program(1.3)
[buildInfo = dict<string, string>({{"coremlc-component-MIL", "3600.16.1"}, {"coremlc-version", "3600.25.1"}, {"coremltools-component-milinternal", ""}, {"coremltools-version", "9.0"}})]
{
    func main<ios18>(tensor<fp32, [1, 50, 256]> style_ttl, tensor<int32, [1, ?]> text_ids, tensor<fp32, [1, 1, ?]> text_mask) [FlexibleShapeInformation = tuple<tuple<string, dict<string, tensor<int32, [?]>>>, tuple<string, dict<string, list<tensor<int32, [2]>, ?>>>>((("DefaultShapes", {{"text_ids", [1, 64]}, {"text_mask", [1, 1, 64]}}), ("RangeDims", {{"text_ids", [[1, 1], [8, 1024]]}, {"text_mask", [[1, 1], [1, 1], [8, 1024]]}})))] {
            tensor<fp32, [8322, 256]> const_0 = const()[name = string("const_0"), val = tensor<fp32, [8322, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(64)))];
            int32 gather_0_batch_dims_0 = const()[name = string("gather_0_batch_dims_0"), val = int32(0)];
            bool gather_0_validate_indices_0 = const()[name = string("gather_0_validate_indices_0"), val = bool(false)];
            int32 greater_equal_0_y_0 = const()[name = string("greater_equal_0_y_0"), val = int32(0)];
            tensor<bool, [1, ?]> greater_equal_0 = greater_equal(x = text_ids, y = greater_equal_0_y_0)[name = string("greater_equal_0")];
            int32 slice_by_index_72 = const()[name = string("slice_by_index_72"), val = int32(8322)];
            tensor<int32, [1, ?]> add_49 = add(x = text_ids, y = slice_by_index_72)[name = string("add_49")];
            tensor<int32, [1, ?]> select_6 = select(a = text_ids, b = add_49, cond = greater_equal_0)[name = string("select_6")];
            int32 gather_0_axis_1 = const()[name = string("gather_0_axis_1"), val = int32(0)];
            tensor<fp32, [1, ?, 256]> gather_0 = gather(axis = gather_0_axis_1, batch_dims = gather_0_batch_dims_0, indices = select_6, validate_indices = gather_0_validate_indices_0, x = const_0)[name = string("gather_0")];
            tensor<int32, [3]> transpose_0_perm_0 = const()[name = string("transpose_0_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp32, [256, 256]> transpose_84 = const()[name = string("transpose_84"), val = tensor<fp32, [256, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8521856)))];
            tensor<fp32, [256]> add_0_bias_0 = const()[name = string("add_0_bias_0"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8784064)))];
            tensor<fp32, [1, 50, 256]> add_0 = linear(bias = add_0_bias_0, weight = transpose_84, x = style_ttl)[name = string("add_0")];
            tensor<fp32, [256, 256]> transpose_85 = const()[name = string("transpose_85"), val = tensor<fp32, [256, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8785152)))];
            tensor<fp32, [256]> add_1_bias_0 = const()[name = string("add_1_bias_0"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9047360)))];
            tensor<fp32, [1, 50, 256]> add_1 = linear(bias = add_1_bias_0, weight = transpose_85, x = style_ttl)[name = string("add_1")];
            tensor<int32, [1]> expand_dims_0_axes_0 = const()[name = string("expand_dims_0_axes_0"), val = tensor<int32, [1]>([2])];
            tensor<fp32, [1, 1, 1, ?]> expand_dims_0 = expand_dims(axes = expand_dims_0_axes_0, x = text_mask)[name = string("expand_dims_0")];
            tensor<int32, [1]> expand_dims_1_axes_0 = const()[name = string("expand_dims_1_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp32, [1, 1, ?, 1]> expand_dims_1 = expand_dims(axes = expand_dims_1_axes_0, x = text_mask)[name = string("expand_dims_1")];
            tensor<int32, [3]> transpose_1_perm_0 = const()[name = string("transpose_1_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> expand_dims_2_axes_0 = const()[name = string("expand_dims_2_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp32, [1, ?, 1]> transpose_0 = transpose(perm = transpose_0_perm_0, x = text_mask)[name = string("transpose_137")];
            tensor<fp32, [1, 1, ?, 1]> expand_dims_2 = expand_dims(axes = expand_dims_2_axes_0, x = transpose_0)[name = string("expand_dims_2")];
            tensor<fp32, [1, 1, ?, ?]> mul_0 = mul(x = expand_dims_0, y = expand_dims_1)[name = string("mul_0")];
            tensor<fp32, [1, 256, ?]> transpose_1 = transpose(perm = transpose_1_perm_0, x = gather_0)[name = string("transpose_136")];
            tensor<fp32, [1, 256, ?]> mul_1 = mul(x = transpose_1, y = text_mask)[name = string("mul_1")];
            tensor<int32, [2]> split_0_split_sizes_0 = const()[name = string("split_0_split_sizes_0"), val = tensor<int32, [2]>([128, 128])];
            int32 split_0_axis_0 = const()[name = string("split_0_axis_0"), val = int32(2)];
            tensor<fp32, [1, 50, 128]> split_0_0, tensor<fp32, [1, 50, 128]> split_0_1 = split(axis = split_0_axis_0, split_sizes = split_0_split_sizes_0, x = add_0)[name = string("split_0")];
            fp32 const_5 = const()[name = string("const_5"), val = fp32(0x0p+0)];
            tensor<bool, [1, 1, ?, 1]> equal_0 = equal(x = expand_dims_2, y = const_5)[name = string("equal_0")];
            tensor<int32, [2]> split_1_split_sizes_0 = const()[name = string("split_1_split_sizes_0"), val = tensor<int32, [2]>([128, 128])];
            int32 split_1_axis_0 = const()[name = string("split_1_axis_0"), val = int32(2)];
            tensor<fp32, [1, 50, 128]> split_1_0, tensor<fp32, [1, 50, 128]> split_1_1 = split(axis = split_1_axis_0, split_sizes = split_1_split_sizes_0, x = add_1)[name = string("split_1")];
            fp32 const_6 = const()[name = string("const_6"), val = fp32(0x0p+0)];
            tensor<bool, [1, 1, ?, ?]> equal_1 = equal(x = mul_0, y = const_6)[name = string("equal_1")];
            tensor<fp32, [1, 256, ?]> mul_2 = mul(x = mul_1, y = text_mask)[name = string("mul_2")];
            tensor<int32, [1]> expand_dims_3_axes_0 = const()[name = string("expand_dims_3_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp32, [1, 1, 50, 128]> expand_dims_3 = expand_dims(axes = expand_dims_3_axes_0, x = split_0_0)[name = string("expand_dims_3")];
            tensor<int32, [1]> expand_dims_4_axes_0 = const()[name = string("expand_dims_4_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp32, [1, 1, 50, 128]> expand_dims_4 = expand_dims(axes = expand_dims_4_axes_0, x = split_0_1)[name = string("expand_dims_4")];
            tensor<int32, [1]> expand_dims_5_axes_0 = const()[name = string("expand_dims_5_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp32, [1, 1, 50, 128]> expand_dims_5 = expand_dims(axes = expand_dims_5_axes_0, x = split_1_0)[name = string("expand_dims_5")];
            tensor<int32, [1]> expand_dims_6_axes_0 = const()[name = string("expand_dims_6_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp32, [1, 1, 50, 128]> expand_dims_6 = expand_dims(axes = expand_dims_6_axes_0, x = split_1_1)[name = string("expand_dims_6")];
            int32 concat_0_axis_0 = const()[name = string("concat_0_axis_0"), val = int32(0)];
            bool concat_0_interleave_0 = const()[name = string("concat_0_interleave_0"), val = bool(false)];
            tensor<fp32, [2, 1, 50, 128]> concat_0 = concat(axis = concat_0_axis_0, interleave = concat_0_interleave_0, values = (expand_dims_3, expand_dims_4))[name = string("concat_0")];
            int32 concat_1_axis_0 = const()[name = string("concat_1_axis_0"), val = int32(0)];
            bool concat_1_interleave_0 = const()[name = string("concat_1_interleave_0"), val = bool(false)];
            tensor<fp32, [2, 1, 50, 128]> concat_1 = concat(axis = concat_1_axis_0, interleave = concat_1_interleave_0, values = (expand_dims_5, expand_dims_6))[name = string("concat_1")];
            tensor<int32, [3]> slice_by_index_0_begin_0 = const()[name = string("slice_by_index_0_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_0_end_0 = const()[name = string("slice_by_index_0_end_0"), val = tensor<int32, [3]>([0, 0, 1])];
            tensor<bool, [3]> slice_by_index_0_begin_mask_0 = const()[name = string("slice_by_index_0_begin_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<bool, [3]> slice_by_index_0_end_mask_0 = const()[name = string("slice_by_index_0_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp32, [1, 256, ?]> slice_by_index_0 = slice_by_index(begin = slice_by_index_0_begin_0, begin_mask = slice_by_index_0_begin_mask_0, end = slice_by_index_0_end_0, end_mask = slice_by_index_0_end_mask_0, x = mul_2)[name = string("slice_by_index_0")];
            tensor<int32, [3]> tile_0_reps_0 = const()[name = string("tile_0_reps_0"), val = tensor<int32, [3]>([1, 1, 2])];
            tensor<fp32, [1, 256, ?]> tile_0 = tile(reps = tile_0_reps_0, x = slice_by_index_0)[name = string("tile_0")];
            tensor<int32, [3]> slice_by_index_1_begin_0 = const()[name = string("slice_by_index_1_begin_0"), val = tensor<int32, [3]>([0, 0, -1])];
            tensor<int32, [3]> slice_by_index_1_end_0 = const()[name = string("slice_by_index_1_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_1_begin_mask_0 = const()[name = string("slice_by_index_1_begin_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<bool, [3]> slice_by_index_1_end_mask_0 = const()[name = string("slice_by_index_1_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp32, [1, 256, 1]> slice_by_index_1 = slice_by_index(begin = slice_by_index_1_begin_0, begin_mask = slice_by_index_1_begin_mask_0, end = slice_by_index_1_end_0, end_mask = slice_by_index_1_end_mask_0, x = mul_2)[name = string("slice_by_index_1")];
            tensor<int32, [3]> tile_1_reps_0 = const()[name = string("tile_1_reps_0"), val = tensor<int32, [3]>([1, 1, 2])];
            tensor<fp32, [1, 256, 2]> tile_1 = tile(reps = tile_1_reps_0, x = slice_by_index_1)[name = string("tile_1")];
            int32 concat_2_axis_0 = const()[name = string("concat_2_axis_0"), val = int32(2)];
            bool concat_2_interleave_0 = const()[name = string("concat_2_interleave_0"), val = bool(false)];
            tensor<fp32, [1, 256, ?]> concat_2 = concat(axis = concat_2_axis_0, interleave = concat_2_interleave_0, values = (tile_0, mul_2, tile_1))[name = string("concat_2")];
            tensor<fp32, [256, 1, 5]> const_7 = const()[name = string("const_7"), val = tensor<fp32, [256, 1, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9048448)))];
            tensor<fp32, [256]> const_8 = const()[name = string("const_8"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9053632)))];
            tensor<int32, [1]> conv_0_strides_0 = const()[name = string("conv_0_strides_0"), val = tensor<int32, [1]>([1])];
            string conv_0_pad_type_0 = const()[name = string("conv_0_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> conv_0_pad_0 = const()[name = string("conv_0_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> conv_0_dilations_0 = const()[name = string("conv_0_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 conv_0_groups_0 = const()[name = string("conv_0_groups_0"), val = int32(256)];
            tensor<fp32, [1, 256, ?]> conv_0 = conv(bias = const_8, dilations = conv_0_dilations_0, groups = conv_0_groups_0, pad = conv_0_pad_0, pad_type = conv_0_pad_type_0, strides = conv_0_strides_0, weight = const_7, x = concat_2)[name = string("conv_0")];
            tensor<fp32, [1, 256, ?]> mul_3 = mul(x = conv_0, y = text_mask)[name = string("mul_3")];
            tensor<int32, [3]> transpose_2_perm_0 = const()[name = string("transpose_2_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp32, [256]> const_9 = const()[name = string("const_9"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9054720)))];
            tensor<fp32, [256]> const_10 = const()[name = string("const_10"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9055808)))];
            tensor<int32, [1]> layer_norm_0_axes_0 = const()[name = string("layer_norm_0_axes_0"), val = tensor<int32, [1]>([2])];
            fp32 layer_norm_0_epsilon_0 = const()[name = string("layer_norm_0_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp32, [1, ?, 256]> transpose_2 = transpose(perm = transpose_2_perm_0, x = mul_3)[name = string("transpose_135")];
            tensor<fp32, [1, ?, 256]> layer_norm_0 = layer_norm(axes = layer_norm_0_axes_0, beta = const_10, epsilon = layer_norm_0_epsilon_0, gamma = const_9, x = transpose_2)[name = string("layer_norm_0")];
            tensor<int32, [3]> transpose_3_perm_0 = const()[name = string("transpose_3_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp32, [1024, 256, 1]> const_11 = const()[name = string("const_11"), val = tensor<fp32, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9056896)))];
            tensor<fp32, [1024]> const_12 = const()[name = string("const_12"), val = tensor<fp32, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10105536)))];
            tensor<int32, [1]> conv_1_strides_0 = const()[name = string("conv_1_strides_0"), val = tensor<int32, [1]>([1])];
            string conv_1_pad_type_0 = const()[name = string("conv_1_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> conv_1_pad_0 = const()[name = string("conv_1_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> conv_1_dilations_0 = const()[name = string("conv_1_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 conv_1_groups_0 = const()[name = string("conv_1_groups_0"), val = int32(1)];
            tensor<fp32, [1, 256, ?]> transpose_3 = transpose(perm = transpose_3_perm_0, x = layer_norm_0)[name = string("transpose_134")];
            tensor<fp32, [1, 1024, ?]> conv_1 = conv(bias = const_12, dilations = conv_1_dilations_0, groups = conv_1_groups_0, pad = conv_1_pad_0, pad_type = conv_1_pad_type_0, strides = conv_1_strides_0, weight = const_11, x = transpose_3)[name = string("conv_1")];
            string mul_5_mode_0 = const()[name = string("mul_5_mode_0"), val = string("EXACT")];
            tensor<fp32, [1, 1024, ?]> mul_5 = gelu(mode = mul_5_mode_0, x = conv_1)[name = string("mul_5")];
            tensor<int32, [1]> conv_2_strides_0 = const()[name = string("conv_2_strides_0"), val = tensor<int32, [1]>([1])];
            string conv_2_pad_type_0 = const()[name = string("conv_2_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> conv_2_pad_0 = const()[name = string("conv_2_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> conv_2_dilations_0 = const()[name = string("conv_2_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 conv_2_groups_0 = const()[name = string("conv_2_groups_0"), val = int32(1)];
            tensor<fp32, [256, 1024, 1]> mul_6_weight_0 = const()[name = string("mul_6_weight_0"), val = tensor<fp32, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10109696)))];
            tensor<fp32, [256]> mul_6_bias_0 = const()[name = string("mul_6_bias_0"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11158336)))];
            tensor<fp32, [1, 256, ?]> mul_6 = conv(bias = mul_6_bias_0, dilations = conv_2_dilations_0, groups = conv_2_groups_0, pad = conv_2_pad_0, pad_type = conv_2_pad_type_0, strides = conv_2_strides_0, weight = mul_6_weight_0, x = mul_5)[name = string("mul_6")];
            tensor<fp32, [1, 256, ?]> add_3 = add(x = mul_2, y = mul_6)[name = string("add_3")];
            tensor<fp32, [1, 256, ?]> mul_7 = mul(x = add_3, y = text_mask)[name = string("mul_7")];
            tensor<fp32, [1, 256, ?]> mul_8 = mul(x = mul_7, y = text_mask)[name = string("mul_8")];
            tensor<int32, [3]> slice_by_index_2_begin_0 = const()[name = string("slice_by_index_2_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_2_end_0 = const()[name = string("slice_by_index_2_end_0"), val = tensor<int32, [3]>([0, 0, 1])];
            tensor<bool, [3]> slice_by_index_2_begin_mask_0 = const()[name = string("slice_by_index_2_begin_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<bool, [3]> slice_by_index_2_end_mask_0 = const()[name = string("slice_by_index_2_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp32, [1, 256, ?]> slice_by_index_2 = slice_by_index(begin = slice_by_index_2_begin_0, begin_mask = slice_by_index_2_begin_mask_0, end = slice_by_index_2_end_0, end_mask = slice_by_index_2_end_mask_0, x = mul_8)[name = string("slice_by_index_2")];
            tensor<int32, [3]> tile_2_reps_0 = const()[name = string("tile_2_reps_0"), val = tensor<int32, [3]>([1, 1, 2])];
            tensor<fp32, [1, 256, ?]> tile_2 = tile(reps = tile_2_reps_0, x = slice_by_index_2)[name = string("tile_2")];
            tensor<int32, [3]> slice_by_index_3_begin_0 = const()[name = string("slice_by_index_3_begin_0"), val = tensor<int32, [3]>([0, 0, -1])];
            tensor<int32, [3]> slice_by_index_3_end_0 = const()[name = string("slice_by_index_3_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_3_begin_mask_0 = const()[name = string("slice_by_index_3_begin_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<bool, [3]> slice_by_index_3_end_mask_0 = const()[name = string("slice_by_index_3_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp32, [1, 256, 1]> slice_by_index_3 = slice_by_index(begin = slice_by_index_3_begin_0, begin_mask = slice_by_index_3_begin_mask_0, end = slice_by_index_3_end_0, end_mask = slice_by_index_3_end_mask_0, x = mul_8)[name = string("slice_by_index_3")];
            tensor<int32, [3]> tile_3_reps_0 = const()[name = string("tile_3_reps_0"), val = tensor<int32, [3]>([1, 1, 2])];
            tensor<fp32, [1, 256, 2]> tile_3 = tile(reps = tile_3_reps_0, x = slice_by_index_3)[name = string("tile_3")];
            int32 concat_3_axis_0 = const()[name = string("concat_3_axis_0"), val = int32(2)];
            bool concat_3_interleave_0 = const()[name = string("concat_3_interleave_0"), val = bool(false)];
            tensor<fp32, [1, 256, ?]> concat_3 = concat(axis = concat_3_axis_0, interleave = concat_3_interleave_0, values = (tile_2, mul_8, tile_3))[name = string("concat_3")];
            tensor<fp32, [256, 1, 5]> const_19 = const()[name = string("const_19"), val = tensor<fp32, [256, 1, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11159424)))];
            tensor<fp32, [256]> const_20 = const()[name = string("const_20"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11164608)))];
            tensor<int32, [1]> conv_3_strides_0 = const()[name = string("conv_3_strides_0"), val = tensor<int32, [1]>([1])];
            string conv_3_pad_type_0 = const()[name = string("conv_3_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> conv_3_pad_0 = const()[name = string("conv_3_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> conv_3_dilations_0 = const()[name = string("conv_3_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 conv_3_groups_0 = const()[name = string("conv_3_groups_0"), val = int32(256)];
            tensor<fp32, [1, 256, ?]> conv_3 = conv(bias = const_20, dilations = conv_3_dilations_0, groups = conv_3_groups_0, pad = conv_3_pad_0, pad_type = conv_3_pad_type_0, strides = conv_3_strides_0, weight = const_19, x = concat_3)[name = string("conv_3")];
            tensor<fp32, [1, 256, ?]> mul_9 = mul(x = conv_3, y = text_mask)[name = string("mul_9")];
            tensor<int32, [3]> transpose_4_perm_0 = const()[name = string("transpose_4_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp32, [256]> const_21 = const()[name = string("const_21"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11165696)))];
            tensor<fp32, [256]> const_22 = const()[name = string("const_22"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11166784)))];
            tensor<int32, [1]> layer_norm_1_axes_0 = const()[name = string("layer_norm_1_axes_0"), val = tensor<int32, [1]>([2])];
            fp32 layer_norm_1_epsilon_0 = const()[name = string("layer_norm_1_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp32, [1, ?, 256]> transpose_4 = transpose(perm = transpose_4_perm_0, x = mul_9)[name = string("transpose_133")];
            tensor<fp32, [1, ?, 256]> layer_norm_1 = layer_norm(axes = layer_norm_1_axes_0, beta = const_22, epsilon = layer_norm_1_epsilon_0, gamma = const_21, x = transpose_4)[name = string("layer_norm_1")];
            tensor<int32, [3]> transpose_5_perm_0 = const()[name = string("transpose_5_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp32, [1024, 256, 1]> const_23 = const()[name = string("const_23"), val = tensor<fp32, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11167872)))];
            tensor<fp32, [1024]> const_24 = const()[name = string("const_24"), val = tensor<fp32, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12216512)))];
            tensor<int32, [1]> conv_4_strides_0 = const()[name = string("conv_4_strides_0"), val = tensor<int32, [1]>([1])];
            string conv_4_pad_type_0 = const()[name = string("conv_4_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> conv_4_pad_0 = const()[name = string("conv_4_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> conv_4_dilations_0 = const()[name = string("conv_4_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 conv_4_groups_0 = const()[name = string("conv_4_groups_0"), val = int32(1)];
            tensor<fp32, [1, 256, ?]> transpose_5 = transpose(perm = transpose_5_perm_0, x = layer_norm_1)[name = string("transpose_132")];
            tensor<fp32, [1, 1024, ?]> conv_4 = conv(bias = const_24, dilations = conv_4_dilations_0, groups = conv_4_groups_0, pad = conv_4_pad_0, pad_type = conv_4_pad_type_0, strides = conv_4_strides_0, weight = const_23, x = transpose_5)[name = string("conv_4")];
            string mul_11_mode_0 = const()[name = string("mul_11_mode_0"), val = string("EXACT")];
            tensor<fp32, [1, 1024, ?]> mul_11 = gelu(mode = mul_11_mode_0, x = conv_4)[name = string("mul_11")];
            tensor<int32, [1]> conv_5_strides_0 = const()[name = string("conv_5_strides_0"), val = tensor<int32, [1]>([1])];
            string conv_5_pad_type_0 = const()[name = string("conv_5_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> conv_5_pad_0 = const()[name = string("conv_5_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> conv_5_dilations_0 = const()[name = string("conv_5_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 conv_5_groups_0 = const()[name = string("conv_5_groups_0"), val = int32(1)];
            tensor<fp32, [256, 1024, 1]> mul_12_weight_0 = const()[name = string("mul_12_weight_0"), val = tensor<fp32, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12220672)))];
            tensor<fp32, [256]> mul_12_bias_0 = const()[name = string("mul_12_bias_0"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13269312)))];
            tensor<fp32, [1, 256, ?]> mul_12 = conv(bias = mul_12_bias_0, dilations = conv_5_dilations_0, groups = conv_5_groups_0, pad = conv_5_pad_0, pad_type = conv_5_pad_type_0, strides = conv_5_strides_0, weight = mul_12_weight_0, x = mul_11)[name = string("mul_12")];
            tensor<fp32, [1, 256, ?]> add_5 = add(x = mul_8, y = mul_12)[name = string("add_5")];
            tensor<fp32, [1, 256, ?]> mul_13 = mul(x = add_5, y = text_mask)[name = string("mul_13")];
            tensor<fp32, [1, 256, ?]> mul_14 = mul(x = mul_13, y = text_mask)[name = string("mul_14")];
            tensor<int32, [3]> slice_by_index_4_begin_0 = const()[name = string("slice_by_index_4_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_4_end_0 = const()[name = string("slice_by_index_4_end_0"), val = tensor<int32, [3]>([0, 0, 1])];
            tensor<bool, [3]> slice_by_index_4_begin_mask_0 = const()[name = string("slice_by_index_4_begin_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<bool, [3]> slice_by_index_4_end_mask_0 = const()[name = string("slice_by_index_4_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp32, [1, 256, ?]> slice_by_index_4 = slice_by_index(begin = slice_by_index_4_begin_0, begin_mask = slice_by_index_4_begin_mask_0, end = slice_by_index_4_end_0, end_mask = slice_by_index_4_end_mask_0, x = mul_14)[name = string("slice_by_index_4")];
            tensor<int32, [3]> tile_4_reps_0 = const()[name = string("tile_4_reps_0"), val = tensor<int32, [3]>([1, 1, 4])];
            tensor<fp32, [1, 256, ?]> tile_4 = tile(reps = tile_4_reps_0, x = slice_by_index_4)[name = string("tile_4")];
            tensor<int32, [3]> slice_by_index_5_begin_0 = const()[name = string("slice_by_index_5_begin_0"), val = tensor<int32, [3]>([0, 0, -1])];
            tensor<int32, [3]> slice_by_index_5_end_0 = const()[name = string("slice_by_index_5_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_5_begin_mask_0 = const()[name = string("slice_by_index_5_begin_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<bool, [3]> slice_by_index_5_end_mask_0 = const()[name = string("slice_by_index_5_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp32, [1, 256, 1]> slice_by_index_5 = slice_by_index(begin = slice_by_index_5_begin_0, begin_mask = slice_by_index_5_begin_mask_0, end = slice_by_index_5_end_0, end_mask = slice_by_index_5_end_mask_0, x = mul_14)[name = string("slice_by_index_5")];
            tensor<int32, [3]> tile_5_reps_0 = const()[name = string("tile_5_reps_0"), val = tensor<int32, [3]>([1, 1, 4])];
            tensor<fp32, [1, 256, 4]> tile_5 = tile(reps = tile_5_reps_0, x = slice_by_index_5)[name = string("tile_5")];
            int32 concat_4_axis_0 = const()[name = string("concat_4_axis_0"), val = int32(2)];
            bool concat_4_interleave_0 = const()[name = string("concat_4_interleave_0"), val = bool(false)];
            tensor<fp32, [1, 256, ?]> concat_4 = concat(axis = concat_4_axis_0, interleave = concat_4_interleave_0, values = (tile_4, mul_14, tile_5))[name = string("concat_4")];
            tensor<fp32, [256, 1, 5]> const_31 = const()[name = string("const_31"), val = tensor<fp32, [256, 1, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13270400)))];
            tensor<fp32, [256]> const_32 = const()[name = string("const_32"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13275584)))];
            tensor<int32, [1]> conv_6_strides_0 = const()[name = string("conv_6_strides_0"), val = tensor<int32, [1]>([1])];
            string conv_6_pad_type_0 = const()[name = string("conv_6_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> conv_6_pad_0 = const()[name = string("conv_6_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> conv_6_dilations_0 = const()[name = string("conv_6_dilations_0"), val = tensor<int32, [1]>([2])];
            int32 conv_6_groups_0 = const()[name = string("conv_6_groups_0"), val = int32(256)];
            tensor<fp32, [1, 256, ?]> conv_6 = conv(bias = const_32, dilations = conv_6_dilations_0, groups = conv_6_groups_0, pad = conv_6_pad_0, pad_type = conv_6_pad_type_0, strides = conv_6_strides_0, weight = const_31, x = concat_4)[name = string("conv_6")];
            tensor<fp32, [1, 256, ?]> mul_15 = mul(x = conv_6, y = text_mask)[name = string("mul_15")];
            tensor<int32, [3]> transpose_6_perm_0 = const()[name = string("transpose_6_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp32, [256]> const_33 = const()[name = string("const_33"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13276672)))];
            tensor<fp32, [256]> const_34 = const()[name = string("const_34"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13277760)))];
            tensor<int32, [1]> layer_norm_2_axes_0 = const()[name = string("layer_norm_2_axes_0"), val = tensor<int32, [1]>([2])];
            fp32 layer_norm_2_epsilon_0 = const()[name = string("layer_norm_2_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp32, [1, ?, 256]> transpose_6 = transpose(perm = transpose_6_perm_0, x = mul_15)[name = string("transpose_131")];
            tensor<fp32, [1, ?, 256]> layer_norm_2 = layer_norm(axes = layer_norm_2_axes_0, beta = const_34, epsilon = layer_norm_2_epsilon_0, gamma = const_33, x = transpose_6)[name = string("layer_norm_2")];
            tensor<int32, [3]> transpose_7_perm_0 = const()[name = string("transpose_7_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp32, [1024, 256, 1]> const_35 = const()[name = string("const_35"), val = tensor<fp32, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13278848)))];
            tensor<fp32, [1024]> const_36 = const()[name = string("const_36"), val = tensor<fp32, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14327488)))];
            tensor<int32, [1]> conv_7_strides_0 = const()[name = string("conv_7_strides_0"), val = tensor<int32, [1]>([1])];
            string conv_7_pad_type_0 = const()[name = string("conv_7_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> conv_7_pad_0 = const()[name = string("conv_7_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> conv_7_dilations_0 = const()[name = string("conv_7_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 conv_7_groups_0 = const()[name = string("conv_7_groups_0"), val = int32(1)];
            tensor<fp32, [1, 256, ?]> transpose_7 = transpose(perm = transpose_7_perm_0, x = layer_norm_2)[name = string("transpose_130")];
            tensor<fp32, [1, 1024, ?]> conv_7 = conv(bias = const_36, dilations = conv_7_dilations_0, groups = conv_7_groups_0, pad = conv_7_pad_0, pad_type = conv_7_pad_type_0, strides = conv_7_strides_0, weight = const_35, x = transpose_7)[name = string("conv_7")];
            string mul_17_mode_0 = const()[name = string("mul_17_mode_0"), val = string("EXACT")];
            tensor<fp32, [1, 1024, ?]> mul_17 = gelu(mode = mul_17_mode_0, x = conv_7)[name = string("mul_17")];
            tensor<int32, [1]> conv_8_strides_0 = const()[name = string("conv_8_strides_0"), val = tensor<int32, [1]>([1])];
            string conv_8_pad_type_0 = const()[name = string("conv_8_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> conv_8_pad_0 = const()[name = string("conv_8_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> conv_8_dilations_0 = const()[name = string("conv_8_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 conv_8_groups_0 = const()[name = string("conv_8_groups_0"), val = int32(1)];
            tensor<fp32, [256, 1024, 1]> mul_18_weight_0 = const()[name = string("mul_18_weight_0"), val = tensor<fp32, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14331648)))];
            tensor<fp32, [256]> mul_18_bias_0 = const()[name = string("mul_18_bias_0"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15380288)))];
            tensor<fp32, [1, 256, ?]> mul_18 = conv(bias = mul_18_bias_0, dilations = conv_8_dilations_0, groups = conv_8_groups_0, pad = conv_8_pad_0, pad_type = conv_8_pad_type_0, strides = conv_8_strides_0, weight = mul_18_weight_0, x = mul_17)[name = string("mul_18")];
            tensor<fp32, [1, 256, ?]> add_7 = add(x = mul_14, y = mul_18)[name = string("add_7")];
            tensor<fp32, [1, 256, ?]> mul_19 = mul(x = add_7, y = text_mask)[name = string("mul_19")];
            tensor<fp32, [1, 256, ?]> mul_20 = mul(x = mul_19, y = text_mask)[name = string("mul_20")];
            tensor<int32, [3]> slice_by_index_6_begin_0 = const()[name = string("slice_by_index_6_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_6_end_0 = const()[name = string("slice_by_index_6_end_0"), val = tensor<int32, [3]>([0, 0, 1])];
