program(1.3)
[buildInfo = dict<string, string>({{"coremlc-component-MIL", "3600.16.1"}, {"coremlc-version", "3600.22.1"}})]
{
    func text_t128<ios18>(tensor<fp16, [1, 50, 256]> style_ttl, tensor<int32, [1, 128]> text_ids, tensor<fp16, [1, 1, 128]> text_mask) {
            int32 input_tensor_3_batch_dims_0 = const()[name = string("input_tensor_3_batch_dims_0"), val = int32(0)];
            bool input_tensor_3_validate_indices_0 = const()[name = string("input_tensor_3_validate_indices_0"), val = bool(false)];
            tensor<fp16, [8322, 256]> initializers_onnx_initializer_0_to_fp16 = const()[name = string("initializers_onnx_initializer_0_to_fp16"), val = tensor<fp16, [8322, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(64)))];
            string text_ids_to_int16_dtype_0 = const()[name = string("text_ids_to_int16_dtype_0"), val = string("int16")];
            string cast_59_dtype_0 = const()[name = string("cast_59_dtype_0"), val = string("int32")];
            int32 greater_equal_0_y_0 = const()[name = string("greater_equal_0_y_0"), val = int32(0)];
            tensor<int16, [1, 128]> text_ids_to_int16 = cast(dtype = text_ids_to_int16_dtype_0, x = text_ids)[name = string("cast_62")];
            tensor<int32, [1, 128]> cast_59 = cast(dtype = cast_59_dtype_0, x = text_ids_to_int16)[name = string("cast_61")];
            tensor<bool, [1, 128]> greater_equal_0 = greater_equal(x = cast_59, y = greater_equal_0_y_0)[name = string("greater_equal_0")];
            int32 slice_by_index_0 = const()[name = string("slice_by_index_0"), val = int32(8322)];
            tensor<int32, [1, 128]> add_0 = add(x = cast_59, y = slice_by_index_0)[name = string("add_0")];
            tensor<int32, [1, 128]> select_0 = select(a = cast_59, b = add_0, cond = greater_equal_0)[name = string("select_0")];
            int32 input_tensor_3_cast_fp16_cast_uint16_axis_0 = const()[name = string("input_tensor_3_cast_fp16_cast_uint16_axis_0"), val = int32(0)];
            string select_0_to_int16_dtype_0 = const()[name = string("select_0_to_int16_dtype_0"), val = string("int16")];
            tensor<int16, [1, 128]> select_0_to_int16 = cast(dtype = select_0_to_int16_dtype_0, x = select_0)[name = string("cast_60")];
            tensor<fp16, [1, 128, 256]> input_tensor_3_cast_fp16_cast_uint16_cast_uint16 = gather(axis = input_tensor_3_cast_fp16_cast_uint16_axis_0, batch_dims = input_tensor_3_batch_dims_0, indices = select_0_to_int16, validate_indices = input_tensor_3_validate_indices_0, x = initializers_onnx_initializer_0_to_fp16)[name = string("input_tensor_3_cast_fp16_cast_uint16_cast_uint16")];
            tensor<int32, [3]> var_446 = const()[name = string("op_446"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 256, 128]> first_1_cast_fp16 = transpose(perm = var_446, x = input_tensor_3_cast_fp16_cast_uint16_cast_uint16)[name = string("transpose_47")];
            tensor<fp16, [1, 256, 128]> first_3_cast_fp16 = mul(x = first_1_cast_fp16, y = text_mask)[name = string("first_3_cast_fp16")];
            tensor<fp16, [1, 256, 128]> input_1_cast_fp16 = mul(x = first_3_cast_fp16, y = text_mask)[name = string("input_1_cast_fp16")];
            tensor<int32, [6]> input_3_pad_0 = const()[name = string("input_3_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 2, 2])];
            string input_3_mode_0 = const()[name = string("input_3_mode_0"), val = string("replicate")];
            fp16 const_0_to_fp16 = const()[name = string("const_0_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 256, 132]> input_3_cast_fp16 = pad(constant_val = const_0_to_fp16, mode = input_3_mode_0, pad = input_3_pad_0, x = input_1_cast_fp16)[name = string("input_3_cast_fp16")];
            string first_5_pad_type_0 = const()[name = string("first_5_pad_type_0"), val = string("valid")];
            int32 first_5_groups_0 = const()[name = string("first_5_groups_0"), val = int32(256)];
            tensor<int32, [1]> first_5_strides_0 = const()[name = string("first_5_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_5_pad_0 = const()[name = string("first_5_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_5_dilations_0 = const()[name = string("first_5_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [256, 1, 5]> text_encoder_convnext_convnext_0_dwconv_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_0_dwconv_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4260992)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_0_dwconv_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_0_dwconv_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4263616)))];
            tensor<fp16, [1, 256, 128]> first_5_cast_fp16 = conv(bias = text_encoder_convnext_convnext_0_dwconv_Conv_bias_to_fp16, dilations = first_5_dilations_0, groups = first_5_groups_0, pad = first_5_pad_0, pad_type = first_5_pad_type_0, strides = first_5_strides_0, weight = text_encoder_convnext_convnext_0_dwconv_Conv_weight_to_fp16, x = input_3_cast_fp16)[name = string("first_5_cast_fp16")];
            tensor<fp16, [1, 256, 128]> input_tensor_13_cast_fp16 = mul(x = first_5_cast_fp16, y = text_mask)[name = string("input_tensor_13_cast_fp16")];
            tensor<int32, [3]> var_471 = const()[name = string("op_471"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_15_axes_0 = const()[name = string("input_tensor_15_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_convnext_convnext_0_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_0_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4264192)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_0_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_0_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4264768)))];
            fp16 var_474_to_fp16 = const()[name = string("op_474_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 128, 256]> input_5_cast_fp16 = transpose(perm = var_471, x = input_tensor_13_cast_fp16)[name = string("transpose_46")];
            tensor<fp16, [1, 128, 256]> input_tensor_15_cast_fp16 = layer_norm(axes = input_tensor_15_axes_0, beta = text_encoder_convnext_convnext_0_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_474_to_fp16, gamma = text_encoder_convnext_convnext_0_norm_norm_LayerNormalization_weight_to_fp16, x = input_5_cast_fp16)[name = string("input_tensor_15_cast_fp16")];
            tensor<int32, [3]> var_483 = const()[name = string("op_483"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_7_pad_type_0 = const()[name = string("first_7_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_7_strides_0 = const()[name = string("first_7_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_7_pad_0 = const()[name = string("first_7_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_7_dilations_0 = const()[name = string("first_7_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_7_groups_0 = const()[name = string("first_7_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_convnext_convnext_0_pwconv1_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_0_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4265344)))];
            tensor<fp16, [1024]> text_encoder_convnext_convnext_0_pwconv1_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_0_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4789696)))];
            tensor<fp16, [1, 256, 128]> input_7_cast_fp16 = transpose(perm = var_483, x = input_tensor_15_cast_fp16)[name = string("transpose_45")];
            tensor<fp16, [1, 1024, 128]> first_7_cast_fp16 = conv(bias = text_encoder_convnext_convnext_0_pwconv1_Conv_bias_to_fp16, dilations = first_7_dilations_0, groups = first_7_groups_0, pad = first_7_pad_0, pad_type = first_7_pad_type_0, strides = first_7_strides_0, weight = text_encoder_convnext_convnext_0_pwconv1_Conv_weight_to_fp16, x = input_7_cast_fp16)[name = string("first_7_cast_fp16")];
            string input_9_mode_0 = const()[name = string("input_9_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 1024, 128]> input_9_cast_fp16 = gelu(mode = input_9_mode_0, x = first_7_cast_fp16)[name = string("input_9_cast_fp16")];
            string second_9_pad_type_0 = const()[name = string("second_9_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_9_strides_0 = const()[name = string("second_9_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_9_pad_0 = const()[name = string("second_9_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_9_dilations_0 = const()[name = string("second_9_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_9_groups_0 = const()[name = string("second_9_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> second_11_weight_0_to_fp16 = const()[name = string("second_11_weight_0_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4791808)))];
            tensor<fp16, [256]> second_11_bias_0_to_fp16 = const()[name = string("second_11_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5316160)))];
            tensor<fp16, [1, 256, 128]> second_11_cast_fp16 = conv(bias = second_11_bias_0_to_fp16, dilations = second_9_dilations_0, groups = second_9_groups_0, pad = second_9_pad_0, pad_type = second_9_pad_type_0, strides = second_9_strides_0, weight = second_11_weight_0_to_fp16, x = input_9_cast_fp16)[name = string("second_11_cast_fp16")];
            tensor<fp16, [1, 256, 128]> first_15_cast_fp16 = add(x = input_1_cast_fp16, y = second_11_cast_fp16)[name = string("first_15_cast_fp16")];
            tensor<fp16, [1, 256, 128]> first_17_cast_fp16 = mul(x = first_15_cast_fp16, y = text_mask)[name = string("first_17_cast_fp16")];
            tensor<fp16, [1, 256, 128]> input_11_cast_fp16 = mul(x = first_17_cast_fp16, y = text_mask)[name = string("input_11_cast_fp16")];
            tensor<int32, [6]> input_13_pad_0 = const()[name = string("input_13_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 2, 2])];
            string input_13_mode_0 = const()[name = string("input_13_mode_0"), val = string("replicate")];
            fp16 const_1_to_fp16 = const()[name = string("const_1_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 256, 132]> input_13_cast_fp16 = pad(constant_val = const_1_to_fp16, mode = input_13_mode_0, pad = input_13_pad_0, x = input_11_cast_fp16)[name = string("input_13_cast_fp16")];
            string first_19_pad_type_0 = const()[name = string("first_19_pad_type_0"), val = string("valid")];
            int32 first_19_groups_0 = const()[name = string("first_19_groups_0"), val = int32(256)];
            tensor<int32, [1]> first_19_strides_0 = const()[name = string("first_19_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_19_pad_0 = const()[name = string("first_19_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_19_dilations_0 = const()[name = string("first_19_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [256, 1, 5]> text_encoder_convnext_convnext_1_dwconv_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_1_dwconv_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5316736)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_1_dwconv_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_1_dwconv_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5319360)))];
            tensor<fp16, [1, 256, 128]> first_19_cast_fp16 = conv(bias = text_encoder_convnext_convnext_1_dwconv_Conv_bias_to_fp16, dilations = first_19_dilations_0, groups = first_19_groups_0, pad = first_19_pad_0, pad_type = first_19_pad_type_0, strides = first_19_strides_0, weight = text_encoder_convnext_convnext_1_dwconv_Conv_weight_to_fp16, x = input_13_cast_fp16)[name = string("first_19_cast_fp16")];
            tensor<fp16, [1, 256, 128]> input_tensor_27_cast_fp16 = mul(x = first_19_cast_fp16, y = text_mask)[name = string("input_tensor_27_cast_fp16")];
            tensor<int32, [3]> var_539 = const()[name = string("op_539"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_29_axes_0 = const()[name = string("input_tensor_29_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_convnext_convnext_1_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_1_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5319936)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_1_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_1_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5320512)))];
            fp16 var_542_to_fp16 = const()[name = string("op_542_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 128, 256]> input_15_cast_fp16 = transpose(perm = var_539, x = input_tensor_27_cast_fp16)[name = string("transpose_44")];
            tensor<fp16, [1, 128, 256]> input_tensor_29_cast_fp16 = layer_norm(axes = input_tensor_29_axes_0, beta = text_encoder_convnext_convnext_1_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_542_to_fp16, gamma = text_encoder_convnext_convnext_1_norm_norm_LayerNormalization_weight_to_fp16, x = input_15_cast_fp16)[name = string("input_tensor_29_cast_fp16")];
            tensor<int32, [3]> var_551 = const()[name = string("op_551"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_21_pad_type_0 = const()[name = string("first_21_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_21_strides_0 = const()[name = string("first_21_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_21_pad_0 = const()[name = string("first_21_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_21_dilations_0 = const()[name = string("first_21_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_21_groups_0 = const()[name = string("first_21_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_convnext_convnext_1_pwconv1_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_1_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5321088)))];
            tensor<fp16, [1024]> text_encoder_convnext_convnext_1_pwconv1_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_1_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5845440)))];
            tensor<fp16, [1, 256, 128]> input_17_cast_fp16 = transpose(perm = var_551, x = input_tensor_29_cast_fp16)[name = string("transpose_43")];
            tensor<fp16, [1, 1024, 128]> first_21_cast_fp16 = conv(bias = text_encoder_convnext_convnext_1_pwconv1_Conv_bias_to_fp16, dilations = first_21_dilations_0, groups = first_21_groups_0, pad = first_21_pad_0, pad_type = first_21_pad_type_0, strides = first_21_strides_0, weight = text_encoder_convnext_convnext_1_pwconv1_Conv_weight_to_fp16, x = input_17_cast_fp16)[name = string("first_21_cast_fp16")];
            string input_19_mode_0 = const()[name = string("input_19_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 1024, 128]> input_19_cast_fp16 = gelu(mode = input_19_mode_0, x = first_21_cast_fp16)[name = string("input_19_cast_fp16")];
            string second_21_pad_type_0 = const()[name = string("second_21_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_21_strides_0 = const()[name = string("second_21_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_21_pad_0 = const()[name = string("second_21_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_21_dilations_0 = const()[name = string("second_21_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_21_groups_0 = const()[name = string("second_21_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> second_23_weight_0_to_fp16 = const()[name = string("second_23_weight_0_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5847552)))];
            tensor<fp16, [256]> second_23_bias_0_to_fp16 = const()[name = string("second_23_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6371904)))];
            tensor<fp16, [1, 256, 128]> second_23_cast_fp16 = conv(bias = second_23_bias_0_to_fp16, dilations = second_21_dilations_0, groups = second_21_groups_0, pad = second_21_pad_0, pad_type = second_21_pad_type_0, strides = second_21_strides_0, weight = second_23_weight_0_to_fp16, x = input_19_cast_fp16)[name = string("second_23_cast_fp16")];
