [1]> input_495_axes_0 = const()[name = string("input_495_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_8_norm_out_weight_to_fp16 = const()[name = string("module_layers_8_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(454355136)))];
            tensor<fp16, [1024]> module_layers_8_norm_out_bias_to_fp16 = const()[name = string("module_layers_8_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(454357248)))];
            tensor<fp16, [1, 188, 1024]> input_495_cast_fp16 = layer_norm(axes = input_495_axes_0, beta = module_layers_8_norm_out_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_8_norm_out_weight_to_fp16, x = input_493_cast_fp16)[name = string("input_495_cast_fp16")];
            tensor<int32, [1]> input_497_axes_0 = const()[name = string("input_497_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_9_norm_feed_forward1_weight_to_fp16 = const()[name = string("module_layers_9_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(454359360)))];
            tensor<fp16, [1024]> module_layers_9_norm_feed_forward1_bias_to_fp16 = const()[name = string("module_layers_9_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(454361472)))];
            tensor<fp16, [1, 188, 1024]> input_497_cast_fp16 = layer_norm(axes = input_497_axes_0, beta = module_layers_9_norm_feed_forward1_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_9_norm_feed_forward1_weight_to_fp16, x = input_495_cast_fp16)[name = string("input_497_cast_fp16")];
            tensor<fp16, [4096, 1024]> module_layers_9_feed_forward1_linear1_weight_to_fp16 = const()[name = string("module_layers_9_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(454363584)))];
            tensor<fp16, [1, 188, 4096]> linear_84_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = module_layers_9_feed_forward1_linear1_weight_to_fp16, x = input_497_cast_fp16)[name = string("linear_84_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_501_cast_fp16 = silu(x = linear_84_cast_fp16)[name = string("input_501_cast_fp16")];
            tensor<fp16, [1024, 4096]> module_layers_9_feed_forward1_linear2_weight_to_fp16 = const()[name = string("module_layers_9_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(462752256)))];
            tensor<fp16, [1, 188, 1024]> linear_85_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_9_feed_forward1_linear2_weight_to_fp16, x = input_501_cast_fp16)[name = string("linear_85_cast_fp16")];
            fp16 var_1727_to_fp16 = const()[name = string("op_1727_to_fp16"), val = fp16(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_1728_cast_fp16 = mul(x = linear_85_cast_fp16, y = var_1727_to_fp16)[name = string("op_1728_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_507_cast_fp16 = add(x = input_495_cast_fp16, y = var_1728_cast_fp16)[name = string("input_507_cast_fp16")];
            tensor<int32, [1]> query_19_axes_0 = const()[name = string("query_19_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_9_norm_self_att_weight_to_fp16 = const()[name = string("module_layers_9_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(471140928)))];
            tensor<fp16, [1024]> module_layers_9_norm_self_att_bias_to_fp16 = const()[name = string("module_layers_9_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(471143040)))];
            tensor<fp16, [1, 188, 1024]> query_19_cast_fp16 = layer_norm(axes = query_19_axes_0, beta = module_layers_9_norm_self_att_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_9_norm_self_att_weight_to_fp16, x = input_507_cast_fp16)[name = string("query_19_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_9_self_attn_linear_q_weight_to_fp16 = const()[name = string("module_layers_9_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(471145152)))];
            tensor<fp16, [1, 188, 1024]> linear_86_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_9_self_attn_linear_q_weight_to_fp16, x = query_19_cast_fp16)[name = string("linear_86_cast_fp16")];
            tensor<int32, [4]> var_1744 = const()[name = string("op_1744"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_55_cast_fp16 = reshape(shape = var_1744, x = linear_86_cast_fp16)[name = string("q_55_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_9_self_attn_linear_k_weight_to_fp16 = const()[name = string("module_layers_9_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(473242368)))];
            tensor<fp16, [1, 188, 1024]> linear_87_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_9_self_attn_linear_k_weight_to_fp16, x = query_19_cast_fp16)[name = string("linear_87_cast_fp16")];
            tensor<int32, [4]> var_1748 = const()[name = string("op_1748"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_37_cast_fp16 = reshape(shape = var_1748, x = linear_87_cast_fp16)[name = string("k_37_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_9_self_attn_linear_v_weight_to_fp16 = const()[name = string("module_layers_9_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(475339584)))];
            tensor<fp16, [1, 188, 1024]> linear_88_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_9_self_attn_linear_v_weight_to_fp16, x = query_19_cast_fp16)[name = string("linear_88_cast_fp16")];
            tensor<int32, [4]> var_1752 = const()[name = string("op_1752"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_19_cast_fp16 = reshape(shape = var_1752, x = linear_88_cast_fp16)[name = string("v_19_cast_fp16")];
            tensor<int32, [4]> value_21_perm_0 = const()[name = string("value_21_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> module_layers_9_self_attn_pos_bias_u_to_fp16 = const()[name = string("module_layers_9_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(477436800)))];
            tensor<fp16, [1, 188, 8, 128]> var_1764_cast_fp16 = add(x = q_55_cast_fp16, y = module_layers_9_self_attn_pos_bias_u_to_fp16)[name = string("op_1764_cast_fp16")];
            tensor<fp16, [8, 128]> module_layers_9_self_attn_pos_bias_v_to_fp16 = const()[name = string("module_layers_9_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(477438912)))];
            tensor<fp16, [1, 188, 8, 128]> var_1766_cast_fp16 = add(x = q_55_cast_fp16, y = module_layers_9_self_attn_pos_bias_v_to_fp16)[name = string("op_1766_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_19_perm_0 = const()[name = string("q_with_bias_v_19_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            bool x_205_transpose_x_0 = const()[name = string("x_205_transpose_x_0"), val = bool(false)];
            bool x_205_transpose_y_0 = const()[name = string("x_205_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 128, 375]> var_1768_to_fp16 = const()[name = string("op_1768_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(477441024)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_19_cast_fp16 = transpose(perm = q_with_bias_v_19_perm_0, x = var_1766_cast_fp16)[name = string("transpose_224")];
            tensor<fp16, [1, 8, 188, 375]> x_205_cast_fp16 = matmul(transpose_x = x_205_transpose_x_0, transpose_y = x_205_transpose_y_0, x = q_with_bias_v_19_cast_fp16, y = var_1768_to_fp16)[name = string("x_205_cast_fp16")];
            tensor<int32, [8]> x_207_pad_0 = const()[name = string("x_207_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            string x_207_mode_0 = const()[name = string("x_207_mode_0"), val = string("constant")];
            fp16 const_104_to_fp16 = const()[name = string("const_104_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_207_cast_fp16 = pad(constant_val = const_104_to_fp16, mode = x_207_mode_0, pad = x_207_pad_0, x = x_205_cast_fp16)[name = string("x_207_cast_fp16")];
            tensor<int32, [4]> var_1776 = const()[name = string("op_1776"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_209_cast_fp16 = reshape(shape = var_1776, x = x_207_cast_fp16)[name = string("x_209_cast_fp16")];
            tensor<int32, [4]> var_1780_begin_0 = const()[name = string("op_1780_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_1780_end_0 = const()[name = string("op_1780_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_1780_end_mask_0 = const()[name = string("op_1780_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_1780_cast_fp16 = slice_by_index(begin = var_1780_begin_0, end = var_1780_end_0, end_mask = var_1780_end_mask_0, x = x_209_cast_fp16)[name = string("op_1780_cast_fp16")];
            tensor<int32, [4]> var_1781 = const()[name = string("op_1781"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_37_cast_fp16 = reshape(shape = var_1781, x = var_1780_cast_fp16)[name = string("matrix_bd_37_cast_fp16")];
            bool matrix_ac_19_transpose_x_0 = const()[name = string("matrix_ac_19_transpose_x_0"), val = bool(false)];
            bool matrix_ac_19_transpose_y_0 = const()[name = string("matrix_ac_19_transpose_y_0"), val = bool(false)];
            tensor<int32, [4]> transpose_90_perm_0 = const()[name = string("transpose_90_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_91_perm_0 = const()[name = string("transpose_91_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_91 = transpose(perm = transpose_91_perm_0, x = k_37_cast_fp16)[name = string("transpose_222")];
            tensor<fp16, [1, 8, 188, 128]> transpose_90 = transpose(perm = transpose_90_perm_0, x = var_1764_cast_fp16)[name = string("transpose_223")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_19_cast_fp16 = matmul(transpose_x = matrix_ac_19_transpose_x_0, transpose_y = matrix_ac_19_transpose_y_0, x = transpose_90, y = transpose_91)[name = string("matrix_ac_19_cast_fp16")];
            tensor<int32, [4]> matrix_bd_39_begin_0 = const()[name = string("matrix_bd_39_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_39_end_0 = const()[name = string("matrix_bd_39_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_39_end_mask_0 = const()[name = string("matrix_bd_39_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_39_cast_fp16 = slice_by_index(begin = matrix_bd_39_begin_0, end = matrix_bd_39_end_0, end_mask = matrix_bd_39_end_mask_0, x = matrix_bd_37_cast_fp16)[name = string("matrix_bd_39_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_1790_cast_fp16 = add(x = matrix_ac_19_cast_fp16, y = matrix_bd_39_cast_fp16)[name = string("op_1790_cast_fp16")];
            fp16 _inversed_scores_37_y_0_to_fp16 = const()[name = string("_inversed_scores_37_y_0_to_fp16"), val = fp16(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_37_cast_fp16 = mul(x = var_1790_cast_fp16, y = _inversed_scores_37_y_0_to_fp16)[name = string("_inversed_scores_37_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_39_cast_fp16 = select(a = var_10_to_fp16, b = _inversed_scores_37_cast_fp16, cond = mask_3)[name = string("scores_39_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_1796_cast_fp16 = softmax(axis = var_32, x = scores_39_cast_fp16)[name = string("op_1796_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_509_cast_fp16 = select(a = var_9_to_fp16, b = var_1796_cast_fp16, cond = mask_3)[name = string("input_509_cast_fp16")];
            bool x_211_transpose_x_0 = const()[name = string("x_211_transpose_x_0"), val = bool(false)];
            bool x_211_transpose_y_0 = const()[name = string("x_211_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 188, 128]> value_21_cast_fp16 = transpose(perm = value_21_perm_0, x = v_19_cast_fp16)[name = string("transpose_225")];
            tensor<fp16, [1, 8, 188, 128]> x_211_cast_fp16 = matmul(transpose_x = x_211_transpose_x_0, transpose_y = x_211_transpose_y_0, x = input_509_cast_fp16, y = value_21_cast_fp16)[name = string("x_211_cast_fp16")];
            tensor<int32, [4]> var_1800_perm_0 = const()[name = string("op_1800_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1801 = const()[name = string("op_1801"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_1800_cast_fp16 = transpose(perm = var_1800_perm_0, x = x_211_cast_fp16)[name = string("transpose_221")];
            tensor<fp16, [1, 188, 1024]> input_511_cast_fp16 = reshape(shape = var_1801, x = var_1800_cast_fp16)[name = string("input_511_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_9_self_attn_linear_out_weight_to_fp16 = const()[name = string("module_layers_9_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(478209088)))];
            tensor<fp16, [1, 188, 1024]> linear_90_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_9_self_attn_linear_out_weight_to_fp16, x = input_511_cast_fp16)[name = string("linear_90_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_515_cast_fp16 = add(x = input_507_cast_fp16, y = linear_90_cast_fp16)[name = string("input_515_cast_fp16")];
            tensor<int32, [1]> x_215_axes_0 = const()[name = string("x_215_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_9_norm_conv_weight_to_fp16 = const()[name = string("module_layers_9_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(480306304)))];
            tensor<fp16, [1024]> module_layers_9_norm_conv_bias_to_fp16 = const()[name = string("module_layers_9_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(480308416)))];
            tensor<fp16, [1, 188, 1024]> x_215_cast_fp16 = layer_norm(axes = x_215_axes_0, beta = module_layers_9_norm_conv_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_9_norm_conv_weight_to_fp16, x = input_515_cast_fp16)[name = string("x_215_cast_fp16")];
            tensor<int32, [3]> input_517_perm_0 = const()[name = string("input_517_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            string input_519_pad_type_0 = const()[name = string("input_519_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_519_strides_0 = const()[name = string("input_519_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_519_pad_0 = const()[name = string("input_519_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_519_dilations_0 = const()[name = string("input_519_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_519_groups_0 = const()[name = string("input_519_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 1024, 1]> module_layers_9_conv_pointwise_conv1_weight_to_fp16 = const()[name = string("module_layers_9_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(480310528)))];
            tensor<fp16, [1, 1024, 188]> input_517_cast_fp16 = transpose(perm = input_517_perm_0, x = x_215_cast_fp16)[name = string("transpose_220")];
            tensor<fp16, [1, 2048, 188]> input_519_cast_fp16 = conv(dilations = input_519_dilations_0, groups = input_519_groups_0, pad = input_519_pad_0, pad_type = input_519_pad_type_0, strides = input_519_strides_0, weight = module_layers_9_conv_pointwise_conv1_weight_to_fp16, x = input_517_cast_fp16)[name = string("input_519_cast_fp16")];
            int32 x_217_split_num_splits_0 = const()[name = string("x_217_split_num_splits_0"), val = int32(2)];
            int32 x_217_split_axis_0 = const()[name = string("x_217_split_axis_0"), val = int32(1)];
            tensor<fp16, [1, 1024, 188]> x_217_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_217_split_cast_fp16_1 = split(axis = x_217_split_axis_0, num_splits = x_217_split_num_splits_0, x = input_519_cast_fp16)[name = string("x_217_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_217_split_1_sigmoid_cast_fp16 = sigmoid(x = x_217_split_cast_fp16_1)[name = string("x_217_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_217_cast_fp16 = mul(x = x_217_split_cast_fp16_0, y = x_217_split_1_sigmoid_cast_fp16)[name = string("x_217_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_521_cast_fp16 = select(a = var_9_to_fp16, b = x_217_cast_fp16, cond = var_356)[name = string("input_521_cast_fp16")];
            tensor<int32, [6]> input_523_pad_0 = const()[name = string("input_523_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            string input_523_mode_0 = const()[name = string("input_523_mode_0"), val = string("constant")];
            fp16 const_107_to_fp16 = const()[name = string("const_107_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_523_cast_fp16 = pad(constant_val = const_107_to_fp16, mode = input_523_mode_0, pad = input_523_pad_0, x = input_521_cast_fp16)[name = string("input_523_cast_fp16")];
            string input_525_pad_type_0 = const()[name = string("input_525_pad_type_0"), val = string("valid")];
            int32 input_525_groups_0 = const()[name = string("input_525_groups_0"), val = int32(1024)];
            tensor<int32, [1]> input_525_strides_0 = const()[name = string("input_525_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_525_pad_0 = const()[name = string("input_525_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_525_dilations_0 = const()[name = string("input_525_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_266_to_fp16 = const()[name = string("const_266_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(484504896)))];
            tensor<fp16, [1024]> const_267_to_fp16 = const()[name = string("const_267_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(484523392)))];
            tensor<fp16, [1, 1024, 188]> input_527_cast_fp16 = conv(bias = const_267_to_fp16, dilations = input_525_dilations_0, groups = input_525_groups_0, pad = input_525_pad_0, pad_type = input_525_pad_type_0, strides = input_525_strides_0, weight = const_266_to_fp16, x = input_523_cast_fp16)[name = string("input_527_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_529_cast_fp16 = silu(x = input_527_cast_fp16)[name = string("input_529_cast_fp16")];
            string x_219_pad_type_0 = const()[name = string("x_219_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> x_219_strides_0 = const()[name = string("x_219_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_219_pad_0 = const()[name = string("x_219_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_219_dilations_0 = const()[name = string("x_219_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 x_219_groups_0 = const()[name = string("x_219_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 1024, 1]> module_layers_9_conv_pointwise_conv2_weight_to_fp16 = const()[name = string("module_layers_9_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(484525504)))];
            tensor<fp16, [1, 1024, 188]> x_219_cast_fp16 = conv(dilations = x_219_dilations_0, groups = x_219_groups_0, pad = x_219_pad_0, pad_type = x_219_pad_type_0, strides = x_219_strides_0, weight = module_layers_9_conv_pointwise_conv2_weight_to_fp16, x = input_529_cast_fp16)[name = string("x_219_cast_fp16")];
            tensor<int32, [3]> input_531_perm_0 = const()[name = string("input_531_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_531_cast_fp16 = transpose(perm = input_531_perm_0, x = x_219_cast_fp16)[name = string("transpose_219")];
            tensor<fp16, [1, 188, 1024]> input_533_cast_fp16 = add(x = input_515_cast_fp16, y = input_531_cast_fp16)[name = string("input_533_cast_fp16")];
            tensor<int32, [1]> input_535_axes_0 = const()[name = string("input_535_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_9_norm_feed_forward2_weight_to_fp16 = const()[name = string("module_layers_9_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(486622720)))];
            tensor<fp16, [1024]> module_layers_9_norm_feed_forward2_bias_to_fp16 = const()[name = string("module_layers_9_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(486624832)))];
            tensor<fp16, [1, 188, 1024]> input_535_cast_fp16 = layer_norm(axes = input_535_axes_0, beta = module_layers_9_norm_feed_forward2_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_9_norm_feed_forward2_weight_to_fp16, x = input_533_cast_fp16)[name = string("input_535_cast_fp16")];
            tensor<fp16, [4096, 1024]> module_layers_9_feed_forward2_linear1_weight_to_fp16 = const()[name = string("module_layers_9_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(486626944)))];
            tensor<fp16, [1, 188, 4096]> linear_91_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = module_layers_9_feed_forward2_linear1_weight_to_fp16, x = input_535_cast_fp16)[name = string("linear_91_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_539_cast_fp16 = silu(x = linear_91_cast_fp16)[name = string("input_539_cast_fp16")];
            tensor<fp16, [1024, 4096]> module_layers_9_feed_forward2_linear2_weight_to_fp16 = const()[name = string("module_layers_9_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(495015616)))];
            tensor<fp16, [1, 188, 1024]> linear_92_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_9_feed_forward2_linear2_weight_to_fp16, x = input_539_cast_fp16)[name = string("linear_92_cast_fp16")];
            fp16 var_1861_to_fp16 = const()[name = string("op_1861_to_fp16"), val = fp16(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_1862_cast_fp16 = mul(x = linear_92_cast_fp16, y = var_1861_to_fp16)[name = string("op_1862_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_545_cast_fp16 = add(x = input_533_cast_fp16, y = var_1862_cast_fp16)[name = string("input_545_cast_fp16")];
            tensor<int32, [1]> input_547_axes_0 = const()[name = string("input_547_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_9_norm_out_weight_to_fp16 = const()[name = string("module_layers_9_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(503404288)))];
            tensor<fp16, [1024]> module_layers_9_norm_out_bias_to_fp16 = const()[name = string("module_layers_9_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(503406400)))];
            tensor<fp16, [1, 188, 1024]> input_547_cast_fp16 = layer_norm(axes = input_547_axes_0, beta = module_layers_9_norm_out_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_9_norm_out_weight_to_fp16, x = input_545_cast_fp16)[name = string("input_547_cast_fp16")];
            tensor<int32, [1]> input_549_axes_0 = const()[name = string("input_549_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_10_norm_feed_forward1_weight_to_fp16 = const()[name = string("module_layers_10_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(503408512)))];
            tensor<fp16, [1024]> module_layers_10_norm_feed_forward1_bias_to_fp16 = const()[name = string("module_layers_10_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(503410624)))];
            tensor<fp16, [1, 188, 1024]> input_549_cast_fp16 = layer_norm(axes = input_549_axes_0, beta = module_layers_10_norm_feed_forward1_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_10_norm_feed_forward1_weight_to_fp16, x = input_547_cast_fp16)[name = string("input_549_cast_fp16")];
            tensor<fp16, [4096, 1024]> module_layers_10_feed_forward1_linear1_weight_to_fp16 = const()[name = string("module_layers_10_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(503412736)))];
            tensor<fp16, [1, 188, 4096]> linear_93_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = module_layers_10_feed_forward1_linear1_weight_to_fp16, x = input_549_cast_fp16)[name = string("linear_93_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_553_cast_fp16 = silu(x = linear_93_cast_fp16)[name = string("input_553_cast_fp16")];
            tensor<fp16, [1024, 4096]> module_layers_10_feed_forward1_linear2_weight_to_fp16 = const()[name = string("module_layers_10_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(511801408)))];
            tensor<fp16, [1, 188, 1024]> linear_94_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_10_feed_forward1_linear2_weight_to_fp16, x = input_553_cast_fp16)[name = string("linear_94_cast_fp16")];
            fp16 var_1890_to_fp16 = const()[name = string("op_1890_to_fp16"), val = fp16(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_1891_cast_fp16 = mul(x = linear_94_cast_fp16, y = var_1890_to_fp16)[name = string("op_1891_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_559_cast_fp16 = add(x = input_547_cast_fp16, y = var_1891_cast_fp16)[name = string("input_559_cast_fp16")];
            tensor<int32, [1]> query_21_axes_0 = const()[name = string("query_21_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_10_norm_self_att_weight_to_fp16 = const()[name = string("module_layers_10_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(520190080)))];
            tensor<fp16, [1024]> module_layers_10_norm_self_att_bias_to_fp16 = const()[name = string("module_layers_10_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(520192192)))];
            tensor<fp16, [1, 188, 1024]> query_21_cast_fp16 = layer_norm(axes = query_21_axes_0, beta = module_layers_10_norm_self_att_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_10_norm_self_att_weight_to_fp16, x = input_559_cast_fp16)[name = string("query_21_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_10_self_attn_linear_q_weight_to_fp16 = const()[name = string("module_layers_10_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(520194304)))];
            tensor<fp16, [1, 188, 1024]> linear_95_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_10_self_attn_linear_q_weight_to_fp16, x = query_21_cast_fp16)[name = string("linear_95_cast_fp16")];
            tensor<int32, [4]> var_1907 = const()[name = string("op_1907"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_61_cast_fp16 = reshape(shape = var_1907, x = linear_95_cast_fp16)[name = string("q_61_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_10_self_attn_linear_k_weight_to_fp16 = const()[name = string("module_layers_10_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(522291520)))];
            tensor<fp16, [1, 188, 1024]> linear_96_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_10_self_attn_linear_k_weight_to_fp16, x = query_21_cast_fp16)[name = string("linear_96_cast_fp16")];
            tensor<int32, [4]> var_1911 = const()[name = string("op_1911"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_41_cast_fp16 = reshape(shape = var_1911, x = linear_96_cast_fp16)[name = string("k_41_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_10_self_attn_linear_v_weight_to_fp16 = const()[name = string("module_layers_10_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(524388736)))];
            tensor<fp16, [1, 188, 1024]> linear_97_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_10_self_attn_linear_v_weight_to_fp16, x = query_21_cast_fp16)[name = string("linear_97_cast_fp16")];
            tensor<int32, [4]> var_1915 = const()[name = string("op_1915"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_21_cast_fp16 = reshape(shape = var_1915, x = linear_97_cast_fp16)[name = string("v_21_cast_fp16")];
            tensor<int32, [4]> value_23_perm_0 = const()[name = string("value_23_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> module_layers_10_self_attn_pos_bias_u_to_fp16 = const()[name = string("module_layers_10_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(526485952)))];
            tensor<fp16, [1, 188, 8, 128]> var_1927_cast_fp16 = add(x = q_61_cast_fp16, y = module_layers_10_self_attn_pos_bias_u_to_fp16)[name = string("op_1927_cast_fp16")];
            tensor<fp16, [8, 128]> module_layers_10_self_attn_pos_bias_v_to_fp16 = const()[name = string("module_layers_10_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(526488064)))];
            tensor<fp16, [1, 188, 8, 128]> var_1929_cast_fp16 = add(x = q_61_cast_fp16, y = module_layers_10_self_attn_pos_bias_v_to_fp16)[name = string("op_1929_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_21_perm_0 = const()[name = string("q_with_bias_v_21_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            bool x_227_transpose_x_0 = const()[name = string("x_227_transpose_x_0"), val = bool(false)];
            bool x_227_transpose_y_0 = const()[name = string("x_227_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 128, 375]> var_1931_to_fp16 = const()[name = string("op_1931_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(526490176)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_21_cast_fp16 = transpose(perm = q_with_bias_v_21_perm_0, x = var_1929_cast_fp16)[name = string("transpose_217")];
            tensor<fp16, [1, 8, 188, 375]> x_227_cast_fp16 = matmul(transpose_x = x_227_transpose_x_0, transpose_y = x_227_transpose_y_0, x = q_with_bias_v_21_cast_fp16, y = var_1931_to_fp16)[name = string("x_227_cast_fp16")];
            tensor<int32, [8]> x_229_pad_0 = const()[name = string("x_229_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            string x_229_mode_0 = const()[name = string("x_229_mode_0"), val = string("constant")];
            fp16 const_114_to_fp16 = const()[name = string("const_114_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_229_cast_fp16 = pad(constant_val = const_114_to_fp16, mode = x_229_mode_0, pad = x_229_pad_0, x = x_227_cast_fp16)[name = string("x_229_cast_fp16")];
            tensor<int32, [4]> var_1939 = const()[name = string("op_1939"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_231_cast_fp16 = reshape(shape = var_1939, x = x_229_cast_fp16)[name = string("x_231_cast_fp16")];
            tensor<int32, [4]> var_1943_begin_0 = const()[name = string("op_1943_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_1943_end_0 = const()[name = string("op_1943_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_1943_end_mask_0 = const()[name = string("op_1943_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_1943_cast_fp16 = slice_by_index(begin = var_1943_begin_0, end = var_1943_end_0, end_mask = var_1943_end_mask_0, x = x_231_cast_fp16)[name = string("op_1943_cast_fp16")];
            tensor<int32, [4]> var_1944 = const()[name = string("op_1944"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_41_cast_fp16 = reshape(shape = var_1944, x = var_1943_cast_fp16)[name = string("matrix_bd_41_cast_fp16")];
            bool matrix_ac_21_transpose_x_0 = const()[name = string("matrix_ac_21_transpose_x_0"), val = bool(false)];
            bool matrix_ac_21_transpose_y_0 = const()[name = string("matrix_ac_21_transpose_y_0"), val = bool(false)];
            tensor<int32, [4]> transpose_92_perm_0 = const()[name = string("transpose_92_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_93_perm_0 = const()[name = string("transpose_93_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_93 = transpose(perm = transpose_93_perm_0, x = k_41_cast_fp16)[name = string("transpose_215")];
            tensor<fp16, [1, 8, 188, 128]> transpose_92 = transpose(perm = transpose_92_perm_0, x = var_1927_cast_fp16)[name = string("transpose_216")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_21_cast_fp16 = matmul(transpose_x = matrix_ac_21_transpose_x_0, transpose_y = matrix_ac_21_transpose_y_0, x = transpose_92, y = transpose_93)[name = string("matrix_ac_21_cast_fp16")];
            tensor<int32, [4]> matrix_bd_43_begin_0 = const()[name = string("matrix_bd_43_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_43_end_0 = const()[name = string("matrix_bd_43_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_43_end_mask_0 = const()[name = string("matrix_bd_43_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_43_cast_fp16 = slice_by_index(begin = matrix_bd_43_begin_0, end = matrix_bd_43_end_0, end_mask = matrix_bd_43_end_mask_0, x = matrix_bd_41_cast_fp16)[name = string("matrix_bd_43_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_1953_cast_fp16 = add(x = matrix_ac_21_cast_fp16, y = matrix_bd_43_cast_fp16)[name = string("op_1953_cast_fp16")];
            fp16 _inversed_scores_41_y_0_to_fp16 = const()[name = string("_inversed_scores_41_y_0_to_fp16"), val = fp16(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_41_cast_fp16 = mul(x = var_1953_cast_fp16, y = _inversed_scores_41_y_0_to_fp16)[name = string("_inversed_scores_41_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_43_cast_fp16 = select(a = var_10_to_fp16, b = _inversed_scores_41_cast_fp16, cond = mask_3)[name = string("scores_43_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_1959_cast_fp16 = softmax(axis = var_32, x = scores_43_cast_fp16)[name = string("op_1959_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_561_cast_fp16 = select(a = var_9_to_fp16, b = var_1959_cast_fp16, cond = mask_3)[name = string("input_561_cast_fp16")];
            bool x_233_transpose_x_0 = const()[name = string("x_233_transpose_x_0"), val = bool(false)];
            bool x_233_transpose_y_0 = const()[name = string("x_233_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 188, 128]> value_23_cast_fp16 = transpose(perm = value_23_perm_0, x = v_21_cast_fp16)[name = string("transpose_218")];
            tensor<fp16, [1, 8, 188, 128]> x_233_cast_fp16 = matmul(transpose_x = x_233_transpose_x_0, transpose_y = x_233_transpose_y_0, x = input_561_cast_fp16, y = value_23_cast_fp16)[name = string("x_233_cast_fp16")];
            tensor<int32, [4]> var_1963_perm_0 = const()[name = string("op_1963_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1964 = const()[name = string("op_1964"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_1963_cast_fp16 = transpose(perm = var_1963_perm_0, x = x_233_cast_fp16)[name = string("transpose_214")];
            tensor<fp16, [1, 188, 1024]> input_563_cast_fp16 = reshape(shape = var_1964, x = var_1963_cast_fp16)[name = string("input_563_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_10_self_attn_linear_out_weight_to_fp16 = const()[name = string("module_layers_10_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(527258240)))];
            tensor<fp16, [1, 188, 1024]> linear_99_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_10_self_attn_linear_out_weight_to_fp16, x = input_563_cast_fp16)[name = string("linear_99_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_567_cast_fp16 = add(x = input_559_cast_fp16, y = linear_99_cast_fp16)[name = string("input_567_cast_fp16")];
            tensor<int32, [1]> x_237_axes_0 = const()[name = string("x_237_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_10_norm_conv_weight_to_fp16 = const()[name = string("module_layers_10_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(529355456)))];
            tensor<fp16, [1024]> module_layers_10_norm_conv_bias_to_fp16 = const()[name = string("module_layers_10_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(529357568)))];
            tensor<fp16, [1, 188, 1024]> x_237_cast_fp16 = layer_norm(axes = x_237_axes_0, beta = module_layers_10_norm_conv_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_10_norm_conv_weight_to_fp16, x = input_567_cast_fp16)[name = string("x_237_cast_fp16")];
            tensor<int32, [3]> input_569_perm_0 = const()[name = string("input_569_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            string input_571_pad_type_0 = const()[name = string("input_571_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_571_strides_0 = const()[name = string("input_571_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_571_pad_0 = const()[name = string("input_571_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_571_dilations_0 = const()[name = string("input_571_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_571_groups_0 = const()[name = string("input_571_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 1024, 1]> module_layers_10_conv_pointwise_conv1_weight_to_fp16 = const()[name = string("module_layers_10_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(529359680)))];
            tensor<fp16, [1, 1024, 188]> input_569_cast_fp16 = transpose(perm = input_569_perm_0, x = x_237_cast_fp16)[name = string("transpose_213")];
            tensor<fp16, [1, 2048, 188]> input_571_cast_fp16 = conv(dilations = input_571_dilations_0, groups = input_571_groups_0, pad = input_571_pad_0, pad_type = input_571_pad_type_0, strides = input_571_strides_0, weight = module_layers_10_conv_pointwise_conv1_weight_to_fp16, x = input_569_cast_fp16)[name = string("input_571_cast_fp16")];
            int32 x_239_split_num_splits_0 = const()[name = string("x_239_split_num_splits_0"), val = int32(2)];
            int32 x_239_split_axis_0 = const()[name = string("x_239_split_axis_0"), val = int32(1)];
            tensor<fp16, [1, 1024, 188]> x_239_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_239_split_cast_fp16_1 = split(axis = x_239_split_axis_0, num_splits = x_239_split_num_splits_0, x = input_571_cast_fp16)[name = string("x_239_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_239_split_1_sigmoid_cast_fp16 = sigmoid(x = x_239_split_cast_fp16_1)[name = string("x_239_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_239_cast_fp16 = mul(x = x_239_split_cast_fp16_0, y = x_239_split_1_sigmoid_cast_fp16)[name = string("x_239_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_573_cast_fp16 = select(a = var_9_to_fp16, b = x_239_cast_fp16, cond = var_356)[name = string("input_573_cast_fp16")];
            tensor<int32, [6]> input_575_pad_0 = const()[name = string("input_575_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            string input_575_mode_0 = const()[name = string("input_575_mode_0"), val = string("constant")];
            fp16 const_117_to_fp16 = const()[name = string("const_117_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_575_cast_fp16 = pad(constant_val = const_117_to_fp16, mode = input_575_mode_0, pad = input_575_pad_0, x = input_573_cast_fp16)[name = string("input_575_cast_fp16")];
            string input_577_pad_type_0 = const()[name = string("input_577_pad_type_0"), val = string("valid")];
            int32 input_577_groups_0 = const()[name = string("input_577_groups_0"), val = int32(1024)];
            tensor<int32, [1]> input_577_strides_0 = const()[name = string("input_577_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_577_pad_0 = const()[name = string("input_577_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_577_dilations_0 = const()[name = string("input_577_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_268_to_fp16 = const()[name = string("const_268_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(533554048)))];
            tensor<fp16, [1024]> const_269_to_fp16 = const()[name = string("const_269_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(533572544)))];
            tensor<fp16, [1, 1024, 188]> input_579_cast_fp16 = conv(bias = const_269_to_fp16, dilations = input_577_dilations_0, groups = input_577_groups_0, pad = input_577_pad_0, pad_type = input_577_pad_type_0, strides = input_577_strides_0, weight = const_268_to_fp16, x = input_575_cast_fp16)[name = string("input_579_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_581_cast_fp16 = silu(x = input_579_cast_fp16)[name = string("input_581_cast_fp16")];
            string x_241_pad_type_0 = const()[name = string("x_241_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> x_241_strides_0 = const()[name = string("x_241_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_241_pad_0 = const()[name = string("x_241_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_241_dilations_0 = const()[name = string("x_241_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 x_241_groups_0 = const()[name = string("x_241_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 1024, 1]> module_layers_10_conv_pointwise_conv2_weight_to_fp16 = const()[name = string("module_layers_10_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(533574656)))];
            tensor<fp16, [1, 1024, 188]> x_241_cast_fp16 = conv(dilations = x_241_dilations_0, groups = x_241_groups_0, pad = x_241_pad_0, pad_type = x_241_pad_type_0, strides = x_241_strides_0, weight = module_layers_10_conv_pointwise_conv2_weight_to_fp16, x = input_581_cast_fp16)[name = string("x_241_cast_fp16")];
            tensor<int32, [3]> input_583_perm_0 = const()[name = string("input_583_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_583_cast_fp16 = transpose(perm = input_583_perm_0, x = x_241_cast_fp16)[name = string("transpose_212")];