            tensor<bool, [3]> slice_by_index_6_begin_mask_0 = const()[name = string("slice_by_index_6_begin_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<bool, [3]> slice_by_index_6_end_mask_0 = const()[name = string("slice_by_index_6_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp32, [1, 256, ?]> slice_by_index_6 = slice_by_index(begin = slice_by_index_6_begin_0, begin_mask = slice_by_index_6_begin_mask_0, end = slice_by_index_6_end_0, end_mask = slice_by_index_6_end_mask_0, x = mul_20)[name = string("slice_by_index_6")];
            tensor<int32, [3]> tile_6_reps_0 = const()[name = string("tile_6_reps_0"), val = tensor<int32, [3]>([1, 1, 4])];
            tensor<fp32, [1, 256, ?]> tile_6 = tile(reps = tile_6_reps_0, x = slice_by_index_6)[name = string("tile_6")];
            tensor<int32, [3]> slice_by_index_7_begin_0 = const()[name = string("slice_by_index_7_begin_0"), val = tensor<int32, [3]>([0, 0, -1])];
            tensor<int32, [3]> slice_by_index_7_end_0 = const()[name = string("slice_by_index_7_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_7_begin_mask_0 = const()[name = string("slice_by_index_7_begin_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<bool, [3]> slice_by_index_7_end_mask_0 = const()[name = string("slice_by_index_7_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp32, [1, 256, 1]> slice_by_index_7 = slice_by_index(begin = slice_by_index_7_begin_0, begin_mask = slice_by_index_7_begin_mask_0, end = slice_by_index_7_end_0, end_mask = slice_by_index_7_end_mask_0, x = mul_20)[name = string("slice_by_index_7")];
            tensor<int32, [3]> tile_7_reps_0 = const()[name = string("tile_7_reps_0"), val = tensor<int32, [3]>([1, 1, 4])];
            tensor<fp32, [1, 256, 4]> tile_7 = tile(reps = tile_7_reps_0, x = slice_by_index_7)[name = string("tile_7")];
            int32 concat_5_axis_0 = const()[name = string("concat_5_axis_0"), val = int32(2)];
            bool concat_5_interleave_0 = const()[name = string("concat_5_interleave_0"), val = bool(false)];
            tensor<fp32, [1, 256, ?]> concat_5 = concat(axis = concat_5_axis_0, interleave = concat_5_interleave_0, values = (tile_6, mul_20, tile_7))[name = string("concat_5")];
            tensor<fp32, [256, 1, 5]> const_43 = const()[name = string("const_43"), val = tensor<fp32, [256, 1, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15381376)))];
            tensor<fp32, [256]> const_44 = const()[name = string("const_44"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15386560)))];
            tensor<int32, [1]> conv_9_strides_0 = const()[name = string("conv_9_strides_0"), val = tensor<int32, [1]>([1])];
            string conv_9_pad_type_0 = const()[name = string("conv_9_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> conv_9_pad_0 = const()[name = string("conv_9_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> conv_9_dilations_0 = const()[name = string("conv_9_dilations_0"), val = tensor<int32, [1]>([2])];
            int32 conv_9_groups_0 = const()[name = string("conv_9_groups_0"), val = int32(256)];
            tensor<fp32, [1, 256, ?]> conv_9 = conv(bias = const_44, dilations = conv_9_dilations_0, groups = conv_9_groups_0, pad = conv_9_pad_0, pad_type = conv_9_pad_type_0, strides = conv_9_strides_0, weight = const_43, x = concat_5)[name = string("conv_9")];
            tensor<fp32, [1, 256, ?]> mul_21 = mul(x = conv_9, y = text_mask)[name = string("mul_21")];
            tensor<int32, [3]> transpose_8_perm_0 = const()[name = string("transpose_8_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp32, [256]> const_45 = const()[name = string("const_45"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15387648)))];
            tensor<fp32, [256]> const_46 = const()[name = string("const_46"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15388736)))];
            tensor<int32, [1]> layer_norm_3_axes_0 = const()[name = string("layer_norm_3_axes_0"), val = tensor<int32, [1]>([2])];
            fp32 layer_norm_3_epsilon_0 = const()[name = string("layer_norm_3_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp32, [1, ?, 256]> transpose_8 = transpose(perm = transpose_8_perm_0, x = mul_21)[name = string("transpose_129")];
            tensor<fp32, [1, ?, 256]> layer_norm_3 = layer_norm(axes = layer_norm_3_axes_0, beta = const_46, epsilon = layer_norm_3_epsilon_0, gamma = const_45, x = transpose_8)[name = string("layer_norm_3")];
            tensor<int32, [3]> transpose_9_perm_0 = const()[name = string("transpose_9_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp32, [1024, 256, 1]> const_47 = const()[name = string("const_47"), val = tensor<fp32, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15389824)))];
            tensor<fp32, [1024]> const_48 = const()[name = string("const_48"), val = tensor<fp32, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16438464)))];
            tensor<int32, [1]> conv_10_strides_0 = const()[name = string("conv_10_strides_0"), val = tensor<int32, [1]>([1])];
            string conv_10_pad_type_0 = const()[name = string("conv_10_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> conv_10_pad_0 = const()[name = string("conv_10_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> conv_10_dilations_0 = const()[name = string("conv_10_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 conv_10_groups_0 = const()[name = string("conv_10_groups_0"), val = int32(1)];
            tensor<fp32, [1, 256, ?]> transpose_9 = transpose(perm = transpose_9_perm_0, x = layer_norm_3)[name = string("transpose_128")];
            tensor<fp32, [1, 1024, ?]> conv_10 = conv(bias = const_48, dilations = conv_10_dilations_0, groups = conv_10_groups_0, pad = conv_10_pad_0, pad_type = conv_10_pad_type_0, strides = conv_10_strides_0, weight = const_47, x = transpose_9)[name = string("conv_10")];
            string mul_23_mode_0 = const()[name = string("mul_23_mode_0"), val = string("EXACT")];
            tensor<fp32, [1, 1024, ?]> mul_23 = gelu(mode = mul_23_mode_0, x = conv_10)[name = string("mul_23")];
            tensor<int32, [1]> conv_11_strides_0 = const()[name = string("conv_11_strides_0"), val = tensor<int32, [1]>([1])];
            string conv_11_pad_type_0 = const()[name = string("conv_11_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> conv_11_pad_0 = const()[name = string("conv_11_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> conv_11_dilations_0 = const()[name = string("conv_11_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 conv_11_groups_0 = const()[name = string("conv_11_groups_0"), val = int32(1)];
            tensor<fp32, [256, 1024, 1]> mul_24_weight_0 = const()[name = string("mul_24_weight_0"), val = tensor<fp32, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16442624)))];
            tensor<fp32, [256]> mul_24_bias_0 = const()[name = string("mul_24_bias_0"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17491264)))];
            tensor<fp32, [1, 256, ?]> mul_24 = conv(bias = mul_24_bias_0, dilations = conv_11_dilations_0, groups = conv_11_groups_0, pad = conv_11_pad_0, pad_type = conv_11_pad_type_0, strides = conv_11_strides_0, weight = mul_24_weight_0, x = mul_23)[name = string("mul_24")];
            tensor<fp32, [1, 256, ?]> add_9 = add(x = mul_20, y = mul_24)[name = string("add_9")];
            tensor<fp32, [1, 256, ?]> mul_25 = mul(x = add_9, y = text_mask)[name = string("mul_25")];
            tensor<fp32, [1, 256, ?]> mul_26 = mul(x = mul_25, y = text_mask)[name = string("mul_26")];
            tensor<int32, [3]> slice_by_index_8_begin_0 = const()[name = string("slice_by_index_8_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_8_end_0 = const()[name = string("slice_by_index_8_end_0"), val = tensor<int32, [3]>([0, 0, 1])];
            tensor<bool, [3]> slice_by_index_8_begin_mask_0 = const()[name = string("slice_by_index_8_begin_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<bool, [3]> slice_by_index_8_end_mask_0 = const()[name = string("slice_by_index_8_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp32, [1, 256, ?]> slice_by_index_8 = slice_by_index(begin = slice_by_index_8_begin_0, begin_mask = slice_by_index_8_begin_mask_0, end = slice_by_index_8_end_0, end_mask = slice_by_index_8_end_mask_0, x = mul_26)[name = string("slice_by_index_8")];
            tensor<int32, [3]> tile_8_reps_0 = const()[name = string("tile_8_reps_0"), val = tensor<int32, [3]>([1, 1, 8])];
            tensor<fp32, [1, 256, ?]> tile_8 = tile(reps = tile_8_reps_0, x = slice_by_index_8)[name = string("tile_8")];
            tensor<int32, [3]> slice_by_index_9_begin_0 = const()[name = string("slice_by_index_9_begin_0"), val = tensor<int32, [3]>([0, 0, -1])];
            tensor<int32, [3]> slice_by_index_9_end_0 = const()[name = string("slice_by_index_9_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_9_begin_mask_0 = const()[name = string("slice_by_index_9_begin_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<bool, [3]> slice_by_index_9_end_mask_0 = const()[name = string("slice_by_index_9_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp32, [1, 256, 1]> slice_by_index_9 = slice_by_index(begin = slice_by_index_9_begin_0, begin_mask = slice_by_index_9_begin_mask_0, end = slice_by_index_9_end_0, end_mask = slice_by_index_9_end_mask_0, x = mul_26)[name = string("slice_by_index_9")];
            tensor<int32, [3]> tile_9_reps_0 = const()[name = string("tile_9_reps_0"), val = tensor<int32, [3]>([1, 1, 8])];
            tensor<fp32, [1, 256, 8]> tile_9 = tile(reps = tile_9_reps_0, x = slice_by_index_9)[name = string("tile_9")];
            int32 concat_6_axis_0 = const()[name = string("concat_6_axis_0"), val = int32(2)];
            bool concat_6_interleave_0 = const()[name = string("concat_6_interleave_0"), val = bool(false)];
            tensor<fp32, [1, 256, ?]> concat_6 = concat(axis = concat_6_axis_0, interleave = concat_6_interleave_0, values = (tile_8, mul_26, tile_9))[name = string("concat_6")];
            tensor<fp32, [256, 1, 5]> const_55 = const()[name = string("const_55"), val = tensor<fp32, [256, 1, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17492352)))];
            tensor<fp32, [256]> const_56 = const()[name = string("const_56"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17497536)))];
            tensor<int32, [1]> conv_12_strides_0 = const()[name = string("conv_12_strides_0"), val = tensor<int32, [1]>([1])];
            string conv_12_pad_type_0 = const()[name = string("conv_12_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> conv_12_pad_0 = const()[name = string("conv_12_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> conv_12_dilations_0 = const()[name = string("conv_12_dilations_0"), val = tensor<int32, [1]>([4])];
            int32 conv_12_groups_0 = const()[name = string("conv_12_groups_0"), val = int32(256)];
            tensor<fp32, [1, 256, ?]> conv_12 = conv(bias = const_56, dilations = conv_12_dilations_0, groups = conv_12_groups_0, pad = conv_12_pad_0, pad_type = conv_12_pad_type_0, strides = conv_12_strides_0, weight = const_55, x = concat_6)[name = string("conv_12")];
            tensor<fp32, [1, 256, ?]> mul_27 = mul(x = conv_12, y = text_mask)[name = string("mul_27")];
            tensor<int32, [3]> transpose_10_perm_0 = const()[name = string("transpose_10_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp32, [256]> const_57 = const()[name = string("const_57"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17498624)))];
            tensor<fp32, [256]> const_58 = const()[name = string("const_58"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17499712)))];
            tensor<int32, [1]> layer_norm_4_axes_0 = const()[name = string("layer_norm_4_axes_0"), val = tensor<int32, [1]>([2])];
            fp32 layer_norm_4_epsilon_0 = const()[name = string("layer_norm_4_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp32, [1, ?, 256]> transpose_10 = transpose(perm = transpose_10_perm_0, x = mul_27)[name = string("transpose_127")];
            tensor<fp32, [1, ?, 256]> layer_norm_4 = layer_norm(axes = layer_norm_4_axes_0, beta = const_58, epsilon = layer_norm_4_epsilon_0, gamma = const_57, x = transpose_10)[name = string("layer_norm_4")];
            tensor<int32, [3]> transpose_11_perm_0 = const()[name = string("transpose_11_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp32, [1024, 256, 1]> const_59 = const()[name = string("const_59"), val = tensor<fp32, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17500800)))];
            tensor<fp32, [1024]> const_60 = const()[name = string("const_60"), val = tensor<fp32, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(18549440)))];
            tensor<int32, [1]> conv_13_strides_0 = const()[name = string("conv_13_strides_0"), val = tensor<int32, [1]>([1])];
            string conv_13_pad_type_0 = const()[name = string("conv_13_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> conv_13_pad_0 = const()[name = string("conv_13_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> conv_13_dilations_0 = const()[name = string("conv_13_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 conv_13_groups_0 = const()[name = string("conv_13_groups_0"), val = int32(1)];
            tensor<fp32, [1, 256, ?]> transpose_11 = transpose(perm = transpose_11_perm_0, x = layer_norm_4)[name = string("transpose_126")];
            tensor<fp32, [1, 1024, ?]> conv_13 = conv(bias = const_60, dilations = conv_13_dilations_0, groups = conv_13_groups_0, pad = conv_13_pad_0, pad_type = conv_13_pad_type_0, strides = conv_13_strides_0, weight = const_59, x = transpose_11)[name = string("conv_13")];
            string mul_29_mode_0 = const()[name = string("mul_29_mode_0"), val = string("EXACT")];
            tensor<fp32, [1, 1024, ?]> mul_29 = gelu(mode = mul_29_mode_0, x = conv_13)[name = string("mul_29")];
            tensor<int32, [1]> conv_14_strides_0 = const()[name = string("conv_14_strides_0"), val = tensor<int32, [1]>([1])];
            string conv_14_pad_type_0 = const()[name = string("conv_14_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> conv_14_pad_0 = const()[name = string("conv_14_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> conv_14_dilations_0 = const()[name = string("conv_14_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 conv_14_groups_0 = const()[name = string("conv_14_groups_0"), val = int32(1)];
            tensor<fp32, [256, 1024, 1]> mul_30_weight_0 = const()[name = string("mul_30_weight_0"), val = tensor<fp32, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(18553600)))];
            tensor<fp32, [256]> mul_30_bias_0 = const()[name = string("mul_30_bias_0"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(19602240)))];
            tensor<fp32, [1, 256, ?]> mul_30 = conv(bias = mul_30_bias_0, dilations = conv_14_dilations_0, groups = conv_14_groups_0, pad = conv_14_pad_0, pad_type = conv_14_pad_type_0, strides = conv_14_strides_0, weight = mul_30_weight_0, x = mul_29)[name = string("mul_30")];
            tensor<fp32, [1, 256, ?]> add_11 = add(x = mul_26, y = mul_30)[name = string("add_11")];
            tensor<fp32, [1, 256, ?]> mul_31 = mul(x = add_11, y = text_mask)[name = string("mul_31")];
            tensor<fp32, [1, 256, ?]> mul_32 = mul(x = mul_31, y = text_mask)[name = string("mul_32")];
            tensor<int32, [3]> slice_by_index_10_begin_0 = const()[name = string("slice_by_index_10_begin_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<int32, [3]> slice_by_index_10_end_0 = const()[name = string("slice_by_index_10_end_0"), val = tensor<int32, [3]>([0, 0, 1])];
            tensor<bool, [3]> slice_by_index_10_begin_mask_0 = const()[name = string("slice_by_index_10_begin_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<bool, [3]> slice_by_index_10_end_mask_0 = const()[name = string("slice_by_index_10_end_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<fp32, [1, 256, ?]> slice_by_index_10 = slice_by_index(begin = slice_by_index_10_begin_0, begin_mask = slice_by_index_10_begin_mask_0, end = slice_by_index_10_end_0, end_mask = slice_by_index_10_end_mask_0, x = mul_32)[name = string("slice_by_index_10")];
            tensor<int32, [3]> tile_10_reps_0 = const()[name = string("tile_10_reps_0"), val = tensor<int32, [3]>([1, 1, 8])];
            tensor<fp32, [1, 256, ?]> tile_10 = tile(reps = tile_10_reps_0, x = slice_by_index_10)[name = string("tile_10")];
            tensor<int32, [3]> slice_by_index_11_begin_0 = const()[name = string("slice_by_index_11_begin_0"), val = tensor<int32, [3]>([0, 0, -1])];
            tensor<int32, [3]> slice_by_index_11_end_0 = const()[name = string("slice_by_index_11_end_0"), val = tensor<int32, [3]>([0, 0, 0])];
            tensor<bool, [3]> slice_by_index_11_begin_mask_0 = const()[name = string("slice_by_index_11_begin_mask_0"), val = tensor<bool, [3]>([true, true, false])];
            tensor<bool, [3]> slice_by_index_11_end_mask_0 = const()[name = string("slice_by_index_11_end_mask_0"), val = tensor<bool, [3]>([true, true, true])];
            tensor<fp32, [1, 256, 1]> slice_by_index_11 = slice_by_index(begin = slice_by_index_11_begin_0, begin_mask = slice_by_index_11_begin_mask_0, end = slice_by_index_11_end_0, end_mask = slice_by_index_11_end_mask_0, x = mul_32)[name = string("slice_by_index_11")];
            tensor<int32, [3]> tile_11_reps_0 = const()[name = string("tile_11_reps_0"), val = tensor<int32, [3]>([1, 1, 8])];
            tensor<fp32, [1, 256, 8]> tile_11 = tile(reps = tile_11_reps_0, x = slice_by_index_11)[name = string("tile_11")];
            int32 concat_7_axis_0 = const()[name = string("concat_7_axis_0"), val = int32(2)];
            bool concat_7_interleave_0 = const()[name = string("concat_7_interleave_0"), val = bool(false)];
            tensor<fp32, [1, 256, ?]> concat_7 = concat(axis = concat_7_axis_0, interleave = concat_7_interleave_0, values = (tile_10, mul_32, tile_11))[name = string("concat_7")];
            tensor<fp32, [256, 1, 5]> const_67 = const()[name = string("const_67"), val = tensor<fp32, [256, 1, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(19603328)))];
            tensor<fp32, [256]> const_68 = const()[name = string("const_68"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(19608512)))];
            tensor<int32, [1]> conv_15_strides_0 = const()[name = string("conv_15_strides_0"), val = tensor<int32, [1]>([1])];
            string conv_15_pad_type_0 = const()[name = string("conv_15_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> conv_15_pad_0 = const()[name = string("conv_15_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> conv_15_dilations_0 = const()[name = string("conv_15_dilations_0"), val = tensor<int32, [1]>([4])];
            int32 conv_15_groups_0 = const()[name = string("conv_15_groups_0"), val = int32(256)];
            tensor<fp32, [1, 256, ?]> conv_15 = conv(bias = const_68, dilations = conv_15_dilations_0, groups = conv_15_groups_0, pad = conv_15_pad_0, pad_type = conv_15_pad_type_0, strides = conv_15_strides_0, weight = const_67, x = concat_7)[name = string("conv_15")];
            tensor<fp32, [1, 256, ?]> mul_33 = mul(x = conv_15, y = text_mask)[name = string("mul_33")];
            tensor<int32, [3]> transpose_12_perm_0 = const()[name = string("transpose_12_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp32, [256]> const_69 = const()[name = string("const_69"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(19609600)))];
            tensor<fp32, [256]> const_70 = const()[name = string("const_70"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(19610688)))];
            tensor<int32, [1]> layer_norm_5_axes_0 = const()[name = string("layer_norm_5_axes_0"), val = tensor<int32, [1]>([2])];
            fp32 layer_norm_5_epsilon_0 = const()[name = string("layer_norm_5_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp32, [1, ?, 256]> transpose_12 = transpose(perm = transpose_12_perm_0, x = mul_33)[name = string("transpose_125")];
            tensor<fp32, [1, ?, 256]> layer_norm_5 = layer_norm(axes = layer_norm_5_axes_0, beta = const_70, epsilon = layer_norm_5_epsilon_0, gamma = const_69, x = transpose_12)[name = string("layer_norm_5")];
            tensor<int32, [3]> transpose_13_perm_0 = const()[name = string("transpose_13_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp32, [1024, 256, 1]> const_71 = const()[name = string("const_71"), val = tensor<fp32, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(19611776)))];
            tensor<fp32, [1024]> const_72 = const()[name = string("const_72"), val = tensor<fp32, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(20660416)))];
            tensor<int32, [1]> conv_16_strides_0 = const()[name = string("conv_16_strides_0"), val = tensor<int32, [1]>([1])];
            string conv_16_pad_type_0 = const()[name = string("conv_16_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> conv_16_pad_0 = const()[name = string("conv_16_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> conv_16_dilations_0 = const()[name = string("conv_16_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 conv_16_groups_0 = const()[name = string("conv_16_groups_0"), val = int32(1)];
            tensor<fp32, [1, 256, ?]> transpose_13 = transpose(perm = transpose_13_perm_0, x = layer_norm_5)[name = string("transpose_124")];
            tensor<fp32, [1, 1024, ?]> conv_16 = conv(bias = const_72, dilations = conv_16_dilations_0, groups = conv_16_groups_0, pad = conv_16_pad_0, pad_type = conv_16_pad_type_0, strides = conv_16_strides_0, weight = const_71, x = transpose_13)[name = string("conv_16")];
            string mul_35_mode_0 = const()[name = string("mul_35_mode_0"), val = string("EXACT")];
            tensor<fp32, [1, 1024, ?]> mul_35 = gelu(mode = mul_35_mode_0, x = conv_16)[name = string("mul_35")];
            tensor<int32, [1]> conv_17_strides_0 = const()[name = string("conv_17_strides_0"), val = tensor<int32, [1]>([1])];
            string conv_17_pad_type_0 = const()[name = string("conv_17_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> conv_17_pad_0 = const()[name = string("conv_17_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> conv_17_dilations_0 = const()[name = string("conv_17_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 conv_17_groups_0 = const()[name = string("conv_17_groups_0"), val = int32(1)];
            tensor<fp32, [256, 1024, 1]> mul_36_weight_0 = const()[name = string("mul_36_weight_0"), val = tensor<fp32, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(20664576)))];
            tensor<fp32, [256]> mul_36_bias_0 = const()[name = string("mul_36_bias_0"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21713216)))];
            tensor<fp32, [1, 256, ?]> mul_36 = conv(bias = mul_36_bias_0, dilations = conv_17_dilations_0, groups = conv_17_groups_0, pad = conv_17_pad_0, pad_type = conv_17_pad_type_0, strides = conv_17_strides_0, weight = mul_36_weight_0, x = mul_35)[name = string("mul_36")];
            tensor<fp32, [1, 256, ?]> add_13 = add(x = mul_32, y = mul_36)[name = string("add_13")];
            tensor<fp32, [1, 256, ?]> mul_37 = mul(x = add_13, y = text_mask)[name = string("mul_37")];
            tensor<fp32, [1, 256, ?]> mul_38 = mul(x = mul_37, y = text_mask)[name = string("mul_38")];
            tensor<fp32, [256, 256, 1]> const_79 = const()[name = string("const_79"), val = tensor<fp32, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21714304)))];
            tensor<fp32, [256]> const_80 = const()[name = string("const_80"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21976512)))];
            tensor<int32, [1]> conv_18_strides_0 = const()[name = string("conv_18_strides_0"), val = tensor<int32, [1]>([1])];
            string conv_18_pad_type_0 = const()[name = string("conv_18_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> conv_18_pad_0 = const()[name = string("conv_18_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> conv_18_dilations_0 = const()[name = string("conv_18_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 conv_18_groups_0 = const()[name = string("conv_18_groups_0"), val = int32(1)];
            tensor<fp32, [1, 256, ?]> conv_18 = conv(bias = const_80, dilations = conv_18_dilations_0, groups = conv_18_groups_0, pad = conv_18_pad_0, pad_type = conv_18_pad_type_0, strides = conv_18_strides_0, weight = const_79, x = mul_38)[name = string("conv_18")];
            tensor<fp32, [256, 256, 1]> const_81 = const()[name = string("const_81"), val = tensor<fp32, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21977600)))];
            tensor<fp32, [256]> const_82 = const()[name = string("const_82"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(22239808)))];
            tensor<int32, [1]> conv_19_strides_0 = const()[name = string("conv_19_strides_0"), val = tensor<int32, [1]>([1])];
            string conv_19_pad_type_0 = const()[name = string("conv_19_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> conv_19_pad_0 = const()[name = string("conv_19_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> conv_19_dilations_0 = const()[name = string("conv_19_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 conv_19_groups_0 = const()[name = string("conv_19_groups_0"), val = int32(1)];
            tensor<fp32, [1, 256, ?]> conv_19 = conv(bias = const_82, dilations = conv_19_dilations_0, groups = conv_19_groups_0, pad = conv_19_pad_0, pad_type = conv_19_pad_type_0, strides = conv_19_strides_0, weight = const_81, x = mul_38)[name = string("conv_19")];
            tensor<fp32, [256, 256, 1]> const_83 = const()[name = string("const_83"), val = tensor<fp32, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(22240896)))];
            tensor<fp32, [256]> const_84 = const()[name = string("const_84"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(22503104)))];
            tensor<int32, [1]> conv_20_strides_0 = const()[name = string("conv_20_strides_0"), val = tensor<int32, [1]>([1])];
            string conv_20_pad_type_0 = const()[name = string("conv_20_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> conv_20_pad_0 = const()[name = string("conv_20_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> conv_20_dilations_0 = const()[name = string("conv_20_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 conv_20_groups_0 = const()[name = string("conv_20_groups_0"), val = int32(1)];
            tensor<fp32, [1, 256, ?]> conv_20 = conv(bias = const_84, dilations = conv_20_dilations_0, groups = conv_20_groups_0, pad = conv_20_pad_0, pad_type = conv_20_pad_type_0, strides = conv_20_strides_0, weight = const_83, x = mul_38)[name = string("conv_20")];
            tensor<int32, [3]> shape_0 = shape(x = conv_19)[name = string("shape_0")];
            int32 gather_2_batch_dims_0 = const()[name = string("gather_2_batch_dims_0"), val = int32(0)];
            bool gather_2_validate_indices_0 = const()[name = string("gather_2_validate_indices_0"), val = bool(false)];
            tensor<int32, [1]> select_7 = const()[name = string("select_7"), val = tensor<int32, [1]>([2])];
            int32 gather_2_axis_1 = const()[name = string("gather_2_axis_1"), val = int32(0)];
            tensor<int32, [1]> gather_2 = gather(axis = gather_2_axis_1, batch_dims = gather_2_batch_dims_0, indices = select_7, validate_indices = gather_2_validate_indices_0, x = shape_0)[name = string("gather_2")];
            tensor<int32, [1]> squeeze_1_axes_0 = const()[name = string("squeeze_1_axes_0"), val = tensor<int32, [1]>([0])];
            int32 squeeze_1 = squeeze(axes = squeeze_1_axes_0, x = gather_2)[name = string("squeeze_1")];
            tensor<int32, [1]> expand_dims_7 = const()[name = string("expand_dims_7"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> expand_dims_9_axes_0 = const()[name = string("expand_dims_9_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> expand_dims_9 = expand_dims(axes = expand_dims_9_axes_0, x = squeeze_1)[name = string("expand_dims_9")];
            int32 const_88 = const()[name = string("const_88"), val = int32(5)];
            int32 sub_0 = sub(x = squeeze_1, y = const_88)[name = string("sub_0")];
            int32 const_89 = const()[name = string("const_89"), val = int32(5)];
            int32 sub_1 = sub(x = const_89, y = squeeze_1)[name = string("sub_1")];
            int32 const_90 = const()[name = string("const_90"), val = int32(2)];
            int32 mul_39 = mul(x = squeeze_1, y = const_90)[name = string("mul_39")];
            tensor<int32, [1]> const_93 = const()[name = string("const_93"), val = tensor<int32, [1]>([4])];
            tensor<int32, [1]> const_94 = const()[name = string("const_94"), val = tensor<int32, [1]>([64])];
            int32 concat_9_axis_0 = const()[name = string("concat_9_axis_0"), val = int32(0)];
            bool concat_9_interleave_0 = const()[name = string("concat_9_interleave_0"), val = bool(false)];
            tensor<int32, [4]> concat_9 = concat(axis = concat_9_axis_0, interleave = concat_9_interleave_0, values = (expand_dims_7, const_93, const_94, expand_dims_9))[name = string("concat_9")];
            int32 const_95 = const()[name = string("const_95"), val = int32(0)];
            int32 maximum_0 = maximum(x = sub_0, y = const_95)[name = string("maximum_0")];
            int32 const_96 = const()[name = string("const_96"), val = int32(0)];
            int32 maximum_1 = maximum(x = sub_1, y = const_96)[name = string("maximum_1")];
            tensor<int32, [4]> concat_8x = const()[name = string("concat_8x"), val = tensor<int32, [4]>([1, 4, 64, -1])];
            tensor<fp32, [1, 4, 64, ?]> reshape_0 = reshape(shape = concat_8x, x = conv_18)[name = string("reshape_0")];
            tensor<fp32, [1, 4, 64, ?]> reshape_1 = reshape(shape = concat_9, x = conv_19)[name = string("reshape_1")];
            tensor<fp32, [1, 4, 64, ?]> reshape_2 = reshape(shape = concat_9, x = conv_20)[name = string("reshape_2")];
            int32 add_14 = add(x = maximum_1, y = mul_39)[name = string("add_14")];
            tensor<int32, [1]> expand_dims_10_axes_0 = const()[name = string("expand_dims_10_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> expand_dims_10 = expand_dims(axes = expand_dims_10_axes_0, x = maximum_0)[name = string("expand_dims_10")];
            tensor<int32, [1]> expand_dims_11_axes_0 = const()[name = string("expand_dims_11_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> expand_dims_11 = expand_dims(axes = expand_dims_11_axes_0, x = maximum_1)[name = string("expand_dims_11")];
            tensor<int32, [4]> transpose_14_perm_0 = const()[name = string("transpose_14_perm_0"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [1]> expand_dims_95_axes_0 = const()[name = string("expand_dims_95_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> expand_dims_95 = expand_dims(axes = expand_dims_95_axes_0, x = add_14)[name = string("expand_dims_95")];