            tensor<fp16, [1, 256, 128]> first_29_cast_fp16 = add(x = input_11_cast_fp16, y = second_23_cast_fp16)[name = string("first_29_cast_fp16")];
            tensor<fp16, [1, 256, 128]> first_31_cast_fp16 = mul(x = first_29_cast_fp16, y = text_mask)[name = string("first_31_cast_fp16")];
            tensor<fp16, [1, 256, 128]> input_21_cast_fp16 = mul(x = first_31_cast_fp16, y = text_mask)[name = string("input_21_cast_fp16")];
            tensor<int32, [6]> input_23_pad_0 = const()[name = string("input_23_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            string input_23_mode_0 = const()[name = string("input_23_mode_0"), val = string("replicate")];
            fp16 const_2_to_fp16 = const()[name = string("const_2_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 256, 136]> input_23_cast_fp16 = pad(constant_val = const_2_to_fp16, mode = input_23_mode_0, pad = input_23_pad_0, x = input_21_cast_fp16)[name = string("input_23_cast_fp16")];
            string first_33_pad_type_0 = const()[name = string("first_33_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_33_dilations_0 = const()[name = string("first_33_dilations_0"), val = tensor<int32, [1]>([2])];
            int32 first_33_groups_0 = const()[name = string("first_33_groups_0"), val = int32(256)];
            tensor<int32, [1]> first_33_strides_0 = const()[name = string("first_33_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_33_pad_0 = const()[name = string("first_33_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [256, 1, 5]> text_encoder_convnext_convnext_2_dwconv_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_2_dwconv_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6372480)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_2_dwconv_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_2_dwconv_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6375104)))];
            tensor<fp16, [1, 256, 128]> first_33_cast_fp16 = conv(bias = text_encoder_convnext_convnext_2_dwconv_Conv_bias_to_fp16, dilations = first_33_dilations_0, groups = first_33_groups_0, pad = first_33_pad_0, pad_type = first_33_pad_type_0, strides = first_33_strides_0, weight = text_encoder_convnext_convnext_2_dwconv_Conv_weight_to_fp16, x = input_23_cast_fp16)[name = string("first_33_cast_fp16")];
            tensor<fp16, [1, 256, 128]> input_tensor_41_cast_fp16 = mul(x = first_33_cast_fp16, y = text_mask)[name = string("input_tensor_41_cast_fp16")];
            tensor<int32, [3]> var_608 = const()[name = string("op_608"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_43_axes_0 = const()[name = string("input_tensor_43_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_convnext_convnext_2_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_2_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6375680)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_2_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_2_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6376256)))];
            fp16 var_611_to_fp16 = const()[name = string("op_611_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 128, 256]> input_25_cast_fp16 = transpose(perm = var_608, x = input_tensor_41_cast_fp16)[name = string("transpose_42")];
            tensor<fp16, [1, 128, 256]> input_tensor_43_cast_fp16 = layer_norm(axes = input_tensor_43_axes_0, beta = text_encoder_convnext_convnext_2_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_611_to_fp16, gamma = text_encoder_convnext_convnext_2_norm_norm_LayerNormalization_weight_to_fp16, x = input_25_cast_fp16)[name = string("input_tensor_43_cast_fp16")];
            tensor<int32, [3]> var_620 = const()[name = string("op_620"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_35_pad_type_0 = const()[name = string("first_35_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_35_strides_0 = const()[name = string("first_35_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_35_pad_0 = const()[name = string("first_35_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_35_dilations_0 = const()[name = string("first_35_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_35_groups_0 = const()[name = string("first_35_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_convnext_convnext_2_pwconv1_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_2_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6376832)))];
            tensor<fp16, [1024]> text_encoder_convnext_convnext_2_pwconv1_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_2_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6901184)))];
            tensor<fp16, [1, 256, 128]> input_27_cast_fp16 = transpose(perm = var_620, x = input_tensor_43_cast_fp16)[name = string("transpose_41")];
            tensor<fp16, [1, 1024, 128]> first_35_cast_fp16 = conv(bias = text_encoder_convnext_convnext_2_pwconv1_Conv_bias_to_fp16, dilations = first_35_dilations_0, groups = first_35_groups_0, pad = first_35_pad_0, pad_type = first_35_pad_type_0, strides = first_35_strides_0, weight = text_encoder_convnext_convnext_2_pwconv1_Conv_weight_to_fp16, x = input_27_cast_fp16)[name = string("first_35_cast_fp16")];
            string input_29_mode_0 = const()[name = string("input_29_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 1024, 128]> input_29_cast_fp16 = gelu(mode = input_29_mode_0, x = first_35_cast_fp16)[name = string("input_29_cast_fp16")];
            string second_33_pad_type_0 = const()[name = string("second_33_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_33_strides_0 = const()[name = string("second_33_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_33_pad_0 = const()[name = string("second_33_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_33_dilations_0 = const()[name = string("second_33_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_33_groups_0 = const()[name = string("second_33_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> second_35_weight_0_to_fp16 = const()[name = string("second_35_weight_0_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6903296)))];
            tensor<fp16, [256]> second_35_bias_0_to_fp16 = const()[name = string("second_35_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7427648)))];
            tensor<fp16, [1, 256, 128]> second_35_cast_fp16 = conv(bias = second_35_bias_0_to_fp16, dilations = second_33_dilations_0, groups = second_33_groups_0, pad = second_33_pad_0, pad_type = second_33_pad_type_0, strides = second_33_strides_0, weight = second_35_weight_0_to_fp16, x = input_29_cast_fp16)[name = string("second_35_cast_fp16")];
            tensor<fp16, [1, 256, 128]> first_43_cast_fp16 = add(x = input_21_cast_fp16, y = second_35_cast_fp16)[name = string("first_43_cast_fp16")];
            tensor<fp16, [1, 256, 128]> first_45_cast_fp16 = mul(x = first_43_cast_fp16, y = text_mask)[name = string("first_45_cast_fp16")];
            tensor<fp16, [1, 256, 128]> input_31_cast_fp16 = mul(x = first_45_cast_fp16, y = text_mask)[name = string("input_31_cast_fp16")];
            tensor<int32, [6]> input_33_pad_0 = const()[name = string("input_33_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            string input_33_mode_0 = const()[name = string("input_33_mode_0"), val = string("replicate")];
            fp16 const_3_to_fp16 = const()[name = string("const_3_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 256, 136]> input_33_cast_fp16 = pad(constant_val = const_3_to_fp16, mode = input_33_mode_0, pad = input_33_pad_0, x = input_31_cast_fp16)[name = string("input_33_cast_fp16")];
            string first_47_pad_type_0 = const()[name = string("first_47_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_47_dilations_0 = const()[name = string("first_47_dilations_0"), val = tensor<int32, [1]>([2])];
            int32 first_47_groups_0 = const()[name = string("first_47_groups_0"), val = int32(256)];
            tensor<int32, [1]> first_47_strides_0 = const()[name = string("first_47_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_47_pad_0 = const()[name = string("first_47_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [256, 1, 5]> text_encoder_convnext_convnext_3_dwconv_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_3_dwconv_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7428224)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_3_dwconv_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_3_dwconv_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7430848)))];
            tensor<fp16, [1, 256, 128]> first_47_cast_fp16 = conv(bias = text_encoder_convnext_convnext_3_dwconv_Conv_bias_to_fp16, dilations = first_47_dilations_0, groups = first_47_groups_0, pad = first_47_pad_0, pad_type = first_47_pad_type_0, strides = first_47_strides_0, weight = text_encoder_convnext_convnext_3_dwconv_Conv_weight_to_fp16, x = input_33_cast_fp16)[name = string("first_47_cast_fp16")];
            tensor<fp16, [1, 256, 128]> input_tensor_55_cast_fp16 = mul(x = first_47_cast_fp16, y = text_mask)[name = string("input_tensor_55_cast_fp16")];
            tensor<int32, [3]> var_677 = const()[name = string("op_677"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_57_axes_0 = const()[name = string("input_tensor_57_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_convnext_convnext_3_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_3_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7431424)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_3_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_3_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7432000)))];
            fp16 var_680_to_fp16 = const()[name = string("op_680_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 128, 256]> input_35_cast_fp16 = transpose(perm = var_677, x = input_tensor_55_cast_fp16)[name = string("transpose_40")];
            tensor<fp16, [1, 128, 256]> input_tensor_57_cast_fp16 = layer_norm(axes = input_tensor_57_axes_0, beta = text_encoder_convnext_convnext_3_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_680_to_fp16, gamma = text_encoder_convnext_convnext_3_norm_norm_LayerNormalization_weight_to_fp16, x = input_35_cast_fp16)[name = string("input_tensor_57_cast_fp16")];
            tensor<int32, [3]> var_689 = const()[name = string("op_689"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_49_pad_type_0 = const()[name = string("first_49_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_49_strides_0 = const()[name = string("first_49_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_49_pad_0 = const()[name = string("first_49_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_49_dilations_0 = const()[name = string("first_49_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_49_groups_0 = const()[name = string("first_49_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_convnext_convnext_3_pwconv1_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_3_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7432576)))];
            tensor<fp16, [1024]> text_encoder_convnext_convnext_3_pwconv1_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_3_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7956928)))];
            tensor<fp16, [1, 256, 128]> input_37_cast_fp16 = transpose(perm = var_689, x = input_tensor_57_cast_fp16)[name = string("transpose_39")];
            tensor<fp16, [1, 1024, 128]> first_49_cast_fp16 = conv(bias = text_encoder_convnext_convnext_3_pwconv1_Conv_bias_to_fp16, dilations = first_49_dilations_0, groups = first_49_groups_0, pad = first_49_pad_0, pad_type = first_49_pad_type_0, strides = first_49_strides_0, weight = text_encoder_convnext_convnext_3_pwconv1_Conv_weight_to_fp16, x = input_37_cast_fp16)[name = string("first_49_cast_fp16")];
            string input_39_mode_0 = const()[name = string("input_39_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 1024, 128]> input_39_cast_fp16 = gelu(mode = input_39_mode_0, x = first_49_cast_fp16)[name = string("input_39_cast_fp16")];
            string second_45_pad_type_0 = const()[name = string("second_45_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_45_strides_0 = const()[name = string("second_45_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_45_pad_0 = const()[name = string("second_45_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_45_dilations_0 = const()[name = string("second_45_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_45_groups_0 = const()[name = string("second_45_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> second_47_weight_0_to_fp16 = const()[name = string("second_47_weight_0_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7959040)))];
            tensor<fp16, [256]> second_47_bias_0_to_fp16 = const()[name = string("second_47_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8483392)))];
            tensor<fp16, [1, 256, 128]> second_47_cast_fp16 = conv(bias = second_47_bias_0_to_fp16, dilations = second_45_dilations_0, groups = second_45_groups_0, pad = second_45_pad_0, pad_type = second_45_pad_type_0, strides = second_45_strides_0, weight = second_47_weight_0_to_fp16, x = input_39_cast_fp16)[name = string("second_47_cast_fp16")];
            tensor<fp16, [1, 256, 128]> first_57_cast_fp16 = add(x = input_31_cast_fp16, y = second_47_cast_fp16)[name = string("first_57_cast_fp16")];
            tensor<fp16, [1, 256, 128]> first_59_cast_fp16 = mul(x = first_57_cast_fp16, y = text_mask)[name = string("first_59_cast_fp16")];
            tensor<fp16, [1, 256, 128]> input_41_cast_fp16 = mul(x = first_59_cast_fp16, y = text_mask)[name = string("input_41_cast_fp16")];
            tensor<int32, [6]> input_43_pad_0 = const()[name = string("input_43_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 8, 8])];
            string input_43_mode_0 = const()[name = string("input_43_mode_0"), val = string("replicate")];
            fp16 const_4_to_fp16 = const()[name = string("const_4_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 256, 144]> input_43_cast_fp16 = pad(constant_val = const_4_to_fp16, mode = input_43_mode_0, pad = input_43_pad_0, x = input_41_cast_fp16)[name = string("input_43_cast_fp16")];
            string first_61_pad_type_0 = const()[name = string("first_61_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_61_dilations_0 = const()[name = string("first_61_dilations_0"), val = tensor<int32, [1]>([4])];
            int32 first_61_groups_0 = const()[name = string("first_61_groups_0"), val = int32(256)];
            tensor<int32, [1]> first_61_strides_0 = const()[name = string("first_61_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_61_pad_0 = const()[name = string("first_61_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [256, 1, 5]> text_encoder_convnext_convnext_4_dwconv_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_4_dwconv_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8483968)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_4_dwconv_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_4_dwconv_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8486592)))];
            tensor<fp16, [1, 256, 128]> first_61_cast_fp16 = conv(bias = text_encoder_convnext_convnext_4_dwconv_Conv_bias_to_fp16, dilations = first_61_dilations_0, groups = first_61_groups_0, pad = first_61_pad_0, pad_type = first_61_pad_type_0, strides = first_61_strides_0, weight = text_encoder_convnext_convnext_4_dwconv_Conv_weight_to_fp16, x = input_43_cast_fp16)[name = string("first_61_cast_fp16")];
            tensor<fp16, [1, 256, 128]> input_tensor_69_cast_fp16 = mul(x = first_61_cast_fp16, y = text_mask)[name = string("input_tensor_69_cast_fp16")];