            tensor<fp16, [1, 188, 1024]> input_585_cast_fp16 = add(x = input_567_cast_fp16, y = input_583_cast_fp16)[name = string("input_585_cast_fp16")];
            tensor<int32, [1]> input_587_axes_0 = const()[name = string("input_587_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_10_norm_feed_forward2_weight_to_fp16 = const()[name = string("module_layers_10_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(535671872)))];
            tensor<fp16, [1024]> module_layers_10_norm_feed_forward2_bias_to_fp16 = const()[name = string("module_layers_10_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(535673984)))];
            tensor<fp16, [1, 188, 1024]> input_587_cast_fp16 = layer_norm(axes = input_587_axes_0, beta = module_layers_10_norm_feed_forward2_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_10_norm_feed_forward2_weight_to_fp16, x = input_585_cast_fp16)[name = string("input_587_cast_fp16")];
            tensor<fp16, [4096, 1024]> module_layers_10_feed_forward2_linear1_weight_to_fp16 = const()[name = string("module_layers_10_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(535676096)))];
            tensor<fp16, [1, 188, 4096]> linear_100_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = module_layers_10_feed_forward2_linear1_weight_to_fp16, x = input_587_cast_fp16)[name = string("linear_100_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_591_cast_fp16 = silu(x = linear_100_cast_fp16)[name = string("input_591_cast_fp16")];
            tensor<fp16, [1024, 4096]> module_layers_10_feed_forward2_linear2_weight_to_fp16 = const()[name = string("module_layers_10_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(544064768)))];
            tensor<fp16, [1, 188, 1024]> linear_101_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_10_feed_forward2_linear2_weight_to_fp16, x = input_591_cast_fp16)[name = string("linear_101_cast_fp16")];
            fp16 var_2024_to_fp16 = const()[name = string("op_2024_to_fp16"), val = fp16(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_2025_cast_fp16 = mul(x = linear_101_cast_fp16, y = var_2024_to_fp16)[name = string("op_2025_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_597_cast_fp16 = add(x = input_585_cast_fp16, y = var_2025_cast_fp16)[name = string("input_597_cast_fp16")];
            tensor<int32, [1]> input_599_axes_0 = const()[name = string("input_599_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_10_norm_out_weight_to_fp16 = const()[name = string("module_layers_10_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(552453440)))];
            tensor<fp16, [1024]> module_layers_10_norm_out_bias_to_fp16 = const()[name = string("module_layers_10_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(552455552)))];
            tensor<fp16, [1, 188, 1024]> input_599_cast_fp16 = layer_norm(axes = input_599_axes_0, beta = module_layers_10_norm_out_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_10_norm_out_weight_to_fp16, x = input_597_cast_fp16)[name = string("input_599_cast_fp16")];
            tensor<int32, [1]> input_601_axes_0 = const()[name = string("input_601_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_11_norm_feed_forward1_weight_to_fp16 = const()[name = string("module_layers_11_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(552457664)))];
            tensor<fp16, [1024]> module_layers_11_norm_feed_forward1_bias_to_fp16 = const()[name = string("module_layers_11_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(552459776)))];
            tensor<fp16, [1, 188, 1024]> input_601_cast_fp16 = layer_norm(axes = input_601_axes_0, beta = module_layers_11_norm_feed_forward1_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_11_norm_feed_forward1_weight_to_fp16, x = input_599_cast_fp16)[name = string("input_601_cast_fp16")];
            tensor<fp16, [4096, 1024]> module_layers_11_feed_forward1_linear1_weight_to_fp16 = const()[name = string("module_layers_11_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(552461888)))];
            tensor<fp16, [1, 188, 4096]> linear_102_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = module_layers_11_feed_forward1_linear1_weight_to_fp16, x = input_601_cast_fp16)[name = string("linear_102_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_605_cast_fp16 = silu(x = linear_102_cast_fp16)[name = string("input_605_cast_fp16")];
            tensor<fp16, [1024, 4096]> module_layers_11_feed_forward1_linear2_weight_to_fp16 = const()[name = string("module_layers_11_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(560850560)))];
            tensor<fp16, [1, 188, 1024]> linear_103_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_11_feed_forward1_linear2_weight_to_fp16, x = input_605_cast_fp16)[name = string("linear_103_cast_fp16")];
            fp16 var_2053_to_fp16 = const()[name = string("op_2053_to_fp16"), val = fp16(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_2054_cast_fp16 = mul(x = linear_103_cast_fp16, y = var_2053_to_fp16)[name = string("op_2054_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_611_cast_fp16 = add(x = input_599_cast_fp16, y = var_2054_cast_fp16)[name = string("input_611_cast_fp16")];
            tensor<int32, [1]> query_23_axes_0 = const()[name = string("query_23_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_11_norm_self_att_weight_to_fp16 = const()[name = string("module_layers_11_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(569239232)))];
            tensor<fp16, [1024]> module_layers_11_norm_self_att_bias_to_fp16 = const()[name = string("module_layers_11_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(569241344)))];
            tensor<fp16, [1, 188, 1024]> query_23_cast_fp16 = layer_norm(axes = query_23_axes_0, beta = module_layers_11_norm_self_att_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_11_norm_self_att_weight_to_fp16, x = input_611_cast_fp16)[name = string("query_23_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_11_self_attn_linear_q_weight_to_fp16 = const()[name = string("module_layers_11_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(569243456)))];
            tensor<fp16, [1, 188, 1024]> linear_104_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_11_self_attn_linear_q_weight_to_fp16, x = query_23_cast_fp16)[name = string("linear_104_cast_fp16")];
            tensor<int32, [4]> var_2070 = const()[name = string("op_2070"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_67_cast_fp16 = reshape(shape = var_2070, x = linear_104_cast_fp16)[name = string("q_67_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_11_self_attn_linear_k_weight_to_fp16 = const()[name = string("module_layers_11_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(571340672)))];
            tensor<fp16, [1, 188, 1024]> linear_105_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_11_self_attn_linear_k_weight_to_fp16, x = query_23_cast_fp16)[name = string("linear_105_cast_fp16")];
            tensor<int32, [4]> var_2074 = const()[name = string("op_2074"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_45_cast_fp16 = reshape(shape = var_2074, x = linear_105_cast_fp16)[name = string("k_45_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_11_self_attn_linear_v_weight_to_fp16 = const()[name = string("module_layers_11_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(573437888)))];
            tensor<fp16, [1, 188, 1024]> linear_106_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_11_self_attn_linear_v_weight_to_fp16, x = query_23_cast_fp16)[name = string("linear_106_cast_fp16")];
            tensor<int32, [4]> var_2078 = const()[name = string("op_2078"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_23_cast_fp16 = reshape(shape = var_2078, x = linear_106_cast_fp16)[name = string("v_23_cast_fp16")];
            tensor<int32, [4]> value_25_perm_0 = const()[name = string("value_25_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> module_layers_11_self_attn_pos_bias_u_to_fp16 = const()[name = string("module_layers_11_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(575535104)))];
            tensor<fp16, [1, 188, 8, 128]> var_2090_cast_fp16 = add(x = q_67_cast_fp16, y = module_layers_11_self_attn_pos_bias_u_to_fp16)[name = string("op_2090_cast_fp16")];
            tensor<fp16, [8, 128]> module_layers_11_self_attn_pos_bias_v_to_fp16 = const()[name = string("module_layers_11_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(575537216)))];
            tensor<fp16, [1, 188, 8, 128]> var_2092_cast_fp16 = add(x = q_67_cast_fp16, y = module_layers_11_self_attn_pos_bias_v_to_fp16)[name = string("op_2092_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_23_perm_0 = const()[name = string("q_with_bias_v_23_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            bool x_249_transpose_x_0 = const()[name = string("x_249_transpose_x_0"), val = bool(false)];
            bool x_249_transpose_y_0 = const()[name = string("x_249_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 128, 375]> var_2094_to_fp16 = const()[name = string("op_2094_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(575539328)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_23_cast_fp16 = transpose(perm = q_with_bias_v_23_perm_0, x = var_2092_cast_fp16)[name = string("transpose_210")];
            tensor<fp16, [1, 8, 188, 375]> x_249_cast_fp16 = matmul(transpose_x = x_249_transpose_x_0, transpose_y = x_249_transpose_y_0, x = q_with_bias_v_23_cast_fp16, y = var_2094_to_fp16)[name = string("x_249_cast_fp16")];
            tensor<int32, [8]> x_251_pad_0 = const()[name = string("x_251_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            string x_251_mode_0 = const()[name = string("x_251_mode_0"), val = string("constant")];
            fp16 const_124_to_fp16 = const()[name = string("const_124_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_251_cast_fp16 = pad(constant_val = const_124_to_fp16, mode = x_251_mode_0, pad = x_251_pad_0, x = x_249_cast_fp16)[name = string("x_251_cast_fp16")];
            tensor<int32, [4]> var_2102 = const()[name = string("op_2102"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_253_cast_fp16 = reshape(shape = var_2102, x = x_251_cast_fp16)[name = string("x_253_cast_fp16")];
            tensor<int32, [4]> var_2106_begin_0 = const()[name = string("op_2106_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_2106_end_0 = const()[name = string("op_2106_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_2106_end_mask_0 = const()[name = string("op_2106_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_2106_cast_fp16 = slice_by_index(begin = var_2106_begin_0, end = var_2106_end_0, end_mask = var_2106_end_mask_0, x = x_253_cast_fp16)[name = string("op_2106_cast_fp16")];
            tensor<int32, [4]> var_2107 = const()[name = string("op_2107"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_45_cast_fp16 = reshape(shape = var_2107, x = var_2106_cast_fp16)[name = string("matrix_bd_45_cast_fp16")];
            bool matrix_ac_23_transpose_x_0 = const()[name = string("matrix_ac_23_transpose_x_0"), val = bool(false)];
            bool matrix_ac_23_transpose_y_0 = const()[name = string("matrix_ac_23_transpose_y_0"), val = bool(false)];
            tensor<int32, [4]> transpose_94_perm_0 = const()[name = string("transpose_94_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_95_perm_0 = const()[name = string("transpose_95_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_95 = transpose(perm = transpose_95_perm_0, x = k_45_cast_fp16)[name = string("transpose_208")];
            tensor<fp16, [1, 8, 188, 128]> transpose_94 = transpose(perm = transpose_94_perm_0, x = var_2090_cast_fp16)[name = string("transpose_209")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_23_cast_fp16 = matmul(transpose_x = matrix_ac_23_transpose_x_0, transpose_y = matrix_ac_23_transpose_y_0, x = transpose_94, y = transpose_95)[name = string("matrix_ac_23_cast_fp16")];
            tensor<int32, [4]> matrix_bd_47_begin_0 = const()[name = string("matrix_bd_47_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_47_end_0 = const()[name = string("matrix_bd_47_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_47_end_mask_0 = const()[name = string("matrix_bd_47_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_47_cast_fp16 = slice_by_index(begin = matrix_bd_47_begin_0, end = matrix_bd_47_end_0, end_mask = matrix_bd_47_end_mask_0, x = matrix_bd_45_cast_fp16)[name = string("matrix_bd_47_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_2116_cast_fp16 = add(x = matrix_ac_23_cast_fp16, y = matrix_bd_47_cast_fp16)[name = string("op_2116_cast_fp16")];
            fp16 _inversed_scores_45_y_0_to_fp16 = const()[name = string("_inversed_scores_45_y_0_to_fp16"), val = fp16(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_45_cast_fp16 = mul(x = var_2116_cast_fp16, y = _inversed_scores_45_y_0_to_fp16)[name = string("_inversed_scores_45_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_47_cast_fp16 = select(a = var_10_to_fp16, b = _inversed_scores_45_cast_fp16, cond = mask_3)[name = string("scores_47_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_2122_cast_fp16 = softmax(axis = var_32, x = scores_47_cast_fp16)[name = string("op_2122_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_613_cast_fp16 = select(a = var_9_to_fp16, b = var_2122_cast_fp16, cond = mask_3)[name = string("input_613_cast_fp16")];
            bool x_255_transpose_x_0 = const()[name = string("x_255_transpose_x_0"), val = bool(false)];
            bool x_255_transpose_y_0 = const()[name = string("x_255_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 188, 128]> value_25_cast_fp16 = transpose(perm = value_25_perm_0, x = v_23_cast_fp16)[name = string("transpose_211")];
            tensor<fp16, [1, 8, 188, 128]> x_255_cast_fp16 = matmul(transpose_x = x_255_transpose_x_0, transpose_y = x_255_transpose_y_0, x = input_613_cast_fp16, y = value_25_cast_fp16)[name = string("x_255_cast_fp16")];
            tensor<int32, [4]> var_2126_perm_0 = const()[name = string("op_2126_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2127 = const()[name = string("op_2127"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_2126_cast_fp16 = transpose(perm = var_2126_perm_0, x = x_255_cast_fp16)[name = string("transpose_207")];
            tensor<fp16, [1, 188, 1024]> input_615_cast_fp16 = reshape(shape = var_2127, x = var_2126_cast_fp16)[name = string("input_615_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_11_self_attn_linear_out_weight_to_fp16 = const()[name = string("module_layers_11_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(576307392)))];
            tensor<fp16, [1, 188, 1024]> linear_108_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_11_self_attn_linear_out_weight_to_fp16, x = input_615_cast_fp16)[name = string("linear_108_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_619_cast_fp16 = add(x = input_611_cast_fp16, y = linear_108_cast_fp16)[name = string("input_619_cast_fp16")];
            tensor<int32, [1]> x_259_axes_0 = const()[name = string("x_259_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_11_norm_conv_weight_to_fp16 = const()[name = string("module_layers_11_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(578404608)))];
            tensor<fp16, [1024]> module_layers_11_norm_conv_bias_to_fp16 = const()[name = string("module_layers_11_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(578406720)))];
            tensor<fp16, [1, 188, 1024]> x_259_cast_fp16 = layer_norm(axes = x_259_axes_0, beta = module_layers_11_norm_conv_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_11_norm_conv_weight_to_fp16, x = input_619_cast_fp16)[name = string("x_259_cast_fp16")];
            tensor<int32, [3]> input_621_perm_0 = const()[name = string("input_621_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            string input_623_pad_type_0 = const()[name = string("input_623_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_623_strides_0 = const()[name = string("input_623_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_623_pad_0 = const()[name = string("input_623_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_623_dilations_0 = const()[name = string("input_623_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_623_groups_0 = const()[name = string("input_623_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 1024, 1]> module_layers_11_conv_pointwise_conv1_weight_to_fp16 = const()[name = string("module_layers_11_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(578408832)))];
            tensor<fp16, [1, 1024, 188]> input_621_cast_fp16 = transpose(perm = input_621_perm_0, x = x_259_cast_fp16)[name = string("transpose_206")];
            tensor<fp16, [1, 2048, 188]> input_623_cast_fp16 = conv(dilations = input_623_dilations_0, groups = input_623_groups_0, pad = input_623_pad_0, pad_type = input_623_pad_type_0, strides = input_623_strides_0, weight = module_layers_11_conv_pointwise_conv1_weight_to_fp16, x = input_621_cast_fp16)[name = string("input_623_cast_fp16")];
            int32 x_261_split_num_splits_0 = const()[name = string("x_261_split_num_splits_0"), val = int32(2)];
            int32 x_261_split_axis_0 = const()[name = string("x_261_split_axis_0"), val = int32(1)];
            tensor<fp16, [1, 1024, 188]> x_261_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_261_split_cast_fp16_1 = split(axis = x_261_split_axis_0, num_splits = x_261_split_num_splits_0, x = input_623_cast_fp16)[name = string("x_261_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_261_split_1_sigmoid_cast_fp16 = sigmoid(x = x_261_split_cast_fp16_1)[name = string("x_261_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_261_cast_fp16 = mul(x = x_261_split_cast_fp16_0, y = x_261_split_1_sigmoid_cast_fp16)[name = string("x_261_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_625_cast_fp16 = select(a = var_9_to_fp16, b = x_261_cast_fp16, cond = var_356)[name = string("input_625_cast_fp16")];
            tensor<int32, [6]> input_627_pad_0 = const()[name = string("input_627_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            string input_627_mode_0 = const()[name = string("input_627_mode_0"), val = string("constant")];
            fp16 const_127_to_fp16 = const()[name = string("const_127_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_627_cast_fp16 = pad(constant_val = const_127_to_fp16, mode = input_627_mode_0, pad = input_627_pad_0, x = input_625_cast_fp16)[name = string("input_627_cast_fp16")];
            string input_629_pad_type_0 = const()[name = string("input_629_pad_type_0"), val = string("valid")];
            int32 input_629_groups_0 = const()[name = string("input_629_groups_0"), val = int32(1024)];
            tensor<int32, [1]> input_629_strides_0 = const()[name = string("input_629_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_629_pad_0 = const()[name = string("input_629_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_629_dilations_0 = const()[name = string("input_629_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_270_to_fp16 = const()[name = string("const_270_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(582603200)))];
            tensor<fp16, [1024]> const_271_to_fp16 = const()[name = string("const_271_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(582621696)))];
            tensor<fp16, [1, 1024, 188]> input_631_cast_fp16 = conv(bias = const_271_to_fp16, dilations = input_629_dilations_0, groups = input_629_groups_0, pad = input_629_pad_0, pad_type = input_629_pad_type_0, strides = input_629_strides_0, weight = const_270_to_fp16, x = input_627_cast_fp16)[name = string("input_631_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_633_cast_fp16 = silu(x = input_631_cast_fp16)[name = string("input_633_cast_fp16")];
            string x_263_pad_type_0 = const()[name = string("x_263_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> x_263_strides_0 = const()[name = string("x_263_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_263_pad_0 = const()[name = string("x_263_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_263_dilations_0 = const()[name = string("x_263_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 x_263_groups_0 = const()[name = string("x_263_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 1024, 1]> module_layers_11_conv_pointwise_conv2_weight_to_fp16 = const()[name = string("module_layers_11_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(582623808)))];
            tensor<fp16, [1, 1024, 188]> x_263_cast_fp16 = conv(dilations = x_263_dilations_0, groups = x_263_groups_0, pad = x_263_pad_0, pad_type = x_263_pad_type_0, strides = x_263_strides_0, weight = module_layers_11_conv_pointwise_conv2_weight_to_fp16, x = input_633_cast_fp16)[name = string("x_263_cast_fp16")];
            tensor<int32, [3]> input_635_perm_0 = const()[name = string("input_635_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_635_cast_fp16 = transpose(perm = input_635_perm_0, x = x_263_cast_fp16)[name = string("transpose_205")];
            tensor<fp16, [1, 188, 1024]> input_637_cast_fp16 = add(x = input_619_cast_fp16, y = input_635_cast_fp16)[name = string("input_637_cast_fp16")];
            tensor<int32, [1]> input_639_axes_0 = const()[name = string("input_639_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_11_norm_feed_forward2_weight_to_fp16 = const()[name = string("module_layers_11_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(584721024)))];
            tensor<fp16, [1024]> module_layers_11_norm_feed_forward2_bias_to_fp16 = const()[name = string("module_layers_11_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(584723136)))];
            tensor<fp16, [1, 188, 1024]> input_639_cast_fp16 = layer_norm(axes = input_639_axes_0, beta = module_layers_11_norm_feed_forward2_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_11_norm_feed_forward2_weight_to_fp16, x = input_637_cast_fp16)[name = string("input_639_cast_fp16")];
            tensor<fp16, [4096, 1024]> module_layers_11_feed_forward2_linear1_weight_to_fp16 = const()[name = string("module_layers_11_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(584725248)))];
            tensor<fp16, [1, 188, 4096]> linear_109_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = module_layers_11_feed_forward2_linear1_weight_to_fp16, x = input_639_cast_fp16)[name = string("linear_109_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_643_cast_fp16 = silu(x = linear_109_cast_fp16)[name = string("input_643_cast_fp16")];
            tensor<fp16, [1024, 4096]> module_layers_11_feed_forward2_linear2_weight_to_fp16 = const()[name = string("module_layers_11_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(593113920)))];
            tensor<fp16, [1, 188, 1024]> linear_110_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_11_feed_forward2_linear2_weight_to_fp16, x = input_643_cast_fp16)[name = string("linear_110_cast_fp16")];
            fp16 var_2187_to_fp16 = const()[name = string("op_2187_to_fp16"), val = fp16(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_2188_cast_fp16 = mul(x = linear_110_cast_fp16, y = var_2187_to_fp16)[name = string("op_2188_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_649_cast_fp16 = add(x = input_637_cast_fp16, y = var_2188_cast_fp16)[name = string("input_649_cast_fp16")];
            tensor<int32, [1]> input_651_axes_0 = const()[name = string("input_651_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_11_norm_out_weight_to_fp16 = const()[name = string("module_layers_11_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(601502592)))];
            tensor<fp16, [1024]> module_layers_11_norm_out_bias_to_fp16 = const()[name = string("module_layers_11_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(601504704)))];
            tensor<fp16, [1, 188, 1024]> input_651_cast_fp16 = layer_norm(axes = input_651_axes_0, beta = module_layers_11_norm_out_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_11_norm_out_weight_to_fp16, x = input_649_cast_fp16)[name = string("input_651_cast_fp16")];
            tensor<int32, [1]> input_653_axes_0 = const()[name = string("input_653_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_12_norm_feed_forward1_weight_to_fp16 = const()[name = string("module_layers_12_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(601506816)))];
            tensor<fp16, [1024]> module_layers_12_norm_feed_forward1_bias_to_fp16 = const()[name = string("module_layers_12_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(601508928)))];
            tensor<fp16, [1, 188, 1024]> input_653_cast_fp16 = layer_norm(axes = input_653_axes_0, beta = module_layers_12_norm_feed_forward1_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_12_norm_feed_forward1_weight_to_fp16, x = input_651_cast_fp16)[name = string("input_653_cast_fp16")];
            tensor<fp16, [4096, 1024]> module_layers_12_feed_forward1_linear1_weight_to_fp16 = const()[name = string("module_layers_12_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(601511040)))];
            tensor<fp16, [1, 188, 4096]> linear_111_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = module_layers_12_feed_forward1_linear1_weight_to_fp16, x = input_653_cast_fp16)[name = string("linear_111_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_657_cast_fp16 = silu(x = linear_111_cast_fp16)[name = string("input_657_cast_fp16")];
            tensor<fp16, [1024, 4096]> module_layers_12_feed_forward1_linear2_weight_to_fp16 = const()[name = string("module_layers_12_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(609899712)))];
            tensor<fp16, [1, 188, 1024]> linear_112_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_12_feed_forward1_linear2_weight_to_fp16, x = input_657_cast_fp16)[name = string("linear_112_cast_fp16")];
            fp16 var_2216_to_fp16 = const()[name = string("op_2216_to_fp16"), val = fp16(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_2217_cast_fp16 = mul(x = linear_112_cast_fp16, y = var_2216_to_fp16)[name = string("op_2217_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_663_cast_fp16 = add(x = input_651_cast_fp16, y = var_2217_cast_fp16)[name = string("input_663_cast_fp16")];
            tensor<int32, [1]> query_25_axes_0 = const()[name = string("query_25_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_12_norm_self_att_weight_to_fp16 = const()[name = string("module_layers_12_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(618288384)))];
            tensor<fp16, [1024]> module_layers_12_norm_self_att_bias_to_fp16 = const()[name = string("module_layers_12_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(618290496)))];
            tensor<fp16, [1, 188, 1024]> query_25_cast_fp16 = layer_norm(axes = query_25_axes_0, beta = module_layers_12_norm_self_att_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_12_norm_self_att_weight_to_fp16, x = input_663_cast_fp16)[name = string("query_25_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_12_self_attn_linear_q_weight_to_fp16 = const()[name = string("module_layers_12_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(618292608)))];
            tensor<fp16, [1, 188, 1024]> linear_113_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_12_self_attn_linear_q_weight_to_fp16, x = query_25_cast_fp16)[name = string("linear_113_cast_fp16")];
            tensor<int32, [4]> var_2233 = const()[name = string("op_2233"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_73_cast_fp16 = reshape(shape = var_2233, x = linear_113_cast_fp16)[name = string("q_73_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_12_self_attn_linear_k_weight_to_fp16 = const()[name = string("module_layers_12_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(620389824)))];
            tensor<fp16, [1, 188, 1024]> linear_114_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_12_self_attn_linear_k_weight_to_fp16, x = query_25_cast_fp16)[name = string("linear_114_cast_fp16")];
            tensor<int32, [4]> var_2237 = const()[name = string("op_2237"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_49_cast_fp16 = reshape(shape = var_2237, x = linear_114_cast_fp16)[name = string("k_49_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_12_self_attn_linear_v_weight_to_fp16 = const()[name = string("module_layers_12_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(622487040)))];
            tensor<fp16, [1, 188, 1024]> linear_115_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_12_self_attn_linear_v_weight_to_fp16, x = query_25_cast_fp16)[name = string("linear_115_cast_fp16")];
            tensor<int32, [4]> var_2241 = const()[name = string("op_2241"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_25_cast_fp16 = reshape(shape = var_2241, x = linear_115_cast_fp16)[name = string("v_25_cast_fp16")];
            tensor<int32, [4]> value_27_perm_0 = const()[name = string("value_27_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> module_layers_12_self_attn_pos_bias_u_to_fp16 = const()[name = string("module_layers_12_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(624584256)))];
            tensor<fp16, [1, 188, 8, 128]> var_2253_cast_fp16 = add(x = q_73_cast_fp16, y = module_layers_12_self_attn_pos_bias_u_to_fp16)[name = string("op_2253_cast_fp16")];
            tensor<fp16, [8, 128]> module_layers_12_self_attn_pos_bias_v_to_fp16 = const()[name = string("module_layers_12_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(624586368)))];
            tensor<fp16, [1, 188, 8, 128]> var_2255_cast_fp16 = add(x = q_73_cast_fp16, y = module_layers_12_self_attn_pos_bias_v_to_fp16)[name = string("op_2255_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_25_perm_0 = const()[name = string("q_with_bias_v_25_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            bool x_271_transpose_x_0 = const()[name = string("x_271_transpose_x_0"), val = bool(false)];
            bool x_271_transpose_y_0 = const()[name = string("x_271_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 128, 375]> var_2257_to_fp16 = const()[name = string("op_2257_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(624588480)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_25_cast_fp16 = transpose(perm = q_with_bias_v_25_perm_0, x = var_2255_cast_fp16)[name = string("transpose_203")];
            tensor<fp16, [1, 8, 188, 375]> x_271_cast_fp16 = matmul(transpose_x = x_271_transpose_x_0, transpose_y = x_271_transpose_y_0, x = q_with_bias_v_25_cast_fp16, y = var_2257_to_fp16)[name = string("x_271_cast_fp16")];
            tensor<int32, [8]> x_273_pad_0 = const()[name = string("x_273_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            string x_273_mode_0 = const()[name = string("x_273_mode_0"), val = string("constant")];
            fp16 const_134_to_fp16 = const()[name = string("const_134_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_273_cast_fp16 = pad(constant_val = const_134_to_fp16, mode = x_273_mode_0, pad = x_273_pad_0, x = x_271_cast_fp16)[name = string("x_273_cast_fp16")];
            tensor<int32, [4]> var_2265 = const()[name = string("op_2265"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_275_cast_fp16 = reshape(shape = var_2265, x = x_273_cast_fp16)[name = string("x_275_cast_fp16")];
            tensor<int32, [4]> var_2269_begin_0 = const()[name = string("op_2269_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_2269_end_0 = const()[name = string("op_2269_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_2269_end_mask_0 = const()[name = string("op_2269_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_2269_cast_fp16 = slice_by_index(begin = var_2269_begin_0, end = var_2269_end_0, end_mask = var_2269_end_mask_0, x = x_275_cast_fp16)[name = string("op_2269_cast_fp16")];
            tensor<int32, [4]> var_2270 = const()[name = string("op_2270"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_49_cast_fp16 = reshape(shape = var_2270, x = var_2269_cast_fp16)[name = string("matrix_bd_49_cast_fp16")];
            bool matrix_ac_25_transpose_x_0 = const()[name = string("matrix_ac_25_transpose_x_0"), val = bool(false)];
            bool matrix_ac_25_transpose_y_0 = const()[name = string("matrix_ac_25_transpose_y_0"), val = bool(false)];
            tensor<int32, [4]> transpose_96_perm_0 = const()[name = string("transpose_96_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_97_perm_0 = const()[name = string("transpose_97_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_97 = transpose(perm = transpose_97_perm_0, x = k_49_cast_fp16)[name = string("transpose_201")];
            tensor<fp16, [1, 8, 188, 128]> transpose_96 = transpose(perm = transpose_96_perm_0, x = var_2253_cast_fp16)[name = string("transpose_202")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_25_cast_fp16 = matmul(transpose_x = matrix_ac_25_transpose_x_0, transpose_y = matrix_ac_25_transpose_y_0, x = transpose_96, y = transpose_97)[name = string("matrix_ac_25_cast_fp16")];
            tensor<int32, [4]> matrix_bd_51_begin_0 = const()[name = string("matrix_bd_51_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_51_end_0 = const()[name = string("matrix_bd_51_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_51_end_mask_0 = const()[name = string("matrix_bd_51_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_51_cast_fp16 = slice_by_index(begin = matrix_bd_51_begin_0, end = matrix_bd_51_end_0, end_mask = matrix_bd_51_end_mask_0, x = matrix_bd_49_cast_fp16)[name = string("matrix_bd_51_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_2279_cast_fp16 = add(x = matrix_ac_25_cast_fp16, y = matrix_bd_51_cast_fp16)[name = string("op_2279_cast_fp16")];
            fp16 _inversed_scores_49_y_0_to_fp16 = const()[name = string("_inversed_scores_49_y_0_to_fp16"), val = fp16(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_49_cast_fp16 = mul(x = var_2279_cast_fp16, y = _inversed_scores_49_y_0_to_fp16)[name = string("_inversed_scores_49_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_51_cast_fp16 = select(a = var_10_to_fp16, b = _inversed_scores_49_cast_fp16, cond = mask_3)[name = string("scores_51_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_2285_cast_fp16 = softmax(axis = var_32, x = scores_51_cast_fp16)[name = string("op_2285_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_665_cast_fp16 = select(a = var_9_to_fp16, b = var_2285_cast_fp16, cond = mask_3)[name = string("input_665_cast_fp16")];
            bool x_277_transpose_x_0 = const()[name = string("x_277_transpose_x_0"), val = bool(false)];
            bool x_277_transpose_y_0 = const()[name = string("x_277_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 188, 128]> value_27_cast_fp16 = transpose(perm = value_27_perm_0, x = v_25_cast_fp16)[name = string("transpose_204")];
            tensor<fp16, [1, 8, 188, 128]> x_277_cast_fp16 = matmul(transpose_x = x_277_transpose_x_0, transpose_y = x_277_transpose_y_0, x = input_665_cast_fp16, y = value_27_cast_fp16)[name = string("x_277_cast_fp16")];
            tensor<int32, [4]> var_2289_perm_0 = const()[name = string("op_2289_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2290 = const()[name = string("op_2290"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_2289_cast_fp16 = transpose(perm = var_2289_perm_0, x = x_277_cast_fp16)[name = string("transpose_200")];
            tensor<fp16, [1, 188, 1024]> input_667_cast_fp16 = reshape(shape = var_2290, x = var_2289_cast_fp16)[name = string("input_667_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_12_self_attn_linear_out_weight_to_fp16 = const()[name = string("module_layers_12_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(625356544)))];
            tensor<fp16, [1, 188, 1024]> linear_117_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_12_self_attn_linear_out_weight_to_fp16, x = input_667_cast_fp16)[name = string("linear_117_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_671_cast_fp16 = add(x = input_663_cast_fp16, y = linear_117_cast_fp16)[name = string("input_671_cast_fp16")];
            tensor<int32, [1]> x_281_axes_0 = const()[name = string("x_281_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_12_norm_conv_weight_to_fp16 = const()[name = string("module_layers_12_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(627453760)))];
            tensor<fp16, [1024]> module_layers_12_norm_conv_bias_to_fp16 = const()[name = string("module_layers_12_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(627455872)))];
            tensor<fp16, [1, 188, 1024]> x_281_cast_fp16 = layer_norm(axes = x_281_axes_0, beta = module_layers_12_norm_conv_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_12_norm_conv_weight_to_fp16, x = input_671_cast_fp16)[name = string("x_281_cast_fp16")];
            tensor<int32, [3]> input_673_perm_0 = const()[name = string("input_673_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            string input_675_pad_type_0 = const()[name = string("input_675_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_675_strides_0 = const()[name = string("input_675_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_675_pad_0 = const()[name = string("input_675_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_675_dilations_0 = const()[name = string("input_675_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_675_groups_0 = const()[name = string("input_675_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 1024, 1]> module_layers_12_conv_pointwise_conv1_weight_to_fp16 = const()[name = string("module_layers_12_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(627457984)))];
            tensor<fp16, [1, 1024, 188]> input_673_cast_fp16 = transpose(perm = input_673_perm_0, x = x_281_cast_fp16)[name = string("transpose_199")];
            tensor<fp16, [1, 2048, 188]> input_675_cast_fp16 = conv(dilations = input_675_dilations_0, groups = input_675_groups_0, pad = input_675_pad_0, pad_type = input_675_pad_type_0, strides = input_675_strides_0, weight = module_layers_12_conv_pointwise_conv1_weight_to_fp16, x = input_673_cast_fp16)[name = string("input_675_cast_fp16")];
            int32 x_283_split_num_splits_0 = const()[name = string("x_283_split_num_splits_0"), val = int32(2)];
            int32 x_283_split_axis_0 = const()[name = string("x_283_split_axis_0"), val = int32(1)];
            tensor<fp16, [1, 1024, 188]> x_283_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_283_split_cast_fp16_1 = split(axis = x_283_split_axis_0, num_splits = x_283_split_num_splits_0, x = input_675_cast_fp16)[name = string("x_283_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_283_split_1_sigmoid_cast_fp16 = sigmoid(x = x_283_split_cast_fp16_1)[name = string("x_283_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_283_cast_fp16 = mul(x = x_283_split_cast_fp16_0, y = x_283_split_1_sigmoid_cast_fp16)[name = string("x_283_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_677_cast_fp16 = select(a = var_9_to_fp16, b = x_283_cast_fp16, cond = var_356)[name = string("input_677_cast_fp16")];
            tensor<int32, [6]> input_679_pad_0 = const()[name = string("input_679_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            string input_679_mode_0 = const()[name = string("input_679_mode_0"), val = string("constant")];
            fp16 const_137_to_fp16 = const()[name = string("const_137_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_679_cast_fp16 = pad(constant_val = const_137_to_fp16, mode = input_679_mode_0, pad = input_679_pad_0, x = input_677_cast_fp16)[name = string("input_679_cast_fp16")];
            string input_681_pad_type_0 = const()[name = string("input_681_pad_type_0"), val = string("valid")];