            tensor<int32, [1]> expand_dims_96 = const()[name = string("expand_dims_96"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> expand_dims_12 = sub(x = expand_dims_95, y = expand_dims_96)[name = string("expand_dims_12")];
            tensor<int32, [1]> const_99 = const()[name = string("const_99"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_100 = const()[name = string("const_100"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_101 = const()[name = string("const_101"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_102 = const()[name = string("const_102"), val = tensor<int32, [1]>([0])];
            int32 concat_11_axis_0 = const()[name = string("concat_11_axis_0"), val = int32(0)];
            bool concat_11_interleave_0 = const()[name = string("concat_11_interleave_0"), val = bool(false)];
            tensor<int32, [6]> concat_11 = concat(axis = concat_11_axis_0, interleave = concat_11_interleave_0, values = (const_99, const_100, expand_dims_10, expand_dims_10, const_101, const_102))[name = string("concat_11")];
            fp32 _inversed_real_div_6_y_0 = const()[name = string("_inversed_real_div_6_y_0"), val = fp32(0x1p-3)];
            tensor<fp32, [1, 4, ?, 64]> transpose_14 = transpose(perm = transpose_14_perm_0, x = reshape_0)[name = string("transpose_123")];
            tensor<fp32, [1, 4, ?, 64]> _inversed_real_div_6 = mul(x = transpose_14, y = _inversed_real_div_6_y_0)[name = string("_inversed_real_div_6")];
            tensor<int32, [2]> const_104 = const()[name = string("const_104"), val = tensor<int32, [2]>([-1, 2])];
            tensor<int32, [3, 2]> reshape_3 = reshape(shape = const_104, x = concat_11)[name = string("reshape_3")];
            bool matmul_2_transpose_x_0 = const()[name = string("matmul_2_transpose_x_0"), val = bool(false)];
            bool matmul_2_transpose_y_0 = const()[name = string("matmul_2_transpose_y_0"), val = bool(false)];
            tensor<fp32, [1, 4, ?, ?]> matmul_2 = matmul(transpose_x = matmul_2_transpose_x_0, transpose_y = matmul_2_transpose_y_0, x = _inversed_real_div_6, y = reshape_1)[name = string("matmul_2")];
            tensor<int32, [2]> slice_by_index_12_begin_0 = const()[name = string("slice_by_index_12_begin_0"), val = tensor<int32, [2]>([2, 0])];
            tensor<int32, [2]> slice_by_index_12_end_0 = const()[name = string("slice_by_index_12_end_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [2]> slice_by_index_12_stride_0 = const()[name = string("slice_by_index_12_stride_0"), val = tensor<int32, [2]>([-1, 1])];
            tensor<bool, [2]> slice_by_index_12_begin_mask_0 = const()[name = string("slice_by_index_12_begin_mask_0"), val = tensor<bool, [2]>([false, true])];
            tensor<bool, [2]> slice_by_index_12_end_mask_0 = const()[name = string("slice_by_index_12_end_mask_0"), val = tensor<bool, [2]>([true, true])];
            tensor<int32, [3, 2]> slice_by_index_12 = slice_by_index(begin = slice_by_index_12_begin_0, begin_mask = slice_by_index_12_begin_mask_0, end = slice_by_index_12_end_0, end_mask = slice_by_index_12_end_mask_0, stride = slice_by_index_12_stride_0, x = reshape_3)[name = string("slice_by_index_12")];
            tensor<int32, [2]> transpose_16_perm_0 = const()[name = string("transpose_16_perm_0"), val = tensor<int32, [2]>([1, 0])];
            tensor<int32, [1]> const_105 = const()[name = string("const_105"), val = tensor<int32, [1]>([-1])];
            tensor<int32, [2, 3]> transpose_16 = transpose(perm = transpose_16_perm_0, x = slice_by_index_12)[name = string("transpose_122")];
            tensor<int32, [6]> reshape_4 = reshape(shape = const_105, x = transpose_16)[name = string("reshape_4")];
            tensor<int32, [2]> reshape_5_shape_0 = const()[name = string("reshape_5_shape_0"), val = tensor<int32, [2]>([2, 3])];
            tensor<int32, [2, 3]> reshape_5 = reshape(shape = reshape_5_shape_0, x = reshape_4)[name = string("reshape_5")];
            tensor<int32, [2]> transpose_17_perm_0 = const()[name = string("transpose_17_perm_0"), val = tensor<int32, [2]>([1, 0])];
            tensor<int32, [1]> reshape_6_shape_0 = const()[name = string("reshape_6_shape_0"), val = tensor<int32, [1]>([-1])];
            tensor<int32, [3, 2]> transpose_17 = transpose(perm = transpose_17_perm_0, x = reshape_5)[name = string("transpose_121")];
            tensor<int32, [6]> reshape_6 = reshape(shape = reshape_6_shape_0, x = transpose_17)[name = string("reshape_6")];
            tensor<fp32, [1, 9, 64]> const_106 = const()[name = string("const_106"), val = tensor<fp32, [1, 9, 64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(22504192)))];
            string pad_0_mode_0 = const()[name = string("pad_0_mode_0"), val = string("constant")];
            fp32 pad_0_constant_val_0 = const()[name = string("pad_0_constant_val_0"), val = fp32(0x0p+0)];
            tensor<fp32, [?, ?, ?]> pad_0 = pad(constant_val = pad_0_constant_val_0, mode = pad_0_mode_0, pad = reshape_6, x = const_106)[name = string("pad_0")];
            tensor<fp32, [1, 9, 64]> const_107 = const()[name = string("const_107"), val = tensor<fp32, [1, 9, 64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(22506560)))];
            string pad_1_mode_0 = const()[name = string("pad_1_mode_0"), val = string("constant")];
            fp32 pad_1_constant_val_0 = const()[name = string("pad_1_constant_val_0"), val = fp32(0x0p+0)];
            tensor<fp32, [?, ?, ?]> pad_1 = pad(constant_val = pad_1_constant_val_0, mode = pad_1_mode_0, pad = reshape_6, x = const_107)[name = string("pad_1")];
            tensor<int32, [1]> const_108 = const()[name = string("const_108"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_109 = const()[name = string("const_109"), val = tensor<int32, [1]>([0])];
            int32 concat_12_axis_0 = const()[name = string("concat_12_axis_0"), val = int32(0)];
            bool concat_12_interleave_0 = const()[name = string("concat_12_interleave_0"), val = bool(false)];
            tensor<int32, [3]> concat_12 = concat(axis = concat_12_axis_0, interleave = concat_12_interleave_0, values = (const_108, expand_dims_11, const_109))[name = string("concat_12")];
            tensor<int32, [1]> const_110 = const()[name = string("const_110"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_111 = const()[name = string("const_111"), val = tensor<int32, [1]>([0])];
            int32 concat_13_axis_0 = const()[name = string("concat_13_axis_0"), val = int32(0)];
            bool concat_13_interleave_0 = const()[name = string("concat_13_interleave_0"), val = bool(false)];
            tensor<int32, [3]> concat_13 = concat(axis = concat_13_axis_0, interleave = concat_13_interleave_0, values = (const_110, expand_dims_12, const_111))[name = string("concat_13")];
            tensor<int32, [3]> slice_by_index_15_stride_0 = const()[name = string("slice_by_index_15_stride_0"), val = tensor<int32, [3]>([1, 1, 1])];
            tensor<bool, [3]> slice_by_index_15_begin_mask_0 = const()[name = string("slice_by_index_15_begin_mask_0"), val = tensor<bool, [3]>([true, false, true])];
            tensor<bool, [3]> slice_by_index_15_end_mask_0 = const()[name = string("slice_by_index_15_end_mask_0"), val = tensor<bool, [3]>([true, false, true])];
            tensor<fp32, [?, ?, ?]> slice_by_index_15 = slice_by_index(begin = concat_12, begin_mask = slice_by_index_15_begin_mask_0, end = concat_13, end_mask = slice_by_index_15_end_mask_0, stride = slice_by_index_15_stride_0, x = pad_0)[name = string("slice_by_index_15")];
            tensor<int32, [3]> slice_by_index_18_stride_0 = const()[name = string("slice_by_index_18_stride_0"), val = tensor<int32, [3]>([1, 1, 1])];
            tensor<bool, [3]> slice_by_index_18_begin_mask_0 = const()[name = string("slice_by_index_18_begin_mask_0"), val = tensor<bool, [3]>([true, false, true])];
            tensor<bool, [3]> slice_by_index_18_end_mask_0 = const()[name = string("slice_by_index_18_end_mask_0"), val = tensor<bool, [3]>([true, false, true])];
            tensor<fp32, [?, ?, ?]> slice_by_index_18 = slice_by_index(begin = concat_12, begin_mask = slice_by_index_18_begin_mask_0, end = concat_13, end_mask = slice_by_index_18_end_mask_0, stride = slice_by_index_18_stride_0, x = pad_1)[name = string("slice_by_index_18")];
            tensor<int32, [1]> expand_dims_13_axes_0 = const()[name = string("expand_dims_13_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp32, [1, ?, ?, ?]> expand_dims_13 = expand_dims(axes = expand_dims_13_axes_0, x = slice_by_index_15)[name = string("expand_dims_13")];
            tensor<int32, [1]> expand_dims_14_axes_0 = const()[name = string("expand_dims_14_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp32, [1, ?, ?, ?]> expand_dims_14 = expand_dims(axes = expand_dims_14_axes_0, x = slice_by_index_18)[name = string("expand_dims_14")];
            bool matmul_3_transpose_x_1 = const()[name = string("matmul_3_transpose_x_1"), val = bool(false)];
            bool matmul_3_transpose_y_1 = const()[name = string("matmul_3_transpose_y_1"), val = bool(true)];
            tensor<fp32, [1, 4, ?, ?]> matmul_3 = matmul(transpose_x = matmul_3_transpose_x_1, transpose_y = matmul_3_transpose_y_1, x = _inversed_real_div_6, y = expand_dims_13)[name = string("matmul_3")];
            tensor<int32, [4]> shape_2 = shape(x = matmul_3)[name = string("shape_2")];
            tensor<int32, [8]> const_116 = const()[name = string("const_116"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 1])];
            string pad_2_mode_0 = const()[name = string("pad_2_mode_0"), val = string("constant")];
            fp32 pad_2_constant_val_0 = const()[name = string("pad_2_constant_val_0"), val = fp32(0x0p+0)];
            tensor<fp32, [1, 4, ?, ?]> pad_2 = pad(constant_val = pad_2_constant_val_0, mode = pad_2_mode_0, pad = const_116, x = matmul_3)[name = string("pad_2")];
            int32 gather_6_batch_dims_0 = const()[name = string("gather_6_batch_dims_0"), val = int32(0)];
            bool gather_6_validate_indices_0 = const()[name = string("gather_6_validate_indices_0"), val = bool(false)];
            tensor<int32, [1]> select_9 = const()[name = string("select_9"), val = tensor<int32, [1]>([2])];
            int32 gather_6_axis_1 = const()[name = string("gather_6_axis_1"), val = int32(0)];
            tensor<int32, [1]> gather_6 = gather(axis = gather_6_axis_1, batch_dims = gather_6_batch_dims_0, indices = select_9, validate_indices = gather_6_validate_indices_0, x = shape_2)[name = string("gather_6")];
            tensor<int32, [1]> squeeze_5_axes_0 = const()[name = string("squeeze_5_axes_0"), val = tensor<int32, [1]>([0])];
            int32 squeeze_5 = squeeze(axes = squeeze_5_axes_0, x = gather_6)[name = string("squeeze_5")];
            tensor<int32, [1]> expand_dims_143_axes_0 = const()[name = string("expand_dims_143_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> expand_dims_143 = expand_dims(axes = expand_dims_143_axes_0, x = squeeze_5)[name = string("expand_dims_143")];
            tensor<int32, [1]> expand_dims_144 = const()[name = string("expand_dims_144"), val = tensor<int32, [1]>([2])];
            tensor<int32, [1]> expand_dims_101 = mul(x = expand_dims_143, y = expand_dims_144)[name = string("expand_dims_101")];
            tensor<int32, [1]> expand_dims_15 = const()[name = string("expand_dims_15"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> expand_dims_16 = const()[name = string("expand_dims_16"), val = tensor<int32, [1]>([4])];
            tensor<int32, [1]> expand_dims_98 = const()[name = string("expand_dims_98"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> expand_dims_18 = sub(x = expand_dims_143, y = expand_dims_98)[name = string("expand_dims_18")];
            tensor<int32, [1]> expand_dims_100 = const()[name = string("expand_dims_100"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> expand_dims_19 = add(x = expand_dims_143, y = expand_dims_100)[name = string("expand_dims_19")];
            tensor<int32, [1]> expand_dims_102 = const()[name = string("expand_dims_102"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> expand_dims_21 = sub(x = expand_dims_101, y = expand_dims_102)[name = string("expand_dims_21")];
            tensor<int32, [1]> const_124 = const()[name = string("const_124"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_125 = const()[name = string("const_125"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_126 = const()[name = string("const_126"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_127 = const()[name = string("const_127"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_128 = const()[name = string("const_128"), val = tensor<int32, [1]>([0])];
            int32 concat_16_axis_0 = const()[name = string("concat_16_axis_0"), val = int32(0)];
            bool concat_16_interleave_0 = const()[name = string("concat_16_interleave_0"), val = bool(false)];
            tensor<int32, [6]> concat_16 = concat(axis = concat_16_axis_0, interleave = concat_16_interleave_0, values = (const_124, expand_dims_18, const_125, const_126, const_127, const_128))[name = string("concat_16")];
            int32 concat_18_axis_0 = const()[name = string("concat_18_axis_0"), val = int32(0)];
            bool concat_18_interleave_0 = const()[name = string("concat_18_interleave_0"), val = bool(false)];
            tensor<int32, [4]> concat_18 = concat(axis = concat_18_axis_0, interleave = concat_18_interleave_0, values = (expand_dims_15, expand_dims_16, expand_dims_19, expand_dims_21))[name = string("concat_18")];
            tensor<int32, [2]> const_129 = const()[name = string("const_129"), val = tensor<int32, [2]>([-1, 2])];
            tensor<int32, [3, 2]> reshape_9 = reshape(shape = const_129, x = concat_16)[name = string("reshape_9")];
            tensor<int32, [3]> concat_17x = const()[name = string("concat_17x"), val = tensor<int32, [3]>([1, 4, -1])];
            tensor<fp32, [1, 4, ?]> reshape_10 = reshape(shape = concat_17x, x = pad_2)[name = string("reshape_10")];
            tensor<int32, [2]> slice_by_index_19_begin_0 = const()[name = string("slice_by_index_19_begin_0"), val = tensor<int32, [2]>([2, 0])];
            tensor<int32, [2]> slice_by_index_19_end_0 = const()[name = string("slice_by_index_19_end_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [2]> slice_by_index_19_stride_0 = const()[name = string("slice_by_index_19_stride_0"), val = tensor<int32, [2]>([-1, 1])];
            tensor<bool, [2]> slice_by_index_19_begin_mask_0 = const()[name = string("slice_by_index_19_begin_mask_0"), val = tensor<bool, [2]>([false, true])];
            tensor<bool, [2]> slice_by_index_19_end_mask_0 = const()[name = string("slice_by_index_19_end_mask_0"), val = tensor<bool, [2]>([true, true])];
            tensor<int32, [3, 2]> slice_by_index_19 = slice_by_index(begin = slice_by_index_19_begin_0, begin_mask = slice_by_index_19_begin_mask_0, end = slice_by_index_19_end_0, end_mask = slice_by_index_19_end_mask_0, stride = slice_by_index_19_stride_0, x = reshape_9)[name = string("slice_by_index_19")];
            tensor<int32, [1]> reshape_13_shape_0 = const()[name = string("reshape_13_shape_0"), val = tensor<int32, [1]>([-1])];
            tensor<int32, [6]> reshape_13 = reshape(shape = reshape_13_shape_0, x = slice_by_index_19)[name = string("reshape_13")];
            string pad_3_mode_0 = const()[name = string("pad_3_mode_0"), val = string("constant")];
            fp32 pad_3_constant_val_0 = const()[name = string("pad_3_constant_val_0"), val = fp32(0x0p+0)];
            tensor<fp32, [1, 4, ?]> pad_3 = pad(constant_val = pad_3_constant_val_0, mode = pad_3_mode_0, pad = reshape_13, x = reshape_10)[name = string("pad_3")];
            tensor<fp32, [1, 4, ?, ?]> reshape_14 = reshape(shape = concat_18, x = pad_3)[name = string("reshape_14")];
            tensor<int32, [1]> const_131 = const()[name = string("const_131"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_132 = const()[name = string("const_132"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_133 = const()[name = string("const_133"), val = tensor<int32, [1]>([0])];
            int32 concat_19_axis_0 = const()[name = string("concat_19_axis_0"), val = int32(0)];
            bool concat_19_interleave_0 = const()[name = string("concat_19_interleave_0"), val = bool(false)];
            tensor<int32, [4]> concat_19 = concat(axis = concat_19_axis_0, interleave = concat_19_interleave_0, values = (const_131, const_132, expand_dims_143, const_133))[name = string("concat_19")];
            tensor<int32, [4]> slice_by_index_21_begin_0 = const()[name = string("slice_by_index_21_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> slice_by_index_21_stride_0 = const()[name = string("slice_by_index_21_stride_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<bool, [4]> slice_by_index_21_begin_mask_0 = const()[name = string("slice_by_index_21_begin_mask_0"), val = tensor<bool, [4]>([true, true, false, true])];
            tensor<bool, [4]> slice_by_index_21_end_mask_0 = const()[name = string("slice_by_index_21_end_mask_0"), val = tensor<bool, [4]>([true, true, false, true])];
            tensor<fp32, [1, 4, ?, ?]> slice_by_index_21 = slice_by_index(begin = slice_by_index_21_begin_0, begin_mask = slice_by_index_21_begin_mask_0, end = concat_19, end_mask = slice_by_index_21_end_mask_0, stride = slice_by_index_21_stride_0, x = reshape_14)[name = string("slice_by_index_21")];
            tensor<int32, [1]> const_134 = const()[name = string("const_134"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_135 = const()[name = string("const_135"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_136 = const()[name = string("const_136"), val = tensor<int32, [1]>([0])];
            int32 concat_20_axis_0 = const()[name = string("concat_20_axis_0"), val = int32(0)];
            bool concat_20_interleave_0 = const()[name = string("concat_20_interleave_0"), val = bool(false)];
            tensor<int32, [4]> concat_20 = concat(axis = concat_20_axis_0, interleave = concat_20_interleave_0, values = (const_134, const_135, const_136, expand_dims_18))[name = string("concat_20")];
            tensor<int32, [4]> slice_by_index_23_end_0 = const()[name = string("slice_by_index_23_end_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> slice_by_index_23_stride_0 = const()[name = string("slice_by_index_23_stride_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<bool, [4]> slice_by_index_23_begin_mask_0 = const()[name = string("slice_by_index_23_begin_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<bool, [4]> slice_by_index_23_end_mask_0 = const()[name = string("slice_by_index_23_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp32, [1, 4, ?, ?]> slice_by_index_23 = slice_by_index(begin = concat_20, begin_mask = slice_by_index_23_begin_mask_0, end = slice_by_index_23_end_0, end_mask = slice_by_index_23_end_mask_0, stride = slice_by_index_23_stride_0, x = slice_by_index_21)[name = string("slice_by_index_23")];
            tensor<fp32, [1, 4, ?, ?]> add_16 = add(x = matmul_2, y = slice_by_index_23)[name = string("add_16")];
            fp32 const_137 = const()[name = string("const_137"), val = fp32(-0x1.388p+13)];
            tensor<fp32, [1, 4, ?, ?]> select_0 = select(a = const_137, b = add_16, cond = equal_1)[name = string("select_0")];
            int32 softmax_0_axis_0 = const()[name = string("softmax_0_axis_0"), val = int32(-1)];
            tensor<fp32, [1, 4, ?, ?]> softmax_0 = softmax(axis = softmax_0_axis_0, x = select_0)[name = string("softmax_0")];
            bool matmul_4_transpose_x_1 = const()[name = string("matmul_4_transpose_x_1"), val = bool(false)];
            bool matmul_4_transpose_y_1 = const()[name = string("matmul_4_transpose_y_1"), val = bool(true)];
            tensor<fp32, [1, 4, ?, 64]> matmul_4 = matmul(transpose_x = matmul_4_transpose_x_1, transpose_y = matmul_4_transpose_y_1, x = softmax_0, y = reshape_2)[name = string("matmul_4")];
            tensor<int32, [4]> shape_3 = shape(x = softmax_0)[name = string("shape_3")];
            int32 gather_9_batch_dims_0 = const()[name = string("gather_9_batch_dims_0"), val = int32(0)];
            bool gather_9_validate_indices_0 = const()[name = string("gather_9_validate_indices_0"), val = bool(false)];
            tensor<int32, [1]> select_10 = const()[name = string("select_10"), val = tensor<int32, [1]>([2])];
            int32 gather_9_axis_1 = const()[name = string("gather_9_axis_1"), val = int32(0)];
            tensor<int32, [1]> gather_9 = gather(axis = gather_9_axis_1, batch_dims = gather_9_batch_dims_0, indices = select_10, validate_indices = gather_9_validate_indices_0, x = shape_3)[name = string("gather_9")];
            tensor<int32, [1]> squeeze_8_axes_0 = const()[name = string("squeeze_8_axes_0"), val = tensor<int32, [1]>([0])];
            int32 squeeze_8 = squeeze(axes = squeeze_8_axes_0, x = gather_9)[name = string("squeeze_8")];
            tensor<int32, [1]> expand_dims_103_axes_0 = const()[name = string("expand_dims_103_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> expand_dims_103 = expand_dims(axes = expand_dims_103_axes_0, x = squeeze_8)[name = string("expand_dims_103")];
            tensor<int32, [1]> expand_dims_104 = const()[name = string("expand_dims_104"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> expand_dims_25 = sub(x = expand_dims_103, y = expand_dims_104)[name = string("expand_dims_25")];
            tensor<int32, [1]> expand_dims_22 = const()[name = string("expand_dims_22"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> expand_dims_23 = const()[name = string("expand_dims_23"), val = tensor<int32, [1]>([4])];
            tensor<int32, [1]> expand_dims_106 = const()[name = string("expand_dims_106"), val = tensor<int32, [1]>([2])];
            tensor<int32, [1]> expand_dims_26 = mul(x = expand_dims_103, y = expand_dims_106)[name = string("expand_dims_26")];
            tensor<int32, [1]> const_143 = const()[name = string("const_143"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_144 = const()[name = string("const_144"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_145 = const()[name = string("const_145"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_146 = const()[name = string("const_146"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_147 = const()[name = string("const_147"), val = tensor<int32, [1]>([0])];
            int32 concat_21_axis_0 = const()[name = string("concat_21_axis_0"), val = int32(0)];
            bool concat_21_interleave_0 = const()[name = string("concat_21_interleave_0"), val = bool(false)];
            tensor<int32, [6]> concat_21 = concat(axis = concat_21_axis_0, interleave = concat_21_interleave_0, values = (expand_dims_103, const_143, const_144, const_145, const_146, const_147))[name = string("concat_21")];
            tensor<int32, [1]> const_148 = const()[name = string("const_148"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_149 = const()[name = string("const_149"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_150 = const()[name = string("const_150"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_151 = const()[name = string("const_151"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_152 = const()[name = string("const_152"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_153 = const()[name = string("const_153"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_154 = const()[name = string("const_154"), val = tensor<int32, [1]>([0])];
            int32 concat_22_axis_0 = const()[name = string("concat_22_axis_0"), val = int32(0)];
            bool concat_22_interleave_0 = const()[name = string("concat_22_interleave_0"), val = bool(false)];
            tensor<int32, [8]> concat_22 = concat(axis = concat_22_axis_0, interleave = concat_22_interleave_0, values = (const_148, expand_dims_25, const_149, const_150, const_151, const_152, const_153, const_154))[name = string("concat_22")];
            int32 concat_23_axis_0 = const()[name = string("concat_23_axis_0"), val = int32(0)];
            bool concat_23_interleave_0 = const()[name = string("concat_23_interleave_0"), val = bool(false)];
            tensor<int32, [4]> concat_23 = concat(axis = concat_23_axis_0, interleave = concat_23_interleave_0, values = (expand_dims_22, expand_dims_23, expand_dims_103, expand_dims_26))[name = string("concat_23")];
            tensor<int32, [2]> const_155 = const()[name = string("const_155"), val = tensor<int32, [2]>([-1, 2])];
            tensor<int32, [3, 2]> reshape_15 = reshape(shape = const_155, x = concat_21)[name = string("reshape_15")];
            tensor<int32, [2]> const_156 = const()[name = string("const_156"), val = tensor<int32, [2]>([-1, 2])];
            tensor<int32, [4, 2]> reshape_16 = reshape(shape = const_156, x = concat_22)[name = string("reshape_16")];
            tensor<int32, [2]> slice_by_index_24_begin_0 = const()[name = string("slice_by_index_24_begin_0"), val = tensor<int32, [2]>([2, 0])];
            tensor<int32, [2]> slice_by_index_24_end_0 = const()[name = string("slice_by_index_24_end_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [2]> slice_by_index_24_stride_0 = const()[name = string("slice_by_index_24_stride_0"), val = tensor<int32, [2]>([-1, 1])];
            tensor<bool, [2]> slice_by_index_24_begin_mask_0 = const()[name = string("slice_by_index_24_begin_mask_0"), val = tensor<bool, [2]>([false, true])];
            tensor<bool, [2]> slice_by_index_24_end_mask_0 = const()[name = string("slice_by_index_24_end_mask_0"), val = tensor<bool, [2]>([true, true])];
            tensor<int32, [3, 2]> slice_by_index_24 = slice_by_index(begin = slice_by_index_24_begin_0, begin_mask = slice_by_index_24_begin_mask_0, end = slice_by_index_24_end_0, end_mask = slice_by_index_24_end_mask_0, stride = slice_by_index_24_stride_0, x = reshape_15)[name = string("slice_by_index_24")];
            tensor<int32, [2]> slice_by_index_25_begin_0 = const()[name = string("slice_by_index_25_begin_0"), val = tensor<int32, [2]>([3, 0])];
            tensor<int32, [2]> slice_by_index_25_end_0 = const()[name = string("slice_by_index_25_end_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [2]> slice_by_index_25_stride_0 = const()[name = string("slice_by_index_25_stride_0"), val = tensor<int32, [2]>([-1, 1])];
            tensor<bool, [2]> slice_by_index_25_begin_mask_0 = const()[name = string("slice_by_index_25_begin_mask_0"), val = tensor<bool, [2]>([false, true])];
            tensor<bool, [2]> slice_by_index_25_end_mask_0 = const()[name = string("slice_by_index_25_end_mask_0"), val = tensor<bool, [2]>([true, true])];
            tensor<int32, [4, 2]> slice_by_index_25 = slice_by_index(begin = slice_by_index_25_begin_0, begin_mask = slice_by_index_25_begin_mask_0, end = slice_by_index_25_end_0, end_mask = slice_by_index_25_end_mask_0, stride = slice_by_index_25_stride_0, x = reshape_16)[name = string("slice_by_index_25")];
            tensor<int32, [1]> reshape_20_shape_0 = const()[name = string("reshape_20_shape_0"), val = tensor<int32, [1]>([-1])];
            tensor<int32, [8]> reshape_20 = reshape(shape = reshape_20_shape_0, x = slice_by_index_25)[name = string("reshape_20")];
            string pad_4_mode_0 = const()[name = string("pad_4_mode_0"), val = string("constant")];
            fp32 pad_4_constant_val_0 = const()[name = string("pad_4_constant_val_0"), val = fp32(0x0p+0)];
            tensor<fp32, [1, 4, ?, ?]> pad_4 = pad(constant_val = pad_4_constant_val_0, mode = pad_4_mode_0, pad = reshape_20, x = softmax_0)[name = string("pad_4")];
            tensor<int32, [3]> concat_24x = const()[name = string("concat_24x"), val = tensor<int32, [3]>([1, 4, -1])];
            tensor<fp32, [1, 4, ?]> reshape_21 = reshape(shape = concat_24x, x = pad_4)[name = string("reshape_21")];
            tensor<int32, [1]> reshape_23_shape_0 = const()[name = string("reshape_23_shape_0"), val = tensor<int32, [1]>([-1])];
            tensor<int32, [6]> reshape_23 = reshape(shape = reshape_23_shape_0, x = slice_by_index_24)[name = string("reshape_23")];
            string pad_5_mode_0 = const()[name = string("pad_5_mode_0"), val = string("constant")];
            fp32 pad_5_constant_val_0 = const()[name = string("pad_5_constant_val_0"), val = fp32(0x0p+0)];
            tensor<fp32, [1, 4, ?]> pad_5 = pad(constant_val = pad_5_constant_val_0, mode = pad_5_mode_0, pad = reshape_23, x = reshape_21)[name = string("pad_5")];
            tensor<fp32, [1, 4, ?, ?]> reshape_24 = reshape(shape = concat_23, x = pad_5)[name = string("reshape_24")];
            tensor<int32, [4]> slice_by_index_26_begin_0 = const()[name = string("slice_by_index_26_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 1])];
            tensor<int32, [4]> slice_by_index_26_end_0 = const()[name = string("slice_by_index_26_end_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> slice_by_index_26_stride_0 = const()[name = string("slice_by_index_26_stride_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<bool, [4]> slice_by_index_26_begin_mask_0 = const()[name = string("slice_by_index_26_begin_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<bool, [4]> slice_by_index_26_end_mask_0 = const()[name = string("slice_by_index_26_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp32, [1, 4, ?, ?]> slice_by_index_26 = slice_by_index(begin = slice_by_index_26_begin_0, begin_mask = slice_by_index_26_begin_mask_0, end = slice_by_index_26_end_0, end_mask = slice_by_index_26_end_mask_0, stride = slice_by_index_26_stride_0, x = reshape_24)[name = string("slice_by_index_26")];
            bool matmul_5_transpose_x_0 = const()[name = string("matmul_5_transpose_x_0"), val = bool(false)];
            bool matmul_5_transpose_y_0 = const()[name = string("matmul_5_transpose_y_0"), val = bool(false)];
            tensor<fp32, [1, 4, ?, ?]> matmul_5 = matmul(transpose_x = matmul_5_transpose_x_0, transpose_y = matmul_5_transpose_y_0, x = slice_by_index_26, y = expand_dims_14)[name = string("matmul_5")];
            tensor<fp32, [1, 4, ?, 64]> add_18 = add(x = matmul_4, y = matmul_5)[name = string("add_18")];
            tensor<int32, [4]> transpose_26_perm_0 = const()[name = string("transpose_26_perm_0"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [3]> concat_10x = const()[name = string("concat_10x"), val = tensor<int32, [3]>([1, 256, -1])];
            tensor<fp32, [1, 4, 64, ?]> transpose_26 = transpose(perm = transpose_26_perm_0, x = add_18)[name = string("transpose_120")];
            tensor<fp32, [1, 256, ?]> reshape_25 = reshape(shape = concat_10x, x = transpose_26)[name = string("reshape_25")];
            tensor<fp32, [256, 256, 1]> const_159 = const()[name = string("const_159"), val = tensor<fp32, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(22508928)))];