            tensor<int32, [3]> var_746 = const()[name = string("op_746"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_71_axes_0 = const()[name = string("input_tensor_71_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_convnext_convnext_4_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_4_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8487168)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_4_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_4_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8487744)))];
            fp16 var_749_to_fp16 = const()[name = string("op_749_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 128, 256]> input_45_cast_fp16 = transpose(perm = var_746, x = input_tensor_69_cast_fp16)[name = string("transpose_38")];
            tensor<fp16, [1, 128, 256]> input_tensor_71_cast_fp16 = layer_norm(axes = input_tensor_71_axes_0, beta = text_encoder_convnext_convnext_4_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_749_to_fp16, gamma = text_encoder_convnext_convnext_4_norm_norm_LayerNormalization_weight_to_fp16, x = input_45_cast_fp16)[name = string("input_tensor_71_cast_fp16")];
            tensor<int32, [3]> var_758 = const()[name = string("op_758"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_63_pad_type_0 = const()[name = string("first_63_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_63_strides_0 = const()[name = string("first_63_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_63_pad_0 = const()[name = string("first_63_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_63_dilations_0 = const()[name = string("first_63_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_63_groups_0 = const()[name = string("first_63_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_convnext_convnext_4_pwconv1_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_4_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8488320)))];
            tensor<fp16, [1024]> text_encoder_convnext_convnext_4_pwconv1_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_4_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9012672)))];
            tensor<fp16, [1, 256, 128]> input_47_cast_fp16 = transpose(perm = var_758, x = input_tensor_71_cast_fp16)[name = string("transpose_37")];
            tensor<fp16, [1, 1024, 128]> first_63_cast_fp16 = conv(bias = text_encoder_convnext_convnext_4_pwconv1_Conv_bias_to_fp16, dilations = first_63_dilations_0, groups = first_63_groups_0, pad = first_63_pad_0, pad_type = first_63_pad_type_0, strides = first_63_strides_0, weight = text_encoder_convnext_convnext_4_pwconv1_Conv_weight_to_fp16, x = input_47_cast_fp16)[name = string("first_63_cast_fp16")];
            string input_49_mode_0 = const()[name = string("input_49_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 1024, 128]> input_49_cast_fp16 = gelu(mode = input_49_mode_0, x = first_63_cast_fp16)[name = string("input_49_cast_fp16")];
            string second_57_pad_type_0 = const()[name = string("second_57_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_57_strides_0 = const()[name = string("second_57_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_57_pad_0 = const()[name = string("second_57_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_57_dilations_0 = const()[name = string("second_57_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_57_groups_0 = const()[name = string("second_57_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> second_59_weight_0_to_fp16 = const()[name = string("second_59_weight_0_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9014784)))];
            tensor<fp16, [256]> second_59_bias_0_to_fp16 = const()[name = string("second_59_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9539136)))];
            tensor<fp16, [1, 256, 128]> second_59_cast_fp16 = conv(bias = second_59_bias_0_to_fp16, dilations = second_57_dilations_0, groups = second_57_groups_0, pad = second_57_pad_0, pad_type = second_57_pad_type_0, strides = second_57_strides_0, weight = second_59_weight_0_to_fp16, x = input_49_cast_fp16)[name = string("second_59_cast_fp16")];
            tensor<fp16, [1, 256, 128]> first_71_cast_fp16 = add(x = input_41_cast_fp16, y = second_59_cast_fp16)[name = string("first_71_cast_fp16")];
            tensor<fp16, [1, 256, 128]> first_73_cast_fp16 = mul(x = first_71_cast_fp16, y = text_mask)[name = string("first_73_cast_fp16")];
            tensor<fp16, [1, 256, 128]> input_51_cast_fp16 = mul(x = first_73_cast_fp16, y = text_mask)[name = string("input_51_cast_fp16")];
            tensor<int32, [6]> input_53_pad_0 = const()[name = string("input_53_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 8, 8])];
            string input_53_mode_0 = const()[name = string("input_53_mode_0"), val = string("replicate")];
            fp16 const_5_to_fp16 = const()[name = string("const_5_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 256, 144]> input_53_cast_fp16 = pad(constant_val = const_5_to_fp16, mode = input_53_mode_0, pad = input_53_pad_0, x = input_51_cast_fp16)[name = string("input_53_cast_fp16")];
            string first_75_pad_type_0 = const()[name = string("first_75_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_75_dilations_0 = const()[name = string("first_75_dilations_0"), val = tensor<int32, [1]>([4])];
            int32 first_75_groups_0 = const()[name = string("first_75_groups_0"), val = int32(256)];
            tensor<int32, [1]> first_75_strides_0 = const()[name = string("first_75_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_75_pad_0 = const()[name = string("first_75_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [256, 1, 5]> text_encoder_convnext_convnext_5_dwconv_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_5_dwconv_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9539712)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_5_dwconv_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_5_dwconv_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9542336)))];
            tensor<fp16, [1, 256, 128]> first_75_cast_fp16 = conv(bias = text_encoder_convnext_convnext_5_dwconv_Conv_bias_to_fp16, dilations = first_75_dilations_0, groups = first_75_groups_0, pad = first_75_pad_0, pad_type = first_75_pad_type_0, strides = first_75_strides_0, weight = text_encoder_convnext_convnext_5_dwconv_Conv_weight_to_fp16, x = input_53_cast_fp16)[name = string("first_75_cast_fp16")];
            tensor<fp16, [1, 256, 128]> input_tensor_83_cast_fp16 = mul(x = first_75_cast_fp16, y = text_mask)[name = string("input_tensor_83_cast_fp16")];
            tensor<int32, [3]> var_815 = const()[name = string("op_815"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_85_axes_0 = const()[name = string("input_tensor_85_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_convnext_convnext_5_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_5_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9542912)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_5_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_5_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9543488)))];
            fp16 var_818_to_fp16 = const()[name = string("op_818_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 128, 256]> input_55_cast_fp16 = transpose(perm = var_815, x = input_tensor_83_cast_fp16)[name = string("transpose_36")];
            tensor<fp16, [1, 128, 256]> input_tensor_85_cast_fp16 = layer_norm(axes = input_tensor_85_axes_0, beta = text_encoder_convnext_convnext_5_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_818_to_fp16, gamma = text_encoder_convnext_convnext_5_norm_norm_LayerNormalization_weight_to_fp16, x = input_55_cast_fp16)[name = string("input_tensor_85_cast_fp16")];
            tensor<int32, [3]> var_827 = const()[name = string("op_827"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_77_pad_type_0 = const()[name = string("first_77_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_77_strides_0 = const()[name = string("first_77_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_77_pad_0 = const()[name = string("first_77_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_77_dilations_0 = const()[name = string("first_77_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_77_groups_0 = const()[name = string("first_77_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_convnext_convnext_5_pwconv1_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_5_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9544064)))];
            tensor<fp16, [1024]> text_encoder_convnext_convnext_5_pwconv1_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_5_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10068416)))];
            tensor<fp16, [1, 256, 128]> input_57_cast_fp16 = transpose(perm = var_827, x = input_tensor_85_cast_fp16)[name = string("transpose_35")];
            tensor<fp16, [1, 1024, 128]> first_77_cast_fp16 = conv(bias = text_encoder_convnext_convnext_5_pwconv1_Conv_bias_to_fp16, dilations = first_77_dilations_0, groups = first_77_groups_0, pad = first_77_pad_0, pad_type = first_77_pad_type_0, strides = first_77_strides_0, weight = text_encoder_convnext_convnext_5_pwconv1_Conv_weight_to_fp16, x = input_57_cast_fp16)[name = string("first_77_cast_fp16")];
            string input_59_mode_0 = const()[name = string("input_59_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 1024, 128]> input_59_cast_fp16 = gelu(mode = input_59_mode_0, x = first_77_cast_fp16)[name = string("input_59_cast_fp16")];
            string second_69_pad_type_0 = const()[name = string("second_69_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_69_strides_0 = const()[name = string("second_69_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_69_pad_0 = const()[name = string("second_69_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_69_dilations_0 = const()[name = string("second_69_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_69_groups_0 = const()[name = string("second_69_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> second_71_weight_0_to_fp16 = const()[name = string("second_71_weight_0_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10070528)))];
            tensor<fp16, [256]> second_71_bias_0_to_fp16 = const()[name = string("second_71_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10594880)))];
            tensor<fp16, [1, 256, 128]> second_71_cast_fp16 = conv(bias = second_71_bias_0_to_fp16, dilations = second_69_dilations_0, groups = second_69_groups_0, pad = second_69_pad_0, pad_type = second_69_pad_type_0, strides = second_69_strides_0, weight = second_71_weight_0_to_fp16, x = input_59_cast_fp16)[name = string("second_71_cast_fp16")];
            tensor<fp16, [1, 256, 128]> first_85_cast_fp16 = add(x = input_51_cast_fp16, y = second_71_cast_fp16)[name = string("first_85_cast_fp16")];
            tensor<fp16, [1, 256, 128]> first_89_cast_fp16 = mul(x = first_85_cast_fp16, y = text_mask)[name = string("first_89_cast_fp16")];
            tensor<int32, [1]> first_87_axes_0 = const()[name = string("first_87_axes_0"), val = tensor<int32, [1]>([2])];
            tensor<fp16, [1, 1, 1, 128]> first_87_cast_fp16 = expand_dims(axes = first_87_axes_0, x = text_mask)[name = string("first_87_cast_fp16")];
            tensor<int32, [1]> second_73_axes_0 = const()[name = string("second_73_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 1, 128, 1]> second_73_cast_fp16 = expand_dims(axes = second_73_axes_0, x = text_mask)[name = string("second_73_cast_fp16")];
            tensor<fp16, [1, 1, 128, 128]> x_45_cast_fp16 = mul(x = first_87_cast_fp16, y = second_73_cast_fp16)[name = string("x_45_cast_fp16")];
            tensor<fp16, [1, 256, 128]> input_61_cast_fp16 = mul(x = first_89_cast_fp16, y = text_mask)[name = string("input_61_cast_fp16")];
            string input_tensor_97_pad_type_0 = const()[name = string("input_tensor_97_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_97_strides_0 = const()[name = string("input_tensor_97_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_97_pad_0 = const()[name = string("input_tensor_97_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_97_dilations_0 = const()[name = string("input_tensor_97_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_97_groups_0 = const()[name = string("input_tensor_97_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_0_conv_q_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_q_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10595456)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_0_conv_q_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_q_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10726592)))];
            tensor<fp16, [1, 256, 128]> input_tensor_97_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_0_conv_q_Conv_bias_to_fp16, dilations = input_tensor_97_dilations_0, groups = input_tensor_97_groups_0, pad = input_tensor_97_pad_0, pad_type = input_tensor_97_pad_type_0, strides = input_tensor_97_strides_0, weight = text_encoder_attn_encoder_attn_layers_0_conv_q_Conv_weight_to_fp16, x = input_61_cast_fp16)[name = string("input_tensor_97_cast_fp16")];
            string input_tensor_89_pad_type_0 = const()[name = string("input_tensor_89_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_89_strides_0 = const()[name = string("input_tensor_89_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_89_pad_0 = const()[name = string("input_tensor_89_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_89_dilations_0 = const()[name = string("input_tensor_89_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_89_groups_0 = const()[name = string("input_tensor_89_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_0_conv_k_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_k_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10727168)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_0_conv_k_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_k_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10858304)))];
            tensor<fp16, [1, 256, 128]> input_tensor_89_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_0_conv_k_Conv_bias_to_fp16, dilations = input_tensor_89_dilations_0, groups = input_tensor_89_groups_0, pad = input_tensor_89_pad_0, pad_type = input_tensor_89_pad_type_0, strides = input_tensor_89_strides_0, weight = text_encoder_attn_encoder_attn_layers_0_conv_k_Conv_weight_to_fp16, x = input_61_cast_fp16)[name = string("input_tensor_89_cast_fp16")];
            string input_tensor_109_pad_type_0 = const()[name = string("input_tensor_109_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_109_strides_0 = const()[name = string("input_tensor_109_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_109_pad_0 = const()[name = string("input_tensor_109_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_109_dilations_0 = const()[name = string("input_tensor_109_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_109_groups_0 = const()[name = string("input_tensor_109_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_0_conv_v_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_v_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10858880)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_0_conv_v_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_v_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10990016)))];
            tensor<fp16, [1, 256, 128]> input_tensor_109_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_0_conv_v_Conv_bias_to_fp16, dilations = input_tensor_109_dilations_0, groups = input_tensor_109_groups_0, pad = input_tensor_109_pad_0, pad_type = input_tensor_109_pad_type_0, strides = input_tensor_109_strides_0, weight = text_encoder_attn_encoder_attn_layers_0_conv_v_Conv_weight_to_fp16, x = input_61_cast_fp16)[name = string("input_tensor_109_cast_fp16")];
            tensor<int32, [4]> var_973 = const()[name = string("op_973"), val = tensor<int32, [4]>([1, 4, 64, 128])];