            int32 input_681_groups_0 = const()[name = string("input_681_groups_0"), val = int32(1024)];
            tensor<int32, [1]> input_681_strides_0 = const()[name = string("input_681_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_681_pad_0 = const()[name = string("input_681_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_681_dilations_0 = const()[name = string("input_681_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_272_to_fp16 = const()[name = string("const_272_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(631652352)))];
            tensor<fp16, [1024]> const_273_to_fp16 = const()[name = string("const_273_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(631670848)))];
            tensor<fp16, [1, 1024, 188]> input_683_cast_fp16 = conv(bias = const_273_to_fp16, dilations = input_681_dilations_0, groups = input_681_groups_0, pad = input_681_pad_0, pad_type = input_681_pad_type_0, strides = input_681_strides_0, weight = const_272_to_fp16, x = input_679_cast_fp16)[name = string("input_683_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_685_cast_fp16 = silu(x = input_683_cast_fp16)[name = string("input_685_cast_fp16")];
            string x_285_pad_type_0 = const()[name = string("x_285_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> x_285_strides_0 = const()[name = string("x_285_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_285_pad_0 = const()[name = string("x_285_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_285_dilations_0 = const()[name = string("x_285_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 x_285_groups_0 = const()[name = string("x_285_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 1024, 1]> module_layers_12_conv_pointwise_conv2_weight_to_fp16 = const()[name = string("module_layers_12_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(631672960)))];
            tensor<fp16, [1, 1024, 188]> x_285_cast_fp16 = conv(dilations = x_285_dilations_0, groups = x_285_groups_0, pad = x_285_pad_0, pad_type = x_285_pad_type_0, strides = x_285_strides_0, weight = module_layers_12_conv_pointwise_conv2_weight_to_fp16, x = input_685_cast_fp16)[name = string("x_285_cast_fp16")];
            tensor<int32, [3]> input_687_perm_0 = const()[name = string("input_687_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_687_cast_fp16 = transpose(perm = input_687_perm_0, x = x_285_cast_fp16)[name = string("transpose_198")];
            tensor<fp16, [1, 188, 1024]> input_689_cast_fp16 = add(x = input_671_cast_fp16, y = input_687_cast_fp16)[name = string("input_689_cast_fp16")];
            tensor<int32, [1]> input_691_axes_0 = const()[name = string("input_691_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_12_norm_feed_forward2_weight_to_fp16 = const()[name = string("module_layers_12_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(633770176)))];
            tensor<fp16, [1024]> module_layers_12_norm_feed_forward2_bias_to_fp16 = const()[name = string("module_layers_12_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(633772288)))];
            tensor<fp16, [1, 188, 1024]> input_691_cast_fp16 = layer_norm(axes = input_691_axes_0, beta = module_layers_12_norm_feed_forward2_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_12_norm_feed_forward2_weight_to_fp16, x = input_689_cast_fp16)[name = string("input_691_cast_fp16")];
            tensor<fp16, [4096, 1024]> module_layers_12_feed_forward2_linear1_weight_to_fp16 = const()[name = string("module_layers_12_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(633774400)))];
            tensor<fp16, [1, 188, 4096]> linear_118_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = module_layers_12_feed_forward2_linear1_weight_to_fp16, x = input_691_cast_fp16)[name = string("linear_118_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_695_cast_fp16 = silu(x = linear_118_cast_fp16)[name = string("input_695_cast_fp16")];
            tensor<fp16, [1024, 4096]> module_layers_12_feed_forward2_linear2_weight_to_fp16 = const()[name = string("module_layers_12_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(642163072)))];
            tensor<fp16, [1, 188, 1024]> linear_119_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_12_feed_forward2_linear2_weight_to_fp16, x = input_695_cast_fp16)[name = string("linear_119_cast_fp16")];
            fp16 var_2350_to_fp16 = const()[name = string("op_2350_to_fp16"), val = fp16(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_2351_cast_fp16 = mul(x = linear_119_cast_fp16, y = var_2350_to_fp16)[name = string("op_2351_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_701_cast_fp16 = add(x = input_689_cast_fp16, y = var_2351_cast_fp16)[name = string("input_701_cast_fp16")];
            tensor<int32, [1]> input_703_axes_0 = const()[name = string("input_703_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_12_norm_out_weight_to_fp16 = const()[name = string("module_layers_12_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(650551744)))];
            tensor<fp16, [1024]> module_layers_12_norm_out_bias_to_fp16 = const()[name = string("module_layers_12_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(650553856)))];
            tensor<fp16, [1, 188, 1024]> input_703_cast_fp16 = layer_norm(axes = input_703_axes_0, beta = module_layers_12_norm_out_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_12_norm_out_weight_to_fp16, x = input_701_cast_fp16)[name = string("input_703_cast_fp16")];
            tensor<int32, [1]> input_705_axes_0 = const()[name = string("input_705_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_13_norm_feed_forward1_weight_to_fp16 = const()[name = string("module_layers_13_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(650555968)))];
            tensor<fp16, [1024]> module_layers_13_norm_feed_forward1_bias_to_fp16 = const()[name = string("module_layers_13_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(650558080)))];
            tensor<fp16, [1, 188, 1024]> input_705_cast_fp16 = layer_norm(axes = input_705_axes_0, beta = module_layers_13_norm_feed_forward1_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_13_norm_feed_forward1_weight_to_fp16, x = input_703_cast_fp16)[name = string("input_705_cast_fp16")];
            tensor<fp16, [4096, 1024]> module_layers_13_feed_forward1_linear1_weight_to_fp16 = const()[name = string("module_layers_13_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(650560192)))];
            tensor<fp16, [1, 188, 4096]> linear_120_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = module_layers_13_feed_forward1_linear1_weight_to_fp16, x = input_705_cast_fp16)[name = string("linear_120_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_709_cast_fp16 = silu(x = linear_120_cast_fp16)[name = string("input_709_cast_fp16")];
            tensor<fp16, [1024, 4096]> module_layers_13_feed_forward1_linear2_weight_to_fp16 = const()[name = string("module_layers_13_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(658948864)))];
            tensor<fp16, [1, 188, 1024]> linear_121_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_13_feed_forward1_linear2_weight_to_fp16, x = input_709_cast_fp16)[name = string("linear_121_cast_fp16")];
            fp16 var_2379_to_fp16 = const()[name = string("op_2379_to_fp16"), val = fp16(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_2380_cast_fp16 = mul(x = linear_121_cast_fp16, y = var_2379_to_fp16)[name = string("op_2380_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_715_cast_fp16 = add(x = input_703_cast_fp16, y = var_2380_cast_fp16)[name = string("input_715_cast_fp16")];
            tensor<int32, [1]> query_27_axes_0 = const()[name = string("query_27_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_13_norm_self_att_weight_to_fp16 = const()[name = string("module_layers_13_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(667337536)))];
            tensor<fp16, [1024]> module_layers_13_norm_self_att_bias_to_fp16 = const()[name = string("module_layers_13_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(667339648)))];
            tensor<fp16, [1, 188, 1024]> query_27_cast_fp16 = layer_norm(axes = query_27_axes_0, beta = module_layers_13_norm_self_att_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_13_norm_self_att_weight_to_fp16, x = input_715_cast_fp16)[name = string("query_27_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_13_self_attn_linear_q_weight_to_fp16 = const()[name = string("module_layers_13_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(667341760)))];
            tensor<fp16, [1, 188, 1024]> linear_122_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_13_self_attn_linear_q_weight_to_fp16, x = query_27_cast_fp16)[name = string("linear_122_cast_fp16")];
            tensor<int32, [4]> var_2396 = const()[name = string("op_2396"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_79_cast_fp16 = reshape(shape = var_2396, x = linear_122_cast_fp16)[name = string("q_79_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_13_self_attn_linear_k_weight_to_fp16 = const()[name = string("module_layers_13_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(669438976)))];
            tensor<fp16, [1, 188, 1024]> linear_123_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_13_self_attn_linear_k_weight_to_fp16, x = query_27_cast_fp16)[name = string("linear_123_cast_fp16")];
            tensor<int32, [4]> var_2400 = const()[name = string("op_2400"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_53_cast_fp16 = reshape(shape = var_2400, x = linear_123_cast_fp16)[name = string("k_53_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_13_self_attn_linear_v_weight_to_fp16 = const()[name = string("module_layers_13_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(671536192)))];
            tensor<fp16, [1, 188, 1024]> linear_124_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_13_self_attn_linear_v_weight_to_fp16, x = query_27_cast_fp16)[name = string("linear_124_cast_fp16")];
            tensor<int32, [4]> var_2404 = const()[name = string("op_2404"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_27_cast_fp16 = reshape(shape = var_2404, x = linear_124_cast_fp16)[name = string("v_27_cast_fp16")];
            tensor<int32, [4]> value_29_perm_0 = const()[name = string("value_29_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> module_layers_13_self_attn_pos_bias_u_to_fp16 = const()[name = string("module_layers_13_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(673633408)))];
            tensor<fp16, [1, 188, 8, 128]> var_2416_cast_fp16 = add(x = q_79_cast_fp16, y = module_layers_13_self_attn_pos_bias_u_to_fp16)[name = string("op_2416_cast_fp16")];
            tensor<fp16, [8, 128]> module_layers_13_self_attn_pos_bias_v_to_fp16 = const()[name = string("module_layers_13_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(673635520)))];
            tensor<fp16, [1, 188, 8, 128]> var_2418_cast_fp16 = add(x = q_79_cast_fp16, y = module_layers_13_self_attn_pos_bias_v_to_fp16)[name = string("op_2418_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_27_perm_0 = const()[name = string("q_with_bias_v_27_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            bool x_293_transpose_x_0 = const()[name = string("x_293_transpose_x_0"), val = bool(false)];
            bool x_293_transpose_y_0 = const()[name = string("x_293_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 128, 375]> var_2420_to_fp16 = const()[name = string("op_2420_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(673637632)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_27_cast_fp16 = transpose(perm = q_with_bias_v_27_perm_0, x = var_2418_cast_fp16)[name = string("transpose_196")];
            tensor<fp16, [1, 8, 188, 375]> x_293_cast_fp16 = matmul(transpose_x = x_293_transpose_x_0, transpose_y = x_293_transpose_y_0, x = q_with_bias_v_27_cast_fp16, y = var_2420_to_fp16)[name = string("x_293_cast_fp16")];
            tensor<int32, [8]> x_295_pad_0 = const()[name = string("x_295_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            string x_295_mode_0 = const()[name = string("x_295_mode_0"), val = string("constant")];
            fp16 const_144_to_fp16 = const()[name = string("const_144_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_295_cast_fp16 = pad(constant_val = const_144_to_fp16, mode = x_295_mode_0, pad = x_295_pad_0, x = x_293_cast_fp16)[name = string("x_295_cast_fp16")];
            tensor<int32, [4]> var_2428 = const()[name = string("op_2428"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_297_cast_fp16 = reshape(shape = var_2428, x = x_295_cast_fp16)[name = string("x_297_cast_fp16")];
            tensor<int32, [4]> var_2432_begin_0 = const()[name = string("op_2432_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_2432_end_0 = const()[name = string("op_2432_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_2432_end_mask_0 = const()[name = string("op_2432_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_2432_cast_fp16 = slice_by_index(begin = var_2432_begin_0, end = var_2432_end_0, end_mask = var_2432_end_mask_0, x = x_297_cast_fp16)[name = string("op_2432_cast_fp16")];
            tensor<int32, [4]> var_2433 = const()[name = string("op_2433"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_53_cast_fp16 = reshape(shape = var_2433, x = var_2432_cast_fp16)[name = string("matrix_bd_53_cast_fp16")];
            bool matrix_ac_27_transpose_x_0 = const()[name = string("matrix_ac_27_transpose_x_0"), val = bool(false)];
            bool matrix_ac_27_transpose_y_0 = const()[name = string("matrix_ac_27_transpose_y_0"), val = bool(false)];
            tensor<int32, [4]> transpose_98_perm_0 = const()[name = string("transpose_98_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_99_perm_0 = const()[name = string("transpose_99_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_99 = transpose(perm = transpose_99_perm_0, x = k_53_cast_fp16)[name = string("transpose_194")];
            tensor<fp16, [1, 8, 188, 128]> transpose_98 = transpose(perm = transpose_98_perm_0, x = var_2416_cast_fp16)[name = string("transpose_195")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_27_cast_fp16 = matmul(transpose_x = matrix_ac_27_transpose_x_0, transpose_y = matrix_ac_27_transpose_y_0, x = transpose_98, y = transpose_99)[name = string("matrix_ac_27_cast_fp16")];
            tensor<int32, [4]> matrix_bd_55_begin_0 = const()[name = string("matrix_bd_55_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_55_end_0 = const()[name = string("matrix_bd_55_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_55_end_mask_0 = const()[name = string("matrix_bd_55_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_55_cast_fp16 = slice_by_index(begin = matrix_bd_55_begin_0, end = matrix_bd_55_end_0, end_mask = matrix_bd_55_end_mask_0, x = matrix_bd_53_cast_fp16)[name = string("matrix_bd_55_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_2442_cast_fp16 = add(x = matrix_ac_27_cast_fp16, y = matrix_bd_55_cast_fp16)[name = string("op_2442_cast_fp16")];
            fp16 _inversed_scores_53_y_0_to_fp16 = const()[name = string("_inversed_scores_53_y_0_to_fp16"), val = fp16(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_53_cast_fp16 = mul(x = var_2442_cast_fp16, y = _inversed_scores_53_y_0_to_fp16)[name = string("_inversed_scores_53_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_55_cast_fp16 = select(a = var_10_to_fp16, b = _inversed_scores_53_cast_fp16, cond = mask_3)[name = string("scores_55_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_2448_cast_fp16 = softmax(axis = var_32, x = scores_55_cast_fp16)[name = string("op_2448_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_717_cast_fp16 = select(a = var_9_to_fp16, b = var_2448_cast_fp16, cond = mask_3)[name = string("input_717_cast_fp16")];
            bool x_299_transpose_x_0 = const()[name = string("x_299_transpose_x_0"), val = bool(false)];
            bool x_299_transpose_y_0 = const()[name = string("x_299_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 188, 128]> value_29_cast_fp16 = transpose(perm = value_29_perm_0, x = v_27_cast_fp16)[name = string("transpose_197")];
            tensor<fp16, [1, 8, 188, 128]> x_299_cast_fp16 = matmul(transpose_x = x_299_transpose_x_0, transpose_y = x_299_transpose_y_0, x = input_717_cast_fp16, y = value_29_cast_fp16)[name = string("x_299_cast_fp16")];
            tensor<int32, [4]> var_2452_perm_0 = const()[name = string("op_2452_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2453 = const()[name = string("op_2453"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_2452_cast_fp16 = transpose(perm = var_2452_perm_0, x = x_299_cast_fp16)[name = string("transpose_193")];
            tensor<fp16, [1, 188, 1024]> input_719_cast_fp16 = reshape(shape = var_2453, x = var_2452_cast_fp16)[name = string("input_719_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_13_self_attn_linear_out_weight_to_fp16 = const()[name = string("module_layers_13_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(674405696)))];
            tensor<fp16, [1, 188, 1024]> linear_126_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_13_self_attn_linear_out_weight_to_fp16, x = input_719_cast_fp16)[name = string("linear_126_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_723_cast_fp16 = add(x = input_715_cast_fp16, y = linear_126_cast_fp16)[name = string("input_723_cast_fp16")];
            tensor<int32, [1]> x_303_axes_0 = const()[name = string("x_303_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_13_norm_conv_weight_to_fp16 = const()[name = string("module_layers_13_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(676502912)))];
            tensor<fp16, [1024]> module_layers_13_norm_conv_bias_to_fp16 = const()[name = string("module_layers_13_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(676505024)))];
            tensor<fp16, [1, 188, 1024]> x_303_cast_fp16 = layer_norm(axes = x_303_axes_0, beta = module_layers_13_norm_conv_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_13_norm_conv_weight_to_fp16, x = input_723_cast_fp16)[name = string("x_303_cast_fp16")];
            tensor<int32, [3]> input_725_perm_0 = const()[name = string("input_725_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            string input_727_pad_type_0 = const()[name = string("input_727_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_727_strides_0 = const()[name = string("input_727_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_727_pad_0 = const()[name = string("input_727_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_727_dilations_0 = const()[name = string("input_727_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_727_groups_0 = const()[name = string("input_727_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 1024, 1]> module_layers_13_conv_pointwise_conv1_weight_to_fp16 = const()[name = string("module_layers_13_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(676507136)))];
            tensor<fp16, [1, 1024, 188]> input_725_cast_fp16 = transpose(perm = input_725_perm_0, x = x_303_cast_fp16)[name = string("transpose_192")];
            tensor<fp16, [1, 2048, 188]> input_727_cast_fp16 = conv(dilations = input_727_dilations_0, groups = input_727_groups_0, pad = input_727_pad_0, pad_type = input_727_pad_type_0, strides = input_727_strides_0, weight = module_layers_13_conv_pointwise_conv1_weight_to_fp16, x = input_725_cast_fp16)[name = string("input_727_cast_fp16")];
            int32 x_305_split_num_splits_0 = const()[name = string("x_305_split_num_splits_0"), val = int32(2)];
            int32 x_305_split_axis_0 = const()[name = string("x_305_split_axis_0"), val = int32(1)];
            tensor<fp16, [1, 1024, 188]> x_305_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_305_split_cast_fp16_1 = split(axis = x_305_split_axis_0, num_splits = x_305_split_num_splits_0, x = input_727_cast_fp16)[name = string("x_305_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_305_split_1_sigmoid_cast_fp16 = sigmoid(x = x_305_split_cast_fp16_1)[name = string("x_305_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_305_cast_fp16 = mul(x = x_305_split_cast_fp16_0, y = x_305_split_1_sigmoid_cast_fp16)[name = string("x_305_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_729_cast_fp16 = select(a = var_9_to_fp16, b = x_305_cast_fp16, cond = var_356)[name = string("input_729_cast_fp16")];
            tensor<int32, [6]> input_731_pad_0 = const()[name = string("input_731_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            string input_731_mode_0 = const()[name = string("input_731_mode_0"), val = string("constant")];
            fp16 const_147_to_fp16 = const()[name = string("const_147_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_731_cast_fp16 = pad(constant_val = const_147_to_fp16, mode = input_731_mode_0, pad = input_731_pad_0, x = input_729_cast_fp16)[name = string("input_731_cast_fp16")];
            string input_733_pad_type_0 = const()[name = string("input_733_pad_type_0"), val = string("valid")];
            int32 input_733_groups_0 = const()[name = string("input_733_groups_0"), val = int32(1024)];
            tensor<int32, [1]> input_733_strides_0 = const()[name = string("input_733_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_733_pad_0 = const()[name = string("input_733_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_733_dilations_0 = const()[name = string("input_733_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_274_to_fp16 = const()[name = string("const_274_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(680701504)))];
            tensor<fp16, [1024]> const_275_to_fp16 = const()[name = string("const_275_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(680720000)))];
            tensor<fp16, [1, 1024, 188]> input_735_cast_fp16 = conv(bias = const_275_to_fp16, dilations = input_733_dilations_0, groups = input_733_groups_0, pad = input_733_pad_0, pad_type = input_733_pad_type_0, strides = input_733_strides_0, weight = const_274_to_fp16, x = input_731_cast_fp16)[name = string("input_735_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_737_cast_fp16 = silu(x = input_735_cast_fp16)[name = string("input_737_cast_fp16")];
            string x_307_pad_type_0 = const()[name = string("x_307_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> x_307_strides_0 = const()[name = string("x_307_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_307_pad_0 = const()[name = string("x_307_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_307_dilations_0 = const()[name = string("x_307_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 x_307_groups_0 = const()[name = string("x_307_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 1024, 1]> module_layers_13_conv_pointwise_conv2_weight_to_fp16 = const()[name = string("module_layers_13_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(680722112)))];
            tensor<fp16, [1, 1024, 188]> x_307_cast_fp16 = conv(dilations = x_307_dilations_0, groups = x_307_groups_0, pad = x_307_pad_0, pad_type = x_307_pad_type_0, strides = x_307_strides_0, weight = module_layers_13_conv_pointwise_conv2_weight_to_fp16, x = input_737_cast_fp16)[name = string("x_307_cast_fp16")];
            tensor<int32, [3]> input_739_perm_0 = const()[name = string("input_739_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_739_cast_fp16 = transpose(perm = input_739_perm_0, x = x_307_cast_fp16)[name = string("transpose_191")];
            tensor<fp16, [1, 188, 1024]> input_741_cast_fp16 = add(x = input_723_cast_fp16, y = input_739_cast_fp16)[name = string("input_741_cast_fp16")];
            tensor<int32, [1]> input_743_axes_0 = const()[name = string("input_743_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_13_norm_feed_forward2_weight_to_fp16 = const()[name = string("module_layers_13_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(682819328)))];
            tensor<fp16, [1024]> module_layers_13_norm_feed_forward2_bias_to_fp16 = const()[name = string("module_layers_13_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(682821440)))];
            tensor<fp16, [1, 188, 1024]> input_743_cast_fp16 = layer_norm(axes = input_743_axes_0, beta = module_layers_13_norm_feed_forward2_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_13_norm_feed_forward2_weight_to_fp16, x = input_741_cast_fp16)[name = string("input_743_cast_fp16")];
            tensor<fp16, [4096, 1024]> module_layers_13_feed_forward2_linear1_weight_to_fp16 = const()[name = string("module_layers_13_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(682823552)))];
            tensor<fp16, [1, 188, 4096]> linear_127_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = module_layers_13_feed_forward2_linear1_weight_to_fp16, x = input_743_cast_fp16)[name = string("linear_127_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_747_cast_fp16 = silu(x = linear_127_cast_fp16)[name = string("input_747_cast_fp16")];
            tensor<fp16, [1024, 4096]> module_layers_13_feed_forward2_linear2_weight_to_fp16 = const()[name = string("module_layers_13_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(691212224)))];
            tensor<fp16, [1, 188, 1024]> linear_128_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_13_feed_forward2_linear2_weight_to_fp16, x = input_747_cast_fp16)[name = string("linear_128_cast_fp16")];
            fp16 var_2513_to_fp16 = const()[name = string("op_2513_to_fp16"), val = fp16(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_2514_cast_fp16 = mul(x = linear_128_cast_fp16, y = var_2513_to_fp16)[name = string("op_2514_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_753_cast_fp16 = add(x = input_741_cast_fp16, y = var_2514_cast_fp16)[name = string("input_753_cast_fp16")];
            tensor<int32, [1]> input_755_axes_0 = const()[name = string("input_755_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_13_norm_out_weight_to_fp16 = const()[name = string("module_layers_13_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(699600896)))];
            tensor<fp16, [1024]> module_layers_13_norm_out_bias_to_fp16 = const()[name = string("module_layers_13_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(699603008)))];
            tensor<fp16, [1, 188, 1024]> input_755_cast_fp16 = layer_norm(axes = input_755_axes_0, beta = module_layers_13_norm_out_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_13_norm_out_weight_to_fp16, x = input_753_cast_fp16)[name = string("input_755_cast_fp16")];
            tensor<int32, [1]> input_757_axes_0 = const()[name = string("input_757_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_14_norm_feed_forward1_weight_to_fp16 = const()[name = string("module_layers_14_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(699605120)))];
            tensor<fp16, [1024]> module_layers_14_norm_feed_forward1_bias_to_fp16 = const()[name = string("module_layers_14_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(699607232)))];
            tensor<fp16, [1, 188, 1024]> input_757_cast_fp16 = layer_norm(axes = input_757_axes_0, beta = module_layers_14_norm_feed_forward1_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_14_norm_feed_forward1_weight_to_fp16, x = input_755_cast_fp16)[name = string("input_757_cast_fp16")];
            tensor<fp16, [4096, 1024]> module_layers_14_feed_forward1_linear1_weight_to_fp16 = const()[name = string("module_layers_14_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(699609344)))];
            tensor<fp16, [1, 188, 4096]> linear_129_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = module_layers_14_feed_forward1_linear1_weight_to_fp16, x = input_757_cast_fp16)[name = string("linear_129_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_761_cast_fp16 = silu(x = linear_129_cast_fp16)[name = string("input_761_cast_fp16")];
            tensor<fp16, [1024, 4096]> module_layers_14_feed_forward1_linear2_weight_to_fp16 = const()[name = string("module_layers_14_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(707998016)))];
            tensor<fp16, [1, 188, 1024]> linear_130_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_14_feed_forward1_linear2_weight_to_fp16, x = input_761_cast_fp16)[name = string("linear_130_cast_fp16")];
            fp16 var_2542_to_fp16 = const()[name = string("op_2542_to_fp16"), val = fp16(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_2543_cast_fp16 = mul(x = linear_130_cast_fp16, y = var_2542_to_fp16)[name = string("op_2543_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_767_cast_fp16 = add(x = input_755_cast_fp16, y = var_2543_cast_fp16)[name = string("input_767_cast_fp16")];
            tensor<int32, [1]> query_29_axes_0 = const()[name = string("query_29_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_14_norm_self_att_weight_to_fp16 = const()[name = string("module_layers_14_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(716386688)))];
            tensor<fp16, [1024]> module_layers_14_norm_self_att_bias_to_fp16 = const()[name = string("module_layers_14_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(716388800)))];
            tensor<fp16, [1, 188, 1024]> query_29_cast_fp16 = layer_norm(axes = query_29_axes_0, beta = module_layers_14_norm_self_att_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_14_norm_self_att_weight_to_fp16, x = input_767_cast_fp16)[name = string("query_29_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_14_self_attn_linear_q_weight_to_fp16 = const()[name = string("module_layers_14_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(716390912)))];
            tensor<fp16, [1, 188, 1024]> linear_131_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_14_self_attn_linear_q_weight_to_fp16, x = query_29_cast_fp16)[name = string("linear_131_cast_fp16")];
            tensor<int32, [4]> var_2559 = const()[name = string("op_2559"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_85_cast_fp16 = reshape(shape = var_2559, x = linear_131_cast_fp16)[name = string("q_85_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_14_self_attn_linear_k_weight_to_fp16 = const()[name = string("module_layers_14_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(718488128)))];
            tensor<fp16, [1, 188, 1024]> linear_132_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_14_self_attn_linear_k_weight_to_fp16, x = query_29_cast_fp16)[name = string("linear_132_cast_fp16")];
            tensor<int32, [4]> var_2563 = const()[name = string("op_2563"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_57_cast_fp16 = reshape(shape = var_2563, x = linear_132_cast_fp16)[name = string("k_57_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_14_self_attn_linear_v_weight_to_fp16 = const()[name = string("module_layers_14_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(720585344)))];
            tensor<fp16, [1, 188, 1024]> linear_133_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_14_self_attn_linear_v_weight_to_fp16, x = query_29_cast_fp16)[name = string("linear_133_cast_fp16")];
            tensor<int32, [4]> var_2567 = const()[name = string("op_2567"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_29_cast_fp16 = reshape(shape = var_2567, x = linear_133_cast_fp16)[name = string("v_29_cast_fp16")];
            tensor<int32, [4]> value_31_perm_0 = const()[name = string("value_31_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> module_layers_14_self_attn_pos_bias_u_to_fp16 = const()[name = string("module_layers_14_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(722682560)))];
            tensor<fp16, [1, 188, 8, 128]> var_2579_cast_fp16 = add(x = q_85_cast_fp16, y = module_layers_14_self_attn_pos_bias_u_to_fp16)[name = string("op_2579_cast_fp16")];
            tensor<fp16, [8, 128]> module_layers_14_self_attn_pos_bias_v_to_fp16 = const()[name = string("module_layers_14_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(722684672)))];
            tensor<fp16, [1, 188, 8, 128]> var_2581_cast_fp16 = add(x = q_85_cast_fp16, y = module_layers_14_self_attn_pos_bias_v_to_fp16)[name = string("op_2581_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_29_perm_0 = const()[name = string("q_with_bias_v_29_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            bool x_315_transpose_x_0 = const()[name = string("x_315_transpose_x_0"), val = bool(false)];
            bool x_315_transpose_y_0 = const()[name = string("x_315_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 128, 375]> var_2583_to_fp16 = const()[name = string("op_2583_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(722686784)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_29_cast_fp16 = transpose(perm = q_with_bias_v_29_perm_0, x = var_2581_cast_fp16)[name = string("transpose_189")];
            tensor<fp16, [1, 8, 188, 375]> x_315_cast_fp16 = matmul(transpose_x = x_315_transpose_x_0, transpose_y = x_315_transpose_y_0, x = q_with_bias_v_29_cast_fp16, y = var_2583_to_fp16)[name = string("x_315_cast_fp16")];
            tensor<int32, [8]> x_317_pad_0 = const()[name = string("x_317_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            string x_317_mode_0 = const()[name = string("x_317_mode_0"), val = string("constant")];
            fp16 const_154_to_fp16 = const()[name = string("const_154_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_317_cast_fp16 = pad(constant_val = const_154_to_fp16, mode = x_317_mode_0, pad = x_317_pad_0, x = x_315_cast_fp16)[name = string("x_317_cast_fp16")];
            tensor<int32, [4]> var_2591 = const()[name = string("op_2591"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_319_cast_fp16 = reshape(shape = var_2591, x = x_317_cast_fp16)[name = string("x_319_cast_fp16")];
            tensor<int32, [4]> var_2595_begin_0 = const()[name = string("op_2595_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_2595_end_0 = const()[name = string("op_2595_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_2595_end_mask_0 = const()[name = string("op_2595_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_2595_cast_fp16 = slice_by_index(begin = var_2595_begin_0, end = var_2595_end_0, end_mask = var_2595_end_mask_0, x = x_319_cast_fp16)[name = string("op_2595_cast_fp16")];
            tensor<int32, [4]> var_2596 = const()[name = string("op_2596"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_57_cast_fp16 = reshape(shape = var_2596, x = var_2595_cast_fp16)[name = string("matrix_bd_57_cast_fp16")];
            bool matrix_ac_29_transpose_x_0 = const()[name = string("matrix_ac_29_transpose_x_0"), val = bool(false)];
            bool matrix_ac_29_transpose_y_0 = const()[name = string("matrix_ac_29_transpose_y_0"), val = bool(false)];
            tensor<int32, [4]> transpose_100_perm_0 = const()[name = string("transpose_100_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_101_perm_0 = const()[name = string("transpose_101_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_101 = transpose(perm = transpose_101_perm_0, x = k_57_cast_fp16)[name = string("transpose_187")];
            tensor<fp16, [1, 8, 188, 128]> transpose_100 = transpose(perm = transpose_100_perm_0, x = var_2579_cast_fp16)[name = string("transpose_188")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_29_cast_fp16 = matmul(transpose_x = matrix_ac_29_transpose_x_0, transpose_y = matrix_ac_29_transpose_y_0, x = transpose_100, y = transpose_101)[name = string("matrix_ac_29_cast_fp16")];
            tensor<int32, [4]> matrix_bd_59_begin_0 = const()[name = string("matrix_bd_59_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_59_end_0 = const()[name = string("matrix_bd_59_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_59_end_mask_0 = const()[name = string("matrix_bd_59_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_59_cast_fp16 = slice_by_index(begin = matrix_bd_59_begin_0, end = matrix_bd_59_end_0, end_mask = matrix_bd_59_end_mask_0, x = matrix_bd_57_cast_fp16)[name = string("matrix_bd_59_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_2605_cast_fp16 = add(x = matrix_ac_29_cast_fp16, y = matrix_bd_59_cast_fp16)[name = string("op_2605_cast_fp16")];
            fp16 _inversed_scores_57_y_0_to_fp16 = const()[name = string("_inversed_scores_57_y_0_to_fp16"), val = fp16(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_57_cast_fp16 = mul(x = var_2605_cast_fp16, y = _inversed_scores_57_y_0_to_fp16)[name = string("_inversed_scores_57_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_59_cast_fp16 = select(a = var_10_to_fp16, b = _inversed_scores_57_cast_fp16, cond = mask_3)[name = string("scores_59_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_2611_cast_fp16 = softmax(axis = var_32, x = scores_59_cast_fp16)[name = string("op_2611_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_769_cast_fp16 = select(a = var_9_to_fp16, b = var_2611_cast_fp16, cond = mask_3)[name = string("input_769_cast_fp16")];
            bool x_321_transpose_x_0 = const()[name = string("x_321_transpose_x_0"), val = bool(false)];
            bool x_321_transpose_y_0 = const()[name = string("x_321_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 188, 128]> value_31_cast_fp16 = transpose(perm = value_31_perm_0, x = v_29_cast_fp16)[name = string("transpose_190")];
            tensor<fp16, [1, 8, 188, 128]> x_321_cast_fp16 = matmul(transpose_x = x_321_transpose_x_0, transpose_y = x_321_transpose_y_0, x = input_769_cast_fp16, y = value_31_cast_fp16)[name = string("x_321_cast_fp16")];
            tensor<int32, [4]> var_2615_perm_0 = const()[name = string("op_2615_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2616 = const()[name = string("op_2616"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_2615_cast_fp16 = transpose(perm = var_2615_perm_0, x = x_321_cast_fp16)[name = string("transpose_186")];
            tensor<fp16, [1, 188, 1024]> input_771_cast_fp16 = reshape(shape = var_2616, x = var_2615_cast_fp16)[name = string("input_771_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_14_self_attn_linear_out_weight_to_fp16 = const()[name = string("module_layers_14_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(723454848)))];
            tensor<fp16, [1, 188, 1024]> linear_135_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_14_self_attn_linear_out_weight_to_fp16, x = input_771_cast_fp16)[name = string("linear_135_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_775_cast_fp16 = add(x = input_767_cast_fp16, y = linear_135_cast_fp16)[name = string("input_775_cast_fp16")];
            tensor<int32, [1]> x_325_axes_0 = const()[name = string("x_325_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_14_norm_conv_weight_to_fp16 = const()[name = string("module_layers_14_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(725552064)))];
            tensor<fp16, [1024]> module_layers_14_norm_conv_bias_to_fp16 = const()[name = string("module_layers_14_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(725554176)))];
            tensor<fp16, [1, 188, 1024]> x_325_cast_fp16 = layer_norm(axes = x_325_axes_0, beta = module_layers_14_norm_conv_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_14_norm_conv_weight_to_fp16, x = input_775_cast_fp16)[name = string("x_325_cast_fp16")];
            tensor<int32, [3]> input_777_perm_0 = const()[name = string("input_777_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            string input_779_pad_type_0 = const()[name = string("input_779_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_779_strides_0 = const()[name = string("input_779_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_779_pad_0 = const()[name = string("input_779_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_779_dilations_0 = const()[name = string("input_779_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_779_groups_0 = const()[name = string("input_779_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 1024, 1]> module_layers_14_conv_pointwise_conv1_weight_to_fp16 = const()[name = string("module_layers_14_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(725556288)))];