            tensor<fp32, [256]> const_160 = const()[name = string("const_160"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(22771136)))];
            tensor<int32, [1]> conv_21_strides_0 = const()[name = string("conv_21_strides_0"), val = tensor<int32, [1]>([1])];
            string conv_21_pad_type_0 = const()[name = string("conv_21_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> conv_21_pad_0 = const()[name = string("conv_21_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> conv_21_dilations_0 = const()[name = string("conv_21_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 conv_21_groups_0 = const()[name = string("conv_21_groups_0"), val = int32(1)];
            tensor<fp32, [1, 256, ?]> conv_21 = conv(bias = const_160, dilations = conv_21_dilations_0, groups = conv_21_groups_0, pad = conv_21_pad_0, pad_type = conv_21_pad_type_0, strides = conv_21_strides_0, weight = const_159, x = reshape_25)[name = string("conv_21")];
            tensor<fp32, [1, 256, ?]> add_19 = add(x = mul_38, y = conv_21)[name = string("add_19")];
            tensor<int32, [3]> transpose_27_perm_0 = const()[name = string("transpose_27_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp32, [256]> const_161 = const()[name = string("const_161"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(22772224)))];
            tensor<fp32, [256]> const_162 = const()[name = string("const_162"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(22773312)))];
            tensor<int32, [1]> layer_norm_6_axes_0 = const()[name = string("layer_norm_6_axes_0"), val = tensor<int32, [1]>([2])];
            fp32 layer_norm_6_epsilon_0 = const()[name = string("layer_norm_6_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp32, [1, ?, 256]> transpose_27 = transpose(perm = transpose_27_perm_0, x = add_19)[name = string("transpose_119")];
            tensor<fp32, [1, ?, 256]> layer_norm_6 = layer_norm(axes = layer_norm_6_axes_0, beta = const_162, epsilon = layer_norm_6_epsilon_0, gamma = const_161, x = transpose_27)[name = string("layer_norm_6")];
            tensor<int32, [3]> transpose_28_perm_0 = const()[name = string("transpose_28_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp32, [1, 256, ?]> transpose_28 = transpose(perm = transpose_28_perm_0, x = layer_norm_6)[name = string("transpose_118")];
            tensor<fp32, [1, 256, ?]> mul_45 = mul(x = transpose_28, y = text_mask)[name = string("mul_45")];
            tensor<fp32, [1024, 256, 1]> const_163 = const()[name = string("const_163"), val = tensor<fp32, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(22774400)))];
            tensor<fp32, [1024]> const_164 = const()[name = string("const_164"), val = tensor<fp32, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(23823040)))];
            tensor<int32, [1]> conv_22_strides_0 = const()[name = string("conv_22_strides_0"), val = tensor<int32, [1]>([1])];
            string conv_22_pad_type_0 = const()[name = string("conv_22_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> conv_22_pad_0 = const()[name = string("conv_22_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> conv_22_dilations_0 = const()[name = string("conv_22_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 conv_22_groups_0 = const()[name = string("conv_22_groups_0"), val = int32(1)];
            tensor<fp32, [1, 1024, ?]> conv_22 = conv(bias = const_164, dilations = conv_22_dilations_0, groups = conv_22_groups_0, pad = conv_22_pad_0, pad_type = conv_22_pad_type_0, strides = conv_22_strides_0, weight = const_163, x = mul_45)[name = string("conv_22")];
            tensor<fp32, [1, 1024, ?]> relu_0 = relu(x = conv_22)[name = string("relu_0")];
            tensor<fp32, [1, 1024, ?]> mul_46 = mul(x = relu_0, y = text_mask)[name = string("mul_46")];
            tensor<fp32, [256, 1024, 1]> const_165 = const()[name = string("const_165"), val = tensor<fp32, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(23827200)))];
            tensor<fp32, [256]> const_166 = const()[name = string("const_166"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(24875840)))];
            tensor<int32, [1]> conv_23_strides_0 = const()[name = string("conv_23_strides_0"), val = tensor<int32, [1]>([1])];
            string conv_23_pad_type_0 = const()[name = string("conv_23_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> conv_23_pad_0 = const()[name = string("conv_23_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> conv_23_dilations_0 = const()[name = string("conv_23_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 conv_23_groups_0 = const()[name = string("conv_23_groups_0"), val = int32(1)];
            tensor<fp32, [1, 256, ?]> conv_23 = conv(bias = const_166, dilations = conv_23_dilations_0, groups = conv_23_groups_0, pad = conv_23_pad_0, pad_type = conv_23_pad_type_0, strides = conv_23_strides_0, weight = const_165, x = mul_46)[name = string("conv_23")];
            tensor<fp32, [1, 256, ?]> mul_47 = mul(x = conv_23, y = text_mask)[name = string("mul_47")];
            tensor<fp32, [1, 256, ?]> add_20 = add(x = transpose_28, y = mul_47)[name = string("add_20")];
            tensor<int32, [3]> transpose_29_perm_0 = const()[name = string("transpose_29_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp32, [256]> const_167 = const()[name = string("const_167"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(24876928)))];
            tensor<fp32, [256]> const_168 = const()[name = string("const_168"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(24878016)))];
            tensor<int32, [1]> layer_norm_7_axes_0 = const()[name = string("layer_norm_7_axes_0"), val = tensor<int32, [1]>([2])];
            fp32 layer_norm_7_epsilon_0 = const()[name = string("layer_norm_7_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp32, [1, ?, 256]> transpose_29 = transpose(perm = transpose_29_perm_0, x = add_20)[name = string("transpose_117")];
            tensor<fp32, [1, ?, 256]> layer_norm_7 = layer_norm(axes = layer_norm_7_axes_0, beta = const_168, epsilon = layer_norm_7_epsilon_0, gamma = const_167, x = transpose_29)[name = string("layer_norm_7")];
            tensor<int32, [3]> transpose_30_perm_0 = const()[name = string("transpose_30_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp32, [256, 256, 1]> const_169 = const()[name = string("const_169"), val = tensor<fp32, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(24879104)))];
            tensor<fp32, [256]> const_170 = const()[name = string("const_170"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25141312)))];
            tensor<int32, [1]> conv_24_strides_0 = const()[name = string("conv_24_strides_0"), val = tensor<int32, [1]>([1])];
            string conv_24_pad_type_0 = const()[name = string("conv_24_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> conv_24_pad_0 = const()[name = string("conv_24_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> conv_24_dilations_0 = const()[name = string("conv_24_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 conv_24_groups_0 = const()[name = string("conv_24_groups_0"), val = int32(1)];
            tensor<fp32, [1, 256, ?]> transpose_30 = transpose(perm = transpose_30_perm_0, x = layer_norm_7)[name = string("transpose_116")];
            tensor<fp32, [1, 256, ?]> conv_24 = conv(bias = const_170, dilations = conv_24_dilations_0, groups = conv_24_groups_0, pad = conv_24_pad_0, pad_type = conv_24_pad_type_0, strides = conv_24_strides_0, weight = const_169, x = transpose_30)[name = string("conv_24")];
            tensor<fp32, [256, 256, 1]> const_171 = const()[name = string("const_171"), val = tensor<fp32, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25142400)))];
            tensor<fp32, [256]> const_172 = const()[name = string("const_172"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25404608)))];
            tensor<int32, [1]> conv_25_strides_0 = const()[name = string("conv_25_strides_0"), val = tensor<int32, [1]>([1])];
            string conv_25_pad_type_0 = const()[name = string("conv_25_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> conv_25_pad_0 = const()[name = string("conv_25_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> conv_25_dilations_0 = const()[name = string("conv_25_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 conv_25_groups_0 = const()[name = string("conv_25_groups_0"), val = int32(1)];
            tensor<fp32, [1, 256, ?]> conv_25 = conv(bias = const_172, dilations = conv_25_dilations_0, groups = conv_25_groups_0, pad = conv_25_pad_0, pad_type = conv_25_pad_type_0, strides = conv_25_strides_0, weight = const_171, x = transpose_30)[name = string("conv_25")];
            tensor<fp32, [256, 256, 1]> const_173 = const()[name = string("const_173"), val = tensor<fp32, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25405696)))];
            tensor<fp32, [256]> const_174 = const()[name = string("const_174"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25667904)))];
            tensor<int32, [1]> conv_26_strides_0 = const()[name = string("conv_26_strides_0"), val = tensor<int32, [1]>([1])];
            string conv_26_pad_type_0 = const()[name = string("conv_26_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> conv_26_pad_0 = const()[name = string("conv_26_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> conv_26_dilations_0 = const()[name = string("conv_26_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 conv_26_groups_0 = const()[name = string("conv_26_groups_0"), val = int32(1)];
            tensor<fp32, [1, 256, ?]> conv_26 = conv(bias = const_174, dilations = conv_26_dilations_0, groups = conv_26_groups_0, pad = conv_26_pad_0, pad_type = conv_26_pad_type_0, strides = conv_26_strides_0, weight = const_173, x = transpose_30)[name = string("conv_26")];
            tensor<int32, [3]> shape_4 = shape(x = conv_25)[name = string("shape_4")];
            int32 gather_11_batch_dims_0 = const()[name = string("gather_11_batch_dims_0"), val = int32(0)];
            bool gather_11_validate_indices_0 = const()[name = string("gather_11_validate_indices_0"), val = bool(false)];
            tensor<int32, [1]> select_11 = const()[name = string("select_11"), val = tensor<int32, [1]>([2])];
            int32 gather_11_axis_1 = const()[name = string("gather_11_axis_1"), val = int32(0)];
            tensor<int32, [1]> gather_11 = gather(axis = gather_11_axis_1, batch_dims = gather_11_batch_dims_0, indices = select_11, validate_indices = gather_11_validate_indices_0, x = shape_4)[name = string("gather_11")];
            tensor<int32, [1]> squeeze_10_axes_0 = const()[name = string("squeeze_10_axes_0"), val = tensor<int32, [1]>([0])];
            int32 squeeze_10 = squeeze(axes = squeeze_10_axes_0, x = gather_11)[name = string("squeeze_10")];
            tensor<int32, [1]> expand_dims_28 = const()[name = string("expand_dims_28"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> expand_dims_30_axes_0 = const()[name = string("expand_dims_30_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> expand_dims_30 = expand_dims(axes = expand_dims_30_axes_0, x = squeeze_10)[name = string("expand_dims_30")];
            int32 const_178 = const()[name = string("const_178"), val = int32(5)];
            int32 sub_6 = sub(x = squeeze_10, y = const_178)[name = string("sub_6")];
            int32 const_179 = const()[name = string("const_179"), val = int32(5)];
            int32 sub_7 = sub(x = const_179, y = squeeze_10)[name = string("sub_7")];
            int32 const_180 = const()[name = string("const_180"), val = int32(2)];
            int32 mul_48 = mul(x = squeeze_10, y = const_180)[name = string("mul_48")];
            tensor<int32, [1]> const_183 = const()[name = string("const_183"), val = tensor<int32, [1]>([4])];
            tensor<int32, [1]> const_184 = const()[name = string("const_184"), val = tensor<int32, [1]>([64])];
            int32 concat_26_axis_0 = const()[name = string("concat_26_axis_0"), val = int32(0)];
            bool concat_26_interleave_0 = const()[name = string("concat_26_interleave_0"), val = bool(false)];
            tensor<int32, [4]> concat_26 = concat(axis = concat_26_axis_0, interleave = concat_26_interleave_0, values = (expand_dims_28, const_183, const_184, expand_dims_30))[name = string("concat_26")];
            int32 const_185 = const()[name = string("const_185"), val = int32(0)];
            int32 maximum_2 = maximum(x = sub_6, y = const_185)[name = string("maximum_2")];
            int32 const_186 = const()[name = string("const_186"), val = int32(0)];
            int32 maximum_3 = maximum(x = sub_7, y = const_186)[name = string("maximum_3")];
            tensor<int32, [4]> concat_25x = const()[name = string("concat_25x"), val = tensor<int32, [4]>([1, 4, 64, -1])];
            tensor<fp32, [1, 4, 64, ?]> reshape_26 = reshape(shape = concat_25x, x = conv_24)[name = string("reshape_26")];
            tensor<fp32, [1, 4, 64, ?]> reshape_27 = reshape(shape = concat_26, x = conv_25)[name = string("reshape_27")];
            tensor<fp32, [1, 4, 64, ?]> reshape_28 = reshape(shape = concat_26, x = conv_26)[name = string("reshape_28")];
            int32 add_21 = add(x = maximum_3, y = mul_48)[name = string("add_21")];
            tensor<int32, [1]> expand_dims_31_axes_0 = const()[name = string("expand_dims_31_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> expand_dims_31 = expand_dims(axes = expand_dims_31_axes_0, x = maximum_2)[name = string("expand_dims_31")];
            tensor<int32, [1]> expand_dims_32_axes_0 = const()[name = string("expand_dims_32_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> expand_dims_32 = expand_dims(axes = expand_dims_32_axes_0, x = maximum_3)[name = string("expand_dims_32")];
            tensor<int32, [4]> transpose_31_perm_0 = const()[name = string("transpose_31_perm_0"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [1]> expand_dims_107_axes_0 = const()[name = string("expand_dims_107_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> expand_dims_107 = expand_dims(axes = expand_dims_107_axes_0, x = add_21)[name = string("expand_dims_107")];
            tensor<int32, [1]> expand_dims_108 = const()[name = string("expand_dims_108"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> expand_dims_33 = sub(x = expand_dims_107, y = expand_dims_108)[name = string("expand_dims_33")];
            tensor<int32, [1]> const_189 = const()[name = string("const_189"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_190 = const()[name = string("const_190"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_191 = const()[name = string("const_191"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_192 = const()[name = string("const_192"), val = tensor<int32, [1]>([0])];
            int32 concat_28_axis_0 = const()[name = string("concat_28_axis_0"), val = int32(0)];
            bool concat_28_interleave_0 = const()[name = string("concat_28_interleave_0"), val = bool(false)];
            tensor<int32, [6]> concat_28 = concat(axis = concat_28_axis_0, interleave = concat_28_interleave_0, values = (const_189, const_190, expand_dims_31, expand_dims_31, const_191, const_192))[name = string("concat_28")];
            fp32 _inversed_real_div_7_y_0 = const()[name = string("_inversed_real_div_7_y_0"), val = fp32(0x1p-3)];
            tensor<fp32, [1, 4, ?, 64]> transpose_31 = transpose(perm = transpose_31_perm_0, x = reshape_26)[name = string("transpose_115")];
            tensor<fp32, [1, 4, ?, 64]> _inversed_real_div_7 = mul(x = transpose_31, y = _inversed_real_div_7_y_0)[name = string("_inversed_real_div_7")];
            tensor<int32, [2]> const_194 = const()[name = string("const_194"), val = tensor<int32, [2]>([-1, 2])];
            tensor<int32, [3, 2]> reshape_29 = reshape(shape = const_194, x = concat_28)[name = string("reshape_29")];
            bool matmul_6_transpose_x_0 = const()[name = string("matmul_6_transpose_x_0"), val = bool(false)];
            bool matmul_6_transpose_y_0 = const()[name = string("matmul_6_transpose_y_0"), val = bool(false)];
            tensor<fp32, [1, 4, ?, ?]> matmul_6 = matmul(transpose_x = matmul_6_transpose_x_0, transpose_y = matmul_6_transpose_y_0, x = _inversed_real_div_7, y = reshape_27)[name = string("matmul_6")];
            tensor<int32, [2]> slice_by_index_27_begin_0 = const()[name = string("slice_by_index_27_begin_0"), val = tensor<int32, [2]>([2, 0])];
            tensor<int32, [2]> slice_by_index_27_end_0 = const()[name = string("slice_by_index_27_end_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [2]> slice_by_index_27_stride_0 = const()[name = string("slice_by_index_27_stride_0"), val = tensor<int32, [2]>([-1, 1])];
            tensor<bool, [2]> slice_by_index_27_begin_mask_0 = const()[name = string("slice_by_index_27_begin_mask_0"), val = tensor<bool, [2]>([false, true])];
            tensor<bool, [2]> slice_by_index_27_end_mask_0 = const()[name = string("slice_by_index_27_end_mask_0"), val = tensor<bool, [2]>([true, true])];
            tensor<int32, [3, 2]> slice_by_index_27 = slice_by_index(begin = slice_by_index_27_begin_0, begin_mask = slice_by_index_27_begin_mask_0, end = slice_by_index_27_end_0, end_mask = slice_by_index_27_end_mask_0, stride = slice_by_index_27_stride_0, x = reshape_29)[name = string("slice_by_index_27")];
            tensor<int32, [2]> transpose_33_perm_0 = const()[name = string("transpose_33_perm_0"), val = tensor<int32, [2]>([1, 0])];
            tensor<int32, [1]> const_195 = const()[name = string("const_195"), val = tensor<int32, [1]>([-1])];
            tensor<int32, [2, 3]> transpose_33 = transpose(perm = transpose_33_perm_0, x = slice_by_index_27)[name = string("transpose_114")];
            tensor<int32, [6]> reshape_30 = reshape(shape = const_195, x = transpose_33)[name = string("reshape_30")];
            tensor<int32, [2]> reshape_31_shape_0 = const()[name = string("reshape_31_shape_0"), val = tensor<int32, [2]>([2, 3])];
            tensor<int32, [2, 3]> reshape_31 = reshape(shape = reshape_31_shape_0, x = reshape_30)[name = string("reshape_31")];
            tensor<int32, [2]> transpose_34_perm_0 = const()[name = string("transpose_34_perm_0"), val = tensor<int32, [2]>([1, 0])];
            tensor<int32, [1]> reshape_32_shape_0 = const()[name = string("reshape_32_shape_0"), val = tensor<int32, [1]>([-1])];
            tensor<int32, [3, 2]> transpose_34 = transpose(perm = transpose_34_perm_0, x = reshape_31)[name = string("transpose_113")];
            tensor<int32, [6]> reshape_32 = reshape(shape = reshape_32_shape_0, x = transpose_34)[name = string("reshape_32")];
            tensor<fp32, [1, 9, 64]> const_196 = const()[name = string("const_196"), val = tensor<fp32, [1, 9, 64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25668992)))];
            string pad_6_mode_0 = const()[name = string("pad_6_mode_0"), val = string("constant")];
            fp32 pad_6_constant_val_0 = const()[name = string("pad_6_constant_val_0"), val = fp32(0x0p+0)];
            tensor<fp32, [?, ?, ?]> pad_6 = pad(constant_val = pad_6_constant_val_0, mode = pad_6_mode_0, pad = reshape_32, x = const_196)[name = string("pad_6")];
            tensor<fp32, [1, 9, 64]> const_197 = const()[name = string("const_197"), val = tensor<fp32, [1, 9, 64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25671360)))];
            string pad_7_mode_0 = const()[name = string("pad_7_mode_0"), val = string("constant")];
            fp32 pad_7_constant_val_0 = const()[name = string("pad_7_constant_val_0"), val = fp32(0x0p+0)];
            tensor<fp32, [?, ?, ?]> pad_7 = pad(constant_val = pad_7_constant_val_0, mode = pad_7_mode_0, pad = reshape_32, x = const_197)[name = string("pad_7")];
            tensor<int32, [1]> const_198 = const()[name = string("const_198"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_199 = const()[name = string("const_199"), val = tensor<int32, [1]>([0])];
            int32 concat_29_axis_0 = const()[name = string("concat_29_axis_0"), val = int32(0)];
            bool concat_29_interleave_0 = const()[name = string("concat_29_interleave_0"), val = bool(false)];
            tensor<int32, [3]> concat_29 = concat(axis = concat_29_axis_0, interleave = concat_29_interleave_0, values = (const_198, expand_dims_32, const_199))[name = string("concat_29")];
            tensor<int32, [1]> const_200 = const()[name = string("const_200"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_201 = const()[name = string("const_201"), val = tensor<int32, [1]>([0])];
            int32 concat_30_axis_0 = const()[name = string("concat_30_axis_0"), val = int32(0)];
            bool concat_30_interleave_0 = const()[name = string("concat_30_interleave_0"), val = bool(false)];
            tensor<int32, [3]> concat_30 = concat(axis = concat_30_axis_0, interleave = concat_30_interleave_0, values = (const_200, expand_dims_33, const_201))[name = string("concat_30")];
            tensor<int32, [3]> slice_by_index_30_stride_0 = const()[name = string("slice_by_index_30_stride_0"), val = tensor<int32, [3]>([1, 1, 1])];
            tensor<bool, [3]> slice_by_index_30_begin_mask_0 = const()[name = string("slice_by_index_30_begin_mask_0"), val = tensor<bool, [3]>([true, false, true])];
            tensor<bool, [3]> slice_by_index_30_end_mask_0 = const()[name = string("slice_by_index_30_end_mask_0"), val = tensor<bool, [3]>([true, false, true])];
            tensor<fp32, [?, ?, ?]> slice_by_index_30 = slice_by_index(begin = concat_29, begin_mask = slice_by_index_30_begin_mask_0, end = concat_30, end_mask = slice_by_index_30_end_mask_0, stride = slice_by_index_30_stride_0, x = pad_6)[name = string("slice_by_index_30")];
            tensor<int32, [3]> slice_by_index_33_stride_0 = const()[name = string("slice_by_index_33_stride_0"), val = tensor<int32, [3]>([1, 1, 1])];
            tensor<bool, [3]> slice_by_index_33_begin_mask_0 = const()[name = string("slice_by_index_33_begin_mask_0"), val = tensor<bool, [3]>([true, false, true])];
            tensor<bool, [3]> slice_by_index_33_end_mask_0 = const()[name = string("slice_by_index_33_end_mask_0"), val = tensor<bool, [3]>([true, false, true])];
            tensor<fp32, [?, ?, ?]> slice_by_index_33 = slice_by_index(begin = concat_29, begin_mask = slice_by_index_33_begin_mask_0, end = concat_30, end_mask = slice_by_index_33_end_mask_0, stride = slice_by_index_33_stride_0, x = pad_7)[name = string("slice_by_index_33")];
            tensor<int32, [1]> expand_dims_34_axes_0 = const()[name = string("expand_dims_34_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp32, [1, ?, ?, ?]> expand_dims_34 = expand_dims(axes = expand_dims_34_axes_0, x = slice_by_index_30)[name = string("expand_dims_34")];
            tensor<int32, [1]> expand_dims_35_axes_0 = const()[name = string("expand_dims_35_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp32, [1, ?, ?, ?]> expand_dims_35 = expand_dims(axes = expand_dims_35_axes_0, x = slice_by_index_33)[name = string("expand_dims_35")];
            bool matmul_7_transpose_x_1 = const()[name = string("matmul_7_transpose_x_1"), val = bool(false)];
            bool matmul_7_transpose_y_1 = const()[name = string("matmul_7_transpose_y_1"), val = bool(true)];
            tensor<fp32, [1, 4, ?, ?]> matmul_7 = matmul(transpose_x = matmul_7_transpose_x_1, transpose_y = matmul_7_transpose_y_1, x = _inversed_real_div_7, y = expand_dims_34)[name = string("matmul_7")];
            tensor<int32, [4]> shape_6 = shape(x = matmul_7)[name = string("shape_6")];
            tensor<int32, [8]> const_206 = const()[name = string("const_206"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 1])];
            string pad_8_mode_0 = const()[name = string("pad_8_mode_0"), val = string("constant")];
            fp32 pad_8_constant_val_0 = const()[name = string("pad_8_constant_val_0"), val = fp32(0x0p+0)];
            tensor<fp32, [1, 4, ?, ?]> pad_8 = pad(constant_val = pad_8_constant_val_0, mode = pad_8_mode_0, pad = const_206, x = matmul_7)[name = string("pad_8")];
            int32 gather_15_batch_dims_0 = const()[name = string("gather_15_batch_dims_0"), val = int32(0)];
            bool gather_15_validate_indices_0 = const()[name = string("gather_15_validate_indices_0"), val = bool(false)];
            tensor<int32, [1]> select_13 = const()[name = string("select_13"), val = tensor<int32, [1]>([2])];
            int32 gather_15_axis_1 = const()[name = string("gather_15_axis_1"), val = int32(0)];
            tensor<int32, [1]> gather_15 = gather(axis = gather_15_axis_1, batch_dims = gather_15_batch_dims_0, indices = select_13, validate_indices = gather_15_validate_indices_0, x = shape_6)[name = string("gather_15")];
            tensor<int32, [1]> squeeze_14_axes_0 = const()[name = string("squeeze_14_axes_0"), val = tensor<int32, [1]>([0])];
            int32 squeeze_14 = squeeze(axes = squeeze_14_axes_0, x = gather_15)[name = string("squeeze_14")];
            tensor<int32, [1]> expand_dims_145_axes_0 = const()[name = string("expand_dims_145_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> expand_dims_145 = expand_dims(axes = expand_dims_145_axes_0, x = squeeze_14)[name = string("expand_dims_145")];
            tensor<int32, [1]> expand_dims_146 = const()[name = string("expand_dims_146"), val = tensor<int32, [1]>([2])];
            tensor<int32, [1]> expand_dims_113 = mul(x = expand_dims_145, y = expand_dims_146)[name = string("expand_dims_113")];
            tensor<int32, [1]> expand_dims_36 = const()[name = string("expand_dims_36"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> expand_dims_37 = const()[name = string("expand_dims_37"), val = tensor<int32, [1]>([4])];
            tensor<int32, [1]> expand_dims_110 = const()[name = string("expand_dims_110"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> expand_dims_39 = sub(x = expand_dims_145, y = expand_dims_110)[name = string("expand_dims_39")];
            tensor<int32, [1]> expand_dims_112 = const()[name = string("expand_dims_112"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> expand_dims_40 = add(x = expand_dims_145, y = expand_dims_112)[name = string("expand_dims_40")];
            tensor<int32, [1]> expand_dims_114 = const()[name = string("expand_dims_114"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> expand_dims_42 = sub(x = expand_dims_113, y = expand_dims_114)[name = string("expand_dims_42")];
            tensor<int32, [1]> const_214 = const()[name = string("const_214"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_215 = const()[name = string("const_215"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_216 = const()[name = string("const_216"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_217 = const()[name = string("const_217"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_218 = const()[name = string("const_218"), val = tensor<int32, [1]>([0])];
            int32 concat_33_axis_0 = const()[name = string("concat_33_axis_0"), val = int32(0)];
            bool concat_33_interleave_0 = const()[name = string("concat_33_interleave_0"), val = bool(false)];
            tensor<int32, [6]> concat_33 = concat(axis = concat_33_axis_0, interleave = concat_33_interleave_0, values = (const_214, expand_dims_39, const_215, const_216, const_217, const_218))[name = string("concat_33")];
            int32 concat_35_axis_0 = const()[name = string("concat_35_axis_0"), val = int32(0)];
            bool concat_35_interleave_0 = const()[name = string("concat_35_interleave_0"), val = bool(false)];
            tensor<int32, [4]> concat_35 = concat(axis = concat_35_axis_0, interleave = concat_35_interleave_0, values = (expand_dims_36, expand_dims_37, expand_dims_40, expand_dims_42))[name = string("concat_35")];
            tensor<int32, [2]> const_219 = const()[name = string("const_219"), val = tensor<int32, [2]>([-1, 2])];
            tensor<int32, [3, 2]> reshape_35 = reshape(shape = const_219, x = concat_33)[name = string("reshape_35")];
            tensor<int32, [3]> concat_34x = const()[name = string("concat_34x"), val = tensor<int32, [3]>([1, 4, -1])];
            tensor<fp32, [1, 4, ?]> reshape_36 = reshape(shape = concat_34x, x = pad_8)[name = string("reshape_36")];
            tensor<int32, [2]> slice_by_index_34_begin_0 = const()[name = string("slice_by_index_34_begin_0"), val = tensor<int32, [2]>([2, 0])];
            tensor<int32, [2]> slice_by_index_34_end_0 = const()[name = string("slice_by_index_34_end_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [2]> slice_by_index_34_stride_0 = const()[name = string("slice_by_index_34_stride_0"), val = tensor<int32, [2]>([-1, 1])];
            tensor<bool, [2]> slice_by_index_34_begin_mask_0 = const()[name = string("slice_by_index_34_begin_mask_0"), val = tensor<bool, [2]>([false, true])];
            tensor<bool, [2]> slice_by_index_34_end_mask_0 = const()[name = string("slice_by_index_34_end_mask_0"), val = tensor<bool, [2]>([true, true])];
            tensor<int32, [3, 2]> slice_by_index_34 = slice_by_index(begin = slice_by_index_34_begin_0, begin_mask = slice_by_index_34_begin_mask_0, end = slice_by_index_34_end_0, end_mask = slice_by_index_34_end_mask_0, stride = slice_by_index_34_stride_0, x = reshape_35)[name = string("slice_by_index_34")];
            tensor<int32, [1]> reshape_39_shape_0 = const()[name = string("reshape_39_shape_0"), val = tensor<int32, [1]>([-1])];
            tensor<int32, [6]> reshape_39 = reshape(shape = reshape_39_shape_0, x = slice_by_index_34)[name = string("reshape_39")];
            string pad_9_mode_0 = const()[name = string("pad_9_mode_0"), val = string("constant")];
            fp32 pad_9_constant_val_0 = const()[name = string("pad_9_constant_val_0"), val = fp32(0x0p+0)];
            tensor<fp32, [1, 4, ?]> pad_9 = pad(constant_val = pad_9_constant_val_0, mode = pad_9_mode_0, pad = reshape_39, x = reshape_36)[name = string("pad_9")];
            tensor<fp32, [1, 4, ?, ?]> reshape_40 = reshape(shape = concat_35, x = pad_9)[name = string("reshape_40")];
            tensor<int32, [1]> const_221 = const()[name = string("const_221"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_222 = const()[name = string("const_222"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_223 = const()[name = string("const_223"), val = tensor<int32, [1]>([0])];
            int32 concat_36_axis_0 = const()[name = string("concat_36_axis_0"), val = int32(0)];
            bool concat_36_interleave_0 = const()[name = string("concat_36_interleave_0"), val = bool(false)];
            tensor<int32, [4]> concat_36 = concat(axis = concat_36_axis_0, interleave = concat_36_interleave_0, values = (const_221, const_222, expand_dims_145, const_223))[name = string("concat_36")];