            tensor<fp16, [1, 4, 64, 128]> input_tensor_105_cast_fp16 = reshape(shape = var_973, x = input_tensor_97_cast_fp16)[name = string("input_tensor_105_cast_fp16")];
            tensor<int32, [4]> var_979 = const()[name = string("op_979"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [4]> var_1005 = const()[name = string("op_1005"), val = tensor<int32, [4]>([1, 4, 64, 128])];
            tensor<fp16, [1, 4, 64, 128]> y_1_cast_fp16 = reshape(shape = var_1005, x = input_tensor_89_cast_fp16)[name = string("y_1_cast_fp16")];
            tensor<int32, [4]> var_1017 = const()[name = string("op_1017"), val = tensor<int32, [4]>([1, 4, 64, 128])];
            tensor<fp16, [1, 4, 64, 128]> input_tensor_111_cast_fp16 = reshape(shape = var_1017, x = input_tensor_109_cast_fp16)[name = string("input_tensor_111_cast_fp16")];
            fp16 _inversed_x_25_y_0_to_fp16 = const()[name = string("_inversed_x_25_y_0_to_fp16"), val = fp16(0x1p-3)];
            tensor<fp16, [1, 4, 128, 64]> first_91_cast_fp16 = transpose(perm = var_979, x = input_tensor_105_cast_fp16)[name = string("transpose_34")];
            tensor<fp16, [1, 4, 128, 64]> _inversed_x_25_cast_fp16 = mul(x = first_91_cast_fp16, y = _inversed_x_25_y_0_to_fp16)[name = string("_inversed_x_25_cast_fp16")];
            bool first_107_transpose_x_0 = const()[name = string("first_107_transpose_x_0"), val = bool(false)];
            bool first_107_transpose_y_0 = const()[name = string("first_107_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 4, 128, 128]> first_107_cast_fp16 = matmul(transpose_x = first_107_transpose_x_0, transpose_y = first_107_transpose_y_0, x = _inversed_x_25_cast_fp16, y = y_1_cast_fp16)[name = string("first_107_cast_fp16")];
            bool input_tensor_143_transpose_x_0 = const()[name = string("input_tensor_143_transpose_x_0"), val = bool(false)];
            bool input_tensor_143_transpose_y_0 = const()[name = string("input_tensor_143_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 64, 255]> y_3_to_fp16 = const()[name = string("y_3_to_fp16"), val = tensor<fp16, [1, 1, 64, 255]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(18054016)))];
            tensor<fp16, [1, 4, 128, 255]> input_tensor_143_cast_fp16 = matmul(transpose_x = input_tensor_143_transpose_x_0, transpose_y = input_tensor_143_transpose_y_0, x = _inversed_x_25_cast_fp16, y = y_3_to_fp16)[name = string("input_tensor_143_cast_fp16")];
            tensor<int32, [8]> input_tensor_165_pad_0 = const()[name = string("input_tensor_165_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 1])];
            string input_tensor_165_mode_0 = const()[name = string("input_tensor_165_mode_0"), val = string("constant")];
            fp16 const_23_to_fp16 = const()[name = string("const_23_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 128, 256]> input_tensor_165_cast_fp16 = pad(constant_val = const_23_to_fp16, mode = input_tensor_165_mode_0, pad = input_tensor_165_pad_0, x = input_tensor_143_cast_fp16)[name = string("input_tensor_165_cast_fp16")];
            tensor<int32, [3]> var_1140 = const()[name = string("op_1140"), val = tensor<int32, [3]>([1, 4, 32768])];
            tensor<fp16, [1, 4, 32768]> input_69_cast_fp16 = reshape(shape = var_1140, x = input_tensor_165_cast_fp16)[name = string("input_69_cast_fp16")];
            tensor<int32, [6]> input_tensor_187_pad_0 = const()[name = string("input_tensor_187_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 0, 127])];
            string input_tensor_187_mode_0 = const()[name = string("input_tensor_187_mode_0"), val = string("constant")];
            fp16 const_24_to_fp16 = const()[name = string("const_24_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 32895]> input_tensor_187_cast_fp16 = pad(constant_val = const_24_to_fp16, mode = input_tensor_187_mode_0, pad = input_tensor_187_pad_0, x = input_69_cast_fp16)[name = string("input_tensor_187_cast_fp16")];
            tensor<int32, [4]> var_1175 = const()[name = string("op_1175"), val = tensor<int32, [4]>([1, 4, 129, 255])];
            tensor<fp16, [1, 4, 129, 255]> x_41_cast_fp16 = reshape(shape = var_1175, x = input_tensor_187_cast_fp16)[name = string("x_41_cast_fp16")];
            tensor<int32, [4]> x_43_begin_0 = const()[name = string("x_43_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> x_43_end_0 = const()[name = string("x_43_end_0"), val = tensor<int32, [4]>([1, 4, 128, 255])];
            tensor<bool, [4]> x_43_end_mask_0 = const()[name = string("x_43_end_mask_0"), val = tensor<bool, [4]>([true, true, false, true])];
            tensor<fp16, [1, 4, 128, 255]> x_43_cast_fp16 = slice_by_index(begin = x_43_begin_0, end = x_43_end_0, end_mask = x_43_end_mask_0, x = x_41_cast_fp16)[name = string("x_43_cast_fp16")];
            tensor<int32, [4]> second_97_begin_0 = const()[name = string("second_97_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 127])];
            tensor<int32, [4]> second_97_end_0 = const()[name = string("second_97_end_0"), val = tensor<int32, [4]>([1, 4, 128, 1])];
            tensor<bool, [4]> second_97_end_mask_0 = const()[name = string("second_97_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 128, 128]> second_97_cast_fp16 = slice_by_index(begin = second_97_begin_0, end = second_97_end_0, end_mask = second_97_end_mask_0, x = x_43_cast_fp16)[name = string("second_97_cast_fp16")];
            tensor<fp16, [1, 4, 128, 128]> y_7_cast_fp16 = add(x = first_107_cast_fp16, y = second_97_cast_fp16)[name = string("y_7_cast_fp16")];
            fp16 text_encoder_attn_encoder_attn_layers_0_Constant_87_value_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_Constant_87_value_to_fp16"), val = fp16(0x0p+0)];
            tensor<bool, [1, 1, 128, 128]> input_tensor_189_cast_fp16 = equal(x = x_45_cast_fp16, y = text_encoder_attn_encoder_attn_layers_0_Constant_87_value_to_fp16)[name = string("input_tensor_189_cast_fp16")];
            tensor<int32, [4]> condition_1_after_broadcast_reps_0 = const()[name = string("condition_1_after_broadcast_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<bool, [1, 4, 128, 128]> condition_1_after_broadcast = tile(reps = condition_1_after_broadcast_reps_0, x = input_tensor_189_cast_fp16)[name = string("condition_1_after_broadcast")];
            tensor<fp16, [1, 4, 128, 128]> text_encoder_attn_encoder_attn_layers_0_Constant_88_value_after_broadcast_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_Constant_88_value_after_broadcast_to_fp16"), val = tensor<fp16, [1, 4, 128, 128]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(18086720)))];
            tensor<fp16, [1, 4, 128, 128]> input_71_cast_fp16 = select(a = text_encoder_attn_encoder_attn_layers_0_Constant_88_value_after_broadcast_to_fp16, b = y_7_cast_fp16, cond = condition_1_after_broadcast)[name = string("input_71_cast_fp16")];
            int32 var_1218 = const()[name = string("op_1218"), val = int32(-1)];
            tensor<fp16, [1, 4, 128, 128]> x_49_cast_fp16 = softmax(axis = var_1218, x = input_71_cast_fp16)[name = string("x_49_cast_fp16")];
            bool first_119_transpose_x_1 = const()[name = string("first_119_transpose_x_1"), val = bool(false)];
            bool first_119_transpose_y_1 = const()[name = string("first_119_transpose_y_1"), val = bool(true)];
            tensor<fp16, [1, 4, 128, 64]> first_119_cast_fp16 = matmul(transpose_x = first_119_transpose_x_1, transpose_y = first_119_transpose_y_1, x = x_49_cast_fp16, y = input_tensor_111_cast_fp16)[name = string("first_119_cast_fp16")];
            tensor<int32, [8]> input_tensor_219_pad_0 = const()[name = string("input_tensor_219_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 127])];
            string input_tensor_219_mode_0 = const()[name = string("input_tensor_219_mode_0"), val = string("constant")];
            fp16 const_31_to_fp16 = const()[name = string("const_31_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 128, 255]> input_tensor_219_cast_fp16 = pad(constant_val = const_31_to_fp16, mode = input_tensor_219_mode_0, pad = input_tensor_219_pad_0, x = x_49_cast_fp16)[name = string("input_tensor_219_cast_fp16")];
            tensor<int32, [3]> var_1292 = const()[name = string("op_1292"), val = tensor<int32, [3]>([1, 4, 32640])];
            tensor<fp16, [1, 4, 32640]> input_73_cast_fp16 = reshape(shape = var_1292, x = input_tensor_219_cast_fp16)[name = string("input_73_cast_fp16")];
            tensor<int32, [6]> input_tensor_237_pad_0 = const()[name = string("input_tensor_237_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 128, 0])];
            string input_tensor_237_mode_0 = const()[name = string("input_tensor_237_mode_0"), val = string("constant")];
            fp16 const_32_to_fp16 = const()[name = string("const_32_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 32768]> input_tensor_237_cast_fp16 = pad(constant_val = const_32_to_fp16, mode = input_tensor_237_mode_0, pad = input_tensor_237_pad_0, x = input_73_cast_fp16)[name = string("input_tensor_237_cast_fp16")];
            tensor<int32, [4]> var_1322 = const()[name = string("op_1322"), val = tensor<int32, [4]>([1, 4, 128, 256])];
            tensor<fp16, [1, 4, 128, 256]> x_59_cast_fp16 = reshape(shape = var_1322, x = input_tensor_237_cast_fp16)[name = string("x_59_cast_fp16")];
            tensor<int32, [4]> x_67_begin_0 = const()[name = string("x_67_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 1])];
            tensor<int32, [4]> x_67_end_0 = const()[name = string("x_67_end_0"), val = tensor<int32, [4]>([1, 4, 128, 1])];
            tensor<bool, [4]> x_67_end_mask_0 = const()[name = string("x_67_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 128, 255]> x_67_cast_fp16 = slice_by_index(begin = x_67_begin_0, end = x_67_end_0, end_mask = x_67_end_mask_0, x = x_59_cast_fp16)[name = string("x_67_cast_fp16")];
            bool second_111_transpose_x_0 = const()[name = string("second_111_transpose_x_0"), val = bool(false)];
            bool second_111_transpose_y_0 = const()[name = string("second_111_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 255, 64]> y_11_to_fp16 = const()[name = string("y_11_to_fp16"), val = tensor<fp16, [1, 1, 255, 64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(18217856)))];
            tensor<fp16, [1, 4, 128, 64]> second_111_cast_fp16 = matmul(transpose_x = second_111_transpose_x_0, transpose_y = second_111_transpose_y_0, x = x_67_cast_fp16, y = y_11_to_fp16)[name = string("second_111_cast_fp16")];
            tensor<fp16, [1, 4, 128, 64]> input_tensor_255_cast_fp16 = add(x = first_119_cast_fp16, y = second_111_cast_fp16)[name = string("input_tensor_255_cast_fp16")];
            tensor<int32, [4]> var_1369 = const()[name = string("op_1369"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [3]> var_1388 = const()[name = string("op_1388"), val = tensor<int32, [3]>([1, 256, 128])];
            tensor<fp16, [1, 4, 64, 128]> input_tensor_259_cast_fp16 = transpose(perm = var_1369, x = input_tensor_255_cast_fp16)[name = string("transpose_33")];
            tensor<fp16, [1, 256, 128]> input_77_cast_fp16 = reshape(shape = var_1388, x = input_tensor_259_cast_fp16)[name = string("input_77_cast_fp16")];
            string second_113_pad_type_0 = const()[name = string("second_113_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_113_strides_0 = const()[name = string("second_113_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_113_pad_0 = const()[name = string("second_113_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_113_dilations_0 = const()[name = string("second_113_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_113_groups_0 = const()[name = string("second_113_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_0_conv_o_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_o_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11000768)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_0_conv_o_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_o_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11131904)))];
            tensor<fp16, [1, 256, 128]> second_113_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_0_conv_o_Conv_bias_to_fp16, dilations = second_113_dilations_0, groups = second_113_groups_0, pad = second_113_pad_0, pad_type = second_113_pad_type_0, strides = second_113_strides_0, weight = text_encoder_attn_encoder_attn_layers_0_conv_o_Conv_weight_to_fp16, x = input_77_cast_fp16)[name = string("second_113_cast_fp16")];
            tensor<fp16, [1, 256, 128]> input_tensor_261_cast_fp16 = add(x = input_61_cast_fp16, y = second_113_cast_fp16)[name = string("input_tensor_261_cast_fp16")];
            tensor<int32, [3]> var_1406 = const()[name = string("op_1406"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_263_axes_0 = const()[name = string("input_tensor_263_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_0_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_0_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11132480)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_0_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_0_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11133056)))];
            fp16 var_1409_to_fp16 = const()[name = string("op_1409_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 128, 256]> input_79_cast_fp16 = transpose(perm = var_1406, x = input_tensor_261_cast_fp16)[name = string("transpose_32")];
            tensor<fp16, [1, 128, 256]> input_tensor_263_cast_fp16 = layer_norm(axes = input_tensor_263_axes_0, beta = text_encoder_attn_encoder_norm_layers_1_0_norm_LayerNormalization_bias_to_fp16, epsilon = var_1409_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_1_0_norm_LayerNormalization_weight_to_fp16, x = input_79_cast_fp16)[name = string("input_tensor_263_cast_fp16")];
            tensor<int32, [3]> var_1418 = const()[name = string("op_1418"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 256, 128]> first_121_cast_fp16 = transpose(perm = var_1418, x = input_tensor_263_cast_fp16)[name = string("transpose_31")];
            tensor<fp16, [1, 256, 128]> input_81_cast_fp16 = mul(x = first_121_cast_fp16, y = text_mask)[name = string("input_81_cast_fp16")];
            string input_83_pad_type_0 = const()[name = string("input_83_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_83_strides_0 = const()[name = string("input_83_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_83_pad_0 = const()[name = string("input_83_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_83_dilations_0 = const()[name = string("input_83_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_83_groups_0 = const()[name = string("input_83_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_attn_encoder_ffn_layers_0_conv_1_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_0_conv_1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11133632)))];
            tensor<fp16, [1024]> text_encoder_attn_encoder_ffn_layers_0_conv_1_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_0_conv_1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11657984)))];
            tensor<fp16, [1, 1024, 128]> input_83_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_0_conv_1_Conv_bias_to_fp16, dilations = input_83_dilations_0, groups = input_83_groups_0, pad = input_83_pad_0, pad_type = input_83_pad_type_0, strides = input_83_strides_0, weight = text_encoder_attn_encoder_ffn_layers_0_conv_1_Conv_weight_to_fp16, x = input_81_cast_fp16)[name = string("input_83_cast_fp16")];
            tensor<fp16, [1, 1024, 128]> first_123_cast_fp16 = relu(x = input_83_cast_fp16)[name = string("first_123_cast_fp16")];
            tensor<fp16, [1, 1024, 128]> input_85_cast_fp16 = mul(x = first_123_cast_fp16, y = text_mask)[name = string("input_85_cast_fp16")];