            tensor<fp16, [1, 1024, 188]> input_777_cast_fp16 = transpose(perm = input_777_perm_0, x = x_325_cast_fp16)[name = string("transpose_185")];
            tensor<fp16, [1, 2048, 188]> input_779_cast_fp16 = conv(dilations = input_779_dilations_0, groups = input_779_groups_0, pad = input_779_pad_0, pad_type = input_779_pad_type_0, strides = input_779_strides_0, weight = module_layers_14_conv_pointwise_conv1_weight_to_fp16, x = input_777_cast_fp16)[name = string("input_779_cast_fp16")];
            int32 x_327_split_num_splits_0 = const()[name = string("x_327_split_num_splits_0"), val = int32(2)];
            int32 x_327_split_axis_0 = const()[name = string("x_327_split_axis_0"), val = int32(1)];
            tensor<fp16, [1, 1024, 188]> x_327_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_327_split_cast_fp16_1 = split(axis = x_327_split_axis_0, num_splits = x_327_split_num_splits_0, x = input_779_cast_fp16)[name = string("x_327_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_327_split_1_sigmoid_cast_fp16 = sigmoid(x = x_327_split_cast_fp16_1)[name = string("x_327_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_327_cast_fp16 = mul(x = x_327_split_cast_fp16_0, y = x_327_split_1_sigmoid_cast_fp16)[name = string("x_327_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_781_cast_fp16 = select(a = var_9_to_fp16, b = x_327_cast_fp16, cond = var_356)[name = string("input_781_cast_fp16")];
            tensor<int32, [6]> input_783_pad_0 = const()[name = string("input_783_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            string input_783_mode_0 = const()[name = string("input_783_mode_0"), val = string("constant")];
            fp16 const_157_to_fp16 = const()[name = string("const_157_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_783_cast_fp16 = pad(constant_val = const_157_to_fp16, mode = input_783_mode_0, pad = input_783_pad_0, x = input_781_cast_fp16)[name = string("input_783_cast_fp16")];
            string input_785_pad_type_0 = const()[name = string("input_785_pad_type_0"), val = string("valid")];
            int32 input_785_groups_0 = const()[name = string("input_785_groups_0"), val = int32(1024)];
            tensor<int32, [1]> input_785_strides_0 = const()[name = string("input_785_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_785_pad_0 = const()[name = string("input_785_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_785_dilations_0 = const()[name = string("input_785_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_276_to_fp16 = const()[name = string("const_276_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(729750656)))];
            tensor<fp16, [1024]> const_277_to_fp16 = const()[name = string("const_277_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(729769152)))];
            tensor<fp16, [1, 1024, 188]> input_787_cast_fp16 = conv(bias = const_277_to_fp16, dilations = input_785_dilations_0, groups = input_785_groups_0, pad = input_785_pad_0, pad_type = input_785_pad_type_0, strides = input_785_strides_0, weight = const_276_to_fp16, x = input_783_cast_fp16)[name = string("input_787_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_789_cast_fp16 = silu(x = input_787_cast_fp16)[name = string("input_789_cast_fp16")];
            string x_329_pad_type_0 = const()[name = string("x_329_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> x_329_strides_0 = const()[name = string("x_329_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_329_pad_0 = const()[name = string("x_329_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_329_dilations_0 = const()[name = string("x_329_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 x_329_groups_0 = const()[name = string("x_329_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 1024, 1]> module_layers_14_conv_pointwise_conv2_weight_to_fp16 = const()[name = string("module_layers_14_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(729771264)))];
            tensor<fp16, [1, 1024, 188]> x_329_cast_fp16 = conv(dilations = x_329_dilations_0, groups = x_329_groups_0, pad = x_329_pad_0, pad_type = x_329_pad_type_0, strides = x_329_strides_0, weight = module_layers_14_conv_pointwise_conv2_weight_to_fp16, x = input_789_cast_fp16)[name = string("x_329_cast_fp16")];
            tensor<int32, [3]> input_791_perm_0 = const()[name = string("input_791_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_791_cast_fp16 = transpose(perm = input_791_perm_0, x = x_329_cast_fp16)[name = string("transpose_184")];
            tensor<fp16, [1, 188, 1024]> input_793_cast_fp16 = add(x = input_775_cast_fp16, y = input_791_cast_fp16)[name = string("input_793_cast_fp16")];
            tensor<int32, [1]> input_795_axes_0 = const()[name = string("input_795_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_14_norm_feed_forward2_weight_to_fp16 = const()[name = string("module_layers_14_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(731868480)))];
            tensor<fp16, [1024]> module_layers_14_norm_feed_forward2_bias_to_fp16 = const()[name = string("module_layers_14_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(731870592)))];
            tensor<fp16, [1, 188, 1024]> input_795_cast_fp16 = layer_norm(axes = input_795_axes_0, beta = module_layers_14_norm_feed_forward2_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_14_norm_feed_forward2_weight_to_fp16, x = input_793_cast_fp16)[name = string("input_795_cast_fp16")];
            tensor<fp16, [4096, 1024]> module_layers_14_feed_forward2_linear1_weight_to_fp16 = const()[name = string("module_layers_14_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(731872704)))];
            tensor<fp16, [1, 188, 4096]> linear_136_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = module_layers_14_feed_forward2_linear1_weight_to_fp16, x = input_795_cast_fp16)[name = string("linear_136_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_799_cast_fp16 = silu(x = linear_136_cast_fp16)[name = string("input_799_cast_fp16")];
            tensor<fp16, [1024, 4096]> module_layers_14_feed_forward2_linear2_weight_to_fp16 = const()[name = string("module_layers_14_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(740261376)))];
            tensor<fp16, [1, 188, 1024]> linear_137_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_14_feed_forward2_linear2_weight_to_fp16, x = input_799_cast_fp16)[name = string("linear_137_cast_fp16")];
            fp16 var_2676_to_fp16 = const()[name = string("op_2676_to_fp16"), val = fp16(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_2677_cast_fp16 = mul(x = linear_137_cast_fp16, y = var_2676_to_fp16)[name = string("op_2677_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_805_cast_fp16 = add(x = input_793_cast_fp16, y = var_2677_cast_fp16)[name = string("input_805_cast_fp16")];
            tensor<int32, [1]> input_807_axes_0 = const()[name = string("input_807_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_14_norm_out_weight_to_fp16 = const()[name = string("module_layers_14_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(748650048)))];
            tensor<fp16, [1024]> module_layers_14_norm_out_bias_to_fp16 = const()[name = string("module_layers_14_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(748652160)))];
            tensor<fp16, [1, 188, 1024]> input_807_cast_fp16 = layer_norm(axes = input_807_axes_0, beta = module_layers_14_norm_out_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_14_norm_out_weight_to_fp16, x = input_805_cast_fp16)[name = string("input_807_cast_fp16")];
            tensor<int32, [1]> input_809_axes_0 = const()[name = string("input_809_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_15_norm_feed_forward1_weight_to_fp16 = const()[name = string("module_layers_15_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(748654272)))];
            tensor<fp16, [1024]> module_layers_15_norm_feed_forward1_bias_to_fp16 = const()[name = string("module_layers_15_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(748656384)))];
            tensor<fp16, [1, 188, 1024]> input_809_cast_fp16 = layer_norm(axes = input_809_axes_0, beta = module_layers_15_norm_feed_forward1_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_15_norm_feed_forward1_weight_to_fp16, x = input_807_cast_fp16)[name = string("input_809_cast_fp16")];
            tensor<fp16, [4096, 1024]> module_layers_15_feed_forward1_linear1_weight_to_fp16 = const()[name = string("module_layers_15_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(748658496)))];
            tensor<fp16, [1, 188, 4096]> linear_138_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = module_layers_15_feed_forward1_linear1_weight_to_fp16, x = input_809_cast_fp16)[name = string("linear_138_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_813_cast_fp16 = silu(x = linear_138_cast_fp16)[name = string("input_813_cast_fp16")];
            tensor<fp16, [1024, 4096]> module_layers_15_feed_forward1_linear2_weight_to_fp16 = const()[name = string("module_layers_15_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(757047168)))];
            tensor<fp16, [1, 188, 1024]> linear_139_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_15_feed_forward1_linear2_weight_to_fp16, x = input_813_cast_fp16)[name = string("linear_139_cast_fp16")];
            fp16 var_2705_to_fp16 = const()[name = string("op_2705_to_fp16"), val = fp16(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_2706_cast_fp16 = mul(x = linear_139_cast_fp16, y = var_2705_to_fp16)[name = string("op_2706_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_819_cast_fp16 = add(x = input_807_cast_fp16, y = var_2706_cast_fp16)[name = string("input_819_cast_fp16")];
            tensor<int32, [1]> query_31_axes_0 = const()[name = string("query_31_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_15_norm_self_att_weight_to_fp16 = const()[name = string("module_layers_15_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(765435840)))];
            tensor<fp16, [1024]> module_layers_15_norm_self_att_bias_to_fp16 = const()[name = string("module_layers_15_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(765437952)))];
            tensor<fp16, [1, 188, 1024]> query_31_cast_fp16 = layer_norm(axes = query_31_axes_0, beta = module_layers_15_norm_self_att_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_15_norm_self_att_weight_to_fp16, x = input_819_cast_fp16)[name = string("query_31_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_15_self_attn_linear_q_weight_to_fp16 = const()[name = string("module_layers_15_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(765440064)))];
            tensor<fp16, [1, 188, 1024]> linear_140_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_15_self_attn_linear_q_weight_to_fp16, x = query_31_cast_fp16)[name = string("linear_140_cast_fp16")];
            tensor<int32, [4]> var_2722 = const()[name = string("op_2722"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_91_cast_fp16 = reshape(shape = var_2722, x = linear_140_cast_fp16)[name = string("q_91_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_15_self_attn_linear_k_weight_to_fp16 = const()[name = string("module_layers_15_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(767537280)))];
            tensor<fp16, [1, 188, 1024]> linear_141_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_15_self_attn_linear_k_weight_to_fp16, x = query_31_cast_fp16)[name = string("linear_141_cast_fp16")];
            tensor<int32, [4]> var_2726 = const()[name = string("op_2726"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_61_cast_fp16 = reshape(shape = var_2726, x = linear_141_cast_fp16)[name = string("k_61_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_15_self_attn_linear_v_weight_to_fp16 = const()[name = string("module_layers_15_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(769634496)))];
            tensor<fp16, [1, 188, 1024]> linear_142_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_15_self_attn_linear_v_weight_to_fp16, x = query_31_cast_fp16)[name = string("linear_142_cast_fp16")];
            tensor<int32, [4]> var_2730 = const()[name = string("op_2730"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_31_cast_fp16 = reshape(shape = var_2730, x = linear_142_cast_fp16)[name = string("v_31_cast_fp16")];
            tensor<int32, [4]> value_33_perm_0 = const()[name = string("value_33_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> module_layers_15_self_attn_pos_bias_u_to_fp16 = const()[name = string("module_layers_15_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(771731712)))];
            tensor<fp16, [1, 188, 8, 128]> var_2742_cast_fp16 = add(x = q_91_cast_fp16, y = module_layers_15_self_attn_pos_bias_u_to_fp16)[name = string("op_2742_cast_fp16")];
            tensor<fp16, [8, 128]> module_layers_15_self_attn_pos_bias_v_to_fp16 = const()[name = string("module_layers_15_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(771733824)))];
            tensor<fp16, [1, 188, 8, 128]> var_2744_cast_fp16 = add(x = q_91_cast_fp16, y = module_layers_15_self_attn_pos_bias_v_to_fp16)[name = string("op_2744_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_31_perm_0 = const()[name = string("q_with_bias_v_31_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            bool x_337_transpose_x_0 = const()[name = string("x_337_transpose_x_0"), val = bool(false)];
            bool x_337_transpose_y_0 = const()[name = string("x_337_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 128, 375]> var_2746_to_fp16 = const()[name = string("op_2746_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(771735936)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_31_cast_fp16 = transpose(perm = q_with_bias_v_31_perm_0, x = var_2744_cast_fp16)[name = string("transpose_182")];
            tensor<fp16, [1, 8, 188, 375]> x_337_cast_fp16 = matmul(transpose_x = x_337_transpose_x_0, transpose_y = x_337_transpose_y_0, x = q_with_bias_v_31_cast_fp16, y = var_2746_to_fp16)[name = string("x_337_cast_fp16")];
            tensor<int32, [8]> x_339_pad_0 = const()[name = string("x_339_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            string x_339_mode_0 = const()[name = string("x_339_mode_0"), val = string("constant")];
            fp16 const_164_to_fp16 = const()[name = string("const_164_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_339_cast_fp16 = pad(constant_val = const_164_to_fp16, mode = x_339_mode_0, pad = x_339_pad_0, x = x_337_cast_fp16)[name = string("x_339_cast_fp16")];
            tensor<int32, [4]> var_2754 = const()[name = string("op_2754"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_341_cast_fp16 = reshape(shape = var_2754, x = x_339_cast_fp16)[name = string("x_341_cast_fp16")];
            tensor<int32, [4]> var_2758_begin_0 = const()[name = string("op_2758_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_2758_end_0 = const()[name = string("op_2758_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_2758_end_mask_0 = const()[name = string("op_2758_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_2758_cast_fp16 = slice_by_index(begin = var_2758_begin_0, end = var_2758_end_0, end_mask = var_2758_end_mask_0, x = x_341_cast_fp16)[name = string("op_2758_cast_fp16")];
            tensor<int32, [4]> var_2759 = const()[name = string("op_2759"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_61_cast_fp16 = reshape(shape = var_2759, x = var_2758_cast_fp16)[name = string("matrix_bd_61_cast_fp16")];
            bool matrix_ac_31_transpose_x_0 = const()[name = string("matrix_ac_31_transpose_x_0"), val = bool(false)];
            bool matrix_ac_31_transpose_y_0 = const()[name = string("matrix_ac_31_transpose_y_0"), val = bool(false)];
            tensor<int32, [4]> transpose_102_perm_0 = const()[name = string("transpose_102_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_103_perm_0 = const()[name = string("transpose_103_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_103 = transpose(perm = transpose_103_perm_0, x = k_61_cast_fp16)[name = string("transpose_180")];
            tensor<fp16, [1, 8, 188, 128]> transpose_102 = transpose(perm = transpose_102_perm_0, x = var_2742_cast_fp16)[name = string("transpose_181")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_31_cast_fp16 = matmul(transpose_x = matrix_ac_31_transpose_x_0, transpose_y = matrix_ac_31_transpose_y_0, x = transpose_102, y = transpose_103)[name = string("matrix_ac_31_cast_fp16")];
            tensor<int32, [4]> matrix_bd_63_begin_0 = const()[name = string("matrix_bd_63_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_63_end_0 = const()[name = string("matrix_bd_63_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_63_end_mask_0 = const()[name = string("matrix_bd_63_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_63_cast_fp16 = slice_by_index(begin = matrix_bd_63_begin_0, end = matrix_bd_63_end_0, end_mask = matrix_bd_63_end_mask_0, x = matrix_bd_61_cast_fp16)[name = string("matrix_bd_63_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_2768_cast_fp16 = add(x = matrix_ac_31_cast_fp16, y = matrix_bd_63_cast_fp16)[name = string("op_2768_cast_fp16")];
            fp16 _inversed_scores_61_y_0_to_fp16 = const()[name = string("_inversed_scores_61_y_0_to_fp16"), val = fp16(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_61_cast_fp16 = mul(x = var_2768_cast_fp16, y = _inversed_scores_61_y_0_to_fp16)[name = string("_inversed_scores_61_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_63_cast_fp16 = select(a = var_10_to_fp16, b = _inversed_scores_61_cast_fp16, cond = mask_3)[name = string("scores_63_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_2774_cast_fp16 = softmax(axis = var_32, x = scores_63_cast_fp16)[name = string("op_2774_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_821_cast_fp16 = select(a = var_9_to_fp16, b = var_2774_cast_fp16, cond = mask_3)[name = string("input_821_cast_fp16")];
            bool x_343_transpose_x_0 = const()[name = string("x_343_transpose_x_0"), val = bool(false)];
            bool x_343_transpose_y_0 = const()[name = string("x_343_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 188, 128]> value_33_cast_fp16 = transpose(perm = value_33_perm_0, x = v_31_cast_fp16)[name = string("transpose_183")];
            tensor<fp16, [1, 8, 188, 128]> x_343_cast_fp16 = matmul(transpose_x = x_343_transpose_x_0, transpose_y = x_343_transpose_y_0, x = input_821_cast_fp16, y = value_33_cast_fp16)[name = string("x_343_cast_fp16")];
            tensor<int32, [4]> var_2778_perm_0 = const()[name = string("op_2778_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2779 = const()[name = string("op_2779"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_2778_cast_fp16 = transpose(perm = var_2778_perm_0, x = x_343_cast_fp16)[name = string("transpose_179")];
            tensor<fp16, [1, 188, 1024]> input_823_cast_fp16 = reshape(shape = var_2779, x = var_2778_cast_fp16)[name = string("input_823_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_15_self_attn_linear_out_weight_to_fp16 = const()[name = string("module_layers_15_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(772504000)))];
            tensor<fp16, [1, 188, 1024]> linear_144_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_15_self_attn_linear_out_weight_to_fp16, x = input_823_cast_fp16)[name = string("linear_144_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_827_cast_fp16 = add(x = input_819_cast_fp16, y = linear_144_cast_fp16)[name = string("input_827_cast_fp16")];
            tensor<int32, [1]> x_347_axes_0 = const()[name = string("x_347_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_15_norm_conv_weight_to_fp16 = const()[name = string("module_layers_15_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(774601216)))];
            tensor<fp16, [1024]> module_layers_15_norm_conv_bias_to_fp16 = const()[name = string("module_layers_15_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(774603328)))];
            tensor<fp16, [1, 188, 1024]> x_347_cast_fp16 = layer_norm(axes = x_347_axes_0, beta = module_layers_15_norm_conv_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_15_norm_conv_weight_to_fp16, x = input_827_cast_fp16)[name = string("x_347_cast_fp16")];
            tensor<int32, [3]> input_829_perm_0 = const()[name = string("input_829_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            string input_831_pad_type_0 = const()[name = string("input_831_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_831_strides_0 = const()[name = string("input_831_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_831_pad_0 = const()[name = string("input_831_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_831_dilations_0 = const()[name = string("input_831_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_831_groups_0 = const()[name = string("input_831_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 1024, 1]> module_layers_15_conv_pointwise_conv1_weight_to_fp16 = const()[name = string("module_layers_15_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(774605440)))];
            tensor<fp16, [1, 1024, 188]> input_829_cast_fp16 = transpose(perm = input_829_perm_0, x = x_347_cast_fp16)[name = string("transpose_178")];
            tensor<fp16, [1, 2048, 188]> input_831_cast_fp16 = conv(dilations = input_831_dilations_0, groups = input_831_groups_0, pad = input_831_pad_0, pad_type = input_831_pad_type_0, strides = input_831_strides_0, weight = module_layers_15_conv_pointwise_conv1_weight_to_fp16, x = input_829_cast_fp16)[name = string("input_831_cast_fp16")];
            int32 x_349_split_num_splits_0 = const()[name = string("x_349_split_num_splits_0"), val = int32(2)];
            int32 x_349_split_axis_0 = const()[name = string("x_349_split_axis_0"), val = int32(1)];
            tensor<fp16, [1, 1024, 188]> x_349_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_349_split_cast_fp16_1 = split(axis = x_349_split_axis_0, num_splits = x_349_split_num_splits_0, x = input_831_cast_fp16)[name = string("x_349_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_349_split_1_sigmoid_cast_fp16 = sigmoid(x = x_349_split_cast_fp16_1)[name = string("x_349_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_349_cast_fp16 = mul(x = x_349_split_cast_fp16_0, y = x_349_split_1_sigmoid_cast_fp16)[name = string("x_349_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_833_cast_fp16 = select(a = var_9_to_fp16, b = x_349_cast_fp16, cond = var_356)[name = string("input_833_cast_fp16")];
            tensor<int32, [6]> input_835_pad_0 = const()[name = string("input_835_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            string input_835_mode_0 = const()[name = string("input_835_mode_0"), val = string("constant")];
            fp16 const_167_to_fp16 = const()[name = string("const_167_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_835_cast_fp16 = pad(constant_val = const_167_to_fp16, mode = input_835_mode_0, pad = input_835_pad_0, x = input_833_cast_fp16)[name = string("input_835_cast_fp16")];
            string input_837_pad_type_0 = const()[name = string("input_837_pad_type_0"), val = string("valid")];
            int32 input_837_groups_0 = const()[name = string("input_837_groups_0"), val = int32(1024)];
            tensor<int32, [1]> input_837_strides_0 = const()[name = string("input_837_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_837_pad_0 = const()[name = string("input_837_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_837_dilations_0 = const()[name = string("input_837_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_278_to_fp16 = const()[name = string("const_278_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(778799808)))];
            tensor<fp16, [1024]> const_279_to_fp16 = const()[name = string("const_279_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(778818304)))];
            tensor<fp16, [1, 1024, 188]> input_839_cast_fp16 = conv(bias = const_279_to_fp16, dilations = input_837_dilations_0, groups = input_837_groups_0, pad = input_837_pad_0, pad_type = input_837_pad_type_0, strides = input_837_strides_0, weight = const_278_to_fp16, x = input_835_cast_fp16)[name = string("input_839_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_841_cast_fp16 = silu(x = input_839_cast_fp16)[name = string("input_841_cast_fp16")];
            string x_351_pad_type_0 = const()[name = string("x_351_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> x_351_strides_0 = const()[name = string("x_351_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_351_pad_0 = const()[name = string("x_351_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_351_dilations_0 = const()[name = string("x_351_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 x_351_groups_0 = const()[name = string("x_351_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 1024, 1]> module_layers_15_conv_pointwise_conv2_weight_to_fp16 = const()[name = string("module_layers_15_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(778820416)))];
            tensor<fp16, [1, 1024, 188]> x_351_cast_fp16 = conv(dilations = x_351_dilations_0, groups = x_351_groups_0, pad = x_351_pad_0, pad_type = x_351_pad_type_0, strides = x_351_strides_0, weight = module_layers_15_conv_pointwise_conv2_weight_to_fp16, x = input_841_cast_fp16)[name = string("x_351_cast_fp16")];
            tensor<int32, [3]> input_843_perm_0 = const()[name = string("input_843_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_843_cast_fp16 = transpose(perm = input_843_perm_0, x = x_351_cast_fp16)[name = string("transpose_177")];
            tensor<fp16, [1, 188, 1024]> input_845_cast_fp16 = add(x = input_827_cast_fp16, y = input_843_cast_fp16)[name = string("input_845_cast_fp16")];
            tensor<int32, [1]> input_847_axes_0 = const()[name = string("input_847_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_15_norm_feed_forward2_weight_to_fp16 = const()[name = string("module_layers_15_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(780917632)))];
            tensor<fp16, [1024]> module_layers_15_norm_feed_forward2_bias_to_fp16 = const()[name = string("module_layers_15_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(780919744)))];
            tensor<fp16, [1, 188, 1024]> input_847_cast_fp16 = layer_norm(axes = input_847_axes_0, beta = module_layers_15_norm_feed_forward2_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_15_norm_feed_forward2_weight_to_fp16, x = input_845_cast_fp16)[name = string("input_847_cast_fp16")];
            tensor<fp16, [4096, 1024]> module_layers_15_feed_forward2_linear1_weight_to_fp16 = const()[name = string("module_layers_15_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(780921856)))];
            tensor<fp16, [1, 188, 4096]> linear_145_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = module_layers_15_feed_forward2_linear1_weight_to_fp16, x = input_847_cast_fp16)[name = string("linear_145_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_851_cast_fp16 = silu(x = linear_145_cast_fp16)[name = string("input_851_cast_fp16")];
            tensor<fp16, [1024, 4096]> module_layers_15_feed_forward2_linear2_weight_to_fp16 = const()[name = string("module_layers_15_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(789310528)))];
            tensor<fp16, [1, 188, 1024]> linear_146_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_15_feed_forward2_linear2_weight_to_fp16, x = input_851_cast_fp16)[name = string("linear_146_cast_fp16")];
            fp16 var_2839_to_fp16 = const()[name = string("op_2839_to_fp16"), val = fp16(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_2840_cast_fp16 = mul(x = linear_146_cast_fp16, y = var_2839_to_fp16)[name = string("op_2840_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_857_cast_fp16 = add(x = input_845_cast_fp16, y = var_2840_cast_fp16)[name = string("input_857_cast_fp16")];
            tensor<int32, [1]> input_859_axes_0 = const()[name = string("input_859_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_15_norm_out_weight_to_fp16 = const()[name = string("module_layers_15_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(797699200)))];
            tensor<fp16, [1024]> module_layers_15_norm_out_bias_to_fp16 = const()[name = string("module_layers_15_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(797701312)))];
            tensor<fp16, [1, 188, 1024]> input_859_cast_fp16 = layer_norm(axes = input_859_axes_0, beta = module_layers_15_norm_out_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_15_norm_out_weight_to_fp16, x = input_857_cast_fp16)[name = string("input_859_cast_fp16")];
            tensor<int32, [1]> input_861_axes_0 = const()[name = string("input_861_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_16_norm_feed_forward1_weight_to_fp16 = const()[name = string("module_layers_16_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(797703424)))];
            tensor<fp16, [1024]> module_layers_16_norm_feed_forward1_bias_to_fp16 = const()[name = string("module_layers_16_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(797705536)))];
            tensor<fp16, [1, 188, 1024]> input_861_cast_fp16 = layer_norm(axes = input_861_axes_0, beta = module_layers_16_norm_feed_forward1_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_16_norm_feed_forward1_weight_to_fp16, x = input_859_cast_fp16)[name = string("input_861_cast_fp16")];
            tensor<fp16, [4096, 1024]> module_layers_16_feed_forward1_linear1_weight_to_fp16 = const()[name = string("module_layers_16_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(797707648)))];
            tensor<fp16, [1, 188, 4096]> linear_147_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = module_layers_16_feed_forward1_linear1_weight_to_fp16, x = input_861_cast_fp16)[name = string("linear_147_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_865_cast_fp16 = silu(x = linear_147_cast_fp16)[name = string("input_865_cast_fp16")];
            tensor<fp16, [1024, 4096]> module_layers_16_feed_forward1_linear2_weight_to_fp16 = const()[name = string("module_layers_16_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(806096320)))];
            tensor<fp16, [1, 188, 1024]> linear_148_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_16_feed_forward1_linear2_weight_to_fp16, x = input_865_cast_fp16)[name = string("linear_148_cast_fp16")];
            fp16 var_2868_to_fp16 = const()[name = string("op_2868_to_fp16"), val = fp16(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_2869_cast_fp16 = mul(x = linear_148_cast_fp16, y = var_2868_to_fp16)[name = string("op_2869_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_871_cast_fp16 = add(x = input_859_cast_fp16, y = var_2869_cast_fp16)[name = string("input_871_cast_fp16")];
            tensor<int32, [1]> query_33_axes_0 = const()[name = string("query_33_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_16_norm_self_att_weight_to_fp16 = const()[name = string("module_layers_16_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(814484992)))];
            tensor<fp16, [1024]> module_layers_16_norm_self_att_bias_to_fp16 = const()[name = string("module_layers_16_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(814487104)))];
            tensor<fp16, [1, 188, 1024]> query_33_cast_fp16 = layer_norm(axes = query_33_axes_0, beta = module_layers_16_norm_self_att_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_16_norm_self_att_weight_to_fp16, x = input_871_cast_fp16)[name = string("query_33_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_16_self_attn_linear_q_weight_to_fp16 = const()[name = string("module_layers_16_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(814489216)))];
            tensor<fp16, [1, 188, 1024]> linear_149_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_16_self_attn_linear_q_weight_to_fp16, x = query_33_cast_fp16)[name = string("linear_149_cast_fp16")];
            tensor<int32, [4]> var_2885 = const()[name = string("op_2885"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_97_cast_fp16 = reshape(shape = var_2885, x = linear_149_cast_fp16)[name = string("q_97_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_16_self_attn_linear_k_weight_to_fp16 = const()[name = string("module_layers_16_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(816586432)))];
            tensor<fp16, [1, 188, 1024]> linear_150_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_16_self_attn_linear_k_weight_to_fp16, x = query_33_cast_fp16)[name = string("linear_150_cast_fp16")];
            tensor<int32, [4]> var_2889 = const()[name = string("op_2889"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_65_cast_fp16 = reshape(shape = var_2889, x = linear_150_cast_fp16)[name = string("k_65_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_16_self_attn_linear_v_weight_to_fp16 = const()[name = string("module_layers_16_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(818683648)))];
            tensor<fp16, [1, 188, 1024]> linear_151_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_16_self_attn_linear_v_weight_to_fp16, x = query_33_cast_fp16)[name = string("linear_151_cast_fp16")];
            tensor<int32, [4]> var_2893 = const()[name = string("op_2893"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_33_cast_fp16 = reshape(shape = var_2893, x = linear_151_cast_fp16)[name = string("v_33_cast_fp16")];
            tensor<int32, [4]> value_35_perm_0 = const()[name = string("value_35_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> module_layers_16_self_attn_pos_bias_u_to_fp16 = const()[name = string("module_layers_16_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(820780864)))];
            tensor<fp16, [1, 188, 8, 128]> var_2905_cast_fp16 = add(x = q_97_cast_fp16, y = module_layers_16_self_attn_pos_bias_u_to_fp16)[name = string("op_2905_cast_fp16")];
            tensor<fp16, [8, 128]> module_layers_16_self_attn_pos_bias_v_to_fp16 = const()[name = string("module_layers_16_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(820782976)))];
            tensor<fp16, [1, 188, 8, 128]> var_2907_cast_fp16 = add(x = q_97_cast_fp16, y = module_layers_16_self_attn_pos_bias_v_to_fp16)[name = string("op_2907_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_33_perm_0 = const()[name = string("q_with_bias_v_33_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            bool x_359_transpose_x_0 = const()[name = string("x_359_transpose_x_0"), val = bool(false)];
            bool x_359_transpose_y_0 = const()[name = string("x_359_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 128, 375]> var_2909_to_fp16 = const()[name = string("op_2909_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(820785088)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_33_cast_fp16 = transpose(perm = q_with_bias_v_33_perm_0, x = var_2907_cast_fp16)[name = string("transpose_175")];
            tensor<fp16, [1, 8, 188, 375]> x_359_cast_fp16 = matmul(transpose_x = x_359_transpose_x_0, transpose_y = x_359_transpose_y_0, x = q_with_bias_v_33_cast_fp16, y = var_2909_to_fp16)[name = string("x_359_cast_fp16")];
            tensor<int32, [8]> x_361_pad_0 = const()[name = string("x_361_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            string x_361_mode_0 = const()[name = string("x_361_mode_0"), val = string("constant")];
            fp16 const_174_to_fp16 = const()[name = string("const_174_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_361_cast_fp16 = pad(constant_val = const_174_to_fp16, mode = x_361_mode_0, pad = x_361_pad_0, x = x_359_cast_fp16)[name = string("x_361_cast_fp16")];
            tensor<int32, [4]> var_2917 = const()[name = string("op_2917"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_363_cast_fp16 = reshape(shape = var_2917, x = x_361_cast_fp16)[name = string("x_363_cast_fp16")];
            tensor<int32, [4]> var_2921_begin_0 = const()[name = string("op_2921_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_2921_end_0 = const()[name = string("op_2921_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_2921_end_mask_0 = const()[name = string("op_2921_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_2921_cast_fp16 = slice_by_index(begin = var_2921_begin_0, end = var_2921_end_0, end_mask = var_2921_end_mask_0, x = x_363_cast_fp16)[name = string("op_2921_cast_fp16")];
            tensor<int32, [4]> var_2922 = const()[name = string("op_2922"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_65_cast_fp16 = reshape(shape = var_2922, x = var_2921_cast_fp16)[name = string("matrix_bd_65_cast_fp16")];
            bool matrix_ac_33_transpose_x_0 = const()[name = string("matrix_ac_33_transpose_x_0"), val = bool(false)];
            bool matrix_ac_33_transpose_y_0 = const()[name = string("matrix_ac_33_transpose_y_0"), val = bool(false)];
            tensor<int32, [4]> transpose_104_perm_0 = const()[name = string("transpose_104_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_105_perm_0 = const()[name = string("transpose_105_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_105 = transpose(perm = transpose_105_perm_0, x = k_65_cast_fp16)[name = string("transpose_173")];
            tensor<fp16, [1, 8, 188, 128]> transpose_104 = transpose(perm = transpose_104_perm_0, x = var_2905_cast_fp16)[name = string("transpose_174")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_33_cast_fp16 = matmul(transpose_x = matrix_ac_33_transpose_x_0, transpose_y = matrix_ac_33_transpose_y_0, x = transpose_104, y = transpose_105)[name = string("matrix_ac_33_cast_fp16")];
            tensor<int32, [4]> matrix_bd_67_begin_0 = const()[name = string("matrix_bd_67_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_67_end_0 = const()[name = string("matrix_bd_67_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_67_end_mask_0 = const()[name = string("matrix_bd_67_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_67_cast_fp16 = slice_by_index(begin = matrix_bd_67_begin_0, end = matrix_bd_67_end_0, end_mask = matrix_bd_67_end_mask_0, x = matrix_bd_65_cast_fp16)[name = string("matrix_bd_67_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_2931_cast_fp16 = add(x = matrix_ac_33_cast_fp16, y = matrix_bd_67_cast_fp16)[name = string("op_2931_cast_fp16")];
            fp16 _inversed_scores_65_y_0_to_fp16 = const()[name = string("_inversed_scores_65_y_0_to_fp16"), val = fp16(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_65_cast_fp16 = mul(x = var_2931_cast_fp16, y = _inversed_scores_65_y_0_to_fp16)[name = string("_inversed_scores_65_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_67_cast_fp16 = select(a = var_10_to_fp16, b = _inversed_scores_65_cast_fp16, cond = mask_3)[name = string("scores_67_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_2937_cast_fp16 = softmax(axis = var_32, x = scores_67_cast_fp16)[name = string("op_2937_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_873_cast_fp16 = select(a = var_9_to_fp16, b = var_2937_cast_fp16, cond = mask_3)[name = string("input_873_cast_fp16")];
            bool x_365_transpose_x_0 = const()[name = string("x_365_transpose_x_0"), val = bool(false)];
            bool x_365_transpose_y_0 = const()[name = string("x_365_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 188, 128]> value_35_cast_fp16 = transpose(perm = value_35_perm_0, x = v_33_cast_fp16)[name = string("transpose_176")];