            tensor<int32, [4]> slice_by_index_36_begin_0 = const()[name = string("slice_by_index_36_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> slice_by_index_36_stride_0 = const()[name = string("slice_by_index_36_stride_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<bool, [4]> slice_by_index_36_begin_mask_0 = const()[name = string("slice_by_index_36_begin_mask_0"), val = tensor<bool, [4]>([true, true, false, true])];
            tensor<bool, [4]> slice_by_index_36_end_mask_0 = const()[name = string("slice_by_index_36_end_mask_0"), val = tensor<bool, [4]>([true, true, false, true])];
            tensor<fp32, [1, 4, ?, ?]> slice_by_index_36 = slice_by_index(begin = slice_by_index_36_begin_0, begin_mask = slice_by_index_36_begin_mask_0, end = concat_36, end_mask = slice_by_index_36_end_mask_0, stride = slice_by_index_36_stride_0, x = reshape_40)[name = string("slice_by_index_36")];
            tensor<int32, [1]> const_224 = const()[name = string("const_224"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_225 = const()[name = string("const_225"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_226 = const()[name = string("const_226"), val = tensor<int32, [1]>([0])];
            int32 concat_37_axis_0 = const()[name = string("concat_37_axis_0"), val = int32(0)];
            bool concat_37_interleave_0 = const()[name = string("concat_37_interleave_0"), val = bool(false)];
            tensor<int32, [4]> concat_37 = concat(axis = concat_37_axis_0, interleave = concat_37_interleave_0, values = (const_224, const_225, const_226, expand_dims_39))[name = string("concat_37")];
            tensor<int32, [4]> slice_by_index_38_end_0 = const()[name = string("slice_by_index_38_end_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> slice_by_index_38_stride_0 = const()[name = string("slice_by_index_38_stride_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<bool, [4]> slice_by_index_38_begin_mask_0 = const()[name = string("slice_by_index_38_begin_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<bool, [4]> slice_by_index_38_end_mask_0 = const()[name = string("slice_by_index_38_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp32, [1, 4, ?, ?]> slice_by_index_38 = slice_by_index(begin = concat_37, begin_mask = slice_by_index_38_begin_mask_0, end = slice_by_index_38_end_0, end_mask = slice_by_index_38_end_mask_0, stride = slice_by_index_38_stride_0, x = slice_by_index_36)[name = string("slice_by_index_38")];
            tensor<fp32, [1, 4, ?, ?]> add_23 = add(x = matmul_6, y = slice_by_index_38)[name = string("add_23")];
            fp32 const_227 = const()[name = string("const_227"), val = fp32(-0x1.388p+13)];
            tensor<fp32, [1, 4, ?, ?]> select_1 = select(a = const_227, b = add_23, cond = equal_1)[name = string("select_1")];
            int32 softmax_1_axis_0 = const()[name = string("softmax_1_axis_0"), val = int32(-1)];
            tensor<fp32, [1, 4, ?, ?]> softmax_1 = softmax(axis = softmax_1_axis_0, x = select_1)[name = string("softmax_1")];
            bool matmul_8_transpose_x_1 = const()[name = string("matmul_8_transpose_x_1"), val = bool(false)];
            bool matmul_8_transpose_y_1 = const()[name = string("matmul_8_transpose_y_1"), val = bool(true)];
            tensor<fp32, [1, 4, ?, 64]> matmul_8 = matmul(transpose_x = matmul_8_transpose_x_1, transpose_y = matmul_8_transpose_y_1, x = softmax_1, y = reshape_28)[name = string("matmul_8")];
            tensor<int32, [4]> shape_7 = shape(x = softmax_1)[name = string("shape_7")];
            int32 gather_18_batch_dims_0 = const()[name = string("gather_18_batch_dims_0"), val = int32(0)];
            bool gather_18_validate_indices_0 = const()[name = string("gather_18_validate_indices_0"), val = bool(false)];
            tensor<int32, [1]> select_14 = const()[name = string("select_14"), val = tensor<int32, [1]>([2])];
            int32 gather_18_axis_1 = const()[name = string("gather_18_axis_1"), val = int32(0)];
            tensor<int32, [1]> gather_18 = gather(axis = gather_18_axis_1, batch_dims = gather_18_batch_dims_0, indices = select_14, validate_indices = gather_18_validate_indices_0, x = shape_7)[name = string("gather_18")];
            tensor<int32, [1]> squeeze_17_axes_0 = const()[name = string("squeeze_17_axes_0"), val = tensor<int32, [1]>([0])];
            int32 squeeze_17 = squeeze(axes = squeeze_17_axes_0, x = gather_18)[name = string("squeeze_17")];
            tensor<int32, [1]> expand_dims_115_axes_0 = const()[name = string("expand_dims_115_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> expand_dims_115 = expand_dims(axes = expand_dims_115_axes_0, x = squeeze_17)[name = string("expand_dims_115")];
            tensor<int32, [1]> expand_dims_116 = const()[name = string("expand_dims_116"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> expand_dims_46 = sub(x = expand_dims_115, y = expand_dims_116)[name = string("expand_dims_46")];
            tensor<int32, [1]> expand_dims_43 = const()[name = string("expand_dims_43"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> expand_dims_44 = const()[name = string("expand_dims_44"), val = tensor<int32, [1]>([4])];
            tensor<int32, [1]> expand_dims_118 = const()[name = string("expand_dims_118"), val = tensor<int32, [1]>([2])];
            tensor<int32, [1]> expand_dims_47 = mul(x = expand_dims_115, y = expand_dims_118)[name = string("expand_dims_47")];
            tensor<int32, [1]> const_233 = const()[name = string("const_233"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_234 = const()[name = string("const_234"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_235 = const()[name = string("const_235"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_236 = const()[name = string("const_236"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_237 = const()[name = string("const_237"), val = tensor<int32, [1]>([0])];
            int32 concat_38_axis_0 = const()[name = string("concat_38_axis_0"), val = int32(0)];
            bool concat_38_interleave_0 = const()[name = string("concat_38_interleave_0"), val = bool(false)];
            tensor<int32, [6]> concat_38 = concat(axis = concat_38_axis_0, interleave = concat_38_interleave_0, values = (expand_dims_115, const_233, const_234, const_235, const_236, const_237))[name = string("concat_38")];
            tensor<int32, [1]> const_238 = const()[name = string("const_238"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_239 = const()[name = string("const_239"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_240 = const()[name = string("const_240"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_241 = const()[name = string("const_241"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_242 = const()[name = string("const_242"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_243 = const()[name = string("const_243"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_244 = const()[name = string("const_244"), val = tensor<int32, [1]>([0])];
            int32 concat_39_axis_0 = const()[name = string("concat_39_axis_0"), val = int32(0)];
            bool concat_39_interleave_0 = const()[name = string("concat_39_interleave_0"), val = bool(false)];
            tensor<int32, [8]> concat_39 = concat(axis = concat_39_axis_0, interleave = concat_39_interleave_0, values = (const_238, expand_dims_46, const_239, const_240, const_241, const_242, const_243, const_244))[name = string("concat_39")];
            int32 concat_40_axis_0 = const()[name = string("concat_40_axis_0"), val = int32(0)];
            bool concat_40_interleave_0 = const()[name = string("concat_40_interleave_0"), val = bool(false)];
            tensor<int32, [4]> concat_40 = concat(axis = concat_40_axis_0, interleave = concat_40_interleave_0, values = (expand_dims_43, expand_dims_44, expand_dims_115, expand_dims_47))[name = string("concat_40")];
            tensor<int32, [2]> const_245 = const()[name = string("const_245"), val = tensor<int32, [2]>([-1, 2])];
            tensor<int32, [3, 2]> reshape_41 = reshape(shape = const_245, x = concat_38)[name = string("reshape_41")];
            tensor<int32, [2]> const_246 = const()[name = string("const_246"), val = tensor<int32, [2]>([-1, 2])];
            tensor<int32, [4, 2]> reshape_42 = reshape(shape = const_246, x = concat_39)[name = string("reshape_42")];
            tensor<int32, [2]> slice_by_index_39_begin_0 = const()[name = string("slice_by_index_39_begin_0"), val = tensor<int32, [2]>([2, 0])];
            tensor<int32, [2]> slice_by_index_39_end_0 = const()[name = string("slice_by_index_39_end_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [2]> slice_by_index_39_stride_0 = const()[name = string("slice_by_index_39_stride_0"), val = tensor<int32, [2]>([-1, 1])];
            tensor<bool, [2]> slice_by_index_39_begin_mask_0 = const()[name = string("slice_by_index_39_begin_mask_0"), val = tensor<bool, [2]>([false, true])];
            tensor<bool, [2]> slice_by_index_39_end_mask_0 = const()[name = string("slice_by_index_39_end_mask_0"), val = tensor<bool, [2]>([true, true])];
            tensor<int32, [3, 2]> slice_by_index_39 = slice_by_index(begin = slice_by_index_39_begin_0, begin_mask = slice_by_index_39_begin_mask_0, end = slice_by_index_39_end_0, end_mask = slice_by_index_39_end_mask_0, stride = slice_by_index_39_stride_0, x = reshape_41)[name = string("slice_by_index_39")];
            tensor<int32, [2]> slice_by_index_40_begin_0 = const()[name = string("slice_by_index_40_begin_0"), val = tensor<int32, [2]>([3, 0])];
            tensor<int32, [2]> slice_by_index_40_end_0 = const()[name = string("slice_by_index_40_end_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [2]> slice_by_index_40_stride_0 = const()[name = string("slice_by_index_40_stride_0"), val = tensor<int32, [2]>([-1, 1])];
            tensor<bool, [2]> slice_by_index_40_begin_mask_0 = const()[name = string("slice_by_index_40_begin_mask_0"), val = tensor<bool, [2]>([false, true])];
            tensor<bool, [2]> slice_by_index_40_end_mask_0 = const()[name = string("slice_by_index_40_end_mask_0"), val = tensor<bool, [2]>([true, true])];
            tensor<int32, [4, 2]> slice_by_index_40 = slice_by_index(begin = slice_by_index_40_begin_0, begin_mask = slice_by_index_40_begin_mask_0, end = slice_by_index_40_end_0, end_mask = slice_by_index_40_end_mask_0, stride = slice_by_index_40_stride_0, x = reshape_42)[name = string("slice_by_index_40")];
            tensor<int32, [1]> reshape_46_shape_0 = const()[name = string("reshape_46_shape_0"), val = tensor<int32, [1]>([-1])];
            tensor<int32, [8]> reshape_46 = reshape(shape = reshape_46_shape_0, x = slice_by_index_40)[name = string("reshape_46")];
            string pad_10_mode_0 = const()[name = string("pad_10_mode_0"), val = string("constant")];
            fp32 pad_10_constant_val_0 = const()[name = string("pad_10_constant_val_0"), val = fp32(0x0p+0)];
            tensor<fp32, [1, 4, ?, ?]> pad_10 = pad(constant_val = pad_10_constant_val_0, mode = pad_10_mode_0, pad = reshape_46, x = softmax_1)[name = string("pad_10")];
            tensor<int32, [3]> concat_41x = const()[name = string("concat_41x"), val = tensor<int32, [3]>([1, 4, -1])];
            tensor<fp32, [1, 4, ?]> reshape_47 = reshape(shape = concat_41x, x = pad_10)[name = string("reshape_47")];
            tensor<int32, [1]> reshape_49_shape_0 = const()[name = string("reshape_49_shape_0"), val = tensor<int32, [1]>([-1])];
            tensor<int32, [6]> reshape_49 = reshape(shape = reshape_49_shape_0, x = slice_by_index_39)[name = string("reshape_49")];
            string pad_11_mode_0 = const()[name = string("pad_11_mode_0"), val = string("constant")];
            fp32 pad_11_constant_val_0 = const()[name = string("pad_11_constant_val_0"), val = fp32(0x0p+0)];
            tensor<fp32, [1, 4, ?]> pad_11 = pad(constant_val = pad_11_constant_val_0, mode = pad_11_mode_0, pad = reshape_49, x = reshape_47)[name = string("pad_11")];
            tensor<fp32, [1, 4, ?, ?]> reshape_50 = reshape(shape = concat_40, x = pad_11)[name = string("reshape_50")];
            tensor<int32, [4]> slice_by_index_41_begin_0 = const()[name = string("slice_by_index_41_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 1])];
            tensor<int32, [4]> slice_by_index_41_end_0 = const()[name = string("slice_by_index_41_end_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> slice_by_index_41_stride_0 = const()[name = string("slice_by_index_41_stride_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<bool, [4]> slice_by_index_41_begin_mask_0 = const()[name = string("slice_by_index_41_begin_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<bool, [4]> slice_by_index_41_end_mask_0 = const()[name = string("slice_by_index_41_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp32, [1, 4, ?, ?]> slice_by_index_41 = slice_by_index(begin = slice_by_index_41_begin_0, begin_mask = slice_by_index_41_begin_mask_0, end = slice_by_index_41_end_0, end_mask = slice_by_index_41_end_mask_0, stride = slice_by_index_41_stride_0, x = reshape_50)[name = string("slice_by_index_41")];
            bool matmul_9_transpose_x_0 = const()[name = string("matmul_9_transpose_x_0"), val = bool(false)];
            bool matmul_9_transpose_y_0 = const()[name = string("matmul_9_transpose_y_0"), val = bool(false)];
            tensor<fp32, [1, 4, ?, ?]> matmul_9 = matmul(transpose_x = matmul_9_transpose_x_0, transpose_y = matmul_9_transpose_y_0, x = slice_by_index_41, y = expand_dims_35)[name = string("matmul_9")];
            tensor<fp32, [1, 4, ?, 64]> add_25 = add(x = matmul_8, y = matmul_9)[name = string("add_25")];
            tensor<int32, [4]> transpose_43_perm_0 = const()[name = string("transpose_43_perm_0"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [3]> concat_27x = const()[name = string("concat_27x"), val = tensor<int32, [3]>([1, 256, -1])];
            tensor<fp32, [1, 4, 64, ?]> transpose_43 = transpose(perm = transpose_43_perm_0, x = add_25)[name = string("transpose_112")];
            tensor<fp32, [1, 256, ?]> reshape_51 = reshape(shape = concat_27x, x = transpose_43)[name = string("reshape_51")];
            tensor<fp32, [256, 256, 1]> const_249 = const()[name = string("const_249"), val = tensor<fp32, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25673728)))];
            tensor<fp32, [256]> const_250 = const()[name = string("const_250"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25935936)))];
            tensor<int32, [1]> conv_27_strides_0 = const()[name = string("conv_27_strides_0"), val = tensor<int32, [1]>([1])];
            string conv_27_pad_type_0 = const()[name = string("conv_27_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> conv_27_pad_0 = const()[name = string("conv_27_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> conv_27_dilations_0 = const()[name = string("conv_27_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 conv_27_groups_0 = const()[name = string("conv_27_groups_0"), val = int32(1)];
            tensor<fp32, [1, 256, ?]> conv_27 = conv(bias = const_250, dilations = conv_27_dilations_0, groups = conv_27_groups_0, pad = conv_27_pad_0, pad_type = conv_27_pad_type_0, strides = conv_27_strides_0, weight = const_249, x = reshape_51)[name = string("conv_27")];
            tensor<fp32, [1, 256, ?]> add_26 = add(x = transpose_30, y = conv_27)[name = string("add_26")];
            tensor<int32, [3]> transpose_44_perm_0 = const()[name = string("transpose_44_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp32, [256]> const_251 = const()[name = string("const_251"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25937024)))];
            tensor<fp32, [256]> const_252 = const()[name = string("const_252"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25938112)))];
            tensor<int32, [1]> layer_norm_8_axes_0 = const()[name = string("layer_norm_8_axes_0"), val = tensor<int32, [1]>([2])];
            fp32 layer_norm_8_epsilon_0 = const()[name = string("layer_norm_8_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp32, [1, ?, 256]> transpose_44 = transpose(perm = transpose_44_perm_0, x = add_26)[name = string("transpose_111")];
            tensor<fp32, [1, ?, 256]> layer_norm_8 = layer_norm(axes = layer_norm_8_axes_0, beta = const_252, epsilon = layer_norm_8_epsilon_0, gamma = const_251, x = transpose_44)[name = string("layer_norm_8")];
            tensor<int32, [3]> transpose_45_perm_0 = const()[name = string("transpose_45_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp32, [1, 256, ?]> transpose_45 = transpose(perm = transpose_45_perm_0, x = layer_norm_8)[name = string("transpose_110")];
            tensor<fp32, [1, 256, ?]> mul_54 = mul(x = transpose_45, y = text_mask)[name = string("mul_54")];
            tensor<fp32, [1024, 256, 1]> const_253 = const()[name = string("const_253"), val = tensor<fp32, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(25939200)))];
            tensor<fp32, [1024]> const_254 = const()[name = string("const_254"), val = tensor<fp32, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(26987840)))];
            tensor<int32, [1]> conv_28_strides_0 = const()[name = string("conv_28_strides_0"), val = tensor<int32, [1]>([1])];
            string conv_28_pad_type_0 = const()[name = string("conv_28_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> conv_28_pad_0 = const()[name = string("conv_28_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> conv_28_dilations_0 = const()[name = string("conv_28_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 conv_28_groups_0 = const()[name = string("conv_28_groups_0"), val = int32(1)];
            tensor<fp32, [1, 1024, ?]> conv_28 = conv(bias = const_254, dilations = conv_28_dilations_0, groups = conv_28_groups_0, pad = conv_28_pad_0, pad_type = conv_28_pad_type_0, strides = conv_28_strides_0, weight = const_253, x = mul_54)[name = string("conv_28")];
            tensor<fp32, [1, 1024, ?]> relu_1 = relu(x = conv_28)[name = string("relu_1")];
            tensor<fp32, [1, 1024, ?]> mul_55 = mul(x = relu_1, y = text_mask)[name = string("mul_55")];
            tensor<fp32, [256, 1024, 1]> const_255 = const()[name = string("const_255"), val = tensor<fp32, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(26992000)))];
            tensor<fp32, [256]> const_256 = const()[name = string("const_256"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(28040640)))];
            tensor<int32, [1]> conv_29_strides_0 = const()[name = string("conv_29_strides_0"), val = tensor<int32, [1]>([1])];
            string conv_29_pad_type_0 = const()[name = string("conv_29_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> conv_29_pad_0 = const()[name = string("conv_29_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> conv_29_dilations_0 = const()[name = string("conv_29_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 conv_29_groups_0 = const()[name = string("conv_29_groups_0"), val = int32(1)];
            tensor<fp32, [1, 256, ?]> conv_29 = conv(bias = const_256, dilations = conv_29_dilations_0, groups = conv_29_groups_0, pad = conv_29_pad_0, pad_type = conv_29_pad_type_0, strides = conv_29_strides_0, weight = const_255, x = mul_55)[name = string("conv_29")];
            tensor<fp32, [1, 256, ?]> mul_56 = mul(x = conv_29, y = text_mask)[name = string("mul_56")];
            tensor<fp32, [1, 256, ?]> add_27 = add(x = transpose_45, y = mul_56)[name = string("add_27")];
            tensor<int32, [3]> transpose_46_perm_0 = const()[name = string("transpose_46_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp32, [256]> const_257 = const()[name = string("const_257"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(28041728)))];
            tensor<fp32, [256]> const_258 = const()[name = string("const_258"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(28042816)))];
            tensor<int32, [1]> layer_norm_9_axes_0 = const()[name = string("layer_norm_9_axes_0"), val = tensor<int32, [1]>([2])];
            fp32 layer_norm_9_epsilon_0 = const()[name = string("layer_norm_9_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp32, [1, ?, 256]> transpose_46 = transpose(perm = transpose_46_perm_0, x = add_27)[name = string("transpose_109")];
            tensor<fp32, [1, ?, 256]> layer_norm_9 = layer_norm(axes = layer_norm_9_axes_0, beta = const_258, epsilon = layer_norm_9_epsilon_0, gamma = const_257, x = transpose_46)[name = string("layer_norm_9")];
            tensor<int32, [3]> transpose_47_perm_0 = const()[name = string("transpose_47_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp32, [256, 256, 1]> const_259 = const()[name = string("const_259"), val = tensor<fp32, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(28043904)))];
            tensor<fp32, [256]> const_260 = const()[name = string("const_260"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(28306112)))];
            tensor<int32, [1]> conv_30_strides_0 = const()[name = string("conv_30_strides_0"), val = tensor<int32, [1]>([1])];
            string conv_30_pad_type_0 = const()[name = string("conv_30_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> conv_30_pad_0 = const()[name = string("conv_30_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> conv_30_dilations_0 = const()[name = string("conv_30_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 conv_30_groups_0 = const()[name = string("conv_30_groups_0"), val = int32(1)];
            tensor<fp32, [1, 256, ?]> transpose_47 = transpose(perm = transpose_47_perm_0, x = layer_norm_9)[name = string("transpose_108")];
            tensor<fp32, [1, 256, ?]> conv_30 = conv(bias = const_260, dilations = conv_30_dilations_0, groups = conv_30_groups_0, pad = conv_30_pad_0, pad_type = conv_30_pad_type_0, strides = conv_30_strides_0, weight = const_259, x = transpose_47)[name = string("conv_30")];
            tensor<fp32, [256, 256, 1]> const_261 = const()[name = string("const_261"), val = tensor<fp32, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(28307200)))];
            tensor<fp32, [256]> const_262 = const()[name = string("const_262"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(28569408)))];
            tensor<int32, [1]> conv_31_strides_0 = const()[name = string("conv_31_strides_0"), val = tensor<int32, [1]>([1])];
            string conv_31_pad_type_0 = const()[name = string("conv_31_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> conv_31_pad_0 = const()[name = string("conv_31_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> conv_31_dilations_0 = const()[name = string("conv_31_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 conv_31_groups_0 = const()[name = string("conv_31_groups_0"), val = int32(1)];
            tensor<fp32, [1, 256, ?]> conv_31 = conv(bias = const_262, dilations = conv_31_dilations_0, groups = conv_31_groups_0, pad = conv_31_pad_0, pad_type = conv_31_pad_type_0, strides = conv_31_strides_0, weight = const_261, x = transpose_47)[name = string("conv_31")];
            tensor<fp32, [256, 256, 1]> const_263 = const()[name = string("const_263"), val = tensor<fp32, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(28570496)))];
            tensor<fp32, [256]> const_264 = const()[name = string("const_264"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(28832704)))];
            tensor<int32, [1]> conv_32_strides_0 = const()[name = string("conv_32_strides_0"), val = tensor<int32, [1]>([1])];
            string conv_32_pad_type_0 = const()[name = string("conv_32_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> conv_32_pad_0 = const()[name = string("conv_32_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> conv_32_dilations_0 = const()[name = string("conv_32_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 conv_32_groups_0 = const()[name = string("conv_32_groups_0"), val = int32(1)];
            tensor<fp32, [1, 256, ?]> conv_32 = conv(bias = const_264, dilations = conv_32_dilations_0, groups = conv_32_groups_0, pad = conv_32_pad_0, pad_type = conv_32_pad_type_0, strides = conv_32_strides_0, weight = const_263, x = transpose_47)[name = string("conv_32")];
            tensor<int32, [3]> shape_8 = shape(x = conv_31)[name = string("shape_8")];
            int32 gather_20_batch_dims_0 = const()[name = string("gather_20_batch_dims_0"), val = int32(0)];
            bool gather_20_validate_indices_0 = const()[name = string("gather_20_validate_indices_0"), val = bool(false)];
            tensor<int32, [1]> select_15 = const()[name = string("select_15"), val = tensor<int32, [1]>([2])];
            int32 gather_20_axis_1 = const()[name = string("gather_20_axis_1"), val = int32(0)];
            tensor<int32, [1]> gather_20 = gather(axis = gather_20_axis_1, batch_dims = gather_20_batch_dims_0, indices = select_15, validate_indices = gather_20_validate_indices_0, x = shape_8)[name = string("gather_20")];
            tensor<int32, [1]> squeeze_19_axes_0 = const()[name = string("squeeze_19_axes_0"), val = tensor<int32, [1]>([0])];
            int32 squeeze_19 = squeeze(axes = squeeze_19_axes_0, x = gather_20)[name = string("squeeze_19")];
            tensor<int32, [1]> expand_dims_49 = const()[name = string("expand_dims_49"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> expand_dims_51_axes_0 = const()[name = string("expand_dims_51_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> expand_dims_51 = expand_dims(axes = expand_dims_51_axes_0, x = squeeze_19)[name = string("expand_dims_51")];
            int32 const_268 = const()[name = string("const_268"), val = int32(5)];
            int32 sub_12 = sub(x = squeeze_19, y = const_268)[name = string("sub_12")];
            int32 const_269 = const()[name = string("const_269"), val = int32(5)];
            int32 sub_13 = sub(x = const_269, y = squeeze_19)[name = string("sub_13")];
            int32 const_270 = const()[name = string("const_270"), val = int32(2)];
            int32 mul_57 = mul(x = squeeze_19, y = const_270)[name = string("mul_57")];
            tensor<int32, [1]> const_273 = const()[name = string("const_273"), val = tensor<int32, [1]>([4])];
            tensor<int32, [1]> const_274 = const()[name = string("const_274"), val = tensor<int32, [1]>([64])];
            int32 concat_43_axis_0 = const()[name = string("concat_43_axis_0"), val = int32(0)];
            bool concat_43_interleave_0 = const()[name = string("concat_43_interleave_0"), val = bool(false)];
            tensor<int32, [4]> concat_43 = concat(axis = concat_43_axis_0, interleave = concat_43_interleave_0, values = (expand_dims_49, const_273, const_274, expand_dims_51))[name = string("concat_43")];
            int32 const_275 = const()[name = string("const_275"), val = int32(0)];
            int32 maximum_4 = maximum(x = sub_12, y = const_275)[name = string("maximum_4")];
            int32 const_276 = const()[name = string("const_276"), val = int32(0)];
            int32 maximum_5 = maximum(x = sub_13, y = const_276)[name = string("maximum_5")];
            tensor<int32, [4]> concat_42x = const()[name = string("concat_42x"), val = tensor<int32, [4]>([1, 4, 64, -1])];
            tensor<fp32, [1, 4, 64, ?]> reshape_52 = reshape(shape = concat_42x, x = conv_30)[name = string("reshape_52")];
            tensor<fp32, [1, 4, 64, ?]> reshape_53 = reshape(shape = concat_43, x = conv_31)[name = string("reshape_53")];
            tensor<fp32, [1, 4, 64, ?]> reshape_54 = reshape(shape = concat_43, x = conv_32)[name = string("reshape_54")];
            int32 add_28 = add(x = maximum_5, y = mul_57)[name = string("add_28")];
            tensor<int32, [1]> expand_dims_52_axes_0 = const()[name = string("expand_dims_52_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> expand_dims_52 = expand_dims(axes = expand_dims_52_axes_0, x = maximum_4)[name = string("expand_dims_52")];
            tensor<int32, [1]> expand_dims_53_axes_0 = const()[name = string("expand_dims_53_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> expand_dims_53 = expand_dims(axes = expand_dims_53_axes_0, x = maximum_5)[name = string("expand_dims_53")];
            tensor<int32, [4]> transpose_48_perm_0 = const()[name = string("transpose_48_perm_0"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [1]> expand_dims_119_axes_0 = const()[name = string("expand_dims_119_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> expand_dims_119 = expand_dims(axes = expand_dims_119_axes_0, x = add_28)[name = string("expand_dims_119")];
            tensor<int32, [1]> expand_dims_120 = const()[name = string("expand_dims_120"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> expand_dims_54 = sub(x = expand_dims_119, y = expand_dims_120)[name = string("expand_dims_54")];
            tensor<int32, [1]> const_279 = const()[name = string("const_279"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_280 = const()[name = string("const_280"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_281 = const()[name = string("const_281"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_282 = const()[name = string("const_282"), val = tensor<int32, [1]>([0])];
            int32 concat_45_axis_0 = const()[name = string("concat_45_axis_0"), val = int32(0)];
            bool concat_45_interleave_0 = const()[name = string("concat_45_interleave_0"), val = bool(false)];
            tensor<int32, [6]> concat_45 = concat(axis = concat_45_axis_0, interleave = concat_45_interleave_0, values = (const_279, const_280, expand_dims_52, expand_dims_52, const_281, const_282))[name = string("concat_45")];
            fp32 _inversed_real_div_8_y_0 = const()[name = string("_inversed_real_div_8_y_0"), val = fp32(0x1p-3)];
            tensor<fp32, [1, 4, ?, 64]> transpose_48 = transpose(perm = transpose_48_perm_0, x = reshape_52)[name = string("transpose_107")];
            tensor<fp32, [1, 4, ?, 64]> _inversed_real_div_8 = mul(x = transpose_48, y = _inversed_real_div_8_y_0)[name = string("_inversed_real_div_8")];
            tensor<int32, [2]> const_284 = const()[name = string("const_284"), val = tensor<int32, [2]>([-1, 2])];
            tensor<int32, [3, 2]> reshape_55 = reshape(shape = const_284, x = concat_45)[name = string("reshape_55")];
            bool matmul_10_transpose_x_0 = const()[name = string("matmul_10_transpose_x_0"), val = bool(false)];
            bool matmul_10_transpose_y_0 = const()[name = string("matmul_10_transpose_y_0"), val = bool(false)];
            tensor<fp32, [1, 4, ?, ?]> matmul_10 = matmul(transpose_x = matmul_10_transpose_x_0, transpose_y = matmul_10_transpose_y_0, x = _inversed_real_div_8, y = reshape_53)[name = string("matmul_10")];
            tensor<int32, [2]> slice_by_index_42_begin_0 = const()[name = string("slice_by_index_42_begin_0"), val = tensor<int32, [2]>([2, 0])];
            tensor<int32, [2]> slice_by_index_42_end_0 = const()[name = string("slice_by_index_42_end_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [2]> slice_by_index_42_stride_0 = const()[name = string("slice_by_index_42_stride_0"), val = tensor<int32, [2]>([-1, 1])];