            string first_125_pad_type_0 = const()[name = string("first_125_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_125_strides_0 = const()[name = string("first_125_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_125_pad_0 = const()[name = string("first_125_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_125_dilations_0 = const()[name = string("first_125_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_125_groups_0 = const()[name = string("first_125_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> text_encoder_attn_encoder_ffn_layers_0_conv_2_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_0_conv_2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11660096)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_ffn_layers_0_conv_2_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_0_conv_2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12184448)))];
            tensor<fp16, [1, 256, 128]> first_125_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_0_conv_2_Conv_bias_to_fp16, dilations = first_125_dilations_0, groups = first_125_groups_0, pad = first_125_pad_0, pad_type = first_125_pad_type_0, strides = first_125_strides_0, weight = text_encoder_attn_encoder_ffn_layers_0_conv_2_Conv_weight_to_fp16, x = input_85_cast_fp16)[name = string("first_125_cast_fp16")];
            tensor<fp16, [1, 256, 128]> second_115_cast_fp16 = mul(x = first_125_cast_fp16, y = text_mask)[name = string("second_115_cast_fp16")];
            tensor<fp16, [1, 256, 128]> input_tensor_265_cast_fp16 = add(x = first_121_cast_fp16, y = second_115_cast_fp16)[name = string("input_tensor_265_cast_fp16")];
            tensor<int32, [3]> var_1451 = const()[name = string("op_1451"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_267_axes_0 = const()[name = string("input_tensor_267_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_0_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_0_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12185024)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_0_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_0_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12185600)))];
            fp16 var_1454_to_fp16 = const()[name = string("op_1454_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 128, 256]> input_87_cast_fp16 = transpose(perm = var_1451, x = input_tensor_265_cast_fp16)[name = string("transpose_30")];
            tensor<fp16, [1, 128, 256]> input_tensor_267_cast_fp16 = layer_norm(axes = input_tensor_267_axes_0, beta = text_encoder_attn_encoder_norm_layers_2_0_norm_LayerNormalization_bias_to_fp16, epsilon = var_1454_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_2_0_norm_LayerNormalization_weight_to_fp16, x = input_87_cast_fp16)[name = string("input_tensor_267_cast_fp16")];
            tensor<int32, [3]> var_1463 = const()[name = string("op_1463"), val = tensor<int32, [3]>([0, 2, 1])];
            string input_tensor_277_pad_type_0 = const()[name = string("input_tensor_277_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_277_strides_0 = const()[name = string("input_tensor_277_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_277_pad_0 = const()[name = string("input_tensor_277_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_277_dilations_0 = const()[name = string("input_tensor_277_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_277_groups_0 = const()[name = string("input_tensor_277_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_1_conv_q_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_q_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12186176)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_1_conv_q_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_q_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12317312)))];
            tensor<fp16, [1, 256, 128]> input_89_cast_fp16 = transpose(perm = var_1463, x = input_tensor_267_cast_fp16)[name = string("transpose_29")];
            tensor<fp16, [1, 256, 128]> input_tensor_277_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_1_conv_q_Conv_bias_to_fp16, dilations = input_tensor_277_dilations_0, groups = input_tensor_277_groups_0, pad = input_tensor_277_pad_0, pad_type = input_tensor_277_pad_type_0, strides = input_tensor_277_strides_0, weight = text_encoder_attn_encoder_attn_layers_1_conv_q_Conv_weight_to_fp16, x = input_89_cast_fp16)[name = string("input_tensor_277_cast_fp16")];
            string input_tensor_269_pad_type_0 = const()[name = string("input_tensor_269_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_269_strides_0 = const()[name = string("input_tensor_269_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_269_pad_0 = const()[name = string("input_tensor_269_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_269_dilations_0 = const()[name = string("input_tensor_269_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_269_groups_0 = const()[name = string("input_tensor_269_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_1_conv_k_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_k_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12317888)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_1_conv_k_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_k_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12449024)))];
            tensor<fp16, [1, 256, 128]> input_tensor_269_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_1_conv_k_Conv_bias_to_fp16, dilations = input_tensor_269_dilations_0, groups = input_tensor_269_groups_0, pad = input_tensor_269_pad_0, pad_type = input_tensor_269_pad_type_0, strides = input_tensor_269_strides_0, weight = text_encoder_attn_encoder_attn_layers_1_conv_k_Conv_weight_to_fp16, x = input_89_cast_fp16)[name = string("input_tensor_269_cast_fp16")];
            string input_tensor_289_pad_type_0 = const()[name = string("input_tensor_289_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_289_strides_0 = const()[name = string("input_tensor_289_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_289_pad_0 = const()[name = string("input_tensor_289_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_289_dilations_0 = const()[name = string("input_tensor_289_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_289_groups_0 = const()[name = string("input_tensor_289_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_1_conv_v_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_v_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12449600)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_1_conv_v_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_v_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12580736)))];
            tensor<fp16, [1, 256, 128]> input_tensor_289_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_1_conv_v_Conv_bias_to_fp16, dilations = input_tensor_289_dilations_0, groups = input_tensor_289_groups_0, pad = input_tensor_289_pad_0, pad_type = input_tensor_289_pad_type_0, strides = input_tensor_289_strides_0, weight = text_encoder_attn_encoder_attn_layers_1_conv_v_Conv_weight_to_fp16, x = input_89_cast_fp16)[name = string("input_tensor_289_cast_fp16")];
            tensor<int32, [4]> var_1571 = const()[name = string("op_1571"), val = tensor<int32, [4]>([1, 4, 64, 128])];
            tensor<fp16, [1, 4, 64, 128]> input_tensor_285_cast_fp16 = reshape(shape = var_1571, x = input_tensor_277_cast_fp16)[name = string("input_tensor_285_cast_fp16")];
            tensor<int32, [4]> var_1577 = const()[name = string("op_1577"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [4]> var_1603 = const()[name = string("op_1603"), val = tensor<int32, [4]>([1, 4, 64, 128])];
            tensor<fp16, [1, 4, 64, 128]> y_13_cast_fp16 = reshape(shape = var_1603, x = input_tensor_269_cast_fp16)[name = string("y_13_cast_fp16")];
            tensor<int32, [4]> var_1615 = const()[name = string("op_1615"), val = tensor<int32, [4]>([1, 4, 64, 128])];
            tensor<fp16, [1, 4, 64, 128]> input_tensor_291_cast_fp16 = reshape(shape = var_1615, x = input_tensor_289_cast_fp16)[name = string("input_tensor_291_cast_fp16")];
            fp16 _inversed_x_69_y_0_to_fp16 = const()[name = string("_inversed_x_69_y_0_to_fp16"), val = fp16(0x1p-3)];
            tensor<fp16, [1, 4, 128, 64]> first_127_cast_fp16 = transpose(perm = var_1577, x = input_tensor_285_cast_fp16)[name = string("transpose_28")];
            tensor<fp16, [1, 4, 128, 64]> _inversed_x_69_cast_fp16 = mul(x = first_127_cast_fp16, y = _inversed_x_69_y_0_to_fp16)[name = string("_inversed_x_69_cast_fp16")];
            bool first_143_transpose_x_0 = const()[name = string("first_143_transpose_x_0"), val = bool(false)];
            bool first_143_transpose_y_0 = const()[name = string("first_143_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 4, 128, 128]> first_143_cast_fp16 = matmul(transpose_x = first_143_transpose_x_0, transpose_y = first_143_transpose_y_0, x = _inversed_x_69_cast_fp16, y = y_13_cast_fp16)[name = string("first_143_cast_fp16")];
            bool input_tensor_323_transpose_x_0 = const()[name = string("input_tensor_323_transpose_x_0"), val = bool(false)];
            bool input_tensor_323_transpose_y_0 = const()[name = string("input_tensor_323_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 64, 255]> y_15_to_fp16 = const()[name = string("y_15_to_fp16"), val = tensor<fp16, [1, 1, 64, 255]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(18250560)))];
            tensor<fp16, [1, 4, 128, 255]> input_tensor_323_cast_fp16 = matmul(transpose_x = input_tensor_323_transpose_x_0, transpose_y = input_tensor_323_transpose_y_0, x = _inversed_x_69_cast_fp16, y = y_15_to_fp16)[name = string("input_tensor_323_cast_fp16")];
            tensor<int32, [8]> input_tensor_345_pad_0 = const()[name = string("input_tensor_345_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 1])];
            string input_tensor_345_mode_0 = const()[name = string("input_tensor_345_mode_0"), val = string("constant")];
            fp16 const_51_to_fp16 = const()[name = string("const_51_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 128, 256]> input_tensor_345_cast_fp16 = pad(constant_val = const_51_to_fp16, mode = input_tensor_345_mode_0, pad = input_tensor_345_pad_0, x = input_tensor_323_cast_fp16)[name = string("input_tensor_345_cast_fp16")];
            tensor<int32, [3]> var_1738 = const()[name = string("op_1738"), val = tensor<int32, [3]>([1, 4, 32768])];
            tensor<fp16, [1, 4, 32768]> input_97_cast_fp16 = reshape(shape = var_1738, x = input_tensor_345_cast_fp16)[name = string("input_97_cast_fp16")];
            tensor<int32, [6]> input_tensor_367_pad_0 = const()[name = string("input_tensor_367_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 0, 127])];
            string input_tensor_367_mode_0 = const()[name = string("input_tensor_367_mode_0"), val = string("constant")];
            fp16 const_52_to_fp16 = const()[name = string("const_52_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 32895]> input_tensor_367_cast_fp16 = pad(constant_val = const_52_to_fp16, mode = input_tensor_367_mode_0, pad = input_tensor_367_pad_0, x = input_97_cast_fp16)[name = string("input_tensor_367_cast_fp16")];
            tensor<int32, [4]> var_1773 = const()[name = string("op_1773"), val = tensor<int32, [4]>([1, 4, 129, 255])];
            tensor<fp16, [1, 4, 129, 255]> x_85_cast_fp16 = reshape(shape = var_1773, x = input_tensor_367_cast_fp16)[name = string("x_85_cast_fp16")];
            tensor<int32, [4]> x_87_begin_0 = const()[name = string("x_87_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> x_87_end_0 = const()[name = string("x_87_end_0"), val = tensor<int32, [4]>([1, 4, 128, 255])];
            tensor<bool, [4]> x_87_end_mask_0 = const()[name = string("x_87_end_mask_0"), val = tensor<bool, [4]>([true, true, false, true])];
            tensor<fp16, [1, 4, 128, 255]> x_87_cast_fp16 = slice_by_index(begin = x_87_begin_0, end = x_87_end_0, end_mask = x_87_end_mask_0, x = x_85_cast_fp16)[name = string("x_87_cast_fp16")];
            tensor<int32, [4]> second_139_begin_0 = const()[name = string("second_139_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 127])];
            tensor<int32, [4]> second_139_end_0 = const()[name = string("second_139_end_0"), val = tensor<int32, [4]>([1, 4, 128, 1])];
            tensor<bool, [4]> second_139_end_mask_0 = const()[name = string("second_139_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 128, 128]> second_139_cast_fp16 = slice_by_index(begin = second_139_begin_0, end = second_139_end_0, end_mask = second_139_end_mask_0, x = x_87_cast_fp16)[name = string("second_139_cast_fp16")];
            tensor<fp16, [1, 4, 128, 128]> y_17_cast_fp16 = add(x = first_143_cast_fp16, y = second_139_cast_fp16)[name = string("y_17_cast_fp16")];
            tensor<fp16, [1, 4, 128, 128]> input_99_cast_fp16 = select(a = text_encoder_attn_encoder_attn_layers_0_Constant_88_value_after_broadcast_to_fp16, b = y_17_cast_fp16, cond = condition_1_after_broadcast)[name = string("input_99_cast_fp16")];
            int32 var_1815 = const()[name = string("op_1815"), val = int32(-1)];
            tensor<fp16, [1, 4, 128, 128]> x_91_cast_fp16 = softmax(axis = var_1815, x = input_99_cast_fp16)[name = string("x_91_cast_fp16")];
            bool first_155_transpose_x_1 = const()[name = string("first_155_transpose_x_1"), val = bool(false)];
            bool first_155_transpose_y_1 = const()[name = string("first_155_transpose_y_1"), val = bool(true)];
            tensor<fp16, [1, 4, 128, 64]> first_155_cast_fp16 = matmul(transpose_x = first_155_transpose_x_1, transpose_y = first_155_transpose_y_1, x = x_91_cast_fp16, y = input_tensor_291_cast_fp16)[name = string("first_155_cast_fp16")];
            tensor<int32, [8]> input_tensor_397_pad_0 = const()[name = string("input_tensor_397_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 127])];
            string input_tensor_397_mode_0 = const()[name = string("input_tensor_397_mode_0"), val = string("constant")];
            fp16 const_59_to_fp16 = const()[name = string("const_59_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 128, 255]> input_tensor_397_cast_fp16 = pad(constant_val = const_59_to_fp16, mode = input_tensor_397_mode_0, pad = input_tensor_397_pad_0, x = x_91_cast_fp16)[name = string("input_tensor_397_cast_fp16")];
            tensor<int32, [3]> var_1889 = const()[name = string("op_1889"), val = tensor<int32, [3]>([1, 4, 32640])];
            tensor<fp16, [1, 4, 32640]> input_101_cast_fp16 = reshape(shape = var_1889, x = input_tensor_397_cast_fp16)[name = string("input_101_cast_fp16")];
            tensor<int32, [6]> input_tensor_415_pad_0 = const()[name = string("input_tensor_415_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 128, 0])];
            string input_tensor_415_mode_0 = const()[name = string("input_tensor_415_mode_0"), val = string("constant")];
            fp16 const_60_to_fp16 = const()[name = string("const_60_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 32768]> input_tensor_415_cast_fp16 = pad(constant_val = const_60_to_fp16, mode = input_tensor_415_mode_0, pad = input_tensor_415_pad_0, x = input_101_cast_fp16)[name = string("input_tensor_415_cast_fp16")];
            tensor<int32, [4]> var_1919 = const()[name = string("op_1919"), val = tensor<int32, [4]>([1, 4, 128, 256])];
            tensor<fp16, [1, 4, 128, 256]> x_101_cast_fp16 = reshape(shape = var_1919, x = input_tensor_415_cast_fp16)[name = string("x_101_cast_fp16")];
            tensor<int32, [4]> x_109_begin_0 = const()[name = string("x_109_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 1])];
            tensor<int32, [4]> x_109_end_0 = const()[name = string("x_109_end_0"), val = tensor<int32, [4]>([1, 4, 128, 1])];