            tensor<fp16, [1, 8, 188, 128]> x_365_cast_fp16 = matmul(transpose_x = x_365_transpose_x_0, transpose_y = x_365_transpose_y_0, x = input_873_cast_fp16, y = value_35_cast_fp16)[name = string("x_365_cast_fp16")];
            tensor<int32, [4]> var_2941_perm_0 = const()[name = string("op_2941_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2942 = const()[name = string("op_2942"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_2941_cast_fp16 = transpose(perm = var_2941_perm_0, x = x_365_cast_fp16)[name = string("transpose_172")];
            tensor<fp16, [1, 188, 1024]> input_875_cast_fp16 = reshape(shape = var_2942, x = var_2941_cast_fp16)[name = string("input_875_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_16_self_attn_linear_out_weight_to_fp16 = const()[name = string("module_layers_16_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(821553152)))];
            tensor<fp16, [1, 188, 1024]> linear_153_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_16_self_attn_linear_out_weight_to_fp16, x = input_875_cast_fp16)[name = string("linear_153_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_879_cast_fp16 = add(x = input_871_cast_fp16, y = linear_153_cast_fp16)[name = string("input_879_cast_fp16")];
            tensor<int32, [1]> x_369_axes_0 = const()[name = string("x_369_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_16_norm_conv_weight_to_fp16 = const()[name = string("module_layers_16_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(823650368)))];
            tensor<fp16, [1024]> module_layers_16_norm_conv_bias_to_fp16 = const()[name = string("module_layers_16_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(823652480)))];
            tensor<fp16, [1, 188, 1024]> x_369_cast_fp16 = layer_norm(axes = x_369_axes_0, beta = module_layers_16_norm_conv_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_16_norm_conv_weight_to_fp16, x = input_879_cast_fp16)[name = string("x_369_cast_fp16")];
            tensor<int32, [3]> input_881_perm_0 = const()[name = string("input_881_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            string input_883_pad_type_0 = const()[name = string("input_883_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_883_strides_0 = const()[name = string("input_883_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_883_pad_0 = const()[name = string("input_883_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_883_dilations_0 = const()[name = string("input_883_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_883_groups_0 = const()[name = string("input_883_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 1024, 1]> module_layers_16_conv_pointwise_conv1_weight_to_fp16 = const()[name = string("module_layers_16_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(823654592)))];
            tensor<fp16, [1, 1024, 188]> input_881_cast_fp16 = transpose(perm = input_881_perm_0, x = x_369_cast_fp16)[name = string("transpose_171")];
            tensor<fp16, [1, 2048, 188]> input_883_cast_fp16 = conv(dilations = input_883_dilations_0, groups = input_883_groups_0, pad = input_883_pad_0, pad_type = input_883_pad_type_0, strides = input_883_strides_0, weight = module_layers_16_conv_pointwise_conv1_weight_to_fp16, x = input_881_cast_fp16)[name = string("input_883_cast_fp16")];
            int32 x_371_split_num_splits_0 = const()[name = string("x_371_split_num_splits_0"), val = int32(2)];
            int32 x_371_split_axis_0 = const()[name = string("x_371_split_axis_0"), val = int32(1)];
            tensor<fp16, [1, 1024, 188]> x_371_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_371_split_cast_fp16_1 = split(axis = x_371_split_axis_0, num_splits = x_371_split_num_splits_0, x = input_883_cast_fp16)[name = string("x_371_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_371_split_1_sigmoid_cast_fp16 = sigmoid(x = x_371_split_cast_fp16_1)[name = string("x_371_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_371_cast_fp16 = mul(x = x_371_split_cast_fp16_0, y = x_371_split_1_sigmoid_cast_fp16)[name = string("x_371_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_885_cast_fp16 = select(a = var_9_to_fp16, b = x_371_cast_fp16, cond = var_356)[name = string("input_885_cast_fp16")];
            tensor<int32, [6]> input_887_pad_0 = const()[name = string("input_887_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            string input_887_mode_0 = const()[name = string("input_887_mode_0"), val = string("constant")];
            fp16 const_177_to_fp16 = const()[name = string("const_177_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_887_cast_fp16 = pad(constant_val = const_177_to_fp16, mode = input_887_mode_0, pad = input_887_pad_0, x = input_885_cast_fp16)[name = string("input_887_cast_fp16")];
            string input_889_pad_type_0 = const()[name = string("input_889_pad_type_0"), val = string("valid")];
            int32 input_889_groups_0 = const()[name = string("input_889_groups_0"), val = int32(1024)];
            tensor<int32, [1]> input_889_strides_0 = const()[name = string("input_889_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_889_pad_0 = const()[name = string("input_889_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_889_dilations_0 = const()[name = string("input_889_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_280_to_fp16 = const()[name = string("const_280_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(827848960)))];
            tensor<fp16, [1024]> const_281_to_fp16 = const()[name = string("const_281_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(827867456)))];
            tensor<fp16, [1, 1024, 188]> input_891_cast_fp16 = conv(bias = const_281_to_fp16, dilations = input_889_dilations_0, groups = input_889_groups_0, pad = input_889_pad_0, pad_type = input_889_pad_type_0, strides = input_889_strides_0, weight = const_280_to_fp16, x = input_887_cast_fp16)[name = string("input_891_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_893_cast_fp16 = silu(x = input_891_cast_fp16)[name = string("input_893_cast_fp16")];
            string x_373_pad_type_0 = const()[name = string("x_373_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> x_373_strides_0 = const()[name = string("x_373_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_373_pad_0 = const()[name = string("x_373_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_373_dilations_0 = const()[name = string("x_373_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 x_373_groups_0 = const()[name = string("x_373_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 1024, 1]> module_layers_16_conv_pointwise_conv2_weight_to_fp16 = const()[name = string("module_layers_16_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(827869568)))];
            tensor<fp16, [1, 1024, 188]> x_373_cast_fp16 = conv(dilations = x_373_dilations_0, groups = x_373_groups_0, pad = x_373_pad_0, pad_type = x_373_pad_type_0, strides = x_373_strides_0, weight = module_layers_16_conv_pointwise_conv2_weight_to_fp16, x = input_893_cast_fp16)[name = string("x_373_cast_fp16")];
            tensor<int32, [3]> input_895_perm_0 = const()[name = string("input_895_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_895_cast_fp16 = transpose(perm = input_895_perm_0, x = x_373_cast_fp16)[name = string("transpose_170")];
            tensor<fp16, [1, 188, 1024]> input_897_cast_fp16 = add(x = input_879_cast_fp16, y = input_895_cast_fp16)[name = string("input_897_cast_fp16")];
            tensor<int32, [1]> input_899_axes_0 = const()[name = string("input_899_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_16_norm_feed_forward2_weight_to_fp16 = const()[name = string("module_layers_16_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(829966784)))];
            tensor<fp16, [1024]> module_layers_16_norm_feed_forward2_bias_to_fp16 = const()[name = string("module_layers_16_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(829968896)))];
            tensor<fp16, [1, 188, 1024]> input_899_cast_fp16 = layer_norm(axes = input_899_axes_0, beta = module_layers_16_norm_feed_forward2_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_16_norm_feed_forward2_weight_to_fp16, x = input_897_cast_fp16)[name = string("input_899_cast_fp16")];
            tensor<fp16, [4096, 1024]> module_layers_16_feed_forward2_linear1_weight_to_fp16 = const()[name = string("module_layers_16_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(829971008)))];
            tensor<fp16, [1, 188, 4096]> linear_154_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = module_layers_16_feed_forward2_linear1_weight_to_fp16, x = input_899_cast_fp16)[name = string("linear_154_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_903_cast_fp16 = silu(x = linear_154_cast_fp16)[name = string("input_903_cast_fp16")];
            tensor<fp16, [1024, 4096]> module_layers_16_feed_forward2_linear2_weight_to_fp16 = const()[name = string("module_layers_16_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(838359680)))];
            tensor<fp16, [1, 188, 1024]> linear_155_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_16_feed_forward2_linear2_weight_to_fp16, x = input_903_cast_fp16)[name = string("linear_155_cast_fp16")];
            fp16 var_3002_to_fp16 = const()[name = string("op_3002_to_fp16"), val = fp16(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_3003_cast_fp16 = mul(x = linear_155_cast_fp16, y = var_3002_to_fp16)[name = string("op_3003_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_909_cast_fp16 = add(x = input_897_cast_fp16, y = var_3003_cast_fp16)[name = string("input_909_cast_fp16")];
            tensor<int32, [1]> input_911_axes_0 = const()[name = string("input_911_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_16_norm_out_weight_to_fp16 = const()[name = string("module_layers_16_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(846748352)))];
            tensor<fp16, [1024]> module_layers_16_norm_out_bias_to_fp16 = const()[name = string("module_layers_16_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(846750464)))];
            tensor<fp16, [1, 188, 1024]> input_911_cast_fp16 = layer_norm(axes = input_911_axes_0, beta = module_layers_16_norm_out_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_16_norm_out_weight_to_fp16, x = input_909_cast_fp16)[name = string("input_911_cast_fp16")];
            tensor<int32, [1]> input_913_axes_0 = const()[name = string("input_913_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_17_norm_feed_forward1_weight_to_fp16 = const()[name = string("module_layers_17_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(846752576)))];
            tensor<fp16, [1024]> module_layers_17_norm_feed_forward1_bias_to_fp16 = const()[name = string("module_layers_17_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(846754688)))];
            tensor<fp16, [1, 188, 1024]> input_913_cast_fp16 = layer_norm(axes = input_913_axes_0, beta = module_layers_17_norm_feed_forward1_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_17_norm_feed_forward1_weight_to_fp16, x = input_911_cast_fp16)[name = string("input_913_cast_fp16")];
            tensor<fp16, [4096, 1024]> module_layers_17_feed_forward1_linear1_weight_to_fp16 = const()[name = string("module_layers_17_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(846756800)))];
            tensor<fp16, [1, 188, 4096]> linear_156_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = module_layers_17_feed_forward1_linear1_weight_to_fp16, x = input_913_cast_fp16)[name = string("linear_156_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_917_cast_fp16 = silu(x = linear_156_cast_fp16)[name = string("input_917_cast_fp16")];
            tensor<fp16, [1024, 4096]> module_layers_17_feed_forward1_linear2_weight_to_fp16 = const()[name = string("module_layers_17_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(855145472)))];
            tensor<fp16, [1, 188, 1024]> linear_157_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_17_feed_forward1_linear2_weight_to_fp16, x = input_917_cast_fp16)[name = string("linear_157_cast_fp16")];
            fp16 var_3031_to_fp16 = const()[name = string("op_3031_to_fp16"), val = fp16(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_3032_cast_fp16 = mul(x = linear_157_cast_fp16, y = var_3031_to_fp16)[name = string("op_3032_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_923_cast_fp16 = add(x = input_911_cast_fp16, y = var_3032_cast_fp16)[name = string("input_923_cast_fp16")];
            tensor<int32, [1]> query_35_axes_0 = const()[name = string("query_35_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_17_norm_self_att_weight_to_fp16 = const()[name = string("module_layers_17_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(863534144)))];
            tensor<fp16, [1024]> module_layers_17_norm_self_att_bias_to_fp16 = const()[name = string("module_layers_17_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(863536256)))];
            tensor<fp16, [1, 188, 1024]> query_35_cast_fp16 = layer_norm(axes = query_35_axes_0, beta = module_layers_17_norm_self_att_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_17_norm_self_att_weight_to_fp16, x = input_923_cast_fp16)[name = string("query_35_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_17_self_attn_linear_q_weight_to_fp16 = const()[name = string("module_layers_17_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(863538368)))];
            tensor<fp16, [1, 188, 1024]> linear_158_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_17_self_attn_linear_q_weight_to_fp16, x = query_35_cast_fp16)[name = string("linear_158_cast_fp16")];
            tensor<int32, [4]> var_3048 = const()[name = string("op_3048"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_103_cast_fp16 = reshape(shape = var_3048, x = linear_158_cast_fp16)[name = string("q_103_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_17_self_attn_linear_k_weight_to_fp16 = const()[name = string("module_layers_17_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(865635584)))];
            tensor<fp16, [1, 188, 1024]> linear_159_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_17_self_attn_linear_k_weight_to_fp16, x = query_35_cast_fp16)[name = string("linear_159_cast_fp16")];
            tensor<int32, [4]> var_3052 = const()[name = string("op_3052"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_69_cast_fp16 = reshape(shape = var_3052, x = linear_159_cast_fp16)[name = string("k_69_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_17_self_attn_linear_v_weight_to_fp16 = const()[name = string("module_layers_17_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(867732800)))];
            tensor<fp16, [1, 188, 1024]> linear_160_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_17_self_attn_linear_v_weight_to_fp16, x = query_35_cast_fp16)[name = string("linear_160_cast_fp16")];
            tensor<int32, [4]> var_3056 = const()[name = string("op_3056"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_35_cast_fp16 = reshape(shape = var_3056, x = linear_160_cast_fp16)[name = string("v_35_cast_fp16")];
            tensor<int32, [4]> value_37_perm_0 = const()[name = string("value_37_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> module_layers_17_self_attn_pos_bias_u_to_fp16 = const()[name = string("module_layers_17_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(869830016)))];
            tensor<fp16, [1, 188, 8, 128]> var_3068_cast_fp16 = add(x = q_103_cast_fp16, y = module_layers_17_self_attn_pos_bias_u_to_fp16)[name = string("op_3068_cast_fp16")];
            tensor<fp16, [8, 128]> module_layers_17_self_attn_pos_bias_v_to_fp16 = const()[name = string("module_layers_17_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(869832128)))];
            tensor<fp16, [1, 188, 8, 128]> var_3070_cast_fp16 = add(x = q_103_cast_fp16, y = module_layers_17_self_attn_pos_bias_v_to_fp16)[name = string("op_3070_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_35_perm_0 = const()[name = string("q_with_bias_v_35_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            bool x_381_transpose_x_0 = const()[name = string("x_381_transpose_x_0"), val = bool(false)];
            bool x_381_transpose_y_0 = const()[name = string("x_381_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 128, 375]> var_3072_to_fp16 = const()[name = string("op_3072_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(869834240)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_35_cast_fp16 = transpose(perm = q_with_bias_v_35_perm_0, x = var_3070_cast_fp16)[name = string("transpose_168")];
            tensor<fp16, [1, 8, 188, 375]> x_381_cast_fp16 = matmul(transpose_x = x_381_transpose_x_0, transpose_y = x_381_transpose_y_0, x = q_with_bias_v_35_cast_fp16, y = var_3072_to_fp16)[name = string("x_381_cast_fp16")];
            tensor<int32, [8]> x_383_pad_0 = const()[name = string("x_383_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            string x_383_mode_0 = const()[name = string("x_383_mode_0"), val = string("constant")];
            fp16 const_184_to_fp16 = const()[name = string("const_184_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_383_cast_fp16 = pad(constant_val = const_184_to_fp16, mode = x_383_mode_0, pad = x_383_pad_0, x = x_381_cast_fp16)[name = string("x_383_cast_fp16")];
            tensor<int32, [4]> var_3080 = const()[name = string("op_3080"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_385_cast_fp16 = reshape(shape = var_3080, x = x_383_cast_fp16)[name = string("x_385_cast_fp16")];
            tensor<int32, [4]> var_3084_begin_0 = const()[name = string("op_3084_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_3084_end_0 = const()[name = string("op_3084_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_3084_end_mask_0 = const()[name = string("op_3084_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_3084_cast_fp16 = slice_by_index(begin = var_3084_begin_0, end = var_3084_end_0, end_mask = var_3084_end_mask_0, x = x_385_cast_fp16)[name = string("op_3084_cast_fp16")];
            tensor<int32, [4]> var_3085 = const()[name = string("op_3085"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_69_cast_fp16 = reshape(shape = var_3085, x = var_3084_cast_fp16)[name = string("matrix_bd_69_cast_fp16")];
            bool matrix_ac_35_transpose_x_0 = const()[name = string("matrix_ac_35_transpose_x_0"), val = bool(false)];
            bool matrix_ac_35_transpose_y_0 = const()[name = string("matrix_ac_35_transpose_y_0"), val = bool(false)];
            tensor<int32, [4]> transpose_106_perm_0 = const()[name = string("transpose_106_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_107_perm_0 = const()[name = string("transpose_107_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_107 = transpose(perm = transpose_107_perm_0, x = k_69_cast_fp16)[name = string("transpose_166")];
            tensor<fp16, [1, 8, 188, 128]> transpose_106 = transpose(perm = transpose_106_perm_0, x = var_3068_cast_fp16)[name = string("transpose_167")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_35_cast_fp16 = matmul(transpose_x = matrix_ac_35_transpose_x_0, transpose_y = matrix_ac_35_transpose_y_0, x = transpose_106, y = transpose_107)[name = string("matrix_ac_35_cast_fp16")];
            tensor<int32, [4]> matrix_bd_71_begin_0 = const()[name = string("matrix_bd_71_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_71_end_0 = const()[name = string("matrix_bd_71_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_71_end_mask_0 = const()[name = string("matrix_bd_71_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_71_cast_fp16 = slice_by_index(begin = matrix_bd_71_begin_0, end = matrix_bd_71_end_0, end_mask = matrix_bd_71_end_mask_0, x = matrix_bd_69_cast_fp16)[name = string("matrix_bd_71_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_3094_cast_fp16 = add(x = matrix_ac_35_cast_fp16, y = matrix_bd_71_cast_fp16)[name = string("op_3094_cast_fp16")];
            fp16 _inversed_scores_69_y_0_to_fp16 = const()[name = string("_inversed_scores_69_y_0_to_fp16"), val = fp16(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_69_cast_fp16 = mul(x = var_3094_cast_fp16, y = _inversed_scores_69_y_0_to_fp16)[name = string("_inversed_scores_69_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_71_cast_fp16 = select(a = var_10_to_fp16, b = _inversed_scores_69_cast_fp16, cond = mask_3)[name = string("scores_71_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_3100_cast_fp16 = softmax(axis = var_32, x = scores_71_cast_fp16)[name = string("op_3100_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_925_cast_fp16 = select(a = var_9_to_fp16, b = var_3100_cast_fp16, cond = mask_3)[name = string("input_925_cast_fp16")];
            bool x_387_transpose_x_0 = const()[name = string("x_387_transpose_x_0"), val = bool(false)];
            bool x_387_transpose_y_0 = const()[name = string("x_387_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 188, 128]> value_37_cast_fp16 = transpose(perm = value_37_perm_0, x = v_35_cast_fp16)[name = string("transpose_169")];
            tensor<fp16, [1, 8, 188, 128]> x_387_cast_fp16 = matmul(transpose_x = x_387_transpose_x_0, transpose_y = x_387_transpose_y_0, x = input_925_cast_fp16, y = value_37_cast_fp16)[name = string("x_387_cast_fp16")];
            tensor<int32, [4]> var_3104_perm_0 = const()[name = string("op_3104_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_3105 = const()[name = string("op_3105"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_3104_cast_fp16 = transpose(perm = var_3104_perm_0, x = x_387_cast_fp16)[name = string("transpose_165")];
            tensor<fp16, [1, 188, 1024]> input_927_cast_fp16 = reshape(shape = var_3105, x = var_3104_cast_fp16)[name = string("input_927_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_17_self_attn_linear_out_weight_to_fp16 = const()[name = string("module_layers_17_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(870602304)))];
            tensor<fp16, [1, 188, 1024]> linear_162_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_17_self_attn_linear_out_weight_to_fp16, x = input_927_cast_fp16)[name = string("linear_162_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_931_cast_fp16 = add(x = input_923_cast_fp16, y = linear_162_cast_fp16)[name = string("input_931_cast_fp16")];
            tensor<int32, [1]> x_391_axes_0 = const()[name = string("x_391_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_17_norm_conv_weight_to_fp16 = const()[name = string("module_layers_17_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(872699520)))];
            tensor<fp16, [1024]> module_layers_17_norm_conv_bias_to_fp16 = const()[name = string("module_layers_17_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(872701632)))];
            tensor<fp16, [1, 188, 1024]> x_391_cast_fp16 = layer_norm(axes = x_391_axes_0, beta = module_layers_17_norm_conv_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_17_norm_conv_weight_to_fp16, x = input_931_cast_fp16)[name = string("x_391_cast_fp16")];
            tensor<int32, [3]> input_933_perm_0 = const()[name = string("input_933_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            string input_935_pad_type_0 = const()[name = string("input_935_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_935_strides_0 = const()[name = string("input_935_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_935_pad_0 = const()[name = string("input_935_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_935_dilations_0 = const()[name = string("input_935_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_935_groups_0 = const()[name = string("input_935_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 1024, 1]> module_layers_17_conv_pointwise_conv1_weight_to_fp16 = const()[name = string("module_layers_17_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(872703744)))];
            tensor<fp16, [1, 1024, 188]> input_933_cast_fp16 = transpose(perm = input_933_perm_0, x = x_391_cast_fp16)[name = string("transpose_164")];
            tensor<fp16, [1, 2048, 188]> input_935_cast_fp16 = conv(dilations = input_935_dilations_0, groups = input_935_groups_0, pad = input_935_pad_0, pad_type = input_935_pad_type_0, strides = input_935_strides_0, weight = module_layers_17_conv_pointwise_conv1_weight_to_fp16, x = input_933_cast_fp16)[name = string("input_935_cast_fp16")];
            int32 x_393_split_num_splits_0 = const()[name = string("x_393_split_num_splits_0"), val = int32(2)];
            int32 x_393_split_axis_0 = const()[name = string("x_393_split_axis_0"), val = int32(1)];
            tensor<fp16, [1, 1024, 188]> x_393_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_393_split_cast_fp16_1 = split(axis = x_393_split_axis_0, num_splits = x_393_split_num_splits_0, x = input_935_cast_fp16)[name = string("x_393_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_393_split_1_sigmoid_cast_fp16 = sigmoid(x = x_393_split_cast_fp16_1)[name = string("x_393_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_393_cast_fp16 = mul(x = x_393_split_cast_fp16_0, y = x_393_split_1_sigmoid_cast_fp16)[name = string("x_393_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_937_cast_fp16 = select(a = var_9_to_fp16, b = x_393_cast_fp16, cond = var_356)[name = string("input_937_cast_fp16")];
            tensor<int32, [6]> input_939_pad_0 = const()[name = string("input_939_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            string input_939_mode_0 = const()[name = string("input_939_mode_0"), val = string("constant")];
            fp16 const_187_to_fp16 = const()[name = string("const_187_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_939_cast_fp16 = pad(constant_val = const_187_to_fp16, mode = input_939_mode_0, pad = input_939_pad_0, x = input_937_cast_fp16)[name = string("input_939_cast_fp16")];
            string input_941_pad_type_0 = const()[name = string("input_941_pad_type_0"), val = string("valid")];
            int32 input_941_groups_0 = const()[name = string("input_941_groups_0"), val = int32(1024)];
            tensor<int32, [1]> input_941_strides_0 = const()[name = string("input_941_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_941_pad_0 = const()[name = string("input_941_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_941_dilations_0 = const()[name = string("input_941_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_282_to_fp16 = const()[name = string("const_282_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(876898112)))];
            tensor<fp16, [1024]> const_283_to_fp16 = const()[name = string("const_283_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(876916608)))];
            tensor<fp16, [1, 1024, 188]> input_943_cast_fp16 = conv(bias = const_283_to_fp16, dilations = input_941_dilations_0, groups = input_941_groups_0, pad = input_941_pad_0, pad_type = input_941_pad_type_0, strides = input_941_strides_0, weight = const_282_to_fp16, x = input_939_cast_fp16)[name = string("input_943_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_945_cast_fp16 = silu(x = input_943_cast_fp16)[name = string("input_945_cast_fp16")];
            string x_395_pad_type_0 = const()[name = string("x_395_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> x_395_strides_0 = const()[name = string("x_395_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_395_pad_0 = const()[name = string("x_395_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_395_dilations_0 = const()[name = string("x_395_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 x_395_groups_0 = const()[name = string("x_395_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 1024, 1]> module_layers_17_conv_pointwise_conv2_weight_to_fp16 = const()[name = string("module_layers_17_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(876918720)))];
            tensor<fp16, [1, 1024, 188]> x_395_cast_fp16 = conv(dilations = x_395_dilations_0, groups = x_395_groups_0, pad = x_395_pad_0, pad_type = x_395_pad_type_0, strides = x_395_strides_0, weight = module_layers_17_conv_pointwise_conv2_weight_to_fp16, x = input_945_cast_fp16)[name = string("x_395_cast_fp16")];
            tensor<int32, [3]> input_947_perm_0 = const()[name = string("input_947_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_947_cast_fp16 = transpose(perm = input_947_perm_0, x = x_395_cast_fp16)[name = string("transpose_163")];
            tensor<fp16, [1, 188, 1024]> input_949_cast_fp16 = add(x = input_931_cast_fp16, y = input_947_cast_fp16)[name = string("input_949_cast_fp16")];
            tensor<int32, [1]> input_951_axes_0 = const()[name = string("input_951_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_17_norm_feed_forward2_weight_to_fp16 = const()[name = string("module_layers_17_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(879015936)))];
            tensor<fp16, [1024]> module_layers_17_norm_feed_forward2_bias_to_fp16 = const()[name = string("module_layers_17_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(879018048)))];
            tensor<fp16, [1, 188, 1024]> input_951_cast_fp16 = layer_norm(axes = input_951_axes_0, beta = module_layers_17_norm_feed_forward2_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_17_norm_feed_forward2_weight_to_fp16, x = input_949_cast_fp16)[name = string("input_951_cast_fp16")];
            tensor<fp16, [4096, 1024]> module_layers_17_feed_forward2_linear1_weight_to_fp16 = const()[name = string("module_layers_17_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(879020160)))];
            tensor<fp16, [1, 188, 4096]> linear_163_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = module_layers_17_feed_forward2_linear1_weight_to_fp16, x = input_951_cast_fp16)[name = string("linear_163_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_955_cast_fp16 = silu(x = linear_163_cast_fp16)[name = string("input_955_cast_fp16")];
            tensor<fp16, [1024, 4096]> module_layers_17_feed_forward2_linear2_weight_to_fp16 = const()[name = string("module_layers_17_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(887408832)))];
            tensor<fp16, [1, 188, 1024]> linear_164_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_17_feed_forward2_linear2_weight_to_fp16, x = input_955_cast_fp16)[name = string("linear_164_cast_fp16")];
            fp16 var_3165_to_fp16 = const()[name = string("op_3165_to_fp16"), val = fp16(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_3166_cast_fp16 = mul(x = linear_164_cast_fp16, y = var_3165_to_fp16)[name = string("op_3166_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_961_cast_fp16 = add(x = input_949_cast_fp16, y = var_3166_cast_fp16)[name = string("input_961_cast_fp16")];
            tensor<int32, [1]> input_963_axes_0 = const()[name = string("input_963_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_17_norm_out_weight_to_fp16 = const()[name = string("module_layers_17_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(895797504)))];
            tensor<fp16, [1024]> module_layers_17_norm_out_bias_to_fp16 = const()[name = string("module_layers_17_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(895799616)))];
            tensor<fp16, [1, 188, 1024]> input_963_cast_fp16 = layer_norm(axes = input_963_axes_0, beta = module_layers_17_norm_out_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_17_norm_out_weight_to_fp16, x = input_961_cast_fp16)[name = string("input_963_cast_fp16")];
            tensor<int32, [1]> input_965_axes_0 = const()[name = string("input_965_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_18_norm_feed_forward1_weight_to_fp16 = const()[name = string("module_layers_18_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(895801728)))];
            tensor<fp16, [1024]> module_layers_18_norm_feed_forward1_bias_to_fp16 = const()[name = string("module_layers_18_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(895803840)))];
            tensor<fp16, [1, 188, 1024]> input_965_cast_fp16 = layer_norm(axes = input_965_axes_0, beta = module_layers_18_norm_feed_forward1_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_18_norm_feed_forward1_weight_to_fp16, x = input_963_cast_fp16)[name = string("input_965_cast_fp16")];
            tensor<fp16, [4096, 1024]> module_layers_18_feed_forward1_linear1_weight_to_fp16 = const()[name = string("module_layers_18_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(895805952)))];
            tensor<fp16, [1, 188, 4096]> linear_165_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = module_layers_18_feed_forward1_linear1_weight_to_fp16, x = input_965_cast_fp16)[name = string("linear_165_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_969_cast_fp16 = silu(x = linear_165_cast_fp16)[name = string("input_969_cast_fp16")];
            tensor<fp16, [1024, 4096]> module_layers_18_feed_forward1_linear2_weight_to_fp16 = const()[name = string("module_layers_18_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(904194624)))];
            tensor<fp16, [1, 188, 1024]> linear_166_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_18_feed_forward1_linear2_weight_to_fp16, x = input_969_cast_fp16)[name = string("linear_166_cast_fp16")];
            fp16 var_3194_to_fp16 = const()[name = string("op_3194_to_fp16"), val = fp16(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_3195_cast_fp16 = mul(x = linear_166_cast_fp16, y = var_3194_to_fp16)[name = string("op_3195_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_975_cast_fp16 = add(x = input_963_cast_fp16, y = var_3195_cast_fp16)[name = string("input_975_cast_fp16")];
            tensor<int32, [1]> query_37_axes_0 = const()[name = string("query_37_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_18_norm_self_att_weight_to_fp16 = const()[name = string("module_layers_18_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(912583296)))];
            tensor<fp16, [1024]> module_layers_18_norm_self_att_bias_to_fp16 = const()[name = string("module_layers_18_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(912585408)))];
            tensor<fp16, [1, 188, 1024]> query_37_cast_fp16 = layer_norm(axes = query_37_axes_0, beta = module_layers_18_norm_self_att_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_18_norm_self_att_weight_to_fp16, x = input_975_cast_fp16)[name = string("query_37_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_18_self_attn_linear_q_weight_to_fp16 = const()[name = string("module_layers_18_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(912587520)))];
            tensor<fp16, [1, 188, 1024]> linear_167_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_18_self_attn_linear_q_weight_to_fp16, x = query_37_cast_fp16)[name = string("linear_167_cast_fp16")];
            tensor<int32, [4]> var_3211 = const()[name = string("op_3211"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_109_cast_fp16 = reshape(shape = var_3211, x = linear_167_cast_fp16)[name = string("q_109_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_18_self_attn_linear_k_weight_to_fp16 = const()[name = string("module_layers_18_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(914684736)))];
            tensor<fp16, [1, 188, 1024]> linear_168_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_18_self_attn_linear_k_weight_to_fp16, x = query_37_cast_fp16)[name = string("linear_168_cast_fp16")];
            tensor<int32, [4]> var_3215 = const()[name = string("op_3215"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_73_cast_fp16 = reshape(shape = var_3215, x = linear_168_cast_fp16)[name = string("k_73_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_18_self_attn_linear_v_weight_to_fp16 = const()[name = string("module_layers_18_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(916781952)))];
            tensor<fp16, [1, 188, 1024]> linear_169_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_18_self_attn_linear_v_weight_to_fp16, x = query_37_cast_fp16)[name = string("linear_169_cast_fp16")];
            tensor<int32, [4]> var_3219 = const()[name = string("op_3219"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_37_cast_fp16 = reshape(shape = var_3219, x = linear_169_cast_fp16)[name = string("v_37_cast_fp16")];
            tensor<int32, [4]> value_39_perm_0 = const()[name = string("value_39_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> module_layers_18_self_attn_pos_bias_u_to_fp16 = const()[name = string("module_layers_18_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(918879168)))];
            tensor<fp16, [1, 188, 8, 128]> var_3231_cast_fp16 = add(x = q_109_cast_fp16, y = module_layers_18_self_attn_pos_bias_u_to_fp16)[name = string("op_3231_cast_fp16")];
            tensor<fp16, [8, 128]> module_layers_18_self_attn_pos_bias_v_to_fp16 = const()[name = string("module_layers_18_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(918881280)))];
            tensor<fp16, [1, 188, 8, 128]> var_3233_cast_fp16 = add(x = q_109_cast_fp16, y = module_layers_18_self_attn_pos_bias_v_to_fp16)[name = string("op_3233_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_37_perm_0 = const()[name = string("q_with_bias_v_37_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            bool x_403_transpose_x_0 = const()[name = string("x_403_transpose_x_0"), val = bool(false)];
            bool x_403_transpose_y_0 = const()[name = string("x_403_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 128, 375]> var_3235_to_fp16 = const()[name = string("op_3235_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(918883392)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_37_cast_fp16 = transpose(perm = q_with_bias_v_37_perm_0, x = var_3233_cast_fp16)[name = string("transpose_161")];
            tensor<fp16, [1, 8, 188, 375]> x_403_cast_fp16 = matmul(transpose_x = x_403_transpose_x_0, transpose_y = x_403_transpose_y_0, x = q_with_bias_v_37_cast_fp16, y = var_3235_to_fp16)[name = string("x_403_cast_fp16")];
            tensor<int32, [8]> x_405_pad_0 = const()[name = string("x_405_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            string x_405_mode_0 = const()[name = string("x_405_mode_0"), val = string("constant")];
            fp16 const_194_to_fp16 = const()[name = string("const_194_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_405_cast_fp16 = pad(constant_val = const_194_to_fp16, mode = x_405_mode_0, pad = x_405_pad_0, x = x_403_cast_fp16)[name = string("x_405_cast_fp16")];
            tensor<int32, [4]> var_3243 = const()[name = string("op_3243"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_407_cast_fp16 = reshape(shape = var_3243, x = x_405_cast_fp16)[name = string("x_407_cast_fp16")];
            tensor<int32, [4]> var_3247_begin_0 = const()[name = string("op_3247_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_3247_end_0 = const()[name = string("op_3247_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_3247_end_mask_0 = const()[name = string("op_3247_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_3247_cast_fp16 = slice_by_index(begin = var_3247_begin_0, end = var_3247_end_0, end_mask = var_3247_end_mask_0, x = x_407_cast_fp16)[name = string("op_3247_cast_fp16")];
            tensor<int32, [4]> var_3248 = const()[name = string("op_3248"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_73_cast_fp16 = reshape(shape = var_3248, x = var_3247_cast_fp16)[name = string("matrix_bd_73_cast_fp16")];
            bool matrix_ac_37_transpose_x_0 = const()[name = string("matrix_ac_37_transpose_x_0"), val = bool(false)];
            bool matrix_ac_37_transpose_y_0 = const()[name = string("matrix_ac_37_transpose_y_0"), val = bool(false)];
            tensor<int32, [4]> transpose_108_perm_0 = const()[name = string("transpose_108_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_109_perm_0 = const()[name = string("transpose_109_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_109 = transpose(perm = transpose_109_perm_0, x = k_73_cast_fp16)[name = string("transpose_159")];