            tensor<bool, [2]> slice_by_index_42_begin_mask_0 = const()[name = string("slice_by_index_42_begin_mask_0"), val = tensor<bool, [2]>([false, true])];
            tensor<bool, [2]> slice_by_index_42_end_mask_0 = const()[name = string("slice_by_index_42_end_mask_0"), val = tensor<bool, [2]>([true, true])];
            tensor<int32, [3, 2]> slice_by_index_42 = slice_by_index(begin = slice_by_index_42_begin_0, begin_mask = slice_by_index_42_begin_mask_0, end = slice_by_index_42_end_0, end_mask = slice_by_index_42_end_mask_0, stride = slice_by_index_42_stride_0, x = reshape_55)[name = string("slice_by_index_42")];
            tensor<int32, [2]> transpose_50_perm_0 = const()[name = string("transpose_50_perm_0"), val = tensor<int32, [2]>([1, 0])];
            tensor<int32, [1]> const_285 = const()[name = string("const_285"), val = tensor<int32, [1]>([-1])];
            tensor<int32, [2, 3]> transpose_50 = transpose(perm = transpose_50_perm_0, x = slice_by_index_42)[name = string("transpose_106")];
            tensor<int32, [6]> reshape_56 = reshape(shape = const_285, x = transpose_50)[name = string("reshape_56")];
            tensor<int32, [2]> reshape_57_shape_0 = const()[name = string("reshape_57_shape_0"), val = tensor<int32, [2]>([2, 3])];
            tensor<int32, [2, 3]> reshape_57 = reshape(shape = reshape_57_shape_0, x = reshape_56)[name = string("reshape_57")];
            tensor<int32, [2]> transpose_51_perm_0 = const()[name = string("transpose_51_perm_0"), val = tensor<int32, [2]>([1, 0])];
            tensor<int32, [1]> reshape_58_shape_0 = const()[name = string("reshape_58_shape_0"), val = tensor<int32, [1]>([-1])];
            tensor<int32, [3, 2]> transpose_51 = transpose(perm = transpose_51_perm_0, x = reshape_57)[name = string("transpose_105")];
            tensor<int32, [6]> reshape_58 = reshape(shape = reshape_58_shape_0, x = transpose_51)[name = string("reshape_58")];
            tensor<fp32, [1, 9, 64]> const_286 = const()[name = string("const_286"), val = tensor<fp32, [1, 9, 64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(28833792)))];
            string pad_12_mode_0 = const()[name = string("pad_12_mode_0"), val = string("constant")];
            fp32 pad_12_constant_val_0 = const()[name = string("pad_12_constant_val_0"), val = fp32(0x0p+0)];
            tensor<fp32, [?, ?, ?]> pad_12 = pad(constant_val = pad_12_constant_val_0, mode = pad_12_mode_0, pad = reshape_58, x = const_286)[name = string("pad_12")];
            tensor<fp32, [1, 9, 64]> const_287 = const()[name = string("const_287"), val = tensor<fp32, [1, 9, 64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(28836160)))];
            string pad_13_mode_0 = const()[name = string("pad_13_mode_0"), val = string("constant")];
            fp32 pad_13_constant_val_0 = const()[name = string("pad_13_constant_val_0"), val = fp32(0x0p+0)];
            tensor<fp32, [?, ?, ?]> pad_13 = pad(constant_val = pad_13_constant_val_0, mode = pad_13_mode_0, pad = reshape_58, x = const_287)[name = string("pad_13")];
            tensor<int32, [1]> const_288 = const()[name = string("const_288"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_289 = const()[name = string("const_289"), val = tensor<int32, [1]>([0])];
            int32 concat_46_axis_0 = const()[name = string("concat_46_axis_0"), val = int32(0)];
            bool concat_46_interleave_0 = const()[name = string("concat_46_interleave_0"), val = bool(false)];
            tensor<int32, [3]> concat_46 = concat(axis = concat_46_axis_0, interleave = concat_46_interleave_0, values = (const_288, expand_dims_53, const_289))[name = string("concat_46")];
            tensor<int32, [1]> const_290 = const()[name = string("const_290"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_291 = const()[name = string("const_291"), val = tensor<int32, [1]>([0])];
            int32 concat_47_axis_0 = const()[name = string("concat_47_axis_0"), val = int32(0)];
            bool concat_47_interleave_0 = const()[name = string("concat_47_interleave_0"), val = bool(false)];
            tensor<int32, [3]> concat_47 = concat(axis = concat_47_axis_0, interleave = concat_47_interleave_0, values = (const_290, expand_dims_54, const_291))[name = string("concat_47")];
            tensor<int32, [3]> slice_by_index_45_stride_0 = const()[name = string("slice_by_index_45_stride_0"), val = tensor<int32, [3]>([1, 1, 1])];
            tensor<bool, [3]> slice_by_index_45_begin_mask_0 = const()[name = string("slice_by_index_45_begin_mask_0"), val = tensor<bool, [3]>([true, false, true])];
            tensor<bool, [3]> slice_by_index_45_end_mask_0 = const()[name = string("slice_by_index_45_end_mask_0"), val = tensor<bool, [3]>([true, false, true])];
            tensor<fp32, [?, ?, ?]> slice_by_index_45 = slice_by_index(begin = concat_46, begin_mask = slice_by_index_45_begin_mask_0, end = concat_47, end_mask = slice_by_index_45_end_mask_0, stride = slice_by_index_45_stride_0, x = pad_12)[name = string("slice_by_index_45")];
            tensor<int32, [3]> slice_by_index_48_stride_0 = const()[name = string("slice_by_index_48_stride_0"), val = tensor<int32, [3]>([1, 1, 1])];
            tensor<bool, [3]> slice_by_index_48_begin_mask_0 = const()[name = string("slice_by_index_48_begin_mask_0"), val = tensor<bool, [3]>([true, false, true])];
            tensor<bool, [3]> slice_by_index_48_end_mask_0 = const()[name = string("slice_by_index_48_end_mask_0"), val = tensor<bool, [3]>([true, false, true])];
            tensor<fp32, [?, ?, ?]> slice_by_index_48 = slice_by_index(begin = concat_46, begin_mask = slice_by_index_48_begin_mask_0, end = concat_47, end_mask = slice_by_index_48_end_mask_0, stride = slice_by_index_48_stride_0, x = pad_13)[name = string("slice_by_index_48")];
            tensor<int32, [1]> expand_dims_55_axes_0 = const()[name = string("expand_dims_55_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp32, [1, ?, ?, ?]> expand_dims_55 = expand_dims(axes = expand_dims_55_axes_0, x = slice_by_index_45)[name = string("expand_dims_55")];
            tensor<int32, [1]> expand_dims_56_axes_0 = const()[name = string("expand_dims_56_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp32, [1, ?, ?, ?]> expand_dims_56 = expand_dims(axes = expand_dims_56_axes_0, x = slice_by_index_48)[name = string("expand_dims_56")];
            bool matmul_11_transpose_x_1 = const()[name = string("matmul_11_transpose_x_1"), val = bool(false)];
            bool matmul_11_transpose_y_1 = const()[name = string("matmul_11_transpose_y_1"), val = bool(true)];
            tensor<fp32, [1, 4, ?, ?]> matmul_11 = matmul(transpose_x = matmul_11_transpose_x_1, transpose_y = matmul_11_transpose_y_1, x = _inversed_real_div_8, y = expand_dims_55)[name = string("matmul_11")];
            tensor<int32, [4]> shape_10 = shape(x = matmul_11)[name = string("shape_10")];
            tensor<int32, [8]> const_296 = const()[name = string("const_296"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 1])];
            string pad_14_mode_0 = const()[name = string("pad_14_mode_0"), val = string("constant")];
            fp32 pad_14_constant_val_0 = const()[name = string("pad_14_constant_val_0"), val = fp32(0x0p+0)];
            tensor<fp32, [1, 4, ?, ?]> pad_14 = pad(constant_val = pad_14_constant_val_0, mode = pad_14_mode_0, pad = const_296, x = matmul_11)[name = string("pad_14")];
            int32 gather_24_batch_dims_0 = const()[name = string("gather_24_batch_dims_0"), val = int32(0)];
            bool gather_24_validate_indices_0 = const()[name = string("gather_24_validate_indices_0"), val = bool(false)];
            tensor<int32, [1]> select_17 = const()[name = string("select_17"), val = tensor<int32, [1]>([2])];
            int32 gather_24_axis_1 = const()[name = string("gather_24_axis_1"), val = int32(0)];
            tensor<int32, [1]> gather_24 = gather(axis = gather_24_axis_1, batch_dims = gather_24_batch_dims_0, indices = select_17, validate_indices = gather_24_validate_indices_0, x = shape_10)[name = string("gather_24")];
            tensor<int32, [1]> squeeze_23_axes_0 = const()[name = string("squeeze_23_axes_0"), val = tensor<int32, [1]>([0])];
            int32 squeeze_23 = squeeze(axes = squeeze_23_axes_0, x = gather_24)[name = string("squeeze_23")];
            tensor<int32, [1]> expand_dims_147_axes_0 = const()[name = string("expand_dims_147_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> expand_dims_147 = expand_dims(axes = expand_dims_147_axes_0, x = squeeze_23)[name = string("expand_dims_147")];
            tensor<int32, [1]> expand_dims_148 = const()[name = string("expand_dims_148"), val = tensor<int32, [1]>([2])];
            tensor<int32, [1]> expand_dims_125 = mul(x = expand_dims_147, y = expand_dims_148)[name = string("expand_dims_125")];
            tensor<int32, [1]> expand_dims_57 = const()[name = string("expand_dims_57"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> expand_dims_58 = const()[name = string("expand_dims_58"), val = tensor<int32, [1]>([4])];
            tensor<int32, [1]> expand_dims_122 = const()[name = string("expand_dims_122"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> expand_dims_60 = sub(x = expand_dims_147, y = expand_dims_122)[name = string("expand_dims_60")];
            tensor<int32, [1]> expand_dims_124 = const()[name = string("expand_dims_124"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> expand_dims_61 = add(x = expand_dims_147, y = expand_dims_124)[name = string("expand_dims_61")];
            tensor<int32, [1]> expand_dims_126 = const()[name = string("expand_dims_126"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> expand_dims_63 = sub(x = expand_dims_125, y = expand_dims_126)[name = string("expand_dims_63")];
            tensor<int32, [1]> const_304 = const()[name = string("const_304"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_305 = const()[name = string("const_305"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_306 = const()[name = string("const_306"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_307 = const()[name = string("const_307"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_308 = const()[name = string("const_308"), val = tensor<int32, [1]>([0])];
            int32 concat_50_axis_0 = const()[name = string("concat_50_axis_0"), val = int32(0)];
            bool concat_50_interleave_0 = const()[name = string("concat_50_interleave_0"), val = bool(false)];
            tensor<int32, [6]> concat_50 = concat(axis = concat_50_axis_0, interleave = concat_50_interleave_0, values = (const_304, expand_dims_60, const_305, const_306, const_307, const_308))[name = string("concat_50")];
            int32 concat_52_axis_0 = const()[name = string("concat_52_axis_0"), val = int32(0)];
            bool concat_52_interleave_0 = const()[name = string("concat_52_interleave_0"), val = bool(false)];
            tensor<int32, [4]> concat_52 = concat(axis = concat_52_axis_0, interleave = concat_52_interleave_0, values = (expand_dims_57, expand_dims_58, expand_dims_61, expand_dims_63))[name = string("concat_52")];
            tensor<int32, [2]> const_309 = const()[name = string("const_309"), val = tensor<int32, [2]>([-1, 2])];
            tensor<int32, [3, 2]> reshape_61 = reshape(shape = const_309, x = concat_50)[name = string("reshape_61")];
            tensor<int32, [3]> concat_51x = const()[name = string("concat_51x"), val = tensor<int32, [3]>([1, 4, -1])];
            tensor<fp32, [1, 4, ?]> reshape_62 = reshape(shape = concat_51x, x = pad_14)[name = string("reshape_62")];
            tensor<int32, [2]> slice_by_index_49_begin_0 = const()[name = string("slice_by_index_49_begin_0"), val = tensor<int32, [2]>([2, 0])];
            tensor<int32, [2]> slice_by_index_49_end_0 = const()[name = string("slice_by_index_49_end_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [2]> slice_by_index_49_stride_0 = const()[name = string("slice_by_index_49_stride_0"), val = tensor<int32, [2]>([-1, 1])];
            tensor<bool, [2]> slice_by_index_49_begin_mask_0 = const()[name = string("slice_by_index_49_begin_mask_0"), val = tensor<bool, [2]>([false, true])];
            tensor<bool, [2]> slice_by_index_49_end_mask_0 = const()[name = string("slice_by_index_49_end_mask_0"), val = tensor<bool, [2]>([true, true])];
            tensor<int32, [3, 2]> slice_by_index_49 = slice_by_index(begin = slice_by_index_49_begin_0, begin_mask = slice_by_index_49_begin_mask_0, end = slice_by_index_49_end_0, end_mask = slice_by_index_49_end_mask_0, stride = slice_by_index_49_stride_0, x = reshape_61)[name = string("slice_by_index_49")];
            tensor<int32, [1]> reshape_65_shape_0 = const()[name = string("reshape_65_shape_0"), val = tensor<int32, [1]>([-1])];
            tensor<int32, [6]> reshape_65 = reshape(shape = reshape_65_shape_0, x = slice_by_index_49)[name = string("reshape_65")];
            string pad_15_mode_0 = const()[name = string("pad_15_mode_0"), val = string("constant")];
            fp32 pad_15_constant_val_0 = const()[name = string("pad_15_constant_val_0"), val = fp32(0x0p+0)];
            tensor<fp32, [1, 4, ?]> pad_15 = pad(constant_val = pad_15_constant_val_0, mode = pad_15_mode_0, pad = reshape_65, x = reshape_62)[name = string("pad_15")];
            tensor<fp32, [1, 4, ?, ?]> reshape_66 = reshape(shape = concat_52, x = pad_15)[name = string("reshape_66")];
            tensor<int32, [1]> const_311 = const()[name = string("const_311"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_312 = const()[name = string("const_312"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_313 = const()[name = string("const_313"), val = tensor<int32, [1]>([0])];
            int32 concat_53_axis_0 = const()[name = string("concat_53_axis_0"), val = int32(0)];
            bool concat_53_interleave_0 = const()[name = string("concat_53_interleave_0"), val = bool(false)];
            tensor<int32, [4]> concat_53 = concat(axis = concat_53_axis_0, interleave = concat_53_interleave_0, values = (const_311, const_312, expand_dims_147, const_313))[name = string("concat_53")];
            tensor<int32, [4]> slice_by_index_51_begin_0 = const()[name = string("slice_by_index_51_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> slice_by_index_51_stride_0 = const()[name = string("slice_by_index_51_stride_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<bool, [4]> slice_by_index_51_begin_mask_0 = const()[name = string("slice_by_index_51_begin_mask_0"), val = tensor<bool, [4]>([true, true, false, true])];
            tensor<bool, [4]> slice_by_index_51_end_mask_0 = const()[name = string("slice_by_index_51_end_mask_0"), val = tensor<bool, [4]>([true, true, false, true])];
            tensor<fp32, [1, 4, ?, ?]> slice_by_index_51 = slice_by_index(begin = slice_by_index_51_begin_0, begin_mask = slice_by_index_51_begin_mask_0, end = concat_53, end_mask = slice_by_index_51_end_mask_0, stride = slice_by_index_51_stride_0, x = reshape_66)[name = string("slice_by_index_51")];
            tensor<int32, [1]> const_314 = const()[name = string("const_314"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_315 = const()[name = string("const_315"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_316 = const()[name = string("const_316"), val = tensor<int32, [1]>([0])];
            int32 concat_54_axis_0 = const()[name = string("concat_54_axis_0"), val = int32(0)];
            bool concat_54_interleave_0 = const()[name = string("concat_54_interleave_0"), val = bool(false)];
            tensor<int32, [4]> concat_54 = concat(axis = concat_54_axis_0, interleave = concat_54_interleave_0, values = (const_314, const_315, const_316, expand_dims_60))[name = string("concat_54")];
            tensor<int32, [4]> slice_by_index_53_end_0 = const()[name = string("slice_by_index_53_end_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> slice_by_index_53_stride_0 = const()[name = string("slice_by_index_53_stride_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<bool, [4]> slice_by_index_53_begin_mask_0 = const()[name = string("slice_by_index_53_begin_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<bool, [4]> slice_by_index_53_end_mask_0 = const()[name = string("slice_by_index_53_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp32, [1, 4, ?, ?]> slice_by_index_53 = slice_by_index(begin = concat_54, begin_mask = slice_by_index_53_begin_mask_0, end = slice_by_index_53_end_0, end_mask = slice_by_index_53_end_mask_0, stride = slice_by_index_53_stride_0, x = slice_by_index_51)[name = string("slice_by_index_53")];
            tensor<fp32, [1, 4, ?, ?]> add_30 = add(x = matmul_10, y = slice_by_index_53)[name = string("add_30")];
            fp32 const_317 = const()[name = string("const_317"), val = fp32(-0x1.388p+13)];
            tensor<fp32, [1, 4, ?, ?]> select_2 = select(a = const_317, b = add_30, cond = equal_1)[name = string("select_2")];
            int32 softmax_2_axis_0 = const()[name = string("softmax_2_axis_0"), val = int32(-1)];
            tensor<fp32, [1, 4, ?, ?]> softmax_2 = softmax(axis = softmax_2_axis_0, x = select_2)[name = string("softmax_2")];
            bool matmul_12_transpose_x_1 = const()[name = string("matmul_12_transpose_x_1"), val = bool(false)];
            bool matmul_12_transpose_y_1 = const()[name = string("matmul_12_transpose_y_1"), val = bool(true)];
            tensor<fp32, [1, 4, ?, 64]> matmul_12 = matmul(transpose_x = matmul_12_transpose_x_1, transpose_y = matmul_12_transpose_y_1, x = softmax_2, y = reshape_54)[name = string("matmul_12")];
            tensor<int32, [4]> shape_11 = shape(x = softmax_2)[name = string("shape_11")];
            int32 gather_27_batch_dims_0 = const()[name = string("gather_27_batch_dims_0"), val = int32(0)];
            bool gather_27_validate_indices_0 = const()[name = string("gather_27_validate_indices_0"), val = bool(false)];
            tensor<int32, [1]> select_18 = const()[name = string("select_18"), val = tensor<int32, [1]>([2])];
            int32 gather_27_axis_1 = const()[name = string("gather_27_axis_1"), val = int32(0)];
            tensor<int32, [1]> gather_27 = gather(axis = gather_27_axis_1, batch_dims = gather_27_batch_dims_0, indices = select_18, validate_indices = gather_27_validate_indices_0, x = shape_11)[name = string("gather_27")];
            tensor<int32, [1]> squeeze_26_axes_0 = const()[name = string("squeeze_26_axes_0"), val = tensor<int32, [1]>([0])];
            int32 squeeze_26 = squeeze(axes = squeeze_26_axes_0, x = gather_27)[name = string("squeeze_26")];
            tensor<int32, [1]> expand_dims_127_axes_0 = const()[name = string("expand_dims_127_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> expand_dims_127 = expand_dims(axes = expand_dims_127_axes_0, x = squeeze_26)[name = string("expand_dims_127")];
            tensor<int32, [1]> expand_dims_128 = const()[name = string("expand_dims_128"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> expand_dims_67 = sub(x = expand_dims_127, y = expand_dims_128)[name = string("expand_dims_67")];
            tensor<int32, [1]> expand_dims_64 = const()[name = string("expand_dims_64"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> expand_dims_65 = const()[name = string("expand_dims_65"), val = tensor<int32, [1]>([4])];
            tensor<int32, [1]> expand_dims_130 = const()[name = string("expand_dims_130"), val = tensor<int32, [1]>([2])];
            tensor<int32, [1]> expand_dims_68 = mul(x = expand_dims_127, y = expand_dims_130)[name = string("expand_dims_68")];
            tensor<int32, [1]> const_323 = const()[name = string("const_323"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_324 = const()[name = string("const_324"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_325 = const()[name = string("const_325"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_326 = const()[name = string("const_326"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_327 = const()[name = string("const_327"), val = tensor<int32, [1]>([0])];
            int32 concat_55_axis_0 = const()[name = string("concat_55_axis_0"), val = int32(0)];
            bool concat_55_interleave_0 = const()[name = string("concat_55_interleave_0"), val = bool(false)];
            tensor<int32, [6]> concat_55 = concat(axis = concat_55_axis_0, interleave = concat_55_interleave_0, values = (expand_dims_127, const_323, const_324, const_325, const_326, const_327))[name = string("concat_55")];
            tensor<int32, [1]> const_328 = const()[name = string("const_328"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_329 = const()[name = string("const_329"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_330 = const()[name = string("const_330"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_331 = const()[name = string("const_331"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_332 = const()[name = string("const_332"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_333 = const()[name = string("const_333"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_334 = const()[name = string("const_334"), val = tensor<int32, [1]>([0])];
            int32 concat_56_axis_0 = const()[name = string("concat_56_axis_0"), val = int32(0)];
            bool concat_56_interleave_0 = const()[name = string("concat_56_interleave_0"), val = bool(false)];
            tensor<int32, [8]> concat_56 = concat(axis = concat_56_axis_0, interleave = concat_56_interleave_0, values = (const_328, expand_dims_67, const_329, const_330, const_331, const_332, const_333, const_334))[name = string("concat_56")];
            int32 concat_57_axis_0 = const()[name = string("concat_57_axis_0"), val = int32(0)];
            bool concat_57_interleave_0 = const()[name = string("concat_57_interleave_0"), val = bool(false)];
            tensor<int32, [4]> concat_57 = concat(axis = concat_57_axis_0, interleave = concat_57_interleave_0, values = (expand_dims_64, expand_dims_65, expand_dims_127, expand_dims_68))[name = string("concat_57")];
            tensor<int32, [2]> const_335 = const()[name = string("const_335"), val = tensor<int32, [2]>([-1, 2])];
            tensor<int32, [3, 2]> reshape_67 = reshape(shape = const_335, x = concat_55)[name = string("reshape_67")];
            tensor<int32, [2]> const_336 = const()[name = string("const_336"), val = tensor<int32, [2]>([-1, 2])];
            tensor<int32, [4, 2]> reshape_68 = reshape(shape = const_336, x = concat_56)[name = string("reshape_68")];
            tensor<int32, [2]> slice_by_index_54_begin_0 = const()[name = string("slice_by_index_54_begin_0"), val = tensor<int32, [2]>([2, 0])];
            tensor<int32, [2]> slice_by_index_54_end_0 = const()[name = string("slice_by_index_54_end_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [2]> slice_by_index_54_stride_0 = const()[name = string("slice_by_index_54_stride_0"), val = tensor<int32, [2]>([-1, 1])];
            tensor<bool, [2]> slice_by_index_54_begin_mask_0 = const()[name = string("slice_by_index_54_begin_mask_0"), val = tensor<bool, [2]>([false, true])];
            tensor<bool, [2]> slice_by_index_54_end_mask_0 = const()[name = string("slice_by_index_54_end_mask_0"), val = tensor<bool, [2]>([true, true])];
            tensor<int32, [3, 2]> slice_by_index_54 = slice_by_index(begin = slice_by_index_54_begin_0, begin_mask = slice_by_index_54_begin_mask_0, end = slice_by_index_54_end_0, end_mask = slice_by_index_54_end_mask_0, stride = slice_by_index_54_stride_0, x = reshape_67)[name = string("slice_by_index_54")];
            tensor<int32, [2]> slice_by_index_55_begin_0 = const()[name = string("slice_by_index_55_begin_0"), val = tensor<int32, [2]>([3, 0])];
            tensor<int32, [2]> slice_by_index_55_end_0 = const()[name = string("slice_by_index_55_end_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [2]> slice_by_index_55_stride_0 = const()[name = string("slice_by_index_55_stride_0"), val = tensor<int32, [2]>([-1, 1])];
            tensor<bool, [2]> slice_by_index_55_begin_mask_0 = const()[name = string("slice_by_index_55_begin_mask_0"), val = tensor<bool, [2]>([false, true])];
            tensor<bool, [2]> slice_by_index_55_end_mask_0 = const()[name = string("slice_by_index_55_end_mask_0"), val = tensor<bool, [2]>([true, true])];
            tensor<int32, [4, 2]> slice_by_index_55 = slice_by_index(begin = slice_by_index_55_begin_0, begin_mask = slice_by_index_55_begin_mask_0, end = slice_by_index_55_end_0, end_mask = slice_by_index_55_end_mask_0, stride = slice_by_index_55_stride_0, x = reshape_68)[name = string("slice_by_index_55")];
            tensor<int32, [1]> reshape_72_shape_0 = const()[name = string("reshape_72_shape_0"), val = tensor<int32, [1]>([-1])];
            tensor<int32, [8]> reshape_72 = reshape(shape = reshape_72_shape_0, x = slice_by_index_55)[name = string("reshape_72")];
            string pad_16_mode_0 = const()[name = string("pad_16_mode_0"), val = string("constant")];
            fp32 pad_16_constant_val_0 = const()[name = string("pad_16_constant_val_0"), val = fp32(0x0p+0)];
            tensor<fp32, [1, 4, ?, ?]> pad_16 = pad(constant_val = pad_16_constant_val_0, mode = pad_16_mode_0, pad = reshape_72, x = softmax_2)[name = string("pad_16")];
            tensor<int32, [3]> concat_58x = const()[name = string("concat_58x"), val = tensor<int32, [3]>([1, 4, -1])];
            tensor<fp32, [1, 4, ?]> reshape_73 = reshape(shape = concat_58x, x = pad_16)[name = string("reshape_73")];
            tensor<int32, [1]> reshape_75_shape_0 = const()[name = string("reshape_75_shape_0"), val = tensor<int32, [1]>([-1])];
            tensor<int32, [6]> reshape_75 = reshape(shape = reshape_75_shape_0, x = slice_by_index_54)[name = string("reshape_75")];
            string pad_17_mode_0 = const()[name = string("pad_17_mode_0"), val = string("constant")];
            fp32 pad_17_constant_val_0 = const()[name = string("pad_17_constant_val_0"), val = fp32(0x0p+0)];
            tensor<fp32, [1, 4, ?]> pad_17 = pad(constant_val = pad_17_constant_val_0, mode = pad_17_mode_0, pad = reshape_75, x = reshape_73)[name = string("pad_17")];
            tensor<fp32, [1, 4, ?, ?]> reshape_76 = reshape(shape = concat_57, x = pad_17)[name = string("reshape_76")];
            tensor<int32, [4]> slice_by_index_56_begin_0 = const()[name = string("slice_by_index_56_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 1])];
            tensor<int32, [4]> slice_by_index_56_end_0 = const()[name = string("slice_by_index_56_end_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> slice_by_index_56_stride_0 = const()[name = string("slice_by_index_56_stride_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<bool, [4]> slice_by_index_56_begin_mask_0 = const()[name = string("slice_by_index_56_begin_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<bool, [4]> slice_by_index_56_end_mask_0 = const()[name = string("slice_by_index_56_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp32, [1, 4, ?, ?]> slice_by_index_56 = slice_by_index(begin = slice_by_index_56_begin_0, begin_mask = slice_by_index_56_begin_mask_0, end = slice_by_index_56_end_0, end_mask = slice_by_index_56_end_mask_0, stride = slice_by_index_56_stride_0, x = reshape_76)[name = string("slice_by_index_56")];
            bool matmul_13_transpose_x_0 = const()[name = string("matmul_13_transpose_x_0"), val = bool(false)];
            bool matmul_13_transpose_y_0 = const()[name = string("matmul_13_transpose_y_0"), val = bool(false)];
            tensor<fp32, [1, 4, ?, ?]> matmul_13 = matmul(transpose_x = matmul_13_transpose_x_0, transpose_y = matmul_13_transpose_y_0, x = slice_by_index_56, y = expand_dims_56)[name = string("matmul_13")];
            tensor<fp32, [1, 4, ?, 64]> add_32 = add(x = matmul_12, y = matmul_13)[name = string("add_32")];
            tensor<int32, [4]> transpose_60_perm_0 = const()[name = string("transpose_60_perm_0"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [3]> concat_44x = const()[name = string("concat_44x"), val = tensor<int32, [3]>([1, 256, -1])];
            tensor<fp32, [1, 4, 64, ?]> transpose_60 = transpose(perm = transpose_60_perm_0, x = add_32)[name = string("transpose_104")];
            tensor<fp32, [1, 256, ?]> reshape_77 = reshape(shape = concat_44x, x = transpose_60)[name = string("reshape_77")];
            tensor<fp32, [256, 256, 1]> const_339 = const()[name = string("const_339"), val = tensor<fp32, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(28838528)))];
            tensor<fp32, [256]> const_340 = const()[name = string("const_340"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29100736)))];
            tensor<int32, [1]> conv_33_strides_0 = const()[name = string("conv_33_strides_0"), val = tensor<int32, [1]>([1])];
            string conv_33_pad_type_0 = const()[name = string("conv_33_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> conv_33_pad_0 = const()[name = string("conv_33_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> conv_33_dilations_0 = const()[name = string("conv_33_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 conv_33_groups_0 = const()[name = string("conv_33_groups_0"), val = int32(1)];
            tensor<fp32, [1, 256, ?]> conv_33 = conv(bias = const_340, dilations = conv_33_dilations_0, groups = conv_33_groups_0, pad = conv_33_pad_0, pad_type = conv_33_pad_type_0, strides = conv_33_strides_0, weight = const_339, x = reshape_77)[name = string("conv_33")];
            tensor<fp32, [1, 256, ?]> add_33 = add(x = transpose_47, y = conv_33)[name = string("add_33")];
            tensor<int32, [3]> transpose_61_perm_0 = const()[name = string("transpose_61_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp32, [256]> const_341 = const()[name = string("const_341"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29101824)))];
            tensor<fp32, [256]> const_342 = const()[name = string("const_342"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29102912)))];
            tensor<int32, [1]> layer_norm_10_axes_0 = const()[name = string("layer_norm_10_axes_0"), val = tensor<int32, [1]>([2])];
            fp32 layer_norm_10_epsilon_0 = const()[name = string("layer_norm_10_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp32, [1, ?, 256]> transpose_61 = transpose(perm = transpose_61_perm_0, x = add_33)[name = string("transpose_103")];
            tensor<fp32, [1, ?, 256]> layer_norm_10 = layer_norm(axes = layer_norm_10_axes_0, beta = const_342, epsilon = layer_norm_10_epsilon_0, gamma = const_341, x = transpose_61)[name = string("layer_norm_10")];
            tensor<int32, [3]> transpose_62_perm_0 = const()[name = string("transpose_62_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp32, [1, 256, ?]> transpose_62 = transpose(perm = transpose_62_perm_0, x = layer_norm_10)[name = string("transpose_102")];
            tensor<fp32, [1, 256, ?]> mul_63 = mul(x = transpose_62, y = text_mask)[name = string("mul_63")];