            tensor<bool, [4]> x_109_end_mask_0 = const()[name = string("x_109_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 128, 255]> x_109_cast_fp16 = slice_by_index(begin = x_109_begin_0, end = x_109_end_0, end_mask = x_109_end_mask_0, x = x_101_cast_fp16)[name = string("x_109_cast_fp16")];
            bool second_153_transpose_x_0 = const()[name = string("second_153_transpose_x_0"), val = bool(false)];
            bool second_153_transpose_y_0 = const()[name = string("second_153_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 255, 64]> y_21_to_fp16 = const()[name = string("y_21_to_fp16"), val = tensor<fp16, [1, 1, 255, 64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(18283264)))];
            tensor<fp16, [1, 4, 128, 64]> second_153_cast_fp16 = matmul(transpose_x = second_153_transpose_x_0, transpose_y = second_153_transpose_y_0, x = x_109_cast_fp16, y = y_21_to_fp16)[name = string("second_153_cast_fp16")];
            tensor<fp16, [1, 4, 128, 64]> input_tensor_433_cast_fp16 = add(x = first_155_cast_fp16, y = second_153_cast_fp16)[name = string("input_tensor_433_cast_fp16")];
            tensor<int32, [4]> var_1966 = const()[name = string("op_1966"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [3]> var_1985 = const()[name = string("op_1985"), val = tensor<int32, [3]>([1, 256, 128])];
            tensor<fp16, [1, 4, 64, 128]> input_tensor_437_cast_fp16 = transpose(perm = var_1966, x = input_tensor_433_cast_fp16)[name = string("transpose_27")];
            tensor<fp16, [1, 256, 128]> input_105_cast_fp16 = reshape(shape = var_1985, x = input_tensor_437_cast_fp16)[name = string("input_105_cast_fp16")];
            string second_155_pad_type_0 = const()[name = string("second_155_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_155_strides_0 = const()[name = string("second_155_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_155_pad_0 = const()[name = string("second_155_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_155_dilations_0 = const()[name = string("second_155_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_155_groups_0 = const()[name = string("second_155_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_1_conv_o_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_o_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12589376)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_1_conv_o_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_o_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12720512)))];
            tensor<fp16, [1, 256, 128]> second_155_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_1_conv_o_Conv_bias_to_fp16, dilations = second_155_dilations_0, groups = second_155_groups_0, pad = second_155_pad_0, pad_type = second_155_pad_type_0, strides = second_155_strides_0, weight = text_encoder_attn_encoder_attn_layers_1_conv_o_Conv_weight_to_fp16, x = input_105_cast_fp16)[name = string("second_155_cast_fp16")];
            tensor<fp16, [1, 256, 128]> input_tensor_439_cast_fp16 = add(x = input_89_cast_fp16, y = second_155_cast_fp16)[name = string("input_tensor_439_cast_fp16")];
            tensor<int32, [3]> var_2003 = const()[name = string("op_2003"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_441_axes_0 = const()[name = string("input_tensor_441_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_1_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_1_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12721088)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_1_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_1_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12721664)))];
            fp16 var_2006_to_fp16 = const()[name = string("op_2006_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 128, 256]> input_107_cast_fp16 = transpose(perm = var_2003, x = input_tensor_439_cast_fp16)[name = string("transpose_26")];
            tensor<fp16, [1, 128, 256]> input_tensor_441_cast_fp16 = layer_norm(axes = input_tensor_441_axes_0, beta = text_encoder_attn_encoder_norm_layers_1_1_norm_LayerNormalization_bias_to_fp16, epsilon = var_2006_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_1_1_norm_LayerNormalization_weight_to_fp16, x = input_107_cast_fp16)[name = string("input_tensor_441_cast_fp16")];
            tensor<int32, [3]> var_2015 = const()[name = string("op_2015"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 256, 128]> first_157_cast_fp16 = transpose(perm = var_2015, x = input_tensor_441_cast_fp16)[name = string("transpose_25")];
            tensor<fp16, [1, 256, 128]> input_109_cast_fp16 = mul(x = first_157_cast_fp16, y = text_mask)[name = string("input_109_cast_fp16")];
            string input_111_pad_type_0 = const()[name = string("input_111_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_111_strides_0 = const()[name = string("input_111_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_111_pad_0 = const()[name = string("input_111_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_111_dilations_0 = const()[name = string("input_111_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_111_groups_0 = const()[name = string("input_111_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_attn_encoder_ffn_layers_1_conv_1_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_1_conv_1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12722240)))];
            tensor<fp16, [1024]> text_encoder_attn_encoder_ffn_layers_1_conv_1_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_1_conv_1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13246592)))];
            tensor<fp16, [1, 1024, 128]> input_111_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_1_conv_1_Conv_bias_to_fp16, dilations = input_111_dilations_0, groups = input_111_groups_0, pad = input_111_pad_0, pad_type = input_111_pad_type_0, strides = input_111_strides_0, weight = text_encoder_attn_encoder_ffn_layers_1_conv_1_Conv_weight_to_fp16, x = input_109_cast_fp16)[name = string("input_111_cast_fp16")];
            tensor<fp16, [1, 1024, 128]> first_159_cast_fp16 = relu(x = input_111_cast_fp16)[name = string("first_159_cast_fp16")];
            tensor<fp16, [1, 1024, 128]> input_113_cast_fp16 = mul(x = first_159_cast_fp16, y = text_mask)[name = string("input_113_cast_fp16")];
            string first_161_pad_type_0 = const()[name = string("first_161_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_161_strides_0 = const()[name = string("first_161_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_161_pad_0 = const()[name = string("first_161_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_161_dilations_0 = const()[name = string("first_161_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_161_groups_0 = const()[name = string("first_161_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> text_encoder_attn_encoder_ffn_layers_1_conv_2_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_1_conv_2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13248704)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_ffn_layers_1_conv_2_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_1_conv_2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13773056)))];
            tensor<fp16, [1, 256, 128]> first_161_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_1_conv_2_Conv_bias_to_fp16, dilations = first_161_dilations_0, groups = first_161_groups_0, pad = first_161_pad_0, pad_type = first_161_pad_type_0, strides = first_161_strides_0, weight = text_encoder_attn_encoder_ffn_layers_1_conv_2_Conv_weight_to_fp16, x = input_113_cast_fp16)[name = string("first_161_cast_fp16")];
            tensor<fp16, [1, 256, 128]> second_157_cast_fp16 = mul(x = first_161_cast_fp16, y = text_mask)[name = string("second_157_cast_fp16")];
            tensor<fp16, [1, 256, 128]> input_tensor_443_cast_fp16 = add(x = first_157_cast_fp16, y = second_157_cast_fp16)[name = string("input_tensor_443_cast_fp16")];
            tensor<int32, [3]> var_2048 = const()[name = string("op_2048"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_445_axes_0 = const()[name = string("input_tensor_445_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_1_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_1_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13773632)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_1_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_1_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13774208)))];
            fp16 var_2051_to_fp16 = const()[name = string("op_2051_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 128, 256]> input_115_cast_fp16 = transpose(perm = var_2048, x = input_tensor_443_cast_fp16)[name = string("transpose_24")];
            tensor<fp16, [1, 128, 256]> input_tensor_445_cast_fp16 = layer_norm(axes = input_tensor_445_axes_0, beta = text_encoder_attn_encoder_norm_layers_2_1_norm_LayerNormalization_bias_to_fp16, epsilon = var_2051_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_2_1_norm_LayerNormalization_weight_to_fp16, x = input_115_cast_fp16)[name = string("input_tensor_445_cast_fp16")];
            tensor<int32, [3]> var_2060 = const()[name = string("op_2060"), val = tensor<int32, [3]>([0, 2, 1])];
            string input_tensor_455_pad_type_0 = const()[name = string("input_tensor_455_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_455_strides_0 = const()[name = string("input_tensor_455_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_455_pad_0 = const()[name = string("input_tensor_455_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_455_dilations_0 = const()[name = string("input_tensor_455_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_455_groups_0 = const()[name = string("input_tensor_455_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_2_conv_q_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_q_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13774784)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_2_conv_q_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_q_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13905920)))];
            tensor<fp16, [1, 256, 128]> input_117_cast_fp16 = transpose(perm = var_2060, x = input_tensor_445_cast_fp16)[name = string("transpose_23")];
            tensor<fp16, [1, 256, 128]> input_tensor_455_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_2_conv_q_Conv_bias_to_fp16, dilations = input_tensor_455_dilations_0, groups = input_tensor_455_groups_0, pad = input_tensor_455_pad_0, pad_type = input_tensor_455_pad_type_0, strides = input_tensor_455_strides_0, weight = text_encoder_attn_encoder_attn_layers_2_conv_q_Conv_weight_to_fp16, x = input_117_cast_fp16)[name = string("input_tensor_455_cast_fp16")];
            string input_tensor_447_pad_type_0 = const()[name = string("input_tensor_447_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_447_strides_0 = const()[name = string("input_tensor_447_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_447_pad_0 = const()[name = string("input_tensor_447_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_447_dilations_0 = const()[name = string("input_tensor_447_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_447_groups_0 = const()[name = string("input_tensor_447_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_2_conv_k_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_k_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13906496)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_2_conv_k_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_k_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14037632)))];
            tensor<fp16, [1, 256, 128]> input_tensor_447_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_2_conv_k_Conv_bias_to_fp16, dilations = input_tensor_447_dilations_0, groups = input_tensor_447_groups_0, pad = input_tensor_447_pad_0, pad_type = input_tensor_447_pad_type_0, strides = input_tensor_447_strides_0, weight = text_encoder_attn_encoder_attn_layers_2_conv_k_Conv_weight_to_fp16, x = input_117_cast_fp16)[name = string("input_tensor_447_cast_fp16")];
            string input_tensor_467_pad_type_0 = const()[name = string("input_tensor_467_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_467_strides_0 = const()[name = string("input_tensor_467_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_467_pad_0 = const()[name = string("input_tensor_467_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_467_dilations_0 = const()[name = string("input_tensor_467_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_467_groups_0 = const()[name = string("input_tensor_467_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_2_conv_v_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_v_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14038208)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_2_conv_v_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_v_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14169344)))];
            tensor<fp16, [1, 256, 128]> input_tensor_467_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_2_conv_v_Conv_bias_to_fp16, dilations = input_tensor_467_dilations_0, groups = input_tensor_467_groups_0, pad = input_tensor_467_pad_0, pad_type = input_tensor_467_pad_type_0, strides = input_tensor_467_strides_0, weight = text_encoder_attn_encoder_attn_layers_2_conv_v_Conv_weight_to_fp16, x = input_117_cast_fp16)[name = string("input_tensor_467_cast_fp16")];
            tensor<int32, [4]> var_2168 = const()[name = string("op_2168"), val = tensor<int32, [4]>([1, 4, 64, 128])];
            tensor<fp16, [1, 4, 64, 128]> input_tensor_463_cast_fp16 = reshape(shape = var_2168, x = input_tensor_455_cast_fp16)[name = string("input_tensor_463_cast_fp16")];
            tensor<int32, [4]> var_2174 = const()[name = string("op_2174"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [4]> var_2200 = const()[name = string("op_2200"), val = tensor<int32, [4]>([1, 4, 64, 128])];
            tensor<fp16, [1, 4, 64, 128]> y_23_cast_fp16 = reshape(shape = var_2200, x = input_tensor_447_cast_fp16)[name = string("y_23_cast_fp16")];
            tensor<int32, [4]> var_2212 = const()[name = string("op_2212"), val = tensor<int32, [4]>([1, 4, 64, 128])];
            tensor<fp16, [1, 4, 64, 128]> input_tensor_469_cast_fp16 = reshape(shape = var_2212, x = input_tensor_467_cast_fp16)[name = string("input_tensor_469_cast_fp16")];
            fp16 _inversed_x_111_y_0_to_fp16 = const()[name = string("_inversed_x_111_y_0_to_fp16"), val = fp16(0x1p-3)];
            tensor<fp16, [1, 4, 128, 64]> first_163_cast_fp16 = transpose(perm = var_2174, x = input_tensor_463_cast_fp16)[name = string("transpose_22")];
            tensor<fp16, [1, 4, 128, 64]> _inversed_x_111_cast_fp16 = mul(x = first_163_cast_fp16, y = _inversed_x_111_y_0_to_fp16)[name = string("_inversed_x_111_cast_fp16")];
            bool first_179_transpose_x_0 = const()[name = string("first_179_transpose_x_0"), val = bool(false)];
            bool first_179_transpose_y_0 = const()[name = string("first_179_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 4, 128, 128]> first_179_cast_fp16 = matmul(transpose_x = first_179_transpose_x_0, transpose_y = first_179_transpose_y_0, x = _inversed_x_111_cast_fp16, y = y_23_cast_fp16)[name = string("first_179_cast_fp16")];
            bool input_tensor_501_transpose_x_0 = const()[name = string("input_tensor_501_transpose_x_0"), val = bool(false)];
            bool input_tensor_501_transpose_y_0 = const()[name = string("input_tensor_501_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 64, 255]> y_25_to_fp16 = const()[name = string("y_25_to_fp16"), val = tensor<fp16, [1, 1, 64, 255]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(18315968)))];