            tensor<fp16, [1, 8, 188, 128]> transpose_108 = transpose(perm = transpose_108_perm_0, x = var_3231_cast_fp16)[name = string("transpose_160")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_37_cast_fp16 = matmul(transpose_x = matrix_ac_37_transpose_x_0, transpose_y = matrix_ac_37_transpose_y_0, x = transpose_108, y = transpose_109)[name = string("matrix_ac_37_cast_fp16")];
            tensor<int32, [4]> matrix_bd_75_begin_0 = const()[name = string("matrix_bd_75_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_75_end_0 = const()[name = string("matrix_bd_75_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_75_end_mask_0 = const()[name = string("matrix_bd_75_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_75_cast_fp16 = slice_by_index(begin = matrix_bd_75_begin_0, end = matrix_bd_75_end_0, end_mask = matrix_bd_75_end_mask_0, x = matrix_bd_73_cast_fp16)[name = string("matrix_bd_75_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_3257_cast_fp16 = add(x = matrix_ac_37_cast_fp16, y = matrix_bd_75_cast_fp16)[name = string("op_3257_cast_fp16")];
            fp16 _inversed_scores_73_y_0_to_fp16 = const()[name = string("_inversed_scores_73_y_0_to_fp16"), val = fp16(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_73_cast_fp16 = mul(x = var_3257_cast_fp16, y = _inversed_scores_73_y_0_to_fp16)[name = string("_inversed_scores_73_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_75_cast_fp16 = select(a = var_10_to_fp16, b = _inversed_scores_73_cast_fp16, cond = mask_3)[name = string("scores_75_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_3263_cast_fp16 = softmax(axis = var_32, x = scores_75_cast_fp16)[name = string("op_3263_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_977_cast_fp16 = select(a = var_9_to_fp16, b = var_3263_cast_fp16, cond = mask_3)[name = string("input_977_cast_fp16")];
            bool x_409_transpose_x_0 = const()[name = string("x_409_transpose_x_0"), val = bool(false)];
            bool x_409_transpose_y_0 = const()[name = string("x_409_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 188, 128]> value_39_cast_fp16 = transpose(perm = value_39_perm_0, x = v_37_cast_fp16)[name = string("transpose_162")];
            tensor<fp16, [1, 8, 188, 128]> x_409_cast_fp16 = matmul(transpose_x = x_409_transpose_x_0, transpose_y = x_409_transpose_y_0, x = input_977_cast_fp16, y = value_39_cast_fp16)[name = string("x_409_cast_fp16")];
            tensor<int32, [4]> var_3267_perm_0 = const()[name = string("op_3267_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_3268 = const()[name = string("op_3268"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_3267_cast_fp16 = transpose(perm = var_3267_perm_0, x = x_409_cast_fp16)[name = string("transpose_158")];
            tensor<fp16, [1, 188, 1024]> input_979_cast_fp16 = reshape(shape = var_3268, x = var_3267_cast_fp16)[name = string("input_979_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_18_self_attn_linear_out_weight_to_fp16 = const()[name = string("module_layers_18_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(919651456)))];
            tensor<fp16, [1, 188, 1024]> linear_171_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_18_self_attn_linear_out_weight_to_fp16, x = input_979_cast_fp16)[name = string("linear_171_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_983_cast_fp16 = add(x = input_975_cast_fp16, y = linear_171_cast_fp16)[name = string("input_983_cast_fp16")];
            tensor<int32, [1]> x_413_axes_0 = const()[name = string("x_413_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_18_norm_conv_weight_to_fp16 = const()[name = string("module_layers_18_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(921748672)))];
            tensor<fp16, [1024]> module_layers_18_norm_conv_bias_to_fp16 = const()[name = string("module_layers_18_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(921750784)))];
            tensor<fp16, [1, 188, 1024]> x_413_cast_fp16 = layer_norm(axes = x_413_axes_0, beta = module_layers_18_norm_conv_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_18_norm_conv_weight_to_fp16, x = input_983_cast_fp16)[name = string("x_413_cast_fp16")];
            tensor<int32, [3]> input_985_perm_0 = const()[name = string("input_985_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            string input_987_pad_type_0 = const()[name = string("input_987_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_987_strides_0 = const()[name = string("input_987_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_987_pad_0 = const()[name = string("input_987_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_987_dilations_0 = const()[name = string("input_987_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_987_groups_0 = const()[name = string("input_987_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 1024, 1]> module_layers_18_conv_pointwise_conv1_weight_to_fp16 = const()[name = string("module_layers_18_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(921752896)))];
            tensor<fp16, [1, 1024, 188]> input_985_cast_fp16 = transpose(perm = input_985_perm_0, x = x_413_cast_fp16)[name = string("transpose_157")];
            tensor<fp16, [1, 2048, 188]> input_987_cast_fp16 = conv(dilations = input_987_dilations_0, groups = input_987_groups_0, pad = input_987_pad_0, pad_type = input_987_pad_type_0, strides = input_987_strides_0, weight = module_layers_18_conv_pointwise_conv1_weight_to_fp16, x = input_985_cast_fp16)[name = string("input_987_cast_fp16")];
            int32 x_415_split_num_splits_0 = const()[name = string("x_415_split_num_splits_0"), val = int32(2)];
            int32 x_415_split_axis_0 = const()[name = string("x_415_split_axis_0"), val = int32(1)];
            tensor<fp16, [1, 1024, 188]> x_415_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_415_split_cast_fp16_1 = split(axis = x_415_split_axis_0, num_splits = x_415_split_num_splits_0, x = input_987_cast_fp16)[name = string("x_415_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_415_split_1_sigmoid_cast_fp16 = sigmoid(x = x_415_split_cast_fp16_1)[name = string("x_415_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_415_cast_fp16 = mul(x = x_415_split_cast_fp16_0, y = x_415_split_1_sigmoid_cast_fp16)[name = string("x_415_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_989_cast_fp16 = select(a = var_9_to_fp16, b = x_415_cast_fp16, cond = var_356)[name = string("input_989_cast_fp16")];
            tensor<int32, [6]> input_991_pad_0 = const()[name = string("input_991_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            string input_991_mode_0 = const()[name = string("input_991_mode_0"), val = string("constant")];
            fp16 const_197_to_fp16 = const()[name = string("const_197_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_991_cast_fp16 = pad(constant_val = const_197_to_fp16, mode = input_991_mode_0, pad = input_991_pad_0, x = input_989_cast_fp16)[name = string("input_991_cast_fp16")];
            string input_993_pad_type_0 = const()[name = string("input_993_pad_type_0"), val = string("valid")];
            int32 input_993_groups_0 = const()[name = string("input_993_groups_0"), val = int32(1024)];
            tensor<int32, [1]> input_993_strides_0 = const()[name = string("input_993_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_993_pad_0 = const()[name = string("input_993_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_993_dilations_0 = const()[name = string("input_993_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_284_to_fp16 = const()[name = string("const_284_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(925947264)))];
            tensor<fp16, [1024]> const_285_to_fp16 = const()[name = string("const_285_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(925965760)))];
            tensor<fp16, [1, 1024, 188]> input_995_cast_fp16 = conv(bias = const_285_to_fp16, dilations = input_993_dilations_0, groups = input_993_groups_0, pad = input_993_pad_0, pad_type = input_993_pad_type_0, strides = input_993_strides_0, weight = const_284_to_fp16, x = input_991_cast_fp16)[name = string("input_995_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_997_cast_fp16 = silu(x = input_995_cast_fp16)[name = string("input_997_cast_fp16")];
            string x_417_pad_type_0 = const()[name = string("x_417_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> x_417_strides_0 = const()[name = string("x_417_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_417_pad_0 = const()[name = string("x_417_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_417_dilations_0 = const()[name = string("x_417_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 x_417_groups_0 = const()[name = string("x_417_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 1024, 1]> module_layers_18_conv_pointwise_conv2_weight_to_fp16 = const()[name = string("module_layers_18_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(925967872)))];
            tensor<fp16, [1, 1024, 188]> x_417_cast_fp16 = conv(dilations = x_417_dilations_0, groups = x_417_groups_0, pad = x_417_pad_0, pad_type = x_417_pad_type_0, strides = x_417_strides_0, weight = module_layers_18_conv_pointwise_conv2_weight_to_fp16, x = input_997_cast_fp16)[name = string("x_417_cast_fp16")];
            tensor<int32, [3]> input_999_perm_0 = const()[name = string("input_999_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_999_cast_fp16 = transpose(perm = input_999_perm_0, x = x_417_cast_fp16)[name = string("transpose_156")];
            tensor<fp16, [1, 188, 1024]> input_1001_cast_fp16 = add(x = input_983_cast_fp16, y = input_999_cast_fp16)[name = string("input_1001_cast_fp16")];
            tensor<int32, [1]> input_1003_axes_0 = const()[name = string("input_1003_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_18_norm_feed_forward2_weight_to_fp16 = const()[name = string("module_layers_18_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(928065088)))];
            tensor<fp16, [1024]> module_layers_18_norm_feed_forward2_bias_to_fp16 = const()[name = string("module_layers_18_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(928067200)))];
            tensor<fp16, [1, 188, 1024]> input_1003_cast_fp16 = layer_norm(axes = input_1003_axes_0, beta = module_layers_18_norm_feed_forward2_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_18_norm_feed_forward2_weight_to_fp16, x = input_1001_cast_fp16)[name = string("input_1003_cast_fp16")];
            tensor<fp16, [4096, 1024]> module_layers_18_feed_forward2_linear1_weight_to_fp16 = const()[name = string("module_layers_18_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(928069312)))];
            tensor<fp16, [1, 188, 4096]> linear_172_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = module_layers_18_feed_forward2_linear1_weight_to_fp16, x = input_1003_cast_fp16)[name = string("linear_172_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_1007_cast_fp16 = silu(x = linear_172_cast_fp16)[name = string("input_1007_cast_fp16")];
            tensor<fp16, [1024, 4096]> module_layers_18_feed_forward2_linear2_weight_to_fp16 = const()[name = string("module_layers_18_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(936457984)))];
            tensor<fp16, [1, 188, 1024]> linear_173_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_18_feed_forward2_linear2_weight_to_fp16, x = input_1007_cast_fp16)[name = string("linear_173_cast_fp16")];
            fp16 var_3328_to_fp16 = const()[name = string("op_3328_to_fp16"), val = fp16(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_3329_cast_fp16 = mul(x = linear_173_cast_fp16, y = var_3328_to_fp16)[name = string("op_3329_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1013_cast_fp16 = add(x = input_1001_cast_fp16, y = var_3329_cast_fp16)[name = string("input_1013_cast_fp16")];
            tensor<int32, [1]> input_1015_axes_0 = const()[name = string("input_1015_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_18_norm_out_weight_to_fp16 = const()[name = string("module_layers_18_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(944846656)))];
            tensor<fp16, [1024]> module_layers_18_norm_out_bias_to_fp16 = const()[name = string("module_layers_18_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(944848768)))];
            tensor<fp16, [1, 188, 1024]> input_1015_cast_fp16 = layer_norm(axes = input_1015_axes_0, beta = module_layers_18_norm_out_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_18_norm_out_weight_to_fp16, x = input_1013_cast_fp16)[name = string("input_1015_cast_fp16")];
            tensor<int32, [1]> input_1017_axes_0 = const()[name = string("input_1017_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_19_norm_feed_forward1_weight_to_fp16 = const()[name = string("module_layers_19_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(944850880)))];
            tensor<fp16, [1024]> module_layers_19_norm_feed_forward1_bias_to_fp16 = const()[name = string("module_layers_19_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(944852992)))];
            tensor<fp16, [1, 188, 1024]> input_1017_cast_fp16 = layer_norm(axes = input_1017_axes_0, beta = module_layers_19_norm_feed_forward1_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_19_norm_feed_forward1_weight_to_fp16, x = input_1015_cast_fp16)[name = string("input_1017_cast_fp16")];
            tensor<fp16, [4096, 1024]> module_layers_19_feed_forward1_linear1_weight_to_fp16 = const()[name = string("module_layers_19_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(944855104)))];
            tensor<fp16, [1, 188, 4096]> linear_174_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = module_layers_19_feed_forward1_linear1_weight_to_fp16, x = input_1017_cast_fp16)[name = string("linear_174_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_1021_cast_fp16 = silu(x = linear_174_cast_fp16)[name = string("input_1021_cast_fp16")];
            tensor<fp16, [1024, 4096]> module_layers_19_feed_forward1_linear2_weight_to_fp16 = const()[name = string("module_layers_19_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(953243776)))];
            tensor<fp16, [1, 188, 1024]> linear_175_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_19_feed_forward1_linear2_weight_to_fp16, x = input_1021_cast_fp16)[name = string("linear_175_cast_fp16")];
            fp16 var_3357_to_fp16 = const()[name = string("op_3357_to_fp16"), val = fp16(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_3358_cast_fp16 = mul(x = linear_175_cast_fp16, y = var_3357_to_fp16)[name = string("op_3358_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1027_cast_fp16 = add(x = input_1015_cast_fp16, y = var_3358_cast_fp16)[name = string("input_1027_cast_fp16")];
            tensor<int32, [1]> query_39_axes_0 = const()[name = string("query_39_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_19_norm_self_att_weight_to_fp16 = const()[name = string("module_layers_19_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(961632448)))];
            tensor<fp16, [1024]> module_layers_19_norm_self_att_bias_to_fp16 = const()[name = string("module_layers_19_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(961634560)))];
            tensor<fp16, [1, 188, 1024]> query_39_cast_fp16 = layer_norm(axes = query_39_axes_0, beta = module_layers_19_norm_self_att_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_19_norm_self_att_weight_to_fp16, x = input_1027_cast_fp16)[name = string("query_39_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_19_self_attn_linear_q_weight_to_fp16 = const()[name = string("module_layers_19_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(961636672)))];
            tensor<fp16, [1, 188, 1024]> linear_176_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_19_self_attn_linear_q_weight_to_fp16, x = query_39_cast_fp16)[name = string("linear_176_cast_fp16")];
            tensor<int32, [4]> var_3374 = const()[name = string("op_3374"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_115_cast_fp16 = reshape(shape = var_3374, x = linear_176_cast_fp16)[name = string("q_115_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_19_self_attn_linear_k_weight_to_fp16 = const()[name = string("module_layers_19_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(963733888)))];
            tensor<fp16, [1, 188, 1024]> linear_177_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_19_self_attn_linear_k_weight_to_fp16, x = query_39_cast_fp16)[name = string("linear_177_cast_fp16")];
            tensor<int32, [4]> var_3378 = const()[name = string("op_3378"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_77_cast_fp16 = reshape(shape = var_3378, x = linear_177_cast_fp16)[name = string("k_77_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_19_self_attn_linear_v_weight_to_fp16 = const()[name = string("module_layers_19_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(965831104)))];
            tensor<fp16, [1, 188, 1024]> linear_178_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_19_self_attn_linear_v_weight_to_fp16, x = query_39_cast_fp16)[name = string("linear_178_cast_fp16")];
            tensor<int32, [4]> var_3382 = const()[name = string("op_3382"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_39_cast_fp16 = reshape(shape = var_3382, x = linear_178_cast_fp16)[name = string("v_39_cast_fp16")];
            tensor<int32, [4]> value_41_perm_0 = const()[name = string("value_41_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> module_layers_19_self_attn_pos_bias_u_to_fp16 = const()[name = string("module_layers_19_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(967928320)))];
            tensor<fp16, [1, 188, 8, 128]> var_3394_cast_fp16 = add(x = q_115_cast_fp16, y = module_layers_19_self_attn_pos_bias_u_to_fp16)[name = string("op_3394_cast_fp16")];
            tensor<fp16, [8, 128]> module_layers_19_self_attn_pos_bias_v_to_fp16 = const()[name = string("module_layers_19_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(967930432)))];
            tensor<fp16, [1, 188, 8, 128]> var_3396_cast_fp16 = add(x = q_115_cast_fp16, y = module_layers_19_self_attn_pos_bias_v_to_fp16)[name = string("op_3396_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_39_perm_0 = const()[name = string("q_with_bias_v_39_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            bool x_425_transpose_x_0 = const()[name = string("x_425_transpose_x_0"), val = bool(false)];
            bool x_425_transpose_y_0 = const()[name = string("x_425_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 128, 375]> var_3398_to_fp16 = const()[name = string("op_3398_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(967932544)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_39_cast_fp16 = transpose(perm = q_with_bias_v_39_perm_0, x = var_3396_cast_fp16)[name = string("transpose_154")];
            tensor<fp16, [1, 8, 188, 375]> x_425_cast_fp16 = matmul(transpose_x = x_425_transpose_x_0, transpose_y = x_425_transpose_y_0, x = q_with_bias_v_39_cast_fp16, y = var_3398_to_fp16)[name = string("x_425_cast_fp16")];
            tensor<int32, [8]> x_427_pad_0 = const()[name = string("x_427_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            string x_427_mode_0 = const()[name = string("x_427_mode_0"), val = string("constant")];
            fp16 const_204_to_fp16 = const()[name = string("const_204_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_427_cast_fp16 = pad(constant_val = const_204_to_fp16, mode = x_427_mode_0, pad = x_427_pad_0, x = x_425_cast_fp16)[name = string("x_427_cast_fp16")];
            tensor<int32, [4]> var_3406 = const()[name = string("op_3406"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_429_cast_fp16 = reshape(shape = var_3406, x = x_427_cast_fp16)[name = string("x_429_cast_fp16")];
            tensor<int32, [4]> var_3410_begin_0 = const()[name = string("op_3410_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_3410_end_0 = const()[name = string("op_3410_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_3410_end_mask_0 = const()[name = string("op_3410_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_3410_cast_fp16 = slice_by_index(begin = var_3410_begin_0, end = var_3410_end_0, end_mask = var_3410_end_mask_0, x = x_429_cast_fp16)[name = string("op_3410_cast_fp16")];
            tensor<int32, [4]> var_3411 = const()[name = string("op_3411"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_77_cast_fp16 = reshape(shape = var_3411, x = var_3410_cast_fp16)[name = string("matrix_bd_77_cast_fp16")];
            bool matrix_ac_39_transpose_x_0 = const()[name = string("matrix_ac_39_transpose_x_0"), val = bool(false)];
            bool matrix_ac_39_transpose_y_0 = const()[name = string("matrix_ac_39_transpose_y_0"), val = bool(false)];
            tensor<int32, [4]> transpose_110_perm_0 = const()[name = string("transpose_110_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_111_perm_0 = const()[name = string("transpose_111_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_111 = transpose(perm = transpose_111_perm_0, x = k_77_cast_fp16)[name = string("transpose_152")];
            tensor<fp16, [1, 8, 188, 128]> transpose_110 = transpose(perm = transpose_110_perm_0, x = var_3394_cast_fp16)[name = string("transpose_153")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_39_cast_fp16 = matmul(transpose_x = matrix_ac_39_transpose_x_0, transpose_y = matrix_ac_39_transpose_y_0, x = transpose_110, y = transpose_111)[name = string("matrix_ac_39_cast_fp16")];
            tensor<int32, [4]> matrix_bd_79_begin_0 = const()[name = string("matrix_bd_79_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_79_end_0 = const()[name = string("matrix_bd_79_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_79_end_mask_0 = const()[name = string("matrix_bd_79_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_79_cast_fp16 = slice_by_index(begin = matrix_bd_79_begin_0, end = matrix_bd_79_end_0, end_mask = matrix_bd_79_end_mask_0, x = matrix_bd_77_cast_fp16)[name = string("matrix_bd_79_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_3420_cast_fp16 = add(x = matrix_ac_39_cast_fp16, y = matrix_bd_79_cast_fp16)[name = string("op_3420_cast_fp16")];
            fp16 _inversed_scores_77_y_0_to_fp16 = const()[name = string("_inversed_scores_77_y_0_to_fp16"), val = fp16(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_77_cast_fp16 = mul(x = var_3420_cast_fp16, y = _inversed_scores_77_y_0_to_fp16)[name = string("_inversed_scores_77_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_79_cast_fp16 = select(a = var_10_to_fp16, b = _inversed_scores_77_cast_fp16, cond = mask_3)[name = string("scores_79_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_3426_cast_fp16 = softmax(axis = var_32, x = scores_79_cast_fp16)[name = string("op_3426_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_1029_cast_fp16 = select(a = var_9_to_fp16, b = var_3426_cast_fp16, cond = mask_3)[name = string("input_1029_cast_fp16")];
            bool x_431_transpose_x_0 = const()[name = string("x_431_transpose_x_0"), val = bool(false)];
            bool x_431_transpose_y_0 = const()[name = string("x_431_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 188, 128]> value_41_cast_fp16 = transpose(perm = value_41_perm_0, x = v_39_cast_fp16)[name = string("transpose_155")];
            tensor<fp16, [1, 8, 188, 128]> x_431_cast_fp16 = matmul(transpose_x = x_431_transpose_x_0, transpose_y = x_431_transpose_y_0, x = input_1029_cast_fp16, y = value_41_cast_fp16)[name = string("x_431_cast_fp16")];
            tensor<int32, [4]> var_3430_perm_0 = const()[name = string("op_3430_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_3431 = const()[name = string("op_3431"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_3430_cast_fp16 = transpose(perm = var_3430_perm_0, x = x_431_cast_fp16)[name = string("transpose_151")];
            tensor<fp16, [1, 188, 1024]> input_1031_cast_fp16 = reshape(shape = var_3431, x = var_3430_cast_fp16)[name = string("input_1031_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_19_self_attn_linear_out_weight_to_fp16 = const()[name = string("module_layers_19_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(968700608)))];
            tensor<fp16, [1, 188, 1024]> linear_180_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_19_self_attn_linear_out_weight_to_fp16, x = input_1031_cast_fp16)[name = string("linear_180_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1035_cast_fp16 = add(x = input_1027_cast_fp16, y = linear_180_cast_fp16)[name = string("input_1035_cast_fp16")];
            tensor<int32, [1]> x_435_axes_0 = const()[name = string("x_435_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_19_norm_conv_weight_to_fp16 = const()[name = string("module_layers_19_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(970797824)))];
            tensor<fp16, [1024]> module_layers_19_norm_conv_bias_to_fp16 = const()[name = string("module_layers_19_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(970799936)))];
            tensor<fp16, [1, 188, 1024]> x_435_cast_fp16 = layer_norm(axes = x_435_axes_0, beta = module_layers_19_norm_conv_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_19_norm_conv_weight_to_fp16, x = input_1035_cast_fp16)[name = string("x_435_cast_fp16")];
            tensor<int32, [3]> input_1037_perm_0 = const()[name = string("input_1037_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            string input_1039_pad_type_0 = const()[name = string("input_1039_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_1039_strides_0 = const()[name = string("input_1039_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1039_pad_0 = const()[name = string("input_1039_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1039_dilations_0 = const()[name = string("input_1039_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_1039_groups_0 = const()[name = string("input_1039_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 1024, 1]> module_layers_19_conv_pointwise_conv1_weight_to_fp16 = const()[name = string("module_layers_19_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(970802048)))];
            tensor<fp16, [1, 1024, 188]> input_1037_cast_fp16 = transpose(perm = input_1037_perm_0, x = x_435_cast_fp16)[name = string("transpose_150")];
            tensor<fp16, [1, 2048, 188]> input_1039_cast_fp16 = conv(dilations = input_1039_dilations_0, groups = input_1039_groups_0, pad = input_1039_pad_0, pad_type = input_1039_pad_type_0, strides = input_1039_strides_0, weight = module_layers_19_conv_pointwise_conv1_weight_to_fp16, x = input_1037_cast_fp16)[name = string("input_1039_cast_fp16")];
            int32 x_437_split_num_splits_0 = const()[name = string("x_437_split_num_splits_0"), val = int32(2)];
            int32 x_437_split_axis_0 = const()[name = string("x_437_split_axis_0"), val = int32(1)];
            tensor<fp16, [1, 1024, 188]> x_437_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_437_split_cast_fp16_1 = split(axis = x_437_split_axis_0, num_splits = x_437_split_num_splits_0, x = input_1039_cast_fp16)[name = string("x_437_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_437_split_1_sigmoid_cast_fp16 = sigmoid(x = x_437_split_cast_fp16_1)[name = string("x_437_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_437_cast_fp16 = mul(x = x_437_split_cast_fp16_0, y = x_437_split_1_sigmoid_cast_fp16)[name = string("x_437_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_1041_cast_fp16 = select(a = var_9_to_fp16, b = x_437_cast_fp16, cond = var_356)[name = string("input_1041_cast_fp16")];
            tensor<int32, [6]> input_1043_pad_0 = const()[name = string("input_1043_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            string input_1043_mode_0 = const()[name = string("input_1043_mode_0"), val = string("constant")];
            fp16 const_207_to_fp16 = const()[name = string("const_207_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_1043_cast_fp16 = pad(constant_val = const_207_to_fp16, mode = input_1043_mode_0, pad = input_1043_pad_0, x = input_1041_cast_fp16)[name = string("input_1043_cast_fp16")];
            string input_1045_pad_type_0 = const()[name = string("input_1045_pad_type_0"), val = string("valid")];
            int32 input_1045_groups_0 = const()[name = string("input_1045_groups_0"), val = int32(1024)];
            tensor<int32, [1]> input_1045_strides_0 = const()[name = string("input_1045_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1045_pad_0 = const()[name = string("input_1045_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1045_dilations_0 = const()[name = string("input_1045_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_286_to_fp16 = const()[name = string("const_286_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(974996416)))];
            tensor<fp16, [1024]> const_287_to_fp16 = const()[name = string("const_287_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(975014912)))];
            tensor<fp16, [1, 1024, 188]> input_1047_cast_fp16 = conv(bias = const_287_to_fp16, dilations = input_1045_dilations_0, groups = input_1045_groups_0, pad = input_1045_pad_0, pad_type = input_1045_pad_type_0, strides = input_1045_strides_0, weight = const_286_to_fp16, x = input_1043_cast_fp16)[name = string("input_1047_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_1049_cast_fp16 = silu(x = input_1047_cast_fp16)[name = string("input_1049_cast_fp16")];
            string x_439_pad_type_0 = const()[name = string("x_439_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> x_439_strides_0 = const()[name = string("x_439_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_439_pad_0 = const()[name = string("x_439_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_439_dilations_0 = const()[name = string("x_439_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 x_439_groups_0 = const()[name = string("x_439_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 1024, 1]> module_layers_19_conv_pointwise_conv2_weight_to_fp16 = const()[name = string("module_layers_19_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(975017024)))];
            tensor<fp16, [1, 1024, 188]> x_439_cast_fp16 = conv(dilations = x_439_dilations_0, groups = x_439_groups_0, pad = x_439_pad_0, pad_type = x_439_pad_type_0, strides = x_439_strides_0, weight = module_layers_19_conv_pointwise_conv2_weight_to_fp16, x = input_1049_cast_fp16)[name = string("x_439_cast_fp16")];
            tensor<int32, [3]> input_1051_perm_0 = const()[name = string("input_1051_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_1051_cast_fp16 = transpose(perm = input_1051_perm_0, x = x_439_cast_fp16)[name = string("transpose_149")];
            tensor<fp16, [1, 188, 1024]> input_1053_cast_fp16 = add(x = input_1035_cast_fp16, y = input_1051_cast_fp16)[name = string("input_1053_cast_fp16")];
            tensor<int32, [1]> input_1055_axes_0 = const()[name = string("input_1055_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_19_norm_feed_forward2_weight_to_fp16 = const()[name = string("module_layers_19_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(977114240)))];
            tensor<fp16, [1024]> module_layers_19_norm_feed_forward2_bias_to_fp16 = const()[name = string("module_layers_19_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(977116352)))];
            tensor<fp16, [1, 188, 1024]> input_1055_cast_fp16 = layer_norm(axes = input_1055_axes_0, beta = module_layers_19_norm_feed_forward2_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_19_norm_feed_forward2_weight_to_fp16, x = input_1053_cast_fp16)[name = string("input_1055_cast_fp16")];
            tensor<fp16, [4096, 1024]> module_layers_19_feed_forward2_linear1_weight_to_fp16 = const()[name = string("module_layers_19_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(977118464)))];
            tensor<fp16, [1, 188, 4096]> linear_181_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = module_layers_19_feed_forward2_linear1_weight_to_fp16, x = input_1055_cast_fp16)[name = string("linear_181_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_1059_cast_fp16 = silu(x = linear_181_cast_fp16)[name = string("input_1059_cast_fp16")];
            tensor<fp16, [1024, 4096]> module_layers_19_feed_forward2_linear2_weight_to_fp16 = const()[name = string("module_layers_19_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(985507136)))];
            tensor<fp16, [1, 188, 1024]> linear_182_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_19_feed_forward2_linear2_weight_to_fp16, x = input_1059_cast_fp16)[name = string("linear_182_cast_fp16")];
            fp16 var_3491_to_fp16 = const()[name = string("op_3491_to_fp16"), val = fp16(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_3492_cast_fp16 = mul(x = linear_182_cast_fp16, y = var_3491_to_fp16)[name = string("op_3492_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1065_cast_fp16 = add(x = input_1053_cast_fp16, y = var_3492_cast_fp16)[name = string("input_1065_cast_fp16")];
            tensor<int32, [1]> input_1067_axes_0 = const()[name = string("input_1067_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_19_norm_out_weight_to_fp16 = const()[name = string("module_layers_19_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(993895808)))];
            tensor<fp16, [1024]> module_layers_19_norm_out_bias_to_fp16 = const()[name = string("module_layers_19_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(993897920)))];
            tensor<fp16, [1, 188, 1024]> input_1067_cast_fp16 = layer_norm(axes = input_1067_axes_0, beta = module_layers_19_norm_out_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_19_norm_out_weight_to_fp16, x = input_1065_cast_fp16)[name = string("input_1067_cast_fp16")];
            tensor<int32, [1]> input_1069_axes_0 = const()[name = string("input_1069_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_20_norm_feed_forward1_weight_to_fp16 = const()[name = string("module_layers_20_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(993900032)))];
            tensor<fp16, [1024]> module_layers_20_norm_feed_forward1_bias_to_fp16 = const()[name = string("module_layers_20_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(993902144)))];
            tensor<fp16, [1, 188, 1024]> input_1069_cast_fp16 = layer_norm(axes = input_1069_axes_0, beta = module_layers_20_norm_feed_forward1_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_20_norm_feed_forward1_weight_to_fp16, x = input_1067_cast_fp16)[name = string("input_1069_cast_fp16")];
            tensor<fp16, [4096, 1024]> module_layers_20_feed_forward1_linear1_weight_to_fp16 = const()[name = string("module_layers_20_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(993904256)))];
            tensor<fp16, [1, 188, 4096]> linear_183_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = module_layers_20_feed_forward1_linear1_weight_to_fp16, x = input_1069_cast_fp16)[name = string("linear_183_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_1073_cast_fp16 = silu(x = linear_183_cast_fp16)[name = string("input_1073_cast_fp16")];
            tensor<fp16, [1024, 4096]> module_layers_20_feed_forward1_linear2_weight_to_fp16 = const()[name = string("module_layers_20_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1002292928)))];
            tensor<fp16, [1, 188, 1024]> linear_184_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_20_feed_forward1_linear2_weight_to_fp16, x = input_1073_cast_fp16)[name = string("linear_184_cast_fp16")];
            fp16 var_3520_to_fp16 = const()[name = string("op_3520_to_fp16"), val = fp16(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_3521_cast_fp16 = mul(x = linear_184_cast_fp16, y = var_3520_to_fp16)[name = string("op_3521_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1079_cast_fp16 = add(x = input_1067_cast_fp16, y = var_3521_cast_fp16)[name = string("input_1079_cast_fp16")];
            tensor<int32, [1]> query_41_axes_0 = const()[name = string("query_41_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_20_norm_self_att_weight_to_fp16 = const()[name = string("module_layers_20_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1010681600)))];
            tensor<fp16, [1024]> module_layers_20_norm_self_att_bias_to_fp16 = const()[name = string("module_layers_20_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1010683712)))];
            tensor<fp16, [1, 188, 1024]> query_41_cast_fp16 = layer_norm(axes = query_41_axes_0, beta = module_layers_20_norm_self_att_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_20_norm_self_att_weight_to_fp16, x = input_1079_cast_fp16)[name = string("query_41_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_20_self_attn_linear_q_weight_to_fp16 = const()[name = string("module_layers_20_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1010685824)))];
            tensor<fp16, [1, 188, 1024]> linear_185_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_20_self_attn_linear_q_weight_to_fp16, x = query_41_cast_fp16)[name = string("linear_185_cast_fp16")];
            tensor<int32, [4]> var_3537 = const()[name = string("op_3537"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_121_cast_fp16 = reshape(shape = var_3537, x = linear_185_cast_fp16)[name = string("q_121_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_20_self_attn_linear_k_weight_to_fp16 = const()[name = string("module_layers_20_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1012783040)))];
            tensor<fp16, [1, 188, 1024]> linear_186_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_20_self_attn_linear_k_weight_to_fp16, x = query_41_cast_fp16)[name = string("linear_186_cast_fp16")];
            tensor<int32, [4]> var_3541 = const()[name = string("op_3541"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_81_cast_fp16 = reshape(shape = var_3541, x = linear_186_cast_fp16)[name = string("k_81_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_20_self_attn_linear_v_weight_to_fp16 = const()[name = string("module_layers_20_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1014880256)))];
            tensor<fp16, [1, 188, 1024]> linear_187_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_20_self_attn_linear_v_weight_to_fp16, x = query_41_cast_fp16)[name = string("linear_187_cast_fp16")];
            tensor<int32, [4]> var_3545 = const()[name = string("op_3545"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_41_cast_fp16 = reshape(shape = var_3545, x = linear_187_cast_fp16)[name = string("v_41_cast_fp16")];
            tensor<int32, [4]> value_43_perm_0 = const()[name = string("value_43_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> module_layers_20_self_attn_pos_bias_u_to_fp16 = const()[name = string("module_layers_20_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1016977472)))];
            tensor<fp16, [1, 188, 8, 128]> var_3557_cast_fp16 = add(x = q_121_cast_fp16, y = module_layers_20_self_attn_pos_bias_u_to_fp16)[name = string("op_3557_cast_fp16")];
            tensor<fp16, [8, 128]> module_layers_20_self_attn_pos_bias_v_to_fp16 = const()[name = string("module_layers_20_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1016979584)))];
            tensor<fp16, [1, 188, 8, 128]> var_3559_cast_fp16 = add(x = q_121_cast_fp16, y = module_layers_20_self_attn_pos_bias_v_to_fp16)[name = string("op_3559_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_41_perm_0 = const()[name = string("q_with_bias_v_41_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            bool x_447_transpose_x_0 = const()[name = string("x_447_transpose_x_0"), val = bool(false)];