            tensor<fp32, [1024, 256, 1]> const_343 = const()[name = string("const_343"), val = tensor<fp32, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(29104000)))];
            tensor<fp32, [1024]> const_344 = const()[name = string("const_344"), val = tensor<fp32, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(30152640)))];
            tensor<int32, [1]> conv_34_strides_0 = const()[name = string("conv_34_strides_0"), val = tensor<int32, [1]>([1])];
            string conv_34_pad_type_0 = const()[name = string("conv_34_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> conv_34_pad_0 = const()[name = string("conv_34_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> conv_34_dilations_0 = const()[name = string("conv_34_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 conv_34_groups_0 = const()[name = string("conv_34_groups_0"), val = int32(1)];
            tensor<fp32, [1, 1024, ?]> conv_34 = conv(bias = const_344, dilations = conv_34_dilations_0, groups = conv_34_groups_0, pad = conv_34_pad_0, pad_type = conv_34_pad_type_0, strides = conv_34_strides_0, weight = const_343, x = mul_63)[name = string("conv_34")];
            tensor<fp32, [1, 1024, ?]> relu_2 = relu(x = conv_34)[name = string("relu_2")];
            tensor<fp32, [1, 1024, ?]> mul_64 = mul(x = relu_2, y = text_mask)[name = string("mul_64")];
            tensor<fp32, [256, 1024, 1]> const_345 = const()[name = string("const_345"), val = tensor<fp32, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(30156800)))];
            tensor<fp32, [256]> const_346 = const()[name = string("const_346"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(31205440)))];
            tensor<int32, [1]> conv_35_strides_0 = const()[name = string("conv_35_strides_0"), val = tensor<int32, [1]>([1])];
            string conv_35_pad_type_0 = const()[name = string("conv_35_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> conv_35_pad_0 = const()[name = string("conv_35_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> conv_35_dilations_0 = const()[name = string("conv_35_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 conv_35_groups_0 = const()[name = string("conv_35_groups_0"), val = int32(1)];
            tensor<fp32, [1, 256, ?]> conv_35 = conv(bias = const_346, dilations = conv_35_dilations_0, groups = conv_35_groups_0, pad = conv_35_pad_0, pad_type = conv_35_pad_type_0, strides = conv_35_strides_0, weight = const_345, x = mul_64)[name = string("conv_35")];
            tensor<fp32, [1, 256, ?]> mul_65 = mul(x = conv_35, y = text_mask)[name = string("mul_65")];
            tensor<fp32, [1, 256, ?]> add_34 = add(x = transpose_62, y = mul_65)[name = string("add_34")];
            tensor<int32, [3]> transpose_63_perm_0 = const()[name = string("transpose_63_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp32, [256]> const_347 = const()[name = string("const_347"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(31206528)))];
            tensor<fp32, [256]> const_348 = const()[name = string("const_348"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(31207616)))];
            tensor<int32, [1]> layer_norm_11_axes_0 = const()[name = string("layer_norm_11_axes_0"), val = tensor<int32, [1]>([2])];
            fp32 layer_norm_11_epsilon_0 = const()[name = string("layer_norm_11_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp32, [1, ?, 256]> transpose_63 = transpose(perm = transpose_63_perm_0, x = add_34)[name = string("transpose_101")];
            tensor<fp32, [1, ?, 256]> layer_norm_11 = layer_norm(axes = layer_norm_11_axes_0, beta = const_348, epsilon = layer_norm_11_epsilon_0, gamma = const_347, x = transpose_63)[name = string("layer_norm_11")];
            tensor<int32, [3]> transpose_64_perm_0 = const()[name = string("transpose_64_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp32, [256, 256, 1]> const_349 = const()[name = string("const_349"), val = tensor<fp32, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(31208704)))];
            tensor<fp32, [256]> const_350 = const()[name = string("const_350"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(31470912)))];
            tensor<int32, [1]> conv_36_strides_0 = const()[name = string("conv_36_strides_0"), val = tensor<int32, [1]>([1])];
            string conv_36_pad_type_0 = const()[name = string("conv_36_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> conv_36_pad_0 = const()[name = string("conv_36_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> conv_36_dilations_0 = const()[name = string("conv_36_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 conv_36_groups_0 = const()[name = string("conv_36_groups_0"), val = int32(1)];
            tensor<fp32, [1, 256, ?]> transpose_64 = transpose(perm = transpose_64_perm_0, x = layer_norm_11)[name = string("transpose_100")];
            tensor<fp32, [1, 256, ?]> conv_36 = conv(bias = const_350, dilations = conv_36_dilations_0, groups = conv_36_groups_0, pad = conv_36_pad_0, pad_type = conv_36_pad_type_0, strides = conv_36_strides_0, weight = const_349, x = transpose_64)[name = string("conv_36")];
            tensor<fp32, [256, 256, 1]> const_351 = const()[name = string("const_351"), val = tensor<fp32, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(31472000)))];
            tensor<fp32, [256]> const_352 = const()[name = string("const_352"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(31734208)))];
            tensor<int32, [1]> conv_37_strides_0 = const()[name = string("conv_37_strides_0"), val = tensor<int32, [1]>([1])];
            string conv_37_pad_type_0 = const()[name = string("conv_37_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> conv_37_pad_0 = const()[name = string("conv_37_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> conv_37_dilations_0 = const()[name = string("conv_37_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 conv_37_groups_0 = const()[name = string("conv_37_groups_0"), val = int32(1)];
            tensor<fp32, [1, 256, ?]> conv_37 = conv(bias = const_352, dilations = conv_37_dilations_0, groups = conv_37_groups_0, pad = conv_37_pad_0, pad_type = conv_37_pad_type_0, strides = conv_37_strides_0, weight = const_351, x = transpose_64)[name = string("conv_37")];
            tensor<fp32, [256, 256, 1]> const_353 = const()[name = string("const_353"), val = tensor<fp32, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(31735296)))];
            tensor<fp32, [256]> const_354 = const()[name = string("const_354"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(31997504)))];
            tensor<int32, [1]> conv_38_strides_0 = const()[name = string("conv_38_strides_0"), val = tensor<int32, [1]>([1])];
            string conv_38_pad_type_0 = const()[name = string("conv_38_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> conv_38_pad_0 = const()[name = string("conv_38_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> conv_38_dilations_0 = const()[name = string("conv_38_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 conv_38_groups_0 = const()[name = string("conv_38_groups_0"), val = int32(1)];
            tensor<fp32, [1, 256, ?]> conv_38 = conv(bias = const_354, dilations = conv_38_dilations_0, groups = conv_38_groups_0, pad = conv_38_pad_0, pad_type = conv_38_pad_type_0, strides = conv_38_strides_0, weight = const_353, x = transpose_64)[name = string("conv_38")];
            tensor<int32, [3]> shape_12 = shape(x = conv_37)[name = string("shape_12")];
            int32 gather_29_batch_dims_0 = const()[name = string("gather_29_batch_dims_0"), val = int32(0)];
            bool gather_29_validate_indices_0 = const()[name = string("gather_29_validate_indices_0"), val = bool(false)];
            tensor<int32, [1]> select_19 = const()[name = string("select_19"), val = tensor<int32, [1]>([2])];
            int32 gather_29_axis_1 = const()[name = string("gather_29_axis_1"), val = int32(0)];
            tensor<int32, [1]> gather_29 = gather(axis = gather_29_axis_1, batch_dims = gather_29_batch_dims_0, indices = select_19, validate_indices = gather_29_validate_indices_0, x = shape_12)[name = string("gather_29")];
            tensor<int32, [1]> squeeze_28_axes_0 = const()[name = string("squeeze_28_axes_0"), val = tensor<int32, [1]>([0])];
            int32 squeeze_28 = squeeze(axes = squeeze_28_axes_0, x = gather_29)[name = string("squeeze_28")];
            tensor<int32, [1]> expand_dims_70 = const()[name = string("expand_dims_70"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> expand_dims_72_axes_0 = const()[name = string("expand_dims_72_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> expand_dims_72 = expand_dims(axes = expand_dims_72_axes_0, x = squeeze_28)[name = string("expand_dims_72")];
            int32 const_358 = const()[name = string("const_358"), val = int32(5)];
            int32 sub_18 = sub(x = squeeze_28, y = const_358)[name = string("sub_18")];
            int32 const_359 = const()[name = string("const_359"), val = int32(5)];
            int32 sub_19 = sub(x = const_359, y = squeeze_28)[name = string("sub_19")];
            int32 const_360 = const()[name = string("const_360"), val = int32(2)];
            int32 mul_66 = mul(x = squeeze_28, y = const_360)[name = string("mul_66")];
            tensor<int32, [1]> const_363 = const()[name = string("const_363"), val = tensor<int32, [1]>([4])];
            tensor<int32, [1]> const_364 = const()[name = string("const_364"), val = tensor<int32, [1]>([64])];
            int32 concat_60_axis_0 = const()[name = string("concat_60_axis_0"), val = int32(0)];
            bool concat_60_interleave_0 = const()[name = string("concat_60_interleave_0"), val = bool(false)];
            tensor<int32, [4]> concat_60 = concat(axis = concat_60_axis_0, interleave = concat_60_interleave_0, values = (expand_dims_70, const_363, const_364, expand_dims_72))[name = string("concat_60")];
            int32 const_365 = const()[name = string("const_365"), val = int32(0)];
            int32 maximum_6 = maximum(x = sub_18, y = const_365)[name = string("maximum_6")];
            int32 const_366 = const()[name = string("const_366"), val = int32(0)];
            int32 maximum_7 = maximum(x = sub_19, y = const_366)[name = string("maximum_7")];
            tensor<int32, [4]> concat_59x = const()[name = string("concat_59x"), val = tensor<int32, [4]>([1, 4, 64, -1])];
            tensor<fp32, [1, 4, 64, ?]> reshape_78 = reshape(shape = concat_59x, x = conv_36)[name = string("reshape_78")];
            tensor<fp32, [1, 4, 64, ?]> reshape_79 = reshape(shape = concat_60, x = conv_37)[name = string("reshape_79")];
            tensor<fp32, [1, 4, 64, ?]> reshape_80 = reshape(shape = concat_60, x = conv_38)[name = string("reshape_80")];
            int32 add_35 = add(x = maximum_7, y = mul_66)[name = string("add_35")];
            tensor<int32, [1]> expand_dims_73_axes_0 = const()[name = string("expand_dims_73_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> expand_dims_73 = expand_dims(axes = expand_dims_73_axes_0, x = maximum_6)[name = string("expand_dims_73")];
            tensor<int32, [1]> expand_dims_74_axes_0 = const()[name = string("expand_dims_74_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> expand_dims_74 = expand_dims(axes = expand_dims_74_axes_0, x = maximum_7)[name = string("expand_dims_74")];
            tensor<int32, [4]> transpose_65_perm_0 = const()[name = string("transpose_65_perm_0"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [1]> expand_dims_131_axes_0 = const()[name = string("expand_dims_131_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> expand_dims_131 = expand_dims(axes = expand_dims_131_axes_0, x = add_35)[name = string("expand_dims_131")];
            tensor<int32, [1]> expand_dims_132 = const()[name = string("expand_dims_132"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> expand_dims_75 = sub(x = expand_dims_131, y = expand_dims_132)[name = string("expand_dims_75")];
            tensor<int32, [1]> const_369 = const()[name = string("const_369"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_370 = const()[name = string("const_370"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_371 = const()[name = string("const_371"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_372 = const()[name = string("const_372"), val = tensor<int32, [1]>([0])];
            int32 concat_62_axis_0 = const()[name = string("concat_62_axis_0"), val = int32(0)];
            bool concat_62_interleave_0 = const()[name = string("concat_62_interleave_0"), val = bool(false)];
            tensor<int32, [6]> concat_62 = concat(axis = concat_62_axis_0, interleave = concat_62_interleave_0, values = (const_369, const_370, expand_dims_73, expand_dims_73, const_371, const_372))[name = string("concat_62")];
            fp32 _inversed_real_div_9_y_0 = const()[name = string("_inversed_real_div_9_y_0"), val = fp32(0x1p-3)];
            tensor<fp32, [1, 4, ?, 64]> transpose_65 = transpose(perm = transpose_65_perm_0, x = reshape_78)[name = string("transpose_99")];
            tensor<fp32, [1, 4, ?, 64]> _inversed_real_div_9 = mul(x = transpose_65, y = _inversed_real_div_9_y_0)[name = string("_inversed_real_div_9")];
            tensor<int32, [2]> const_374 = const()[name = string("const_374"), val = tensor<int32, [2]>([-1, 2])];
            tensor<int32, [3, 2]> reshape_81 = reshape(shape = const_374, x = concat_62)[name = string("reshape_81")];
            bool matmul_14_transpose_x_0 = const()[name = string("matmul_14_transpose_x_0"), val = bool(false)];
            bool matmul_14_transpose_y_0 = const()[name = string("matmul_14_transpose_y_0"), val = bool(false)];
            tensor<fp32, [1, 4, ?, ?]> matmul_14 = matmul(transpose_x = matmul_14_transpose_x_0, transpose_y = matmul_14_transpose_y_0, x = _inversed_real_div_9, y = reshape_79)[name = string("matmul_14")];
            tensor<int32, [2]> slice_by_index_57_begin_0 = const()[name = string("slice_by_index_57_begin_0"), val = tensor<int32, [2]>([2, 0])];
            tensor<int32, [2]> slice_by_index_57_end_0 = const()[name = string("slice_by_index_57_end_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [2]> slice_by_index_57_stride_0 = const()[name = string("slice_by_index_57_stride_0"), val = tensor<int32, [2]>([-1, 1])];
            tensor<bool, [2]> slice_by_index_57_begin_mask_0 = const()[name = string("slice_by_index_57_begin_mask_0"), val = tensor<bool, [2]>([false, true])];
            tensor<bool, [2]> slice_by_index_57_end_mask_0 = const()[name = string("slice_by_index_57_end_mask_0"), val = tensor<bool, [2]>([true, true])];
            tensor<int32, [3, 2]> slice_by_index_57 = slice_by_index(begin = slice_by_index_57_begin_0, begin_mask = slice_by_index_57_begin_mask_0, end = slice_by_index_57_end_0, end_mask = slice_by_index_57_end_mask_0, stride = slice_by_index_57_stride_0, x = reshape_81)[name = string("slice_by_index_57")];
            tensor<int32, [2]> transpose_67_perm_0 = const()[name = string("transpose_67_perm_0"), val = tensor<int32, [2]>([1, 0])];
            tensor<int32, [1]> const_375 = const()[name = string("const_375"), val = tensor<int32, [1]>([-1])];
            tensor<int32, [2, 3]> transpose_67 = transpose(perm = transpose_67_perm_0, x = slice_by_index_57)[name = string("transpose_98")];
            tensor<int32, [6]> reshape_82 = reshape(shape = const_375, x = transpose_67)[name = string("reshape_82")];
            tensor<int32, [2]> reshape_83_shape_0 = const()[name = string("reshape_83_shape_0"), val = tensor<int32, [2]>([2, 3])];
            tensor<int32, [2, 3]> reshape_83 = reshape(shape = reshape_83_shape_0, x = reshape_82)[name = string("reshape_83")];
            tensor<int32, [2]> transpose_68_perm_0 = const()[name = string("transpose_68_perm_0"), val = tensor<int32, [2]>([1, 0])];
            tensor<int32, [1]> reshape_84_shape_0 = const()[name = string("reshape_84_shape_0"), val = tensor<int32, [1]>([-1])];
            tensor<int32, [3, 2]> transpose_68 = transpose(perm = transpose_68_perm_0, x = reshape_83)[name = string("transpose_97")];
            tensor<int32, [6]> reshape_84 = reshape(shape = reshape_84_shape_0, x = transpose_68)[name = string("reshape_84")];
            tensor<fp32, [1, 9, 64]> const_376 = const()[name = string("const_376"), val = tensor<fp32, [1, 9, 64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(31998592)))];
            string pad_18_mode_0 = const()[name = string("pad_18_mode_0"), val = string("constant")];
            fp32 pad_18_constant_val_0 = const()[name = string("pad_18_constant_val_0"), val = fp32(0x0p+0)];
            tensor<fp32, [?, ?, ?]> pad_18 = pad(constant_val = pad_18_constant_val_0, mode = pad_18_mode_0, pad = reshape_84, x = const_376)[name = string("pad_18")];
            tensor<fp32, [1, 9, 64]> const_377 = const()[name = string("const_377"), val = tensor<fp32, [1, 9, 64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(32000960)))];
            string pad_19_mode_0 = const()[name = string("pad_19_mode_0"), val = string("constant")];
            fp32 pad_19_constant_val_0 = const()[name = string("pad_19_constant_val_0"), val = fp32(0x0p+0)];
            tensor<fp32, [?, ?, ?]> pad_19 = pad(constant_val = pad_19_constant_val_0, mode = pad_19_mode_0, pad = reshape_84, x = const_377)[name = string("pad_19")];
            tensor<int32, [1]> const_378 = const()[name = string("const_378"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_379 = const()[name = string("const_379"), val = tensor<int32, [1]>([0])];
            int32 concat_63_axis_0 = const()[name = string("concat_63_axis_0"), val = int32(0)];
            bool concat_63_interleave_0 = const()[name = string("concat_63_interleave_0"), val = bool(false)];
            tensor<int32, [3]> concat_63 = concat(axis = concat_63_axis_0, interleave = concat_63_interleave_0, values = (const_378, expand_dims_74, const_379))[name = string("concat_63")];
            tensor<int32, [1]> const_380 = const()[name = string("const_380"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_381 = const()[name = string("const_381"), val = tensor<int32, [1]>([0])];
            int32 concat_64_axis_0 = const()[name = string("concat_64_axis_0"), val = int32(0)];
            bool concat_64_interleave_0 = const()[name = string("concat_64_interleave_0"), val = bool(false)];
            tensor<int32, [3]> concat_64 = concat(axis = concat_64_axis_0, interleave = concat_64_interleave_0, values = (const_380, expand_dims_75, const_381))[name = string("concat_64")];
            tensor<int32, [3]> slice_by_index_60_stride_0 = const()[name = string("slice_by_index_60_stride_0"), val = tensor<int32, [3]>([1, 1, 1])];
            tensor<bool, [3]> slice_by_index_60_begin_mask_0 = const()[name = string("slice_by_index_60_begin_mask_0"), val = tensor<bool, [3]>([true, false, true])];
            tensor<bool, [3]> slice_by_index_60_end_mask_0 = const()[name = string("slice_by_index_60_end_mask_0"), val = tensor<bool, [3]>([true, false, true])];
            tensor<fp32, [?, ?, ?]> slice_by_index_60 = slice_by_index(begin = concat_63, begin_mask = slice_by_index_60_begin_mask_0, end = concat_64, end_mask = slice_by_index_60_end_mask_0, stride = slice_by_index_60_stride_0, x = pad_18)[name = string("slice_by_index_60")];
            tensor<int32, [3]> slice_by_index_63_stride_0 = const()[name = string("slice_by_index_63_stride_0"), val = tensor<int32, [3]>([1, 1, 1])];
            tensor<bool, [3]> slice_by_index_63_begin_mask_0 = const()[name = string("slice_by_index_63_begin_mask_0"), val = tensor<bool, [3]>([true, false, true])];
            tensor<bool, [3]> slice_by_index_63_end_mask_0 = const()[name = string("slice_by_index_63_end_mask_0"), val = tensor<bool, [3]>([true, false, true])];
            tensor<fp32, [?, ?, ?]> slice_by_index_63 = slice_by_index(begin = concat_63, begin_mask = slice_by_index_63_begin_mask_0, end = concat_64, end_mask = slice_by_index_63_end_mask_0, stride = slice_by_index_63_stride_0, x = pad_19)[name = string("slice_by_index_63")];
            tensor<int32, [1]> expand_dims_76_axes_0 = const()[name = string("expand_dims_76_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp32, [1, ?, ?, ?]> expand_dims_76 = expand_dims(axes = expand_dims_76_axes_0, x = slice_by_index_60)[name = string("expand_dims_76")];
            tensor<int32, [1]> expand_dims_77_axes_0 = const()[name = string("expand_dims_77_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp32, [1, ?, ?, ?]> expand_dims_77 = expand_dims(axes = expand_dims_77_axes_0, x = slice_by_index_63)[name = string("expand_dims_77")];
            bool matmul_15_transpose_x_1 = const()[name = string("matmul_15_transpose_x_1"), val = bool(false)];
            bool matmul_15_transpose_y_1 = const()[name = string("matmul_15_transpose_y_1"), val = bool(true)];
            tensor<fp32, [1, 4, ?, ?]> matmul_15 = matmul(transpose_x = matmul_15_transpose_x_1, transpose_y = matmul_15_transpose_y_1, x = _inversed_real_div_9, y = expand_dims_76)[name = string("matmul_15")];
            tensor<int32, [4]> shape_14 = shape(x = matmul_15)[name = string("shape_14")];
            tensor<int32, [8]> const_386 = const()[name = string("const_386"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 1])];
            string pad_20_mode_0 = const()[name = string("pad_20_mode_0"), val = string("constant")];
            fp32 pad_20_constant_val_0 = const()[name = string("pad_20_constant_val_0"), val = fp32(0x0p+0)];
            tensor<fp32, [1, 4, ?, ?]> pad_20 = pad(constant_val = pad_20_constant_val_0, mode = pad_20_mode_0, pad = const_386, x = matmul_15)[name = string("pad_20")];
            int32 gather_33_batch_dims_0 = const()[name = string("gather_33_batch_dims_0"), val = int32(0)];
            bool gather_33_validate_indices_0 = const()[name = string("gather_33_validate_indices_0"), val = bool(false)];
            tensor<int32, [1]> select_21 = const()[name = string("select_21"), val = tensor<int32, [1]>([2])];
            int32 gather_33_axis_1 = const()[name = string("gather_33_axis_1"), val = int32(0)];
            tensor<int32, [1]> gather_33 = gather(axis = gather_33_axis_1, batch_dims = gather_33_batch_dims_0, indices = select_21, validate_indices = gather_33_validate_indices_0, x = shape_14)[name = string("gather_33")];
            tensor<int32, [1]> squeeze_32_axes_0 = const()[name = string("squeeze_32_axes_0"), val = tensor<int32, [1]>([0])];
            int32 squeeze_32 = squeeze(axes = squeeze_32_axes_0, x = gather_33)[name = string("squeeze_32")];
            tensor<int32, [1]> expand_dims_149_axes_0 = const()[name = string("expand_dims_149_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> expand_dims_149 = expand_dims(axes = expand_dims_149_axes_0, x = squeeze_32)[name = string("expand_dims_149")];
            tensor<int32, [1]> expand_dims_150 = const()[name = string("expand_dims_150"), val = tensor<int32, [1]>([2])];
            tensor<int32, [1]> expand_dims_137 = mul(x = expand_dims_149, y = expand_dims_150)[name = string("expand_dims_137")];
            tensor<int32, [1]> expand_dims_78 = const()[name = string("expand_dims_78"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> expand_dims_79 = const()[name = string("expand_dims_79"), val = tensor<int32, [1]>([4])];
            tensor<int32, [1]> expand_dims_134 = const()[name = string("expand_dims_134"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> expand_dims_81 = sub(x = expand_dims_149, y = expand_dims_134)[name = string("expand_dims_81")];
            tensor<int32, [1]> expand_dims_136 = const()[name = string("expand_dims_136"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> expand_dims_82 = add(x = expand_dims_149, y = expand_dims_136)[name = string("expand_dims_82")];
            tensor<int32, [1]> expand_dims_138 = const()[name = string("expand_dims_138"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> expand_dims_84 = sub(x = expand_dims_137, y = expand_dims_138)[name = string("expand_dims_84")];
            tensor<int32, [1]> const_394 = const()[name = string("const_394"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_395 = const()[name = string("const_395"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_396 = const()[name = string("const_396"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_397 = const()[name = string("const_397"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_398 = const()[name = string("const_398"), val = tensor<int32, [1]>([0])];
            int32 concat_67_axis_0 = const()[name = string("concat_67_axis_0"), val = int32(0)];
            bool concat_67_interleave_0 = const()[name = string("concat_67_interleave_0"), val = bool(false)];
            tensor<int32, [6]> concat_67 = concat(axis = concat_67_axis_0, interleave = concat_67_interleave_0, values = (const_394, expand_dims_81, const_395, const_396, const_397, const_398))[name = string("concat_67")];
            int32 concat_69_axis_0 = const()[name = string("concat_69_axis_0"), val = int32(0)];
            bool concat_69_interleave_0 = const()[name = string("concat_69_interleave_0"), val = bool(false)];
            tensor<int32, [4]> concat_69 = concat(axis = concat_69_axis_0, interleave = concat_69_interleave_0, values = (expand_dims_78, expand_dims_79, expand_dims_82, expand_dims_84))[name = string("concat_69")];
            tensor<int32, [2]> const_399 = const()[name = string("const_399"), val = tensor<int32, [2]>([-1, 2])];
            tensor<int32, [3, 2]> reshape_87 = reshape(shape = const_399, x = concat_67)[name = string("reshape_87")];
            tensor<int32, [3]> concat_68x = const()[name = string("concat_68x"), val = tensor<int32, [3]>([1, 4, -1])];
            tensor<fp32, [1, 4, ?]> reshape_88 = reshape(shape = concat_68x, x = pad_20)[name = string("reshape_88")];
            tensor<int32, [2]> slice_by_index_64_begin_0 = const()[name = string("slice_by_index_64_begin_0"), val = tensor<int32, [2]>([2, 0])];
            tensor<int32, [2]> slice_by_index_64_end_0 = const()[name = string("slice_by_index_64_end_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [2]> slice_by_index_64_stride_0 = const()[name = string("slice_by_index_64_stride_0"), val = tensor<int32, [2]>([-1, 1])];
            tensor<bool, [2]> slice_by_index_64_begin_mask_0 = const()[name = string("slice_by_index_64_begin_mask_0"), val = tensor<bool, [2]>([false, true])];
            tensor<bool, [2]> slice_by_index_64_end_mask_0 = const()[name = string("slice_by_index_64_end_mask_0"), val = tensor<bool, [2]>([true, true])];
            tensor<int32, [3, 2]> slice_by_index_64 = slice_by_index(begin = slice_by_index_64_begin_0, begin_mask = slice_by_index_64_begin_mask_0, end = slice_by_index_64_end_0, end_mask = slice_by_index_64_end_mask_0, stride = slice_by_index_64_stride_0, x = reshape_87)[name = string("slice_by_index_64")];
            tensor<int32, [1]> reshape_91_shape_0 = const()[name = string("reshape_91_shape_0"), val = tensor<int32, [1]>([-1])];
            tensor<int32, [6]> reshape_91 = reshape(shape = reshape_91_shape_0, x = slice_by_index_64)[name = string("reshape_91")];
            string pad_21_mode_0 = const()[name = string("pad_21_mode_0"), val = string("constant")];
            fp32 pad_21_constant_val_0 = const()[name = string("pad_21_constant_val_0"), val = fp32(0x0p+0)];
            tensor<fp32, [1, 4, ?]> pad_21 = pad(constant_val = pad_21_constant_val_0, mode = pad_21_mode_0, pad = reshape_91, x = reshape_88)[name = string("pad_21")];
            tensor<fp32, [1, 4, ?, ?]> reshape_92 = reshape(shape = concat_69, x = pad_21)[name = string("reshape_92")];
            tensor<int32, [1]> const_401 = const()[name = string("const_401"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_402 = const()[name = string("const_402"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_403 = const()[name = string("const_403"), val = tensor<int32, [1]>([0])];
            int32 concat_70_axis_0 = const()[name = string("concat_70_axis_0"), val = int32(0)];
            bool concat_70_interleave_0 = const()[name = string("concat_70_interleave_0"), val = bool(false)];
            tensor<int32, [4]> concat_70 = concat(axis = concat_70_axis_0, interleave = concat_70_interleave_0, values = (const_401, const_402, expand_dims_149, const_403))[name = string("concat_70")];
            tensor<int32, [4]> slice_by_index_66_begin_0 = const()[name = string("slice_by_index_66_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> slice_by_index_66_stride_0 = const()[name = string("slice_by_index_66_stride_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<bool, [4]> slice_by_index_66_begin_mask_0 = const()[name = string("slice_by_index_66_begin_mask_0"), val = tensor<bool, [4]>([true, true, false, true])];
            tensor<bool, [4]> slice_by_index_66_end_mask_0 = const()[name = string("slice_by_index_66_end_mask_0"), val = tensor<bool, [4]>([true, true, false, true])];
            tensor<fp32, [1, 4, ?, ?]> slice_by_index_66 = slice_by_index(begin = slice_by_index_66_begin_0, begin_mask = slice_by_index_66_begin_mask_0, end = concat_70, end_mask = slice_by_index_66_end_mask_0, stride = slice_by_index_66_stride_0, x = reshape_92)[name = string("slice_by_index_66")];
            tensor<int32, [1]> const_404 = const()[name = string("const_404"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_405 = const()[name = string("const_405"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_406 = const()[name = string("const_406"), val = tensor<int32, [1]>([0])];
            int32 concat_71_axis_0 = const()[name = string("concat_71_axis_0"), val = int32(0)];
            bool concat_71_interleave_0 = const()[name = string("concat_71_interleave_0"), val = bool(false)];
            tensor<int32, [4]> concat_71 = concat(axis = concat_71_axis_0, interleave = concat_71_interleave_0, values = (const_404, const_405, const_406, expand_dims_81))[name = string("concat_71")];
            tensor<int32, [4]> slice_by_index_68_end_0 = const()[name = string("slice_by_index_68_end_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> slice_by_index_68_stride_0 = const()[name = string("slice_by_index_68_stride_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<bool, [4]> slice_by_index_68_begin_mask_0 = const()[name = string("slice_by_index_68_begin_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<bool, [4]> slice_by_index_68_end_mask_0 = const()[name = string("slice_by_index_68_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp32, [1, 4, ?, ?]> slice_by_index_68 = slice_by_index(begin = concat_71, begin_mask = slice_by_index_68_begin_mask_0, end = slice_by_index_68_end_0, end_mask = slice_by_index_68_end_mask_0, stride = slice_by_index_68_stride_0, x = slice_by_index_66)[name = string("slice_by_index_68")];