            tensor<fp16, [1, 4, 128, 255]> input_tensor_501_cast_fp16 = matmul(transpose_x = input_tensor_501_transpose_x_0, transpose_y = input_tensor_501_transpose_y_0, x = _inversed_x_111_cast_fp16, y = y_25_to_fp16)[name = string("input_tensor_501_cast_fp16")];
            tensor<int32, [8]> input_tensor_523_pad_0 = const()[name = string("input_tensor_523_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 1])];
            string input_tensor_523_mode_0 = const()[name = string("input_tensor_523_mode_0"), val = string("constant")];
            fp16 const_79_to_fp16 = const()[name = string("const_79_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 128, 256]> input_tensor_523_cast_fp16 = pad(constant_val = const_79_to_fp16, mode = input_tensor_523_mode_0, pad = input_tensor_523_pad_0, x = input_tensor_501_cast_fp16)[name = string("input_tensor_523_cast_fp16")];
            tensor<int32, [3]> var_2335 = const()[name = string("op_2335"), val = tensor<int32, [3]>([1, 4, 32768])];
            tensor<fp16, [1, 4, 32768]> input_125_cast_fp16 = reshape(shape = var_2335, x = input_tensor_523_cast_fp16)[name = string("input_125_cast_fp16")];
            tensor<int32, [6]> input_tensor_545_pad_0 = const()[name = string("input_tensor_545_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 0, 127])];
            string input_tensor_545_mode_0 = const()[name = string("input_tensor_545_mode_0"), val = string("constant")];
            fp16 const_80_to_fp16 = const()[name = string("const_80_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 32895]> input_tensor_545_cast_fp16 = pad(constant_val = const_80_to_fp16, mode = input_tensor_545_mode_0, pad = input_tensor_545_pad_0, x = input_125_cast_fp16)[name = string("input_tensor_545_cast_fp16")];
            tensor<int32, [4]> var_2370 = const()[name = string("op_2370"), val = tensor<int32, [4]>([1, 4, 129, 255])];
            tensor<fp16, [1, 4, 129, 255]> x_127_cast_fp16 = reshape(shape = var_2370, x = input_tensor_545_cast_fp16)[name = string("x_127_cast_fp16")];
            tensor<int32, [4]> x_129_begin_0 = const()[name = string("x_129_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> x_129_end_0 = const()[name = string("x_129_end_0"), val = tensor<int32, [4]>([1, 4, 128, 255])];
            tensor<bool, [4]> x_129_end_mask_0 = const()[name = string("x_129_end_mask_0"), val = tensor<bool, [4]>([true, true, false, true])];
            tensor<fp16, [1, 4, 128, 255]> x_129_cast_fp16 = slice_by_index(begin = x_129_begin_0, end = x_129_end_0, end_mask = x_129_end_mask_0, x = x_127_cast_fp16)[name = string("x_129_cast_fp16")];
            tensor<int32, [4]> second_181_begin_0 = const()[name = string("second_181_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 127])];
            tensor<int32, [4]> second_181_end_0 = const()[name = string("second_181_end_0"), val = tensor<int32, [4]>([1, 4, 128, 1])];
            tensor<bool, [4]> second_181_end_mask_0 = const()[name = string("second_181_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 128, 128]> second_181_cast_fp16 = slice_by_index(begin = second_181_begin_0, end = second_181_end_0, end_mask = second_181_end_mask_0, x = x_129_cast_fp16)[name = string("second_181_cast_fp16")];
            tensor<fp16, [1, 4, 128, 128]> y_27_cast_fp16 = add(x = first_179_cast_fp16, y = second_181_cast_fp16)[name = string("y_27_cast_fp16")];
            tensor<fp16, [1, 4, 128, 128]> input_127_cast_fp16 = select(a = text_encoder_attn_encoder_attn_layers_0_Constant_88_value_after_broadcast_to_fp16, b = y_27_cast_fp16, cond = condition_1_after_broadcast)[name = string("input_127_cast_fp16")];
            int32 var_2412 = const()[name = string("op_2412"), val = int32(-1)];
            tensor<fp16, [1, 4, 128, 128]> x_133_cast_fp16 = softmax(axis = var_2412, x = input_127_cast_fp16)[name = string("x_133_cast_fp16")];
            bool first_191_transpose_x_1 = const()[name = string("first_191_transpose_x_1"), val = bool(false)];
            bool first_191_transpose_y_1 = const()[name = string("first_191_transpose_y_1"), val = bool(true)];
            tensor<fp16, [1, 4, 128, 64]> first_191_cast_fp16 = matmul(transpose_x = first_191_transpose_x_1, transpose_y = first_191_transpose_y_1, x = x_133_cast_fp16, y = input_tensor_469_cast_fp16)[name = string("first_191_cast_fp16")];
            tensor<int32, [8]> input_tensor_575_pad_0 = const()[name = string("input_tensor_575_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 127])];
            string input_tensor_575_mode_0 = const()[name = string("input_tensor_575_mode_0"), val = string("constant")];
            fp16 const_87_to_fp16 = const()[name = string("const_87_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 128, 255]> input_tensor_575_cast_fp16 = pad(constant_val = const_87_to_fp16, mode = input_tensor_575_mode_0, pad = input_tensor_575_pad_0, x = x_133_cast_fp16)[name = string("input_tensor_575_cast_fp16")];
            tensor<int32, [3]> var_2486 = const()[name = string("op_2486"), val = tensor<int32, [3]>([1, 4, 32640])];
            tensor<fp16, [1, 4, 32640]> input_129_cast_fp16 = reshape(shape = var_2486, x = input_tensor_575_cast_fp16)[name = string("input_129_cast_fp16")];
            tensor<int32, [6]> input_tensor_593_pad_0 = const()[name = string("input_tensor_593_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 128, 0])];
            string input_tensor_593_mode_0 = const()[name = string("input_tensor_593_mode_0"), val = string("constant")];
            fp16 const_88_to_fp16 = const()[name = string("const_88_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 32768]> input_tensor_593_cast_fp16 = pad(constant_val = const_88_to_fp16, mode = input_tensor_593_mode_0, pad = input_tensor_593_pad_0, x = input_129_cast_fp16)[name = string("input_tensor_593_cast_fp16")];
            tensor<int32, [4]> var_2516 = const()[name = string("op_2516"), val = tensor<int32, [4]>([1, 4, 128, 256])];
            tensor<fp16, [1, 4, 128, 256]> x_143_cast_fp16 = reshape(shape = var_2516, x = input_tensor_593_cast_fp16)[name = string("x_143_cast_fp16")];
            tensor<int32, [4]> x_151_begin_0 = const()[name = string("x_151_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 1])];
            tensor<int32, [4]> x_151_end_0 = const()[name = string("x_151_end_0"), val = tensor<int32, [4]>([1, 4, 128, 1])];
            tensor<bool, [4]> x_151_end_mask_0 = const()[name = string("x_151_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 128, 255]> x_151_cast_fp16 = slice_by_index(begin = x_151_begin_0, end = x_151_end_0, end_mask = x_151_end_mask_0, x = x_143_cast_fp16)[name = string("x_151_cast_fp16")];
            bool second_195_transpose_x_0 = const()[name = string("second_195_transpose_x_0"), val = bool(false)];
            bool second_195_transpose_y_0 = const()[name = string("second_195_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 255, 64]> y_31_to_fp16 = const()[name = string("y_31_to_fp16"), val = tensor<fp16, [1, 1, 255, 64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(18348672)))];
            tensor<fp16, [1, 4, 128, 64]> second_195_cast_fp16 = matmul(transpose_x = second_195_transpose_x_0, transpose_y = second_195_transpose_y_0, x = x_151_cast_fp16, y = y_31_to_fp16)[name = string("second_195_cast_fp16")];
            tensor<fp16, [1, 4, 128, 64]> input_tensor_611_cast_fp16 = add(x = first_191_cast_fp16, y = second_195_cast_fp16)[name = string("input_tensor_611_cast_fp16")];
            tensor<int32, [4]> var_2563 = const()[name = string("op_2563"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [3]> var_2582 = const()[name = string("op_2582"), val = tensor<int32, [3]>([1, 256, 128])];
            tensor<fp16, [1, 4, 64, 128]> input_tensor_615_cast_fp16 = transpose(perm = var_2563, x = input_tensor_611_cast_fp16)[name = string("transpose_21")];
            tensor<fp16, [1, 256, 128]> input_133_cast_fp16 = reshape(shape = var_2582, x = input_tensor_615_cast_fp16)[name = string("input_133_cast_fp16")];
            string second_197_pad_type_0 = const()[name = string("second_197_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_197_strides_0 = const()[name = string("second_197_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_197_pad_0 = const()[name = string("second_197_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_197_dilations_0 = const()[name = string("second_197_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_197_groups_0 = const()[name = string("second_197_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_2_conv_o_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_o_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14177984)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_2_conv_o_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_o_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14309120)))];
            tensor<fp16, [1, 256, 128]> second_197_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_2_conv_o_Conv_bias_to_fp16, dilations = second_197_dilations_0, groups = second_197_groups_0, pad = second_197_pad_0, pad_type = second_197_pad_type_0, strides = second_197_strides_0, weight = text_encoder_attn_encoder_attn_layers_2_conv_o_Conv_weight_to_fp16, x = input_133_cast_fp16)[name = string("second_197_cast_fp16")];
            tensor<fp16, [1, 256, 128]> input_tensor_617_cast_fp16 = add(x = input_117_cast_fp16, y = second_197_cast_fp16)[name = string("input_tensor_617_cast_fp16")];
            tensor<int32, [3]> var_2600 = const()[name = string("op_2600"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_619_axes_0 = const()[name = string("input_tensor_619_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_2_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_2_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14309696)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_2_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_2_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14310272)))];
            fp16 var_2603_to_fp16 = const()[name = string("op_2603_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 128, 256]> input_135_cast_fp16 = transpose(perm = var_2600, x = input_tensor_617_cast_fp16)[name = string("transpose_20")];
            tensor<fp16, [1, 128, 256]> input_tensor_619_cast_fp16 = layer_norm(axes = input_tensor_619_axes_0, beta = text_encoder_attn_encoder_norm_layers_1_2_norm_LayerNormalization_bias_to_fp16, epsilon = var_2603_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_1_2_norm_LayerNormalization_weight_to_fp16, x = input_135_cast_fp16)[name = string("input_tensor_619_cast_fp16")];
            tensor<int32, [3]> var_2612 = const()[name = string("op_2612"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 256, 128]> first_193_cast_fp16 = transpose(perm = var_2612, x = input_tensor_619_cast_fp16)[name = string("transpose_19")];
            tensor<fp16, [1, 256, 128]> input_137_cast_fp16 = mul(x = first_193_cast_fp16, y = text_mask)[name = string("input_137_cast_fp16")];
            string input_139_pad_type_0 = const()[name = string("input_139_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_139_strides_0 = const()[name = string("input_139_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_139_pad_0 = const()[name = string("input_139_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_139_dilations_0 = const()[name = string("input_139_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_139_groups_0 = const()[name = string("input_139_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_attn_encoder_ffn_layers_2_conv_1_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_2_conv_1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14310848)))];
            tensor<fp16, [1024]> text_encoder_attn_encoder_ffn_layers_2_conv_1_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_2_conv_1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14835200)))];
            tensor<fp16, [1, 1024, 128]> input_139_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_2_conv_1_Conv_bias_to_fp16, dilations = input_139_dilations_0, groups = input_139_groups_0, pad = input_139_pad_0, pad_type = input_139_pad_type_0, strides = input_139_strides_0, weight = text_encoder_attn_encoder_ffn_layers_2_conv_1_Conv_weight_to_fp16, x = input_137_cast_fp16)[name = string("input_139_cast_fp16")];
            tensor<fp16, [1, 1024, 128]> first_195_cast_fp16 = relu(x = input_139_cast_fp16)[name = string("first_195_cast_fp16")];
            tensor<fp16, [1, 1024, 128]> input_141_cast_fp16 = mul(x = first_195_cast_fp16, y = text_mask)[name = string("input_141_cast_fp16")];
            string first_197_pad_type_0 = const()[name = string("first_197_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_197_strides_0 = const()[name = string("first_197_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_197_pad_0 = const()[name = string("first_197_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_197_dilations_0 = const()[name = string("first_197_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_197_groups_0 = const()[name = string("first_197_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> text_encoder_attn_encoder_ffn_layers_2_conv_2_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_2_conv_2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14837312)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_ffn_layers_2_conv_2_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_2_conv_2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15361664)))];
            tensor<fp16, [1, 256, 128]> first_197_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_2_conv_2_Conv_bias_to_fp16, dilations = first_197_dilations_0, groups = first_197_groups_0, pad = first_197_pad_0, pad_type = first_197_pad_type_0, strides = first_197_strides_0, weight = text_encoder_attn_encoder_ffn_layers_2_conv_2_Conv_weight_to_fp16, x = input_141_cast_fp16)[name = string("first_197_cast_fp16")];
            tensor<fp16, [1, 256, 128]> second_199_cast_fp16 = mul(x = first_197_cast_fp16, y = text_mask)[name = string("second_199_cast_fp16")];
            tensor<fp16, [1, 256, 128]> input_tensor_621_cast_fp16 = add(x = first_193_cast_fp16, y = second_199_cast_fp16)[name = string("input_tensor_621_cast_fp16")];
            tensor<int32, [3]> var_2645 = const()[name = string("op_2645"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_623_axes_0 = const()[name = string("input_tensor_623_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_2_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_2_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15362240)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_2_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_2_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15362816)))];
            fp16 var_2648_to_fp16 = const()[name = string("op_2648_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 128, 256]> input_143_cast_fp16 = transpose(perm = var_2645, x = input_tensor_621_cast_fp16)[name = string("transpose_18")];
            tensor<fp16, [1, 128, 256]> input_tensor_623_cast_fp16 = layer_norm(axes = input_tensor_623_axes_0, beta = text_encoder_attn_encoder_norm_layers_2_2_norm_LayerNormalization_bias_to_fp16, epsilon = var_2648_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_2_2_norm_LayerNormalization_weight_to_fp16, x = input_143_cast_fp16)[name = string("input_tensor_623_cast_fp16")];
            tensor<int32, [3]> var_2657 = const()[name = string("op_2657"), val = tensor<int32, [3]>([0, 2, 1])];