            bool x_447_transpose_y_0 = const()[name = string("x_447_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 128, 375]> var_3561_to_fp16 = const()[name = string("op_3561_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1016981696)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_41_cast_fp16 = transpose(perm = q_with_bias_v_41_perm_0, x = var_3559_cast_fp16)[name = string("transpose_147")];
            tensor<fp16, [1, 8, 188, 375]> x_447_cast_fp16 = matmul(transpose_x = x_447_transpose_x_0, transpose_y = x_447_transpose_y_0, x = q_with_bias_v_41_cast_fp16, y = var_3561_to_fp16)[name = string("x_447_cast_fp16")];
            tensor<int32, [8]> x_449_pad_0 = const()[name = string("x_449_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            string x_449_mode_0 = const()[name = string("x_449_mode_0"), val = string("constant")];
            fp16 const_214_to_fp16 = const()[name = string("const_214_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_449_cast_fp16 = pad(constant_val = const_214_to_fp16, mode = x_449_mode_0, pad = x_449_pad_0, x = x_447_cast_fp16)[name = string("x_449_cast_fp16")];
            tensor<int32, [4]> var_3569 = const()[name = string("op_3569"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_451_cast_fp16 = reshape(shape = var_3569, x = x_449_cast_fp16)[name = string("x_451_cast_fp16")];
            tensor<int32, [4]> var_3573_begin_0 = const()[name = string("op_3573_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_3573_end_0 = const()[name = string("op_3573_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_3573_end_mask_0 = const()[name = string("op_3573_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_3573_cast_fp16 = slice_by_index(begin = var_3573_begin_0, end = var_3573_end_0, end_mask = var_3573_end_mask_0, x = x_451_cast_fp16)[name = string("op_3573_cast_fp16")];
            tensor<int32, [4]> var_3574 = const()[name = string("op_3574"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_81_cast_fp16 = reshape(shape = var_3574, x = var_3573_cast_fp16)[name = string("matrix_bd_81_cast_fp16")];
            bool matrix_ac_41_transpose_x_0 = const()[name = string("matrix_ac_41_transpose_x_0"), val = bool(false)];
            bool matrix_ac_41_transpose_y_0 = const()[name = string("matrix_ac_41_transpose_y_0"), val = bool(false)];
            tensor<int32, [4]> transpose_112_perm_0 = const()[name = string("transpose_112_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_113_perm_0 = const()[name = string("transpose_113_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_113 = transpose(perm = transpose_113_perm_0, x = k_81_cast_fp16)[name = string("transpose_145")];
            tensor<fp16, [1, 8, 188, 128]> transpose_112 = transpose(perm = transpose_112_perm_0, x = var_3557_cast_fp16)[name = string("transpose_146")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_41_cast_fp16 = matmul(transpose_x = matrix_ac_41_transpose_x_0, transpose_y = matrix_ac_41_transpose_y_0, x = transpose_112, y = transpose_113)[name = string("matrix_ac_41_cast_fp16")];
            tensor<int32, [4]> matrix_bd_83_begin_0 = const()[name = string("matrix_bd_83_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_83_end_0 = const()[name = string("matrix_bd_83_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_83_end_mask_0 = const()[name = string("matrix_bd_83_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_83_cast_fp16 = slice_by_index(begin = matrix_bd_83_begin_0, end = matrix_bd_83_end_0, end_mask = matrix_bd_83_end_mask_0, x = matrix_bd_81_cast_fp16)[name = string("matrix_bd_83_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_3583_cast_fp16 = add(x = matrix_ac_41_cast_fp16, y = matrix_bd_83_cast_fp16)[name = string("op_3583_cast_fp16")];
            fp16 _inversed_scores_81_y_0_to_fp16 = const()[name = string("_inversed_scores_81_y_0_to_fp16"), val = fp16(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_81_cast_fp16 = mul(x = var_3583_cast_fp16, y = _inversed_scores_81_y_0_to_fp16)[name = string("_inversed_scores_81_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_83_cast_fp16 = select(a = var_10_to_fp16, b = _inversed_scores_81_cast_fp16, cond = mask_3)[name = string("scores_83_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_3589_cast_fp16 = softmax(axis = var_32, x = scores_83_cast_fp16)[name = string("op_3589_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_1081_cast_fp16 = select(a = var_9_to_fp16, b = var_3589_cast_fp16, cond = mask_3)[name = string("input_1081_cast_fp16")];
            bool x_453_transpose_x_0 = const()[name = string("x_453_transpose_x_0"), val = bool(false)];
            bool x_453_transpose_y_0 = const()[name = string("x_453_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 188, 128]> value_43_cast_fp16 = transpose(perm = value_43_perm_0, x = v_41_cast_fp16)[name = string("transpose_148")];
            tensor<fp16, [1, 8, 188, 128]> x_453_cast_fp16 = matmul(transpose_x = x_453_transpose_x_0, transpose_y = x_453_transpose_y_0, x = input_1081_cast_fp16, y = value_43_cast_fp16)[name = string("x_453_cast_fp16")];
            tensor<int32, [4]> var_3593_perm_0 = const()[name = string("op_3593_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_3594 = const()[name = string("op_3594"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_3593_cast_fp16 = transpose(perm = var_3593_perm_0, x = x_453_cast_fp16)[name = string("transpose_144")];
            tensor<fp16, [1, 188, 1024]> input_1083_cast_fp16 = reshape(shape = var_3594, x = var_3593_cast_fp16)[name = string("input_1083_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_20_self_attn_linear_out_weight_to_fp16 = const()[name = string("module_layers_20_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1017749760)))];
            tensor<fp16, [1, 188, 1024]> linear_189_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_20_self_attn_linear_out_weight_to_fp16, x = input_1083_cast_fp16)[name = string("linear_189_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1087_cast_fp16 = add(x = input_1079_cast_fp16, y = linear_189_cast_fp16)[name = string("input_1087_cast_fp16")];
            tensor<int32, [1]> x_457_axes_0 = const()[name = string("x_457_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_20_norm_conv_weight_to_fp16 = const()[name = string("module_layers_20_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1019846976)))];
            tensor<fp16, [1024]> module_layers_20_norm_conv_bias_to_fp16 = const()[name = string("module_layers_20_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1019849088)))];
            tensor<fp16, [1, 188, 1024]> x_457_cast_fp16 = layer_norm(axes = x_457_axes_0, beta = module_layers_20_norm_conv_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_20_norm_conv_weight_to_fp16, x = input_1087_cast_fp16)[name = string("x_457_cast_fp16")];
            tensor<int32, [3]> input_1089_perm_0 = const()[name = string("input_1089_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            string input_1091_pad_type_0 = const()[name = string("input_1091_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_1091_strides_0 = const()[name = string("input_1091_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1091_pad_0 = const()[name = string("input_1091_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1091_dilations_0 = const()[name = string("input_1091_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_1091_groups_0 = const()[name = string("input_1091_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 1024, 1]> module_layers_20_conv_pointwise_conv1_weight_to_fp16 = const()[name = string("module_layers_20_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1019851200)))];
            tensor<fp16, [1, 1024, 188]> input_1089_cast_fp16 = transpose(perm = input_1089_perm_0, x = x_457_cast_fp16)[name = string("transpose_143")];
            tensor<fp16, [1, 2048, 188]> input_1091_cast_fp16 = conv(dilations = input_1091_dilations_0, groups = input_1091_groups_0, pad = input_1091_pad_0, pad_type = input_1091_pad_type_0, strides = input_1091_strides_0, weight = module_layers_20_conv_pointwise_conv1_weight_to_fp16, x = input_1089_cast_fp16)[name = string("input_1091_cast_fp16")];
            int32 x_459_split_num_splits_0 = const()[name = string("x_459_split_num_splits_0"), val = int32(2)];
            int32 x_459_split_axis_0 = const()[name = string("x_459_split_axis_0"), val = int32(1)];
            tensor<fp16, [1, 1024, 188]> x_459_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_459_split_cast_fp16_1 = split(axis = x_459_split_axis_0, num_splits = x_459_split_num_splits_0, x = input_1091_cast_fp16)[name = string("x_459_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_459_split_1_sigmoid_cast_fp16 = sigmoid(x = x_459_split_cast_fp16_1)[name = string("x_459_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_459_cast_fp16 = mul(x = x_459_split_cast_fp16_0, y = x_459_split_1_sigmoid_cast_fp16)[name = string("x_459_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_1093_cast_fp16 = select(a = var_9_to_fp16, b = x_459_cast_fp16, cond = var_356)[name = string("input_1093_cast_fp16")];
            tensor<int32, [6]> input_1095_pad_0 = const()[name = string("input_1095_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            string input_1095_mode_0 = const()[name = string("input_1095_mode_0"), val = string("constant")];
            fp16 const_217_to_fp16 = const()[name = string("const_217_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_1095_cast_fp16 = pad(constant_val = const_217_to_fp16, mode = input_1095_mode_0, pad = input_1095_pad_0, x = input_1093_cast_fp16)[name = string("input_1095_cast_fp16")];
            string input_1097_pad_type_0 = const()[name = string("input_1097_pad_type_0"), val = string("valid")];
            int32 input_1097_groups_0 = const()[name = string("input_1097_groups_0"), val = int32(1024)];
            tensor<int32, [1]> input_1097_strides_0 = const()[name = string("input_1097_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1097_pad_0 = const()[name = string("input_1097_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1097_dilations_0 = const()[name = string("input_1097_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_288_to_fp16 = const()[name = string("const_288_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1024045568)))];
            tensor<fp16, [1024]> const_289_to_fp16 = const()[name = string("const_289_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1024064064)))];
            tensor<fp16, [1, 1024, 188]> input_1099_cast_fp16 = conv(bias = const_289_to_fp16, dilations = input_1097_dilations_0, groups = input_1097_groups_0, pad = input_1097_pad_0, pad_type = input_1097_pad_type_0, strides = input_1097_strides_0, weight = const_288_to_fp16, x = input_1095_cast_fp16)[name = string("input_1099_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_1101_cast_fp16 = silu(x = input_1099_cast_fp16)[name = string("input_1101_cast_fp16")];
            string x_461_pad_type_0 = const()[name = string("x_461_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> x_461_strides_0 = const()[name = string("x_461_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_461_pad_0 = const()[name = string("x_461_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_461_dilations_0 = const()[name = string("x_461_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 x_461_groups_0 = const()[name = string("x_461_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 1024, 1]> module_layers_20_conv_pointwise_conv2_weight_to_fp16 = const()[name = string("module_layers_20_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1024066176)))];
            tensor<fp16, [1, 1024, 188]> x_461_cast_fp16 = conv(dilations = x_461_dilations_0, groups = x_461_groups_0, pad = x_461_pad_0, pad_type = x_461_pad_type_0, strides = x_461_strides_0, weight = module_layers_20_conv_pointwise_conv2_weight_to_fp16, x = input_1101_cast_fp16)[name = string("x_461_cast_fp16")];
            tensor<int32, [3]> input_1103_perm_0 = const()[name = string("input_1103_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_1103_cast_fp16 = transpose(perm = input_1103_perm_0, x = x_461_cast_fp16)[name = string("transpose_142")];
            tensor<fp16, [1, 188, 1024]> input_1105_cast_fp16 = add(x = input_1087_cast_fp16, y = input_1103_cast_fp16)[name = string("input_1105_cast_fp16")];
            tensor<int32, [1]> input_1107_axes_0 = const()[name = string("input_1107_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_20_norm_feed_forward2_weight_to_fp16 = const()[name = string("module_layers_20_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1026163392)))];
            tensor<fp16, [1024]> module_layers_20_norm_feed_forward2_bias_to_fp16 = const()[name = string("module_layers_20_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1026165504)))];
            tensor<fp16, [1, 188, 1024]> input_1107_cast_fp16 = layer_norm(axes = input_1107_axes_0, beta = module_layers_20_norm_feed_forward2_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_20_norm_feed_forward2_weight_to_fp16, x = input_1105_cast_fp16)[name = string("input_1107_cast_fp16")];
            tensor<fp16, [4096, 1024]> module_layers_20_feed_forward2_linear1_weight_to_fp16 = const()[name = string("module_layers_20_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1026167616)))];
            tensor<fp16, [1, 188, 4096]> linear_190_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = module_layers_20_feed_forward2_linear1_weight_to_fp16, x = input_1107_cast_fp16)[name = string("linear_190_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_1111_cast_fp16 = silu(x = linear_190_cast_fp16)[name = string("input_1111_cast_fp16")];
            tensor<fp16, [1024, 4096]> module_layers_20_feed_forward2_linear2_weight_to_fp16 = const()[name = string("module_layers_20_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1034556288)))];
            tensor<fp16, [1, 188, 1024]> linear_191_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_20_feed_forward2_linear2_weight_to_fp16, x = input_1111_cast_fp16)[name = string("linear_191_cast_fp16")];
            fp16 var_3654_to_fp16 = const()[name = string("op_3654_to_fp16"), val = fp16(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_3655_cast_fp16 = mul(x = linear_191_cast_fp16, y = var_3654_to_fp16)[name = string("op_3655_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1117_cast_fp16 = add(x = input_1105_cast_fp16, y = var_3655_cast_fp16)[name = string("input_1117_cast_fp16")];
            tensor<int32, [1]> input_1119_axes_0 = const()[name = string("input_1119_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_20_norm_out_weight_to_fp16 = const()[name = string("module_layers_20_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1042944960)))];
            tensor<fp16, [1024]> module_layers_20_norm_out_bias_to_fp16 = const()[name = string("module_layers_20_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1042947072)))];
            tensor<fp16, [1, 188, 1024]> input_1119_cast_fp16 = layer_norm(axes = input_1119_axes_0, beta = module_layers_20_norm_out_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_20_norm_out_weight_to_fp16, x = input_1117_cast_fp16)[name = string("input_1119_cast_fp16")];
            tensor<int32, [1]> input_1121_axes_0 = const()[name = string("input_1121_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_21_norm_feed_forward1_weight_to_fp16 = const()[name = string("module_layers_21_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1042949184)))];
            tensor<fp16, [1024]> module_layers_21_norm_feed_forward1_bias_to_fp16 = const()[name = string("module_layers_21_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1042951296)))];
            tensor<fp16, [1, 188, 1024]> input_1121_cast_fp16 = layer_norm(axes = input_1121_axes_0, beta = module_layers_21_norm_feed_forward1_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_21_norm_feed_forward1_weight_to_fp16, x = input_1119_cast_fp16)[name = string("input_1121_cast_fp16")];
            tensor<fp16, [4096, 1024]> module_layers_21_feed_forward1_linear1_weight_to_fp16 = const()[name = string("module_layers_21_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1042953408)))];
            tensor<fp16, [1, 188, 4096]> linear_192_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = module_layers_21_feed_forward1_linear1_weight_to_fp16, x = input_1121_cast_fp16)[name = string("linear_192_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_1125_cast_fp16 = silu(x = linear_192_cast_fp16)[name = string("input_1125_cast_fp16")];
            tensor<fp16, [1024, 4096]> module_layers_21_feed_forward1_linear2_weight_to_fp16 = const()[name = string("module_layers_21_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1051342080)))];
            tensor<fp16, [1, 188, 1024]> linear_193_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_21_feed_forward1_linear2_weight_to_fp16, x = input_1125_cast_fp16)[name = string("linear_193_cast_fp16")];
            fp16 var_3683_to_fp16 = const()[name = string("op_3683_to_fp16"), val = fp16(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_3684_cast_fp16 = mul(x = linear_193_cast_fp16, y = var_3683_to_fp16)[name = string("op_3684_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1131_cast_fp16 = add(x = input_1119_cast_fp16, y = var_3684_cast_fp16)[name = string("input_1131_cast_fp16")];
            tensor<int32, [1]> query_43_axes_0 = const()[name = string("query_43_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_21_norm_self_att_weight_to_fp16 = const()[name = string("module_layers_21_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1059730752)))];
            tensor<fp16, [1024]> module_layers_21_norm_self_att_bias_to_fp16 = const()[name = string("module_layers_21_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1059732864)))];
            tensor<fp16, [1, 188, 1024]> query_43_cast_fp16 = layer_norm(axes = query_43_axes_0, beta = module_layers_21_norm_self_att_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_21_norm_self_att_weight_to_fp16, x = input_1131_cast_fp16)[name = string("query_43_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_21_self_attn_linear_q_weight_to_fp16 = const()[name = string("module_layers_21_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1059734976)))];
            tensor<fp16, [1, 188, 1024]> linear_194_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_21_self_attn_linear_q_weight_to_fp16, x = query_43_cast_fp16)[name = string("linear_194_cast_fp16")];
            tensor<int32, [4]> var_3700 = const()[name = string("op_3700"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_127_cast_fp16 = reshape(shape = var_3700, x = linear_194_cast_fp16)[name = string("q_127_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_21_self_attn_linear_k_weight_to_fp16 = const()[name = string("module_layers_21_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1061832192)))];
            tensor<fp16, [1, 188, 1024]> linear_195_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_21_self_attn_linear_k_weight_to_fp16, x = query_43_cast_fp16)[name = string("linear_195_cast_fp16")];
            tensor<int32, [4]> var_3704 = const()[name = string("op_3704"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_85_cast_fp16 = reshape(shape = var_3704, x = linear_195_cast_fp16)[name = string("k_85_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_21_self_attn_linear_v_weight_to_fp16 = const()[name = string("module_layers_21_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1063929408)))];
            tensor<fp16, [1, 188, 1024]> linear_196_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_21_self_attn_linear_v_weight_to_fp16, x = query_43_cast_fp16)[name = string("linear_196_cast_fp16")];
            tensor<int32, [4]> var_3708 = const()[name = string("op_3708"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_43_cast_fp16 = reshape(shape = var_3708, x = linear_196_cast_fp16)[name = string("v_43_cast_fp16")];
            tensor<int32, [4]> value_45_perm_0 = const()[name = string("value_45_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> module_layers_21_self_attn_pos_bias_u_to_fp16 = const()[name = string("module_layers_21_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1066026624)))];
            tensor<fp16, [1, 188, 8, 128]> var_3720_cast_fp16 = add(x = q_127_cast_fp16, y = module_layers_21_self_attn_pos_bias_u_to_fp16)[name = string("op_3720_cast_fp16")];
            tensor<fp16, [8, 128]> module_layers_21_self_attn_pos_bias_v_to_fp16 = const()[name = string("module_layers_21_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1066028736)))];
            tensor<fp16, [1, 188, 8, 128]> var_3722_cast_fp16 = add(x = q_127_cast_fp16, y = module_layers_21_self_attn_pos_bias_v_to_fp16)[name = string("op_3722_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_43_perm_0 = const()[name = string("q_with_bias_v_43_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            bool x_469_transpose_x_0 = const()[name = string("x_469_transpose_x_0"), val = bool(false)];
            bool x_469_transpose_y_0 = const()[name = string("x_469_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 128, 375]> var_3724_to_fp16 = const()[name = string("op_3724_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1066030848)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_43_cast_fp16 = transpose(perm = q_with_bias_v_43_perm_0, x = var_3722_cast_fp16)[name = string("transpose_140")];
            tensor<fp16, [1, 8, 188, 375]> x_469_cast_fp16 = matmul(transpose_x = x_469_transpose_x_0, transpose_y = x_469_transpose_y_0, x = q_with_bias_v_43_cast_fp16, y = var_3724_to_fp16)[name = string("x_469_cast_fp16")];
            tensor<int32, [8]> x_471_pad_0 = const()[name = string("x_471_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            string x_471_mode_0 = const()[name = string("x_471_mode_0"), val = string("constant")];
            fp16 const_224_to_fp16 = const()[name = string("const_224_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_471_cast_fp16 = pad(constant_val = const_224_to_fp16, mode = x_471_mode_0, pad = x_471_pad_0, x = x_469_cast_fp16)[name = string("x_471_cast_fp16")];
            tensor<int32, [4]> var_3732 = const()[name = string("op_3732"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_473_cast_fp16 = reshape(shape = var_3732, x = x_471_cast_fp16)[name = string("x_473_cast_fp16")];
            tensor<int32, [4]> var_3736_begin_0 = const()[name = string("op_3736_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_3736_end_0 = const()[name = string("op_3736_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_3736_end_mask_0 = const()[name = string("op_3736_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_3736_cast_fp16 = slice_by_index(begin = var_3736_begin_0, end = var_3736_end_0, end_mask = var_3736_end_mask_0, x = x_473_cast_fp16)[name = string("op_3736_cast_fp16")];
            tensor<int32, [4]> var_3737 = const()[name = string("op_3737"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_85_cast_fp16 = reshape(shape = var_3737, x = var_3736_cast_fp16)[name = string("matrix_bd_85_cast_fp16")];
            bool matrix_ac_43_transpose_x_0 = const()[name = string("matrix_ac_43_transpose_x_0"), val = bool(false)];
            bool matrix_ac_43_transpose_y_0 = const()[name = string("matrix_ac_43_transpose_y_0"), val = bool(false)];
            tensor<int32, [4]> transpose_114_perm_0 = const()[name = string("transpose_114_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_115_perm_0 = const()[name = string("transpose_115_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_115 = transpose(perm = transpose_115_perm_0, x = k_85_cast_fp16)[name = string("transpose_138")];
            tensor<fp16, [1, 8, 188, 128]> transpose_114 = transpose(perm = transpose_114_perm_0, x = var_3720_cast_fp16)[name = string("transpose_139")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_43_cast_fp16 = matmul(transpose_x = matrix_ac_43_transpose_x_0, transpose_y = matrix_ac_43_transpose_y_0, x = transpose_114, y = transpose_115)[name = string("matrix_ac_43_cast_fp16")];
            tensor<int32, [4]> matrix_bd_87_begin_0 = const()[name = string("matrix_bd_87_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_87_end_0 = const()[name = string("matrix_bd_87_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_87_end_mask_0 = const()[name = string("matrix_bd_87_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_87_cast_fp16 = slice_by_index(begin = matrix_bd_87_begin_0, end = matrix_bd_87_end_0, end_mask = matrix_bd_87_end_mask_0, x = matrix_bd_85_cast_fp16)[name = string("matrix_bd_87_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_3746_cast_fp16 = add(x = matrix_ac_43_cast_fp16, y = matrix_bd_87_cast_fp16)[name = string("op_3746_cast_fp16")];
            fp16 _inversed_scores_85_y_0_to_fp16 = const()[name = string("_inversed_scores_85_y_0_to_fp16"), val = fp16(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_85_cast_fp16 = mul(x = var_3746_cast_fp16, y = _inversed_scores_85_y_0_to_fp16)[name = string("_inversed_scores_85_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_87_cast_fp16 = select(a = var_10_to_fp16, b = _inversed_scores_85_cast_fp16, cond = mask_3)[name = string("scores_87_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_3752_cast_fp16 = softmax(axis = var_32, x = scores_87_cast_fp16)[name = string("op_3752_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_1133_cast_fp16 = select(a = var_9_to_fp16, b = var_3752_cast_fp16, cond = mask_3)[name = string("input_1133_cast_fp16")];
            bool x_475_transpose_x_0 = const()[name = string("x_475_transpose_x_0"), val = bool(false)];
            bool x_475_transpose_y_0 = const()[name = string("x_475_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 188, 128]> value_45_cast_fp16 = transpose(perm = value_45_perm_0, x = v_43_cast_fp16)[name = string("transpose_141")];
            tensor<fp16, [1, 8, 188, 128]> x_475_cast_fp16 = matmul(transpose_x = x_475_transpose_x_0, transpose_y = x_475_transpose_y_0, x = input_1133_cast_fp16, y = value_45_cast_fp16)[name = string("x_475_cast_fp16")];
            tensor<int32, [4]> var_3756_perm_0 = const()[name = string("op_3756_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_3757 = const()[name = string("op_3757"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_3756_cast_fp16 = transpose(perm = var_3756_perm_0, x = x_475_cast_fp16)[name = string("transpose_137")];
            tensor<fp16, [1, 188, 1024]> input_1135_cast_fp16 = reshape(shape = var_3757, x = var_3756_cast_fp16)[name = string("input_1135_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_21_self_attn_linear_out_weight_to_fp16 = const()[name = string("module_layers_21_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1066798912)))];
            tensor<fp16, [1, 188, 1024]> linear_198_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_21_self_attn_linear_out_weight_to_fp16, x = input_1135_cast_fp16)[name = string("linear_198_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1139_cast_fp16 = add(x = input_1131_cast_fp16, y = linear_198_cast_fp16)[name = string("input_1139_cast_fp16")];
            tensor<int32, [1]> x_479_axes_0 = const()[name = string("x_479_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_21_norm_conv_weight_to_fp16 = const()[name = string("module_layers_21_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1068896128)))];
            tensor<fp16, [1024]> module_layers_21_norm_conv_bias_to_fp16 = const()[name = string("module_layers_21_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1068898240)))];
            tensor<fp16, [1, 188, 1024]> x_479_cast_fp16 = layer_norm(axes = x_479_axes_0, beta = module_layers_21_norm_conv_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_21_norm_conv_weight_to_fp16, x = input_1139_cast_fp16)[name = string("x_479_cast_fp16")];
            tensor<int32, [3]> input_1141_perm_0 = const()[name = string("input_1141_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            string input_1143_pad_type_0 = const()[name = string("input_1143_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_1143_strides_0 = const()[name = string("input_1143_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1143_pad_0 = const()[name = string("input_1143_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1143_dilations_0 = const()[name = string("input_1143_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_1143_groups_0 = const()[name = string("input_1143_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 1024, 1]> module_layers_21_conv_pointwise_conv1_weight_to_fp16 = const()[name = string("module_layers_21_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1068900352)))];
            tensor<fp16, [1, 1024, 188]> input_1141_cast_fp16 = transpose(perm = input_1141_perm_0, x = x_479_cast_fp16)[name = string("transpose_136")];
            tensor<fp16, [1, 2048, 188]> input_1143_cast_fp16 = conv(dilations = input_1143_dilations_0, groups = input_1143_groups_0, pad = input_1143_pad_0, pad_type = input_1143_pad_type_0, strides = input_1143_strides_0, weight = module_layers_21_conv_pointwise_conv1_weight_to_fp16, x = input_1141_cast_fp16)[name = string("input_1143_cast_fp16")];
            int32 x_481_split_num_splits_0 = const()[name = string("x_481_split_num_splits_0"), val = int32(2)];
            int32 x_481_split_axis_0 = const()[name = string("x_481_split_axis_0"), val = int32(1)];
            tensor<fp16, [1, 1024, 188]> x_481_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_481_split_cast_fp16_1 = split(axis = x_481_split_axis_0, num_splits = x_481_split_num_splits_0, x = input_1143_cast_fp16)[name = string("x_481_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_481_split_1_sigmoid_cast_fp16 = sigmoid(x = x_481_split_cast_fp16_1)[name = string("x_481_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_481_cast_fp16 = mul(x = x_481_split_cast_fp16_0, y = x_481_split_1_sigmoid_cast_fp16)[name = string("x_481_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_1145_cast_fp16 = select(a = var_9_to_fp16, b = x_481_cast_fp16, cond = var_356)[name = string("input_1145_cast_fp16")];
            tensor<int32, [6]> input_1147_pad_0 = const()[name = string("input_1147_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            string input_1147_mode_0 = const()[name = string("input_1147_mode_0"), val = string("constant")];
            fp16 const_227_to_fp16 = const()[name = string("const_227_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_1147_cast_fp16 = pad(constant_val = const_227_to_fp16, mode = input_1147_mode_0, pad = input_1147_pad_0, x = input_1145_cast_fp16)[name = string("input_1147_cast_fp16")];
            string input_1149_pad_type_0 = const()[name = string("input_1149_pad_type_0"), val = string("valid")];
            int32 input_1149_groups_0 = const()[name = string("input_1149_groups_0"), val = int32(1024)];
            tensor<int32, [1]> input_1149_strides_0 = const()[name = string("input_1149_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1149_pad_0 = const()[name = string("input_1149_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1149_dilations_0 = const()[name = string("input_1149_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_290_to_fp16 = const()[name = string("const_290_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1073094720)))];
            tensor<fp16, [1024]> const_291_to_fp16 = const()[name = string("const_291_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1073113216)))];
            tensor<fp16, [1, 1024, 188]> input_1151_cast_fp16 = conv(bias = const_291_to_fp16, dilations = input_1149_dilations_0, groups = input_1149_groups_0, pad = input_1149_pad_0, pad_type = input_1149_pad_type_0, strides = input_1149_strides_0, weight = const_290_to_fp16, x = input_1147_cast_fp16)[name = string("input_1151_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_1153_cast_fp16 = silu(x = input_1151_cast_fp16)[name = string("input_1153_cast_fp16")];
            string x_483_pad_type_0 = const()[name = string("x_483_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> x_483_strides_0 = const()[name = string("x_483_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_483_pad_0 = const()[name = string("x_483_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_483_dilations_0 = const()[name = string("x_483_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 x_483_groups_0 = const()[name = string("x_483_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 1024, 1]> module_layers_21_conv_pointwise_conv2_weight_to_fp16 = const()[name = string("module_layers_21_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1073115328)))];
            tensor<fp16, [1, 1024, 188]> x_483_cast_fp16 = conv(dilations = x_483_dilations_0, groups = x_483_groups_0, pad = x_483_pad_0, pad_type = x_483_pad_type_0, strides = x_483_strides_0, weight = module_layers_21_conv_pointwise_conv2_weight_to_fp16, x = input_1153_cast_fp16)[name = string("x_483_cast_fp16")];
            tensor<int32, [3]> input_1155_perm_0 = const()[name = string("input_1155_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_1155_cast_fp16 = transpose(perm = input_1155_perm_0, x = x_483_cast_fp16)[name = string("transpose_135")];
            tensor<fp16, [1, 188, 1024]> input_1157_cast_fp16 = add(x = input_1139_cast_fp16, y = input_1155_cast_fp16)[name = string("input_1157_cast_fp16")];
            tensor<int32, [1]> input_1159_axes_0 = const()[name = string("input_1159_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_21_norm_feed_forward2_weight_to_fp16 = const()[name = string("module_layers_21_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1075212544)))];
            tensor<fp16, [1024]> module_layers_21_norm_feed_forward2_bias_to_fp16 = const()[name = string("module_layers_21_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1075214656)))];
            tensor<fp16, [1, 188, 1024]> input_1159_cast_fp16 = layer_norm(axes = input_1159_axes_0, beta = module_layers_21_norm_feed_forward2_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_21_norm_feed_forward2_weight_to_fp16, x = input_1157_cast_fp16)[name = string("input_1159_cast_fp16")];
            tensor<fp16, [4096, 1024]> module_layers_21_feed_forward2_linear1_weight_to_fp16 = const()[name = string("module_layers_21_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1075216768)))];
            tensor<fp16, [1, 188, 4096]> linear_199_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = module_layers_21_feed_forward2_linear1_weight_to_fp16, x = input_1159_cast_fp16)[name = string("linear_199_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_1163_cast_fp16 = silu(x = linear_199_cast_fp16)[name = string("input_1163_cast_fp16")];
            tensor<fp16, [1024, 4096]> module_layers_21_feed_forward2_linear2_weight_to_fp16 = const()[name = string("module_layers_21_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1083605440)))];
            tensor<fp16, [1, 188, 1024]> linear_200_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_21_feed_forward2_linear2_weight_to_fp16, x = input_1163_cast_fp16)[name = string("linear_200_cast_fp16")];
            fp16 var_3817_to_fp16 = const()[name = string("op_3817_to_fp16"), val = fp16(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_3818_cast_fp16 = mul(x = linear_200_cast_fp16, y = var_3817_to_fp16)[name = string("op_3818_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1169_cast_fp16 = add(x = input_1157_cast_fp16, y = var_3818_cast_fp16)[name = string("input_1169_cast_fp16")];
            tensor<int32, [1]> input_1171_axes_0 = const()[name = string("input_1171_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_21_norm_out_weight_to_fp16 = const()[name = string("module_layers_21_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1091994112)))];
            tensor<fp16, [1024]> module_layers_21_norm_out_bias_to_fp16 = const()[name = string("module_layers_21_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1091996224)))];
            tensor<fp16, [1, 188, 1024]> input_1171_cast_fp16 = layer_norm(axes = input_1171_axes_0, beta = module_layers_21_norm_out_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_21_norm_out_weight_to_fp16, x = input_1169_cast_fp16)[name = string("input_1171_cast_fp16")];
            tensor<int32, [1]> input_1173_axes_0 = const()[name = string("input_1173_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_22_norm_feed_forward1_weight_to_fp16 = const()[name = string("module_layers_22_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1091998336)))];
            tensor<fp16, [1024]> module_layers_22_norm_feed_forward1_bias_to_fp16 = const()[name = string("module_layers_22_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1092000448)))];
            tensor<fp16, [1, 188, 1024]> input_1173_cast_fp16 = layer_norm(axes = input_1173_axes_0, beta = module_layers_22_norm_feed_forward1_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_22_norm_feed_forward1_weight_to_fp16, x = input_1171_cast_fp16)[name = string("input_1173_cast_fp16")];
            tensor<fp16, [4096, 1024]> module_layers_22_feed_forward1_linear1_weight_to_fp16 = const()[name = string("module_layers_22_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1092002560)))];
            tensor<fp16, [1, 188, 4096]> linear_201_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = module_layers_22_feed_forward1_linear1_weight_to_fp16, x = input_1173_cast_fp16)[name = string("linear_201_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_1177_cast_fp16 = silu(x = linear_201_cast_fp16)[name = string("input_1177_cast_fp16")];
            tensor<fp16, [1024, 4096]> module_layers_22_feed_forward1_linear2_weight_to_fp16 = const()[name = string("module_layers_22_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1100391232)))];
            tensor<fp16, [1, 188, 1024]> linear_202_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_22_feed_forward1_linear2_weight_to_fp16, x = input_1177_cast_fp16)[name = string("linear_202_cast_fp16")];
            fp16 var_3846_to_fp16 = const()[name = string("op_3846_to_fp16"), val = fp16(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_3847_cast_fp16 = mul(x = linear_202_cast_fp16, y = var_3846_to_fp16)[name = string("op_3847_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1183_cast_fp16 = add(x = input_1171_cast_fp16, y = var_3847_cast_fp16)[name = string("input_1183_cast_fp16")];
            tensor<int32, [1]> query_45_axes_0 = const()[name = string("query_45_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_22_norm_self_att_weight_to_fp16 = const()[name = string("module_layers_22_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1108779904)))];
            tensor<fp16, [1024]> module_layers_22_norm_self_att_bias_to_fp16 = const()[name = string("module_layers_22_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1108782016)))];
            tensor<fp16, [1, 188, 1024]> query_45_cast_fp16 = layer_norm(axes = query_45_axes_0, beta = module_layers_22_norm_self_att_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_22_norm_self_att_weight_to_fp16, x = input_1183_cast_fp16)[name = string("query_45_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_22_self_attn_linear_q_weight_to_fp16 = const()[name = string("module_layers_22_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1108784128)))];