            tensor<fp32, [1, 4, ?, ?]> add_37 = add(x = matmul_14, y = slice_by_index_68)[name = string("add_37")];
            fp32 const_407 = const()[name = string("const_407"), val = fp32(-0x1.388p+13)];
            tensor<fp32, [1, 4, ?, ?]> select_3 = select(a = const_407, b = add_37, cond = equal_1)[name = string("select_3")];
            int32 softmax_3_axis_0 = const()[name = string("softmax_3_axis_0"), val = int32(-1)];
            tensor<fp32, [1, 4, ?, ?]> softmax_3 = softmax(axis = softmax_3_axis_0, x = select_3)[name = string("softmax_3")];
            bool matmul_16_transpose_x_1 = const()[name = string("matmul_16_transpose_x_1"), val = bool(false)];
            bool matmul_16_transpose_y_1 = const()[name = string("matmul_16_transpose_y_1"), val = bool(true)];
            tensor<fp32, [1, 4, ?, 64]> matmul_16 = matmul(transpose_x = matmul_16_transpose_x_1, transpose_y = matmul_16_transpose_y_1, x = softmax_3, y = reshape_80)[name = string("matmul_16")];
            tensor<int32, [4]> shape_15 = shape(x = softmax_3)[name = string("shape_15")];
            int32 gather_36_batch_dims_0 = const()[name = string("gather_36_batch_dims_0"), val = int32(0)];
            bool gather_36_validate_indices_0 = const()[name = string("gather_36_validate_indices_0"), val = bool(false)];
            tensor<int32, [1]> select_22 = const()[name = string("select_22"), val = tensor<int32, [1]>([2])];
            int32 gather_36_axis_1 = const()[name = string("gather_36_axis_1"), val = int32(0)];
            tensor<int32, [1]> gather_36 = gather(axis = gather_36_axis_1, batch_dims = gather_36_batch_dims_0, indices = select_22, validate_indices = gather_36_validate_indices_0, x = shape_15)[name = string("gather_36")];
            tensor<int32, [1]> squeeze_35_axes_0 = const()[name = string("squeeze_35_axes_0"), val = tensor<int32, [1]>([0])];
            int32 squeeze_35 = squeeze(axes = squeeze_35_axes_0, x = gather_36)[name = string("squeeze_35")];
            tensor<int32, [1]> expand_dims_139_axes_0 = const()[name = string("expand_dims_139_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> expand_dims_139 = expand_dims(axes = expand_dims_139_axes_0, x = squeeze_35)[name = string("expand_dims_139")];
            tensor<int32, [1]> expand_dims_140 = const()[name = string("expand_dims_140"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> expand_dims_88 = sub(x = expand_dims_139, y = expand_dims_140)[name = string("expand_dims_88")];
            tensor<int32, [1]> expand_dims_85 = const()[name = string("expand_dims_85"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> expand_dims_86 = const()[name = string("expand_dims_86"), val = tensor<int32, [1]>([4])];
            tensor<int32, [1]> expand_dims_142 = const()[name = string("expand_dims_142"), val = tensor<int32, [1]>([2])];
            tensor<int32, [1]> expand_dims_89 = mul(x = expand_dims_139, y = expand_dims_142)[name = string("expand_dims_89")];
            tensor<int32, [1]> const_413 = const()[name = string("const_413"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_414 = const()[name = string("const_414"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_415 = const()[name = string("const_415"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_416 = const()[name = string("const_416"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_417 = const()[name = string("const_417"), val = tensor<int32, [1]>([0])];
            int32 concat_72_axis_0 = const()[name = string("concat_72_axis_0"), val = int32(0)];
            bool concat_72_interleave_0 = const()[name = string("concat_72_interleave_0"), val = bool(false)];
            tensor<int32, [6]> concat_72 = concat(axis = concat_72_axis_0, interleave = concat_72_interleave_0, values = (expand_dims_139, const_413, const_414, const_415, const_416, const_417))[name = string("concat_72")];
            tensor<int32, [1]> const_418 = const()[name = string("const_418"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_419 = const()[name = string("const_419"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_420 = const()[name = string("const_420"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_421 = const()[name = string("const_421"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_422 = const()[name = string("const_422"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_423 = const()[name = string("const_423"), val = tensor<int32, [1]>([0])];
            tensor<int32, [1]> const_424 = const()[name = string("const_424"), val = tensor<int32, [1]>([0])];
            int32 concat_73_axis_0 = const()[name = string("concat_73_axis_0"), val = int32(0)];
            bool concat_73_interleave_0 = const()[name = string("concat_73_interleave_0"), val = bool(false)];
            tensor<int32, [8]> concat_73 = concat(axis = concat_73_axis_0, interleave = concat_73_interleave_0, values = (const_418, expand_dims_88, const_419, const_420, const_421, const_422, const_423, const_424))[name = string("concat_73")];
            int32 concat_74_axis_0 = const()[name = string("concat_74_axis_0"), val = int32(0)];
            bool concat_74_interleave_0 = const()[name = string("concat_74_interleave_0"), val = bool(false)];
            tensor<int32, [4]> concat_74 = concat(axis = concat_74_axis_0, interleave = concat_74_interleave_0, values = (expand_dims_85, expand_dims_86, expand_dims_139, expand_dims_89))[name = string("concat_74")];
            tensor<int32, [2]> const_425 = const()[name = string("const_425"), val = tensor<int32, [2]>([-1, 2])];
            tensor<int32, [3, 2]> reshape_93 = reshape(shape = const_425, x = concat_72)[name = string("reshape_93")];
            tensor<int32, [2]> const_426 = const()[name = string("const_426"), val = tensor<int32, [2]>([-1, 2])];
            tensor<int32, [4, 2]> reshape_94 = reshape(shape = const_426, x = concat_73)[name = string("reshape_94")];
            tensor<int32, [2]> slice_by_index_69_begin_0 = const()[name = string("slice_by_index_69_begin_0"), val = tensor<int32, [2]>([2, 0])];
            tensor<int32, [2]> slice_by_index_69_end_0 = const()[name = string("slice_by_index_69_end_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [2]> slice_by_index_69_stride_0 = const()[name = string("slice_by_index_69_stride_0"), val = tensor<int32, [2]>([-1, 1])];
            tensor<bool, [2]> slice_by_index_69_begin_mask_0 = const()[name = string("slice_by_index_69_begin_mask_0"), val = tensor<bool, [2]>([false, true])];
            tensor<bool, [2]> slice_by_index_69_end_mask_0 = const()[name = string("slice_by_index_69_end_mask_0"), val = tensor<bool, [2]>([true, true])];
            tensor<int32, [3, 2]> slice_by_index_69 = slice_by_index(begin = slice_by_index_69_begin_0, begin_mask = slice_by_index_69_begin_mask_0, end = slice_by_index_69_end_0, end_mask = slice_by_index_69_end_mask_0, stride = slice_by_index_69_stride_0, x = reshape_93)[name = string("slice_by_index_69")];
            tensor<int32, [2]> slice_by_index_70_begin_0 = const()[name = string("slice_by_index_70_begin_0"), val = tensor<int32, [2]>([3, 0])];
            tensor<int32, [2]> slice_by_index_70_end_0 = const()[name = string("slice_by_index_70_end_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [2]> slice_by_index_70_stride_0 = const()[name = string("slice_by_index_70_stride_0"), val = tensor<int32, [2]>([-1, 1])];
            tensor<bool, [2]> slice_by_index_70_begin_mask_0 = const()[name = string("slice_by_index_70_begin_mask_0"), val = tensor<bool, [2]>([false, true])];
            tensor<bool, [2]> slice_by_index_70_end_mask_0 = const()[name = string("slice_by_index_70_end_mask_0"), val = tensor<bool, [2]>([true, true])];
            tensor<int32, [4, 2]> slice_by_index_70 = slice_by_index(begin = slice_by_index_70_begin_0, begin_mask = slice_by_index_70_begin_mask_0, end = slice_by_index_70_end_0, end_mask = slice_by_index_70_end_mask_0, stride = slice_by_index_70_stride_0, x = reshape_94)[name = string("slice_by_index_70")];
            tensor<int32, [1]> reshape_98_shape_0 = const()[name = string("reshape_98_shape_0"), val = tensor<int32, [1]>([-1])];
            tensor<int32, [8]> reshape_98 = reshape(shape = reshape_98_shape_0, x = slice_by_index_70)[name = string("reshape_98")];
            string pad_22_mode_0 = const()[name = string("pad_22_mode_0"), val = string("constant")];
            fp32 pad_22_constant_val_0 = const()[name = string("pad_22_constant_val_0"), val = fp32(0x0p+0)];
            tensor<fp32, [1, 4, ?, ?]> pad_22 = pad(constant_val = pad_22_constant_val_0, mode = pad_22_mode_0, pad = reshape_98, x = softmax_3)[name = string("pad_22")];
            tensor<int32, [3]> concat_75x = const()[name = string("concat_75x"), val = tensor<int32, [3]>([1, 4, -1])];
            tensor<fp32, [1, 4, ?]> reshape_99 = reshape(shape = concat_75x, x = pad_22)[name = string("reshape_99")];
            tensor<int32, [1]> reshape_101_shape_0 = const()[name = string("reshape_101_shape_0"), val = tensor<int32, [1]>([-1])];
            tensor<int32, [6]> reshape_101 = reshape(shape = reshape_101_shape_0, x = slice_by_index_69)[name = string("reshape_101")];
            string pad_23_mode_0 = const()[name = string("pad_23_mode_0"), val = string("constant")];
            fp32 pad_23_constant_val_0 = const()[name = string("pad_23_constant_val_0"), val = fp32(0x0p+0)];
            tensor<fp32, [1, 4, ?]> pad_23 = pad(constant_val = pad_23_constant_val_0, mode = pad_23_mode_0, pad = reshape_101, x = reshape_99)[name = string("pad_23")];
            tensor<fp32, [1, 4, ?, ?]> reshape_102 = reshape(shape = concat_74, x = pad_23)[name = string("reshape_102")];
            tensor<int32, [4]> slice_by_index_71_begin_0 = const()[name = string("slice_by_index_71_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 1])];
            tensor<int32, [4]> slice_by_index_71_end_0 = const()[name = string("slice_by_index_71_end_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> slice_by_index_71_stride_0 = const()[name = string("slice_by_index_71_stride_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<bool, [4]> slice_by_index_71_begin_mask_0 = const()[name = string("slice_by_index_71_begin_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<bool, [4]> slice_by_index_71_end_mask_0 = const()[name = string("slice_by_index_71_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp32, [1, 4, ?, ?]> slice_by_index_71 = slice_by_index(begin = slice_by_index_71_begin_0, begin_mask = slice_by_index_71_begin_mask_0, end = slice_by_index_71_end_0, end_mask = slice_by_index_71_end_mask_0, stride = slice_by_index_71_stride_0, x = reshape_102)[name = string("slice_by_index_71")];
            bool matmul_17_transpose_x_0 = const()[name = string("matmul_17_transpose_x_0"), val = bool(false)];
            bool matmul_17_transpose_y_0 = const()[name = string("matmul_17_transpose_y_0"), val = bool(false)];
            tensor<fp32, [1, 4, ?, ?]> matmul_17 = matmul(transpose_x = matmul_17_transpose_x_0, transpose_y = matmul_17_transpose_y_0, x = slice_by_index_71, y = expand_dims_77)[name = string("matmul_17")];
            tensor<fp32, [1, 4, ?, 64]> add_39 = add(x = matmul_16, y = matmul_17)[name = string("add_39")];
            tensor<int32, [4]> transpose_77_perm_0 = const()[name = string("transpose_77_perm_0"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [3]> concat_61x = const()[name = string("concat_61x"), val = tensor<int32, [3]>([1, 256, -1])];
            tensor<fp32, [1, 4, 64, ?]> transpose_77 = transpose(perm = transpose_77_perm_0, x = add_39)[name = string("transpose_96")];
            tensor<fp32, [1, 256, ?]> reshape_103 = reshape(shape = concat_61x, x = transpose_77)[name = string("reshape_103")];
            tensor<fp32, [256, 256, 1]> const_429 = const()[name = string("const_429"), val = tensor<fp32, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(32003328)))];
            tensor<fp32, [256]> const_430 = const()[name = string("const_430"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(32265536)))];
            tensor<int32, [1]> conv_39_strides_0 = const()[name = string("conv_39_strides_0"), val = tensor<int32, [1]>([1])];
            string conv_39_pad_type_0 = const()[name = string("conv_39_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> conv_39_pad_0 = const()[name = string("conv_39_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> conv_39_dilations_0 = const()[name = string("conv_39_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 conv_39_groups_0 = const()[name = string("conv_39_groups_0"), val = int32(1)];
            tensor<fp32, [1, 256, ?]> conv_39 = conv(bias = const_430, dilations = conv_39_dilations_0, groups = conv_39_groups_0, pad = conv_39_pad_0, pad_type = conv_39_pad_type_0, strides = conv_39_strides_0, weight = const_429, x = reshape_103)[name = string("conv_39")];
            tensor<fp32, [1, 256, ?]> add_40 = add(x = transpose_64, y = conv_39)[name = string("add_40")];
            tensor<int32, [3]> transpose_78_perm_0 = const()[name = string("transpose_78_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp32, [256]> const_431 = const()[name = string("const_431"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(32266624)))];
            tensor<fp32, [256]> const_432 = const()[name = string("const_432"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(32267712)))];
            tensor<int32, [1]> layer_norm_12_axes_0 = const()[name = string("layer_norm_12_axes_0"), val = tensor<int32, [1]>([2])];
            fp32 layer_norm_12_epsilon_0 = const()[name = string("layer_norm_12_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp32, [1, ?, 256]> transpose_78 = transpose(perm = transpose_78_perm_0, x = add_40)[name = string("transpose_95")];
            tensor<fp32, [1, ?, 256]> layer_norm_12 = layer_norm(axes = layer_norm_12_axes_0, beta = const_432, epsilon = layer_norm_12_epsilon_0, gamma = const_431, x = transpose_78)[name = string("layer_norm_12")];
            tensor<int32, [3]> transpose_79_perm_0 = const()[name = string("transpose_79_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp32, [1, 256, ?]> transpose_79 = transpose(perm = transpose_79_perm_0, x = layer_norm_12)[name = string("transpose_94")];
            tensor<fp32, [1, 256, ?]> mul_72 = mul(x = transpose_79, y = text_mask)[name = string("mul_72")];
            tensor<fp32, [1024, 256, 1]> const_433 = const()[name = string("const_433"), val = tensor<fp32, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(32268800)))];
            tensor<fp32, [1024]> const_434 = const()[name = string("const_434"), val = tensor<fp32, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33317440)))];
            tensor<int32, [1]> conv_40_strides_0 = const()[name = string("conv_40_strides_0"), val = tensor<int32, [1]>([1])];
            string conv_40_pad_type_0 = const()[name = string("conv_40_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> conv_40_pad_0 = const()[name = string("conv_40_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> conv_40_dilations_0 = const()[name = string("conv_40_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 conv_40_groups_0 = const()[name = string("conv_40_groups_0"), val = int32(1)];
            tensor<fp32, [1, 1024, ?]> conv_40 = conv(bias = const_434, dilations = conv_40_dilations_0, groups = conv_40_groups_0, pad = conv_40_pad_0, pad_type = conv_40_pad_type_0, strides = conv_40_strides_0, weight = const_433, x = mul_72)[name = string("conv_40")];
            tensor<fp32, [1, 1024, ?]> relu_3 = relu(x = conv_40)[name = string("relu_3")];
            tensor<fp32, [1, 1024, ?]> mul_73 = mul(x = relu_3, y = text_mask)[name = string("mul_73")];
            tensor<fp32, [256, 1024, 1]> const_435 = const()[name = string("const_435"), val = tensor<fp32, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(33321600)))];
            tensor<fp32, [256]> const_436 = const()[name = string("const_436"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(34370240)))];
            tensor<int32, [1]> conv_41_strides_0 = const()[name = string("conv_41_strides_0"), val = tensor<int32, [1]>([1])];
            string conv_41_pad_type_0 = const()[name = string("conv_41_pad_type_0"), val = string("custom")];
            tensor<int32, [2]> conv_41_pad_0 = const()[name = string("conv_41_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> conv_41_dilations_0 = const()[name = string("conv_41_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 conv_41_groups_0 = const()[name = string("conv_41_groups_0"), val = int32(1)];
            tensor<fp32, [1, 256, ?]> conv_41 = conv(bias = const_436, dilations = conv_41_dilations_0, groups = conv_41_groups_0, pad = conv_41_pad_0, pad_type = conv_41_pad_type_0, strides = conv_41_strides_0, weight = const_435, x = mul_73)[name = string("conv_41")];
            tensor<fp32, [1, 256, ?]> mul_74 = mul(x = conv_41, y = text_mask)[name = string("mul_74")];
            tensor<fp32, [1, 256, ?]> add_41 = add(x = transpose_79, y = mul_74)[name = string("add_41")];
            tensor<int32, [3]> transpose_80_perm_0 = const()[name = string("transpose_80_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp32, [256]> const_437 = const()[name = string("const_437"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(34371328)))];
            tensor<fp32, [256]> const_438 = const()[name = string("const_438"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(34372416)))];
            tensor<int32, [1]> layer_norm_13_axes_0 = const()[name = string("layer_norm_13_axes_0"), val = tensor<int32, [1]>([2])];
            fp32 layer_norm_13_epsilon_0 = const()[name = string("layer_norm_13_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp32, [1, ?, 256]> transpose_80 = transpose(perm = transpose_80_perm_0, x = add_41)[name = string("transpose_93")];
            tensor<fp32, [1, ?, 256]> layer_norm_13 = layer_norm(axes = layer_norm_13_axes_0, beta = const_438, epsilon = layer_norm_13_epsilon_0, gamma = const_437, x = transpose_80)[name = string("layer_norm_13")];
            tensor<int32, [3]> transpose_81_perm_0 = const()[name = string("transpose_81_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp32, [1, 256, ?]> transpose_81 = transpose(perm = transpose_81_perm_0, x = layer_norm_13)[name = string("transpose_92")];
            tensor<fp32, [1, 256, ?]> mul_75 = mul(x = transpose_81, y = text_mask)[name = string("mul_75")];
            tensor<fp32, [1, 256, ?]> add_42 = add(x = mul_75, y = mul_37)[name = string("add_42")];
            tensor<fp32, [1, 256, ?]> mul_76 = mul(x = add_42, y = text_mask)[name = string("mul_76")];
            tensor<int32, [3]> transpose_82_perm_0 = const()[name = string("transpose_82_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp32, [256, 256]> transpose_86 = const()[name = string("transpose_86"), val = tensor<fp32, [256, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(34373504)))];
            tensor<fp32, [256]> add_43_bias_0 = const()[name = string("add_43_bias_0"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(34635712)))];
            tensor<fp32, [1, ?, 256]> transpose_82 = transpose(perm = transpose_82_perm_0, x = mul_76)[name = string("transpose_91")];
            tensor<fp32, [1, ?, 256]> add_43 = linear(bias = add_43_bias_0, weight = transpose_86, x = transpose_82)[name = string("add_43")];
            tensor<int32, [2]> split_2_split_sizes_0 = const()[name = string("split_2_split_sizes_0"), val = tensor<int32, [2]>([128, 128])];
            int32 split_2_axis_0 = const()[name = string("split_2_axis_0"), val = int32(2)];
            tensor<fp32, [1, ?, 128]> split_2_0, tensor<fp32, [1, ?, 128]> split_2_1 = split(axis = split_2_axis_0, split_sizes = split_2_split_sizes_0, x = add_43)[name = string("split_2")];
            tensor<int32, [1]> expand_dims_91_axes_0 = const()[name = string("expand_dims_91_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp32, [1, 1, ?, 128]> expand_dims_91 = expand_dims(axes = expand_dims_91_axes_0, x = split_2_0)[name = string("expand_dims_91")];
            tensor<int32, [1]> expand_dims_92_axes_0 = const()[name = string("expand_dims_92_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp32, [1, 1, ?, 128]> expand_dims_92 = expand_dims(axes = expand_dims_92_axes_0, x = split_2_1)[name = string("expand_dims_92")];
            int32 concat_76_axis_0 = const()[name = string("concat_76_axis_0"), val = int32(0)];
            bool concat_76_interleave_0 = const()[name = string("concat_76_interleave_0"), val = bool(false)];
            tensor<fp32, [2, 1, ?, 128]> concat_76 = concat(axis = concat_76_axis_0, interleave = concat_76_interleave_0, values = (expand_dims_91, expand_dims_92))[name = string("concat_76")];
            tensor<fp32, [2, 1, 128, 50]> const_441 = const()[name = string("const_441"), val = tensor<fp32, [2, 1, 128, 50]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(34636800)))];
            bool matmul_19_transpose_x_0 = const()[name = string("matmul_19_transpose_x_0"), val = bool(false)];
            bool matmul_19_transpose_y_0 = const()[name = string("matmul_19_transpose_y_0"), val = bool(false)];
            tensor<fp32, [2, 1, ?, 50]> matmul_19 = matmul(transpose_x = matmul_19_transpose_x_0, transpose_y = matmul_19_transpose_y_0, x = concat_76, y = const_441)[name = string("matmul_19")];
            fp32 _inversed_real_div_10_y_0 = const()[name = string("_inversed_real_div_10_y_0"), val = fp32(0x1p-4)];
            tensor<fp32, [2, 1, ?, 50]> _inversed_real_div_10 = mul(x = matmul_19, y = _inversed_real_div_10_y_0)[name = string("_inversed_real_div_10")];
            int32 softmax_4_axis_0 = const()[name = string("softmax_4_axis_0"), val = int32(3)];
            tensor<fp32, [2, 1, ?, 50]> softmax_4 = softmax(axis = softmax_4_axis_0, x = _inversed_real_div_10)[name = string("softmax_4")];
            fp32 const_443 = const()[name = string("const_443"), val = fp32(0x0p+0)];
            tensor<fp32, [2, 1, ?, 50]> select_4 = select(a = const_443, b = softmax_4, cond = equal_0)[name = string("select_4")];
            bool matmul_20_transpose_x_0 = const()[name = string("matmul_20_transpose_x_0"), val = bool(false)];
            bool matmul_20_transpose_y_0 = const()[name = string("matmul_20_transpose_y_0"), val = bool(false)];
            tensor<fp32, [2, 1, ?, 128]> matmul_20 = matmul(transpose_x = matmul_20_transpose_x_0, transpose_y = matmul_20_transpose_y_0, x = select_4, y = concat_0)[name = string("matmul_20")];
            tensor<int32, [2]> split_3_split_sizes_0 = const()[name = string("split_3_split_sizes_0"), val = tensor<int32, [2]>([1, 1])];
            int32 split_3_axis_0 = const()[name = string("split_3_axis_0"), val = int32(0)];
            tensor<fp32, [1, 1, ?, 128]> split_3_0, tensor<fp32, [1, 1, ?, 128]> split_3_1 = split(axis = split_3_axis_0, split_sizes = split_3_split_sizes_0, x = matmul_20)[name = string("split_3")];
            int32 concat_77_axis_0 = const()[name = string("concat_77_axis_0"), val = int32(3)];
            bool concat_77_interleave_0 = const()[name = string("concat_77_interleave_0"), val = bool(false)];
            tensor<fp32, [1, 1, ?, 256]> concat_77 = concat(axis = concat_77_axis_0, interleave = concat_77_interleave_0, values = (split_3_0, split_3_1))[name = string("concat_77")];
            tensor<int32, [1]> squeeze_36_axes_0 = const()[name = string("squeeze_36_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp32, [1, ?, 256]> squeeze_36 = squeeze(axes = squeeze_36_axes_0, x = concat_77)[name = string("squeeze_36")];
            tensor<fp32, [256, 256]> transpose_87 = const()[name = string("transpose_87"), val = tensor<fp32, [256, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(34688064)))];
            tensor<fp32, [256]> add_44_bias_0 = const()[name = string("add_44_bias_0"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(34950272)))];
            tensor<fp32, [1, ?, 256]> add_44 = linear(bias = add_44_bias_0, weight = transpose_87, x = squeeze_36)[name = string("add_44")];
            tensor<fp32, [1, ?, 256]> mul_77 = mul(x = add_44, y = transpose_0)[name = string("mul_77")];
            tensor<fp32, [1, ?, 256]> add_45 = add(x = mul_77, y = transpose_82)[name = string("add_45")];
            tensor<fp32, [256, 256]> transpose_88 = const()[name = string("transpose_88"), val = tensor<fp32, [256, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(34951360)))];
            tensor<fp32, [256]> add_46_bias_0 = const()[name = string("add_46_bias_0"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(35213568)))];
            tensor<fp32, [1, ?, 256]> add_46 = linear(bias = add_46_bias_0, weight = transpose_88, x = add_45)[name = string("add_46")];
            tensor<int32, [2]> split_4_split_sizes_0 = const()[name = string("split_4_split_sizes_0"), val = tensor<int32, [2]>([128, 128])];
            int32 split_4_axis_0 = const()[name = string("split_4_axis_0"), val = int32(2)];
            tensor<fp32, [1, ?, 128]> split_4_0, tensor<fp32, [1, ?, 128]> split_4_1 = split(axis = split_4_axis_0, split_sizes = split_4_split_sizes_0, x = add_46)[name = string("split_4")];
            tensor<int32, [1]> expand_dims_93_axes_0 = const()[name = string("expand_dims_93_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp32, [1, 1, ?, 128]> expand_dims_93 = expand_dims(axes = expand_dims_93_axes_0, x = split_4_0)[name = string("expand_dims_93")];
            tensor<int32, [1]> expand_dims_94_axes_0 = const()[name = string("expand_dims_94_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp32, [1, 1, ?, 128]> expand_dims_94 = expand_dims(axes = expand_dims_94_axes_0, x = split_4_1)[name = string("expand_dims_94")];
            int32 concat_78_axis_0 = const()[name = string("concat_78_axis_0"), val = int32(0)];
            bool concat_78_interleave_0 = const()[name = string("concat_78_interleave_0"), val = bool(false)];
            tensor<fp32, [2, 1, ?, 128]> concat_78 = concat(axis = concat_78_axis_0, interleave = concat_78_interleave_0, values = (expand_dims_93, expand_dims_94))[name = string("concat_78")];
            tensor<fp32, [2, 1, 128, 50]> const_448 = const()[name = string("const_448"), val = tensor<fp32, [2, 1, 128, 50]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(35214656)))];
            bool matmul_23_transpose_x_0 = const()[name = string("matmul_23_transpose_x_0"), val = bool(false)];
            bool matmul_23_transpose_y_0 = const()[name = string("matmul_23_transpose_y_0"), val = bool(false)];
            tensor<fp32, [2, 1, ?, 50]> matmul_23 = matmul(transpose_x = matmul_23_transpose_x_0, transpose_y = matmul_23_transpose_y_0, x = concat_78, y = const_448)[name = string("matmul_23")];
            fp32 _inversed_real_div_11_y_0 = const()[name = string("_inversed_real_div_11_y_0"), val = fp32(0x1p-4)];
            tensor<fp32, [2, 1, ?, 50]> _inversed_real_div_11 = mul(x = matmul_23, y = _inversed_real_div_11_y_0)[name = string("_inversed_real_div_11")];
            int32 softmax_5_axis_0 = const()[name = string("softmax_5_axis_0"), val = int32(3)];
            tensor<fp32, [2, 1, ?, 50]> softmax_5 = softmax(axis = softmax_5_axis_0, x = _inversed_real_div_11)[name = string("softmax_5")];
            fp32 const_450 = const()[name = string("const_450"), val = fp32(0x0p+0)];
            tensor<fp32, [2, 1, ?, 50]> select_5 = select(a = const_450, b = softmax_5, cond = equal_0)[name = string("select_5")];
            bool matmul_24_transpose_x_0 = const()[name = string("matmul_24_transpose_x_0"), val = bool(false)];
            bool matmul_24_transpose_y_0 = const()[name = string("matmul_24_transpose_y_0"), val = bool(false)];
            tensor<fp32, [2, 1, ?, 128]> matmul_24 = matmul(transpose_x = matmul_24_transpose_x_0, transpose_y = matmul_24_transpose_y_0, x = select_5, y = concat_1)[name = string("matmul_24")];
            tensor<int32, [2]> split_5_split_sizes_0 = const()[name = string("split_5_split_sizes_0"), val = tensor<int32, [2]>([1, 1])];
            int32 split_5_axis_0 = const()[name = string("split_5_axis_0"), val = int32(0)];
            tensor<fp32, [1, 1, ?, 128]> split_5_0, tensor<fp32, [1, 1, ?, 128]> split_5_1 = split(axis = split_5_axis_0, split_sizes = split_5_split_sizes_0, x = matmul_24)[name = string("split_5")];
            int32 concat_79_axis_0 = const()[name = string("concat_79_axis_0"), val = int32(3)];
            bool concat_79_interleave_0 = const()[name = string("concat_79_interleave_0"), val = bool(false)];
            tensor<fp32, [1, 1, ?, 256]> concat_79 = concat(axis = concat_79_axis_0, interleave = concat_79_interleave_0, values = (split_5_0, split_5_1))[name = string("concat_79")];
            tensor<int32, [1]> squeeze_37_axes_0 = const()[name = string("squeeze_37_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp32, [1, ?, 256]> squeeze_37 = squeeze(axes = squeeze_37_axes_0, x = concat_79)[name = string("squeeze_37")];
            tensor<fp32, [256, 256]> transpose_89 = const()[name = string("transpose_89"), val = tensor<fp32, [256, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(35265920)))];
            tensor<fp32, [256]> add_47_bias_0 = const()[name = string("add_47_bias_0"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(35528128)))];
            tensor<fp32, [1, ?, 256]> add_47 = linear(bias = add_47_bias_0, weight = transpose_89, x = squeeze_37)[name = string("add_47")];
            tensor<fp32, [1, ?, 256]> mul_78 = mul(x = add_47, y = transpose_0)[name = string("mul_78")];
            tensor<fp32, [1, ?, 256]> add_48 = add(x = mul_78, y = transpose_82)[name = string("add_48")];
            tensor<fp32, [256]> const_453 = const()[name = string("const_453"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(35529216)))];
            tensor<fp32, [256]> const_454 = const()[name = string("const_454"), val = tensor<fp32, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(35530304)))];
            tensor<int32, [1]> layer_norm_14_axes_0 = const()[name = string("layer_norm_14_axes_0"), val = tensor<int32, [1]>([2])];
            fp32 layer_norm_14_epsilon_0 = const()[name = string("layer_norm_14_epsilon_0"), val = fp32(0x1.0c6f7ap-20)];
            tensor<fp32, [1, ?, 256]> layer_norm_14 = layer_norm(axes = layer_norm_14_axes_0, beta = const_454, epsilon = layer_norm_14_epsilon_0, gamma = const_453, x = add_48)[name = string("layer_norm_14")];
            tensor<int32, [3]> transpose_83_perm_0 = const()[name = string("transpose_83_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp32, [1, 256, ?]> transpose_83 = transpose(perm = transpose_83_perm_0, x = layer_norm_14)[name = string("transpose_90")];
            tensor<fp32, [1, 256, ?]> mul_79 = mul(x = transpose_83, y = text_mask)[name = string("mul_79")];
            tensor<fp32, [1, 256, ?]> text_emb = identity(x = mul_79)[name = string("text_emb")];
        } -> (text_emb);
}