            tensor<fp16, [1, 188, 1024]> linear_203_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_22_self_attn_linear_q_weight_to_fp16, x = query_45_cast_fp16)[name = string("linear_203_cast_fp16")];
            tensor<int32, [4]> var_3863 = const()[name = string("op_3863"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_133_cast_fp16 = reshape(shape = var_3863, x = linear_203_cast_fp16)[name = string("q_133_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_22_self_attn_linear_k_weight_to_fp16 = const()[name = string("module_layers_22_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1110881344)))];
            tensor<fp16, [1, 188, 1024]> linear_204_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_22_self_attn_linear_k_weight_to_fp16, x = query_45_cast_fp16)[name = string("linear_204_cast_fp16")];
            tensor<int32, [4]> var_3867 = const()[name = string("op_3867"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_89_cast_fp16 = reshape(shape = var_3867, x = linear_204_cast_fp16)[name = string("k_89_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_22_self_attn_linear_v_weight_to_fp16 = const()[name = string("module_layers_22_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1112978560)))];
            tensor<fp16, [1, 188, 1024]> linear_205_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_22_self_attn_linear_v_weight_to_fp16, x = query_45_cast_fp16)[name = string("linear_205_cast_fp16")];
            tensor<int32, [4]> var_3871 = const()[name = string("op_3871"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_45_cast_fp16 = reshape(shape = var_3871, x = linear_205_cast_fp16)[name = string("v_45_cast_fp16")];
            tensor<int32, [4]> value_47_perm_0 = const()[name = string("value_47_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> module_layers_22_self_attn_pos_bias_u_to_fp16 = const()[name = string("module_layers_22_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1115075776)))];
            tensor<fp16, [1, 188, 8, 128]> var_3883_cast_fp16 = add(x = q_133_cast_fp16, y = module_layers_22_self_attn_pos_bias_u_to_fp16)[name = string("op_3883_cast_fp16")];
            tensor<fp16, [8, 128]> module_layers_22_self_attn_pos_bias_v_to_fp16 = const()[name = string("module_layers_22_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1115077888)))];
            tensor<fp16, [1, 188, 8, 128]> var_3885_cast_fp16 = add(x = q_133_cast_fp16, y = module_layers_22_self_attn_pos_bias_v_to_fp16)[name = string("op_3885_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_45_perm_0 = const()[name = string("q_with_bias_v_45_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            bool x_491_transpose_x_0 = const()[name = string("x_491_transpose_x_0"), val = bool(false)];
            bool x_491_transpose_y_0 = const()[name = string("x_491_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 128, 375]> var_3887_to_fp16 = const()[name = string("op_3887_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1115080000)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_45_cast_fp16 = transpose(perm = q_with_bias_v_45_perm_0, x = var_3885_cast_fp16)[name = string("transpose_133")];
            tensor<fp16, [1, 8, 188, 375]> x_491_cast_fp16 = matmul(transpose_x = x_491_transpose_x_0, transpose_y = x_491_transpose_y_0, x = q_with_bias_v_45_cast_fp16, y = var_3887_to_fp16)[name = string("x_491_cast_fp16")];
            tensor<int32, [8]> x_493_pad_0 = const()[name = string("x_493_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            string x_493_mode_0 = const()[name = string("x_493_mode_0"), val = string("constant")];
            fp16 const_234_to_fp16 = const()[name = string("const_234_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_493_cast_fp16 = pad(constant_val = const_234_to_fp16, mode = x_493_mode_0, pad = x_493_pad_0, x = x_491_cast_fp16)[name = string("x_493_cast_fp16")];
            tensor<int32, [4]> var_3895 = const()[name = string("op_3895"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_495_cast_fp16 = reshape(shape = var_3895, x = x_493_cast_fp16)[name = string("x_495_cast_fp16")];
            tensor<int32, [4]> var_3899_begin_0 = const()[name = string("op_3899_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_3899_end_0 = const()[name = string("op_3899_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_3899_end_mask_0 = const()[name = string("op_3899_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_3899_cast_fp16 = slice_by_index(begin = var_3899_begin_0, end = var_3899_end_0, end_mask = var_3899_end_mask_0, x = x_495_cast_fp16)[name = string("op_3899_cast_fp16")];
            tensor<int32, [4]> var_3900 = const()[name = string("op_3900"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_89_cast_fp16 = reshape(shape = var_3900, x = var_3899_cast_fp16)[name = string("matrix_bd_89_cast_fp16")];
            bool matrix_ac_45_transpose_x_0 = const()[name = string("matrix_ac_45_transpose_x_0"), val = bool(false)];
            bool matrix_ac_45_transpose_y_0 = const()[name = string("matrix_ac_45_transpose_y_0"), val = bool(false)];
            tensor<int32, [4]> transpose_116_perm_0 = const()[name = string("transpose_116_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_117_perm_0 = const()[name = string("transpose_117_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_117 = transpose(perm = transpose_117_perm_0, x = k_89_cast_fp16)[name = string("transpose_131")];
            tensor<fp16, [1, 8, 188, 128]> transpose_116 = transpose(perm = transpose_116_perm_0, x = var_3883_cast_fp16)[name = string("transpose_132")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_45_cast_fp16 = matmul(transpose_x = matrix_ac_45_transpose_x_0, transpose_y = matrix_ac_45_transpose_y_0, x = transpose_116, y = transpose_117)[name = string("matrix_ac_45_cast_fp16")];
            tensor<int32, [4]> matrix_bd_91_begin_0 = const()[name = string("matrix_bd_91_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_91_end_0 = const()[name = string("matrix_bd_91_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_91_end_mask_0 = const()[name = string("matrix_bd_91_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_91_cast_fp16 = slice_by_index(begin = matrix_bd_91_begin_0, end = matrix_bd_91_end_0, end_mask = matrix_bd_91_end_mask_0, x = matrix_bd_89_cast_fp16)[name = string("matrix_bd_91_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_3909_cast_fp16 = add(x = matrix_ac_45_cast_fp16, y = matrix_bd_91_cast_fp16)[name = string("op_3909_cast_fp16")];
            fp16 _inversed_scores_89_y_0_to_fp16 = const()[name = string("_inversed_scores_89_y_0_to_fp16"), val = fp16(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_89_cast_fp16 = mul(x = var_3909_cast_fp16, y = _inversed_scores_89_y_0_to_fp16)[name = string("_inversed_scores_89_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_91_cast_fp16 = select(a = var_10_to_fp16, b = _inversed_scores_89_cast_fp16, cond = mask_3)[name = string("scores_91_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_3915_cast_fp16 = softmax(axis = var_32, x = scores_91_cast_fp16)[name = string("op_3915_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_1185_cast_fp16 = select(a = var_9_to_fp16, b = var_3915_cast_fp16, cond = mask_3)[name = string("input_1185_cast_fp16")];
            bool x_497_transpose_x_0 = const()[name = string("x_497_transpose_x_0"), val = bool(false)];
            bool x_497_transpose_y_0 = const()[name = string("x_497_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 188, 128]> value_47_cast_fp16 = transpose(perm = value_47_perm_0, x = v_45_cast_fp16)[name = string("transpose_134")];
            tensor<fp16, [1, 8, 188, 128]> x_497_cast_fp16 = matmul(transpose_x = x_497_transpose_x_0, transpose_y = x_497_transpose_y_0, x = input_1185_cast_fp16, y = value_47_cast_fp16)[name = string("x_497_cast_fp16")];
            tensor<int32, [4]> var_3919_perm_0 = const()[name = string("op_3919_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_3920 = const()[name = string("op_3920"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_3919_cast_fp16 = transpose(perm = var_3919_perm_0, x = x_497_cast_fp16)[name = string("transpose_130")];
            tensor<fp16, [1, 188, 1024]> input_1187_cast_fp16 = reshape(shape = var_3920, x = var_3919_cast_fp16)[name = string("input_1187_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_22_self_attn_linear_out_weight_to_fp16 = const()[name = string("module_layers_22_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1115848064)))];
            tensor<fp16, [1, 188, 1024]> linear_207_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_22_self_attn_linear_out_weight_to_fp16, x = input_1187_cast_fp16)[name = string("linear_207_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1191_cast_fp16 = add(x = input_1183_cast_fp16, y = linear_207_cast_fp16)[name = string("input_1191_cast_fp16")];
            tensor<int32, [1]> x_501_axes_0 = const()[name = string("x_501_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_22_norm_conv_weight_to_fp16 = const()[name = string("module_layers_22_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1117945280)))];
            tensor<fp16, [1024]> module_layers_22_norm_conv_bias_to_fp16 = const()[name = string("module_layers_22_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1117947392)))];
            tensor<fp16, [1, 188, 1024]> x_501_cast_fp16 = layer_norm(axes = x_501_axes_0, beta = module_layers_22_norm_conv_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_22_norm_conv_weight_to_fp16, x = input_1191_cast_fp16)[name = string("x_501_cast_fp16")];
            tensor<int32, [3]> input_1193_perm_0 = const()[name = string("input_1193_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            string input_1195_pad_type_0 = const()[name = string("input_1195_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_1195_strides_0 = const()[name = string("input_1195_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1195_pad_0 = const()[name = string("input_1195_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1195_dilations_0 = const()[name = string("input_1195_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_1195_groups_0 = const()[name = string("input_1195_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 1024, 1]> module_layers_22_conv_pointwise_conv1_weight_to_fp16 = const()[name = string("module_layers_22_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1117949504)))];
            tensor<fp16, [1, 1024, 188]> input_1193_cast_fp16 = transpose(perm = input_1193_perm_0, x = x_501_cast_fp16)[name = string("transpose_129")];
            tensor<fp16, [1, 2048, 188]> input_1195_cast_fp16 = conv(dilations = input_1195_dilations_0, groups = input_1195_groups_0, pad = input_1195_pad_0, pad_type = input_1195_pad_type_0, strides = input_1195_strides_0, weight = module_layers_22_conv_pointwise_conv1_weight_to_fp16, x = input_1193_cast_fp16)[name = string("input_1195_cast_fp16")];
            int32 x_503_split_num_splits_0 = const()[name = string("x_503_split_num_splits_0"), val = int32(2)];
            int32 x_503_split_axis_0 = const()[name = string("x_503_split_axis_0"), val = int32(1)];
            tensor<fp16, [1, 1024, 188]> x_503_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_503_split_cast_fp16_1 = split(axis = x_503_split_axis_0, num_splits = x_503_split_num_splits_0, x = input_1195_cast_fp16)[name = string("x_503_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_503_split_1_sigmoid_cast_fp16 = sigmoid(x = x_503_split_cast_fp16_1)[name = string("x_503_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_503_cast_fp16 = mul(x = x_503_split_cast_fp16_0, y = x_503_split_1_sigmoid_cast_fp16)[name = string("x_503_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_1197_cast_fp16 = select(a = var_9_to_fp16, b = x_503_cast_fp16, cond = var_356)[name = string("input_1197_cast_fp16")];
            tensor<int32, [6]> input_1199_pad_0 = const()[name = string("input_1199_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            string input_1199_mode_0 = const()[name = string("input_1199_mode_0"), val = string("constant")];
            fp16 const_237_to_fp16 = const()[name = string("const_237_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_1199_cast_fp16 = pad(constant_val = const_237_to_fp16, mode = input_1199_mode_0, pad = input_1199_pad_0, x = input_1197_cast_fp16)[name = string("input_1199_cast_fp16")];
            string input_1201_pad_type_0 = const()[name = string("input_1201_pad_type_0"), val = string("valid")];
            int32 input_1201_groups_0 = const()[name = string("input_1201_groups_0"), val = int32(1024)];
            tensor<int32, [1]> input_1201_strides_0 = const()[name = string("input_1201_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1201_pad_0 = const()[name = string("input_1201_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1201_dilations_0 = const()[name = string("input_1201_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_292_to_fp16 = const()[name = string("const_292_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1122143872)))];
            tensor<fp16, [1024]> const_293_to_fp16 = const()[name = string("const_293_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1122162368)))];
            tensor<fp16, [1, 1024, 188]> input_1203_cast_fp16 = conv(bias = const_293_to_fp16, dilations = input_1201_dilations_0, groups = input_1201_groups_0, pad = input_1201_pad_0, pad_type = input_1201_pad_type_0, strides = input_1201_strides_0, weight = const_292_to_fp16, x = input_1199_cast_fp16)[name = string("input_1203_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_1205_cast_fp16 = silu(x = input_1203_cast_fp16)[name = string("input_1205_cast_fp16")];
            string x_505_pad_type_0 = const()[name = string("x_505_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> x_505_strides_0 = const()[name = string("x_505_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_505_pad_0 = const()[name = string("x_505_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_505_dilations_0 = const()[name = string("x_505_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 x_505_groups_0 = const()[name = string("x_505_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 1024, 1]> module_layers_22_conv_pointwise_conv2_weight_to_fp16 = const()[name = string("module_layers_22_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1122164480)))];
            tensor<fp16, [1, 1024, 188]> x_505_cast_fp16 = conv(dilations = x_505_dilations_0, groups = x_505_groups_0, pad = x_505_pad_0, pad_type = x_505_pad_type_0, strides = x_505_strides_0, weight = module_layers_22_conv_pointwise_conv2_weight_to_fp16, x = input_1205_cast_fp16)[name = string("x_505_cast_fp16")];
            tensor<int32, [3]> input_1207_perm_0 = const()[name = string("input_1207_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_1207_cast_fp16 = transpose(perm = input_1207_perm_0, x = x_505_cast_fp16)[name = string("transpose_128")];
            tensor<fp16, [1, 188, 1024]> input_1209_cast_fp16 = add(x = input_1191_cast_fp16, y = input_1207_cast_fp16)[name = string("input_1209_cast_fp16")];
            tensor<int32, [1]> input_1211_axes_0 = const()[name = string("input_1211_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_22_norm_feed_forward2_weight_to_fp16 = const()[name = string("module_layers_22_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1124261696)))];
            tensor<fp16, [1024]> module_layers_22_norm_feed_forward2_bias_to_fp16 = const()[name = string("module_layers_22_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1124263808)))];
            tensor<fp16, [1, 188, 1024]> input_1211_cast_fp16 = layer_norm(axes = input_1211_axes_0, beta = module_layers_22_norm_feed_forward2_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_22_norm_feed_forward2_weight_to_fp16, x = input_1209_cast_fp16)[name = string("input_1211_cast_fp16")];
            tensor<fp16, [4096, 1024]> module_layers_22_feed_forward2_linear1_weight_to_fp16 = const()[name = string("module_layers_22_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1124265920)))];
            tensor<fp16, [1, 188, 4096]> linear_208_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = module_layers_22_feed_forward2_linear1_weight_to_fp16, x = input_1211_cast_fp16)[name = string("linear_208_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_1215_cast_fp16 = silu(x = linear_208_cast_fp16)[name = string("input_1215_cast_fp16")];
            tensor<fp16, [1024, 4096]> module_layers_22_feed_forward2_linear2_weight_to_fp16 = const()[name = string("module_layers_22_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1132654592)))];
            tensor<fp16, [1, 188, 1024]> linear_209_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_22_feed_forward2_linear2_weight_to_fp16, x = input_1215_cast_fp16)[name = string("linear_209_cast_fp16")];
            fp16 var_3980_to_fp16 = const()[name = string("op_3980_to_fp16"), val = fp16(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_3981_cast_fp16 = mul(x = linear_209_cast_fp16, y = var_3980_to_fp16)[name = string("op_3981_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1221_cast_fp16 = add(x = input_1209_cast_fp16, y = var_3981_cast_fp16)[name = string("input_1221_cast_fp16")];
            tensor<int32, [1]> input_1223_axes_0 = const()[name = string("input_1223_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_22_norm_out_weight_to_fp16 = const()[name = string("module_layers_22_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1141043264)))];
            tensor<fp16, [1024]> module_layers_22_norm_out_bias_to_fp16 = const()[name = string("module_layers_22_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1141045376)))];
            tensor<fp16, [1, 188, 1024]> input_1223_cast_fp16 = layer_norm(axes = input_1223_axes_0, beta = module_layers_22_norm_out_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_22_norm_out_weight_to_fp16, x = input_1221_cast_fp16)[name = string("input_1223_cast_fp16")];
            tensor<int32, [1]> input_1225_axes_0 = const()[name = string("input_1225_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_23_norm_feed_forward1_weight_to_fp16 = const()[name = string("module_layers_23_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1141047488)))];
            tensor<fp16, [1024]> module_layers_23_norm_feed_forward1_bias_to_fp16 = const()[name = string("module_layers_23_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1141049600)))];
            tensor<fp16, [1, 188, 1024]> input_1225_cast_fp16 = layer_norm(axes = input_1225_axes_0, beta = module_layers_23_norm_feed_forward1_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_23_norm_feed_forward1_weight_to_fp16, x = input_1223_cast_fp16)[name = string("input_1225_cast_fp16")];
            tensor<fp16, [4096, 1024]> module_layers_23_feed_forward1_linear1_weight_to_fp16 = const()[name = string("module_layers_23_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1141051712)))];
            tensor<fp16, [1, 188, 4096]> linear_210_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = module_layers_23_feed_forward1_linear1_weight_to_fp16, x = input_1225_cast_fp16)[name = string("linear_210_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_1229_cast_fp16 = silu(x = linear_210_cast_fp16)[name = string("input_1229_cast_fp16")];
            tensor<fp16, [1024, 4096]> module_layers_23_feed_forward1_linear2_weight_to_fp16 = const()[name = string("module_layers_23_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1149440384)))];
            tensor<fp16, [1, 188, 1024]> linear_211_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_23_feed_forward1_linear2_weight_to_fp16, x = input_1229_cast_fp16)[name = string("linear_211_cast_fp16")];
            fp16 var_4009_to_fp16 = const()[name = string("op_4009_to_fp16"), val = fp16(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_4010_cast_fp16 = mul(x = linear_211_cast_fp16, y = var_4009_to_fp16)[name = string("op_4010_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1235_cast_fp16 = add(x = input_1223_cast_fp16, y = var_4010_cast_fp16)[name = string("input_1235_cast_fp16")];
            tensor<int32, [1]> query_axes_0 = const()[name = string("query_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_23_norm_self_att_weight_to_fp16 = const()[name = string("module_layers_23_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1157829056)))];
            tensor<fp16, [1024]> module_layers_23_norm_self_att_bias_to_fp16 = const()[name = string("module_layers_23_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1157831168)))];
            tensor<fp16, [1, 188, 1024]> query_cast_fp16 = layer_norm(axes = query_axes_0, beta = module_layers_23_norm_self_att_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_23_norm_self_att_weight_to_fp16, x = input_1235_cast_fp16)[name = string("query_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_23_self_attn_linear_q_weight_to_fp16 = const()[name = string("module_layers_23_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1157833280)))];
            tensor<fp16, [1, 188, 1024]> linear_212_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_23_self_attn_linear_q_weight_to_fp16, x = query_cast_fp16)[name = string("linear_212_cast_fp16")];
            tensor<int32, [4]> var_4026 = const()[name = string("op_4026"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_139_cast_fp16 = reshape(shape = var_4026, x = linear_212_cast_fp16)[name = string("q_139_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_23_self_attn_linear_k_weight_to_fp16 = const()[name = string("module_layers_23_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1159930496)))];
            tensor<fp16, [1, 188, 1024]> linear_213_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_23_self_attn_linear_k_weight_to_fp16, x = query_cast_fp16)[name = string("linear_213_cast_fp16")];
            tensor<int32, [4]> var_4030 = const()[name = string("op_4030"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_93_cast_fp16 = reshape(shape = var_4030, x = linear_213_cast_fp16)[name = string("k_93_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_23_self_attn_linear_v_weight_to_fp16 = const()[name = string("module_layers_23_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1162027712)))];
            tensor<fp16, [1, 188, 1024]> linear_214_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_23_self_attn_linear_v_weight_to_fp16, x = query_cast_fp16)[name = string("linear_214_cast_fp16")];
            tensor<int32, [4]> var_4034 = const()[name = string("op_4034"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_cast_fp16 = reshape(shape = var_4034, x = linear_214_cast_fp16)[name = string("v_cast_fp16")];
            tensor<int32, [4]> value_perm_0 = const()[name = string("value_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> module_layers_23_self_attn_pos_bias_u_to_fp16 = const()[name = string("module_layers_23_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1164124928)))];
            tensor<fp16, [1, 188, 8, 128]> var_4046_cast_fp16 = add(x = q_139_cast_fp16, y = module_layers_23_self_attn_pos_bias_u_to_fp16)[name = string("op_4046_cast_fp16")];
            tensor<fp16, [8, 128]> module_layers_23_self_attn_pos_bias_v_to_fp16 = const()[name = string("module_layers_23_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1164127040)))];
            tensor<fp16, [1, 188, 8, 128]> var_4048_cast_fp16 = add(x = q_139_cast_fp16, y = module_layers_23_self_attn_pos_bias_v_to_fp16)[name = string("op_4048_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_perm_0 = const()[name = string("q_with_bias_v_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            bool x_513_transpose_x_0 = const()[name = string("x_513_transpose_x_0"), val = bool(false)];
            bool x_513_transpose_y_0 = const()[name = string("x_513_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 128, 375]> var_4050_to_fp16 = const()[name = string("op_4050_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1164129152)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_cast_fp16 = transpose(perm = q_with_bias_v_perm_0, x = var_4048_cast_fp16)[name = string("transpose_126")];
            tensor<fp16, [1, 8, 188, 375]> x_513_cast_fp16 = matmul(transpose_x = x_513_transpose_x_0, transpose_y = x_513_transpose_y_0, x = q_with_bias_v_cast_fp16, y = var_4050_to_fp16)[name = string("x_513_cast_fp16")];
            tensor<int32, [8]> x_515_pad_0 = const()[name = string("x_515_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            string x_515_mode_0 = const()[name = string("x_515_mode_0"), val = string("constant")];
            fp16 const_244_to_fp16 = const()[name = string("const_244_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_515_cast_fp16 = pad(constant_val = const_244_to_fp16, mode = x_515_mode_0, pad = x_515_pad_0, x = x_513_cast_fp16)[name = string("x_515_cast_fp16")];
            tensor<int32, [4]> var_4058 = const()[name = string("op_4058"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_517_cast_fp16 = reshape(shape = var_4058, x = x_515_cast_fp16)[name = string("x_517_cast_fp16")];
            tensor<int32, [4]> var_4062_begin_0 = const()[name = string("op_4062_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_4062_end_0 = const()[name = string("op_4062_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_4062_end_mask_0 = const()[name = string("op_4062_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_4062_cast_fp16 = slice_by_index(begin = var_4062_begin_0, end = var_4062_end_0, end_mask = var_4062_end_mask_0, x = x_517_cast_fp16)[name = string("op_4062_cast_fp16")];
            tensor<int32, [4]> var_4063 = const()[name = string("op_4063"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_93_cast_fp16 = reshape(shape = var_4063, x = var_4062_cast_fp16)[name = string("matrix_bd_93_cast_fp16")];
            bool matrix_ac_transpose_x_0 = const()[name = string("matrix_ac_transpose_x_0"), val = bool(false)];
            bool matrix_ac_transpose_y_0 = const()[name = string("matrix_ac_transpose_y_0"), val = bool(false)];
            tensor<int32, [4]> transpose_118_perm_0 = const()[name = string("transpose_118_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_119_perm_0 = const()[name = string("transpose_119_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_119 = transpose(perm = transpose_119_perm_0, x = k_93_cast_fp16)[name = string("transpose_124")];
            tensor<fp16, [1, 8, 188, 128]> transpose_118 = transpose(perm = transpose_118_perm_0, x = var_4046_cast_fp16)[name = string("transpose_125")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_cast_fp16 = matmul(transpose_x = matrix_ac_transpose_x_0, transpose_y = matrix_ac_transpose_y_0, x = transpose_118, y = transpose_119)[name = string("matrix_ac_cast_fp16")];
            tensor<int32, [4]> matrix_bd_begin_0 = const()[name = string("matrix_bd_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_end_0 = const()[name = string("matrix_bd_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_end_mask_0 = const()[name = string("matrix_bd_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_cast_fp16 = slice_by_index(begin = matrix_bd_begin_0, end = matrix_bd_end_0, end_mask = matrix_bd_end_mask_0, x = matrix_bd_93_cast_fp16)[name = string("matrix_bd_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_4072_cast_fp16 = add(x = matrix_ac_cast_fp16, y = matrix_bd_cast_fp16)[name = string("op_4072_cast_fp16")];
            fp16 _inversed_scores_93_y_0_to_fp16 = const()[name = string("_inversed_scores_93_y_0_to_fp16"), val = fp16(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_93_cast_fp16 = mul(x = var_4072_cast_fp16, y = _inversed_scores_93_y_0_to_fp16)[name = string("_inversed_scores_93_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_cast_fp16 = select(a = var_10_to_fp16, b = _inversed_scores_93_cast_fp16, cond = mask_3)[name = string("scores_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_4078_cast_fp16 = softmax(axis = var_32, x = scores_cast_fp16)[name = string("op_4078_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_1237_cast_fp16 = select(a = var_9_to_fp16, b = var_4078_cast_fp16, cond = mask_3)[name = string("input_1237_cast_fp16")];
            bool x_519_transpose_x_0 = const()[name = string("x_519_transpose_x_0"), val = bool(false)];
            bool x_519_transpose_y_0 = const()[name = string("x_519_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 8, 188, 128]> value_cast_fp16 = transpose(perm = value_perm_0, x = v_cast_fp16)[name = string("transpose_127")];
            tensor<fp16, [1, 8, 188, 128]> x_519_cast_fp16 = matmul(transpose_x = x_519_transpose_x_0, transpose_y = x_519_transpose_y_0, x = input_1237_cast_fp16, y = value_cast_fp16)[name = string("x_519_cast_fp16")];
            tensor<int32, [4]> var_4082_perm_0 = const()[name = string("op_4082_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_4083 = const()[name = string("op_4083"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_4082_cast_fp16 = transpose(perm = var_4082_perm_0, x = x_519_cast_fp16)[name = string("transpose_123")];
            tensor<fp16, [1, 188, 1024]> input_1239_cast_fp16 = reshape(shape = var_4083, x = var_4082_cast_fp16)[name = string("input_1239_cast_fp16")];
            tensor<fp16, [1024, 1024]> module_layers_23_self_attn_linear_out_weight_to_fp16 = const()[name = string("module_layers_23_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1164897216)))];
            tensor<fp16, [1, 188, 1024]> linear_216_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_23_self_attn_linear_out_weight_to_fp16, x = input_1239_cast_fp16)[name = string("linear_216_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1243_cast_fp16 = add(x = input_1235_cast_fp16, y = linear_216_cast_fp16)[name = string("input_1243_cast_fp16")];
            tensor<int32, [1]> x_523_axes_0 = const()[name = string("x_523_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_23_norm_conv_weight_to_fp16 = const()[name = string("module_layers_23_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1166994432)))];
            tensor<fp16, [1024]> module_layers_23_norm_conv_bias_to_fp16 = const()[name = string("module_layers_23_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1166996544)))];
            tensor<fp16, [1, 188, 1024]> x_523_cast_fp16 = layer_norm(axes = x_523_axes_0, beta = module_layers_23_norm_conv_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_23_norm_conv_weight_to_fp16, x = input_1243_cast_fp16)[name = string("x_523_cast_fp16")];
            tensor<int32, [3]> input_1245_perm_0 = const()[name = string("input_1245_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            string input_1247_pad_type_0 = const()[name = string("input_1247_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_1247_strides_0 = const()[name = string("input_1247_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1247_pad_0 = const()[name = string("input_1247_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1247_dilations_0 = const()[name = string("input_1247_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_1247_groups_0 = const()[name = string("input_1247_groups_0"), val = int32(1)];
            tensor<fp16, [2048, 1024, 1]> module_layers_23_conv_pointwise_conv1_weight_to_fp16 = const()[name = string("module_layers_23_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1166998656)))];
            tensor<fp16, [1, 1024, 188]> input_1245_cast_fp16 = transpose(perm = input_1245_perm_0, x = x_523_cast_fp16)[name = string("transpose_122")];
            tensor<fp16, [1, 2048, 188]> input_1247_cast_fp16 = conv(dilations = input_1247_dilations_0, groups = input_1247_groups_0, pad = input_1247_pad_0, pad_type = input_1247_pad_type_0, strides = input_1247_strides_0, weight = module_layers_23_conv_pointwise_conv1_weight_to_fp16, x = input_1245_cast_fp16)[name = string("input_1247_cast_fp16")];
            int32 x_525_split_num_splits_0 = const()[name = string("x_525_split_num_splits_0"), val = int32(2)];
            int32 x_525_split_axis_0 = const()[name = string("x_525_split_axis_0"), val = int32(1)];
            tensor<fp16, [1, 1024, 188]> x_525_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_525_split_cast_fp16_1 = split(axis = x_525_split_axis_0, num_splits = x_525_split_num_splits_0, x = input_1247_cast_fp16)[name = string("x_525_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_525_split_1_sigmoid_cast_fp16 = sigmoid(x = x_525_split_cast_fp16_1)[name = string("x_525_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_525_cast_fp16 = mul(x = x_525_split_cast_fp16_0, y = x_525_split_1_sigmoid_cast_fp16)[name = string("x_525_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_1249_cast_fp16 = select(a = var_9_to_fp16, b = x_525_cast_fp16, cond = var_356)[name = string("input_1249_cast_fp16")];
            tensor<int32, [6]> input_1251_pad_0 = const()[name = string("input_1251_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            string input_1251_mode_0 = const()[name = string("input_1251_mode_0"), val = string("constant")];
            fp16 const_247_to_fp16 = const()[name = string("const_247_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_1251_cast_fp16 = pad(constant_val = const_247_to_fp16, mode = input_1251_mode_0, pad = input_1251_pad_0, x = input_1249_cast_fp16)[name = string("input_1251_cast_fp16")];
            string input_1253_pad_type_0 = const()[name = string("input_1253_pad_type_0"), val = string("valid")];
            int32 input_1253_groups_0 = const()[name = string("input_1253_groups_0"), val = int32(1024)];
            tensor<int32, [1]> input_1253_strides_0 = const()[name = string("input_1253_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1253_pad_0 = const()[name = string("input_1253_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1253_dilations_0 = const()[name = string("input_1253_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_294_to_fp16 = const()[name = string("const_294_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1171193024)))];
            tensor<fp16, [1024]> const_295_to_fp16 = const()[name = string("const_295_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1171211520)))];
            tensor<fp16, [1, 1024, 188]> input_1255_cast_fp16 = conv(bias = const_295_to_fp16, dilations = input_1253_dilations_0, groups = input_1253_groups_0, pad = input_1253_pad_0, pad_type = input_1253_pad_type_0, strides = input_1253_strides_0, weight = const_294_to_fp16, x = input_1251_cast_fp16)[name = string("input_1255_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_1257_cast_fp16 = silu(x = input_1255_cast_fp16)[name = string("input_1257_cast_fp16")];
            string x_527_pad_type_0 = const()[name = string("x_527_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> x_527_strides_0 = const()[name = string("x_527_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_527_pad_0 = const()[name = string("x_527_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_527_dilations_0 = const()[name = string("x_527_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 x_527_groups_0 = const()[name = string("x_527_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 1024, 1]> module_layers_23_conv_pointwise_conv2_weight_to_fp16 = const()[name = string("module_layers_23_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1171213632)))];
            tensor<fp16, [1, 1024, 188]> x_527_cast_fp16 = conv(dilations = x_527_dilations_0, groups = x_527_groups_0, pad = x_527_pad_0, pad_type = x_527_pad_type_0, strides = x_527_strides_0, weight = module_layers_23_conv_pointwise_conv2_weight_to_fp16, x = input_1257_cast_fp16)[name = string("x_527_cast_fp16")];
            tensor<int32, [3]> input_1259_perm_0 = const()[name = string("input_1259_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_1259_cast_fp16 = transpose(perm = input_1259_perm_0, x = x_527_cast_fp16)[name = string("transpose_121")];
            tensor<fp16, [1, 188, 1024]> input_1261_cast_fp16 = add(x = input_1243_cast_fp16, y = input_1259_cast_fp16)[name = string("input_1261_cast_fp16")];
            tensor<int32, [1]> input_1263_axes_0 = const()[name = string("input_1263_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_23_norm_feed_forward2_weight_to_fp16 = const()[name = string("module_layers_23_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1173310848)))];
            tensor<fp16, [1024]> module_layers_23_norm_feed_forward2_bias_to_fp16 = const()[name = string("module_layers_23_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1173312960)))];
            tensor<fp16, [1, 188, 1024]> input_1263_cast_fp16 = layer_norm(axes = input_1263_axes_0, beta = module_layers_23_norm_feed_forward2_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_23_norm_feed_forward2_weight_to_fp16, x = input_1261_cast_fp16)[name = string("input_1263_cast_fp16")];
            tensor<fp16, [4096, 1024]> module_layers_23_feed_forward2_linear1_weight_to_fp16 = const()[name = string("module_layers_23_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1173315072)))];
            tensor<fp16, [1, 188, 4096]> linear_217_cast_fp16 = linear(bias = linear_3_bias_0_to_fp16, weight = module_layers_23_feed_forward2_linear1_weight_to_fp16, x = input_1263_cast_fp16)[name = string("linear_217_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_1267_cast_fp16 = silu(x = linear_217_cast_fp16)[name = string("input_1267_cast_fp16")];
            tensor<fp16, [1024, 4096]> module_layers_23_feed_forward2_linear2_weight_to_fp16 = const()[name = string("module_layers_23_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1181703744)))];
            tensor<fp16, [1, 188, 1024]> linear_218_cast_fp16 = linear(bias = linear_4_bias_0_to_fp16, weight = module_layers_23_feed_forward2_linear2_weight_to_fp16, x = input_1267_cast_fp16)[name = string("linear_218_cast_fp16")];
            fp16 var_4143_to_fp16 = const()[name = string("op_4143_to_fp16"), val = fp16(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_4144_cast_fp16 = mul(x = linear_218_cast_fp16, y = var_4143_to_fp16)[name = string("op_4144_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_cast_fp16 = add(x = input_1261_cast_fp16, y = var_4144_cast_fp16)[name = string("input_cast_fp16")];
            tensor<int32, [1]> audio_signal_axes_0 = const()[name = string("audio_signal_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> module_layers_23_norm_out_weight_to_fp16 = const()[name = string("module_layers_23_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1190092416)))];
            tensor<fp16, [1024]> module_layers_23_norm_out_bias_to_fp16 = const()[name = string("module_layers_23_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(1190094528)))];
            tensor<fp16, [1, 188, 1024]> audio_signal_cast_fp16 = layer_norm(axes = audio_signal_axes_0, beta = module_layers_23_norm_out_bias_to_fp16, epsilon = var_20_to_fp16, gamma = module_layers_23_norm_out_weight_to_fp16, x = input_cast_fp16)[name = string("audio_signal_cast_fp16")];
            tensor<int32, [3]> obj_1_perm_0 = const()[name = string("obj_1_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            string obj_1_cast_fp16_to_fp32_dtype_0 = const()[name = string("obj_1_cast_fp16_to_fp32_dtype_0"), val = string("fp32")];
            tensor<fp16, [1, 1024, 188]> obj_1_cast_fp16 = transpose(perm = obj_1_perm_0, x = audio_signal_cast_fp16)[name = string("transpose_120")];
            tensor<fp32, [1, 1024, 188]> encoder = cast(dtype = obj_1_cast_fp16_to_fp32_dtype_0, x = obj_1_cast_fp16)[name = string("cast_227")];
        } -> (encoder, encoder_length);
}