            string input_tensor_633_pad_type_0 = const()[name = string("input_tensor_633_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_633_strides_0 = const()[name = string("input_tensor_633_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_633_pad_0 = const()[name = string("input_tensor_633_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_633_dilations_0 = const()[name = string("input_tensor_633_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_633_groups_0 = const()[name = string("input_tensor_633_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_3_conv_q_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_q_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15363392)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_3_conv_q_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_q_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15494528)))];
            tensor<fp16, [1, 256, 128]> input_145_cast_fp16 = transpose(perm = var_2657, x = input_tensor_623_cast_fp16)[name = string("transpose_17")];
            tensor<fp16, [1, 256, 128]> input_tensor_633_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_3_conv_q_Conv_bias_to_fp16, dilations = input_tensor_633_dilations_0, groups = input_tensor_633_groups_0, pad = input_tensor_633_pad_0, pad_type = input_tensor_633_pad_type_0, strides = input_tensor_633_strides_0, weight = text_encoder_attn_encoder_attn_layers_3_conv_q_Conv_weight_to_fp16, x = input_145_cast_fp16)[name = string("input_tensor_633_cast_fp16")];
            string input_tensor_625_pad_type_0 = const()[name = string("input_tensor_625_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_625_strides_0 = const()[name = string("input_tensor_625_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_625_pad_0 = const()[name = string("input_tensor_625_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_625_dilations_0 = const()[name = string("input_tensor_625_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_625_groups_0 = const()[name = string("input_tensor_625_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_3_conv_k_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_k_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15495104)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_3_conv_k_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_k_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15626240)))];
            tensor<fp16, [1, 256, 128]> input_tensor_625_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_3_conv_k_Conv_bias_to_fp16, dilations = input_tensor_625_dilations_0, groups = input_tensor_625_groups_0, pad = input_tensor_625_pad_0, pad_type = input_tensor_625_pad_type_0, strides = input_tensor_625_strides_0, weight = text_encoder_attn_encoder_attn_layers_3_conv_k_Conv_weight_to_fp16, x = input_145_cast_fp16)[name = string("input_tensor_625_cast_fp16")];
            string input_tensor_645_pad_type_0 = const()[name = string("input_tensor_645_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_645_strides_0 = const()[name = string("input_tensor_645_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_645_pad_0 = const()[name = string("input_tensor_645_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_645_dilations_0 = const()[name = string("input_tensor_645_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_645_groups_0 = const()[name = string("input_tensor_645_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_3_conv_v_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_v_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15626816)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_3_conv_v_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_v_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15757952)))];
            tensor<fp16, [1, 256, 128]> input_tensor_645_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_3_conv_v_Conv_bias_to_fp16, dilations = input_tensor_645_dilations_0, groups = input_tensor_645_groups_0, pad = input_tensor_645_pad_0, pad_type = input_tensor_645_pad_type_0, strides = input_tensor_645_strides_0, weight = text_encoder_attn_encoder_attn_layers_3_conv_v_Conv_weight_to_fp16, x = input_145_cast_fp16)[name = string("input_tensor_645_cast_fp16")];
            tensor<int32, [4]> var_2765 = const()[name = string("op_2765"), val = tensor<int32, [4]>([1, 4, 64, 128])];
            tensor<fp16, [1, 4, 64, 128]> input_tensor_641_cast_fp16 = reshape(shape = var_2765, x = input_tensor_633_cast_fp16)[name = string("input_tensor_641_cast_fp16")];
            tensor<int32, [4]> var_2771 = const()[name = string("op_2771"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [4]> var_2797 = const()[name = string("op_2797"), val = tensor<int32, [4]>([1, 4, 64, 128])];
            tensor<fp16, [1, 4, 64, 128]> y_33_cast_fp16 = reshape(shape = var_2797, x = input_tensor_625_cast_fp16)[name = string("y_33_cast_fp16")];
            tensor<int32, [4]> var_2809 = const()[name = string("op_2809"), val = tensor<int32, [4]>([1, 4, 64, 128])];
            tensor<fp16, [1, 4, 64, 128]> input_tensor_647_cast_fp16 = reshape(shape = var_2809, x = input_tensor_645_cast_fp16)[name = string("input_tensor_647_cast_fp16")];
            fp16 _inversed_x_153_y_0_to_fp16 = const()[name = string("_inversed_x_153_y_0_to_fp16"), val = fp16(0x1p-3)];
            tensor<fp16, [1, 4, 128, 64]> first_199_cast_fp16 = transpose(perm = var_2771, x = input_tensor_641_cast_fp16)[name = string("transpose_16")];
            tensor<fp16, [1, 4, 128, 64]> _inversed_x_153_cast_fp16 = mul(x = first_199_cast_fp16, y = _inversed_x_153_y_0_to_fp16)[name = string("_inversed_x_153_cast_fp16")];
            bool first_215_transpose_x_0 = const()[name = string("first_215_transpose_x_0"), val = bool(false)];
            bool first_215_transpose_y_0 = const()[name = string("first_215_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 4, 128, 128]> first_215_cast_fp16 = matmul(transpose_x = first_215_transpose_x_0, transpose_y = first_215_transpose_y_0, x = _inversed_x_153_cast_fp16, y = y_33_cast_fp16)[name = string("first_215_cast_fp16")];
            bool input_tensor_679_transpose_x_0 = const()[name = string("input_tensor_679_transpose_x_0"), val = bool(false)];
            bool input_tensor_679_transpose_y_0 = const()[name = string("input_tensor_679_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 64, 255]> y_35_to_fp16 = const()[name = string("y_35_to_fp16"), val = tensor<fp16, [1, 1, 64, 255]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(18381376)))];
            tensor<fp16, [1, 4, 128, 255]> input_tensor_679_cast_fp16 = matmul(transpose_x = input_tensor_679_transpose_x_0, transpose_y = input_tensor_679_transpose_y_0, x = _inversed_x_153_cast_fp16, y = y_35_to_fp16)[name = string("input_tensor_679_cast_fp16")];
            tensor<int32, [8]> input_tensor_701_pad_0 = const()[name = string("input_tensor_701_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 1])];
            string input_tensor_701_mode_0 = const()[name = string("input_tensor_701_mode_0"), val = string("constant")];
            fp16 const_107_to_fp16 = const()[name = string("const_107_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 128, 256]> input_tensor_701_cast_fp16 = pad(constant_val = const_107_to_fp16, mode = input_tensor_701_mode_0, pad = input_tensor_701_pad_0, x = input_tensor_679_cast_fp16)[name = string("input_tensor_701_cast_fp16")];
            tensor<int32, [3]> var_2932 = const()[name = string("op_2932"), val = tensor<int32, [3]>([1, 4, 32768])];
            tensor<fp16, [1, 4, 32768]> input_153_cast_fp16 = reshape(shape = var_2932, x = input_tensor_701_cast_fp16)[name = string("input_153_cast_fp16")];
            tensor<int32, [6]> input_tensor_723_pad_0 = const()[name = string("input_tensor_723_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 0, 127])];
            string input_tensor_723_mode_0 = const()[name = string("input_tensor_723_mode_0"), val = string("constant")];
            fp16 const_108_to_fp16 = const()[name = string("const_108_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 32895]> input_tensor_723_cast_fp16 = pad(constant_val = const_108_to_fp16, mode = input_tensor_723_mode_0, pad = input_tensor_723_pad_0, x = input_153_cast_fp16)[name = string("input_tensor_723_cast_fp16")];
            tensor<int32, [4]> var_2967 = const()[name = string("op_2967"), val = tensor<int32, [4]>([1, 4, 129, 255])];
            tensor<fp16, [1, 4, 129, 255]> x_169_cast_fp16 = reshape(shape = var_2967, x = input_tensor_723_cast_fp16)[name = string("x_169_cast_fp16")];
            tensor<int32, [4]> x_171_begin_0 = const()[name = string("x_171_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> x_171_end_0 = const()[name = string("x_171_end_0"), val = tensor<int32, [4]>([1, 4, 128, 255])];
            tensor<bool, [4]> x_171_end_mask_0 = const()[name = string("x_171_end_mask_0"), val = tensor<bool, [4]>([true, true, false, true])];
            tensor<fp16, [1, 4, 128, 255]> x_171_cast_fp16 = slice_by_index(begin = x_171_begin_0, end = x_171_end_0, end_mask = x_171_end_mask_0, x = x_169_cast_fp16)[name = string("x_171_cast_fp16")];
            tensor<int32, [4]> second_223_begin_0 = const()[name = string("second_223_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 127])];
            tensor<int32, [4]> second_223_end_0 = const()[name = string("second_223_end_0"), val = tensor<int32, [4]>([1, 4, 128, 1])];
            tensor<bool, [4]> second_223_end_mask_0 = const()[name = string("second_223_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 128, 128]> second_223_cast_fp16 = slice_by_index(begin = second_223_begin_0, end = second_223_end_0, end_mask = second_223_end_mask_0, x = x_171_cast_fp16)[name = string("second_223_cast_fp16")];
            tensor<fp16, [1, 4, 128, 128]> y_37_cast_fp16 = add(x = first_215_cast_fp16, y = second_223_cast_fp16)[name = string("y_37_cast_fp16")];
            tensor<fp16, [1, 4, 128, 128]> input_155_cast_fp16 = select(a = text_encoder_attn_encoder_attn_layers_0_Constant_88_value_after_broadcast_to_fp16, b = y_37_cast_fp16, cond = condition_1_after_broadcast)[name = string("input_155_cast_fp16")];
            int32 var_3009 = const()[name = string("op_3009"), val = int32(-1)];
            tensor<fp16, [1, 4, 128, 128]> x_175_cast_fp16 = softmax(axis = var_3009, x = input_155_cast_fp16)[name = string("x_175_cast_fp16")];
            bool first_227_transpose_x_1 = const()[name = string("first_227_transpose_x_1"), val = bool(false)];
            bool first_227_transpose_y_1 = const()[name = string("first_227_transpose_y_1"), val = bool(true)];
            tensor<fp16, [1, 4, 128, 64]> first_227_cast_fp16 = matmul(transpose_x = first_227_transpose_x_1, transpose_y = first_227_transpose_y_1, x = x_175_cast_fp16, y = input_tensor_647_cast_fp16)[name = string("first_227_cast_fp16")];
            tensor<int32, [8]> input_tensor_753_pad_0 = const()[name = string("input_tensor_753_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 127])];
            string input_tensor_753_mode_0 = const()[name = string("input_tensor_753_mode_0"), val = string("constant")];
            fp16 const_115_to_fp16 = const()[name = string("const_115_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 128, 255]> input_tensor_753_cast_fp16 = pad(constant_val = const_115_to_fp16, mode = input_tensor_753_mode_0, pad = input_tensor_753_pad_0, x = x_175_cast_fp16)[name = string("input_tensor_753_cast_fp16")];
            tensor<int32, [3]> var_3083 = const()[name = string("op_3083"), val = tensor<int32, [3]>([1, 4, 32640])];
            tensor<fp16, [1, 4, 32640]> input_157_cast_fp16 = reshape(shape = var_3083, x = input_tensor_753_cast_fp16)[name = string("input_157_cast_fp16")];
            tensor<int32, [6]> input_tensor_771_pad_0 = const()[name = string("input_tensor_771_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 128, 0])];
            string input_tensor_771_mode_0 = const()[name = string("input_tensor_771_mode_0"), val = string("constant")];
            fp16 const_116_to_fp16 = const()[name = string("const_116_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 32768]> input_tensor_771_cast_fp16 = pad(constant_val = const_116_to_fp16, mode = input_tensor_771_mode_0, pad = input_tensor_771_pad_0, x = input_157_cast_fp16)[name = string("input_tensor_771_cast_fp16")];
            tensor<int32, [4]> var_3113 = const()[name = string("op_3113"), val = tensor<int32, [4]>([1, 4, 128, 256])];
            tensor<fp16, [1, 4, 128, 256]> x_185_cast_fp16 = reshape(shape = var_3113, x = input_tensor_771_cast_fp16)[name = string("x_185_cast_fp16")];
            tensor<int32, [4]> x_193_begin_0 = const()[name = string("x_193_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 1])];
            tensor<int32, [4]> x_193_end_0 = const()[name = string("x_193_end_0"), val = tensor<int32, [4]>([1, 4, 128, 1])];
            tensor<bool, [4]> x_193_end_mask_0 = const()[name = string("x_193_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 128, 255]> x_193_cast_fp16 = slice_by_index(begin = x_193_begin_0, end = x_193_end_0, end_mask = x_193_end_mask_0, x = x_185_cast_fp16)[name = string("x_193_cast_fp16")];
            bool second_237_transpose_x_0 = const()[name = string("second_237_transpose_x_0"), val = bool(false)];
            bool second_237_transpose_y_0 = const()[name = string("second_237_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 255, 64]> y_41_to_fp16 = const()[name = string("y_41_to_fp16"), val = tensor<fp16, [1, 1, 255, 64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(18414080)))];
            tensor<fp16, [1, 4, 128, 64]> second_237_cast_fp16 = matmul(transpose_x = second_237_transpose_x_0, transpose_y = second_237_transpose_y_0, x = x_193_cast_fp16, y = y_41_to_fp16)[name = string("second_237_cast_fp16")];
            tensor<fp16, [1, 4, 128, 64]> input_tensor_789_cast_fp16 = add(x = first_227_cast_fp16, y = second_237_cast_fp16)[name = string("input_tensor_789_cast_fp16")];
            tensor<int32, [4]> var_3160 = const()[name = string("op_3160"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [3]> var_3179 = const()[name = string("op_3179"), val = tensor<int32, [3]>([1, 256, 128])];
            tensor<fp16, [1, 4, 64, 128]> input_tensor_793_cast_fp16 = transpose(perm = var_3160, x = input_tensor_789_cast_fp16)[name = string("transpose_15")];
            tensor<fp16, [1, 256, 128]> input_161_cast_fp16 = reshape(shape = var_3179, x = input_tensor_793_cast_fp16)[name = string("input_161_cast_fp16")];
            string second_239_pad_type_0 = const()[name = string("second_239_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_239_strides_0 = const()[name = string("second_239_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_239_pad_0 = const()[name = string("second_239_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_239_dilations_0 = const()[name = string("second_239_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_239_groups_0 = const()[name = string("second_239_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_3_conv_o_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_o_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15766592)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_3_conv_o_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_o_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15897728)))];
            tensor<fp16, [1, 256, 128]> second_239_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_3_conv_o_Conv_bias_to_fp16, dilations = second_239_dilations_0, groups = second_239_groups_0, pad = second_239_pad_0, pad_type = second_239_pad_type_0, strides = second_239_strides_0, weight = text_encoder_attn_encoder_attn_layers_3_conv_o_Conv_weight_to_fp16, x = input_161_cast_fp16)[name = string("second_239_cast_fp16")];
            tensor<fp16, [1, 256, 128]> input_tensor_795_cast_fp16 = add(x = input_145_cast_fp16, y = second_239_cast_fp16)[name = string("input_tensor_795_cast_fp16")];
            tensor<int32, [3]> var_3197 = const()[name = string("op_3197"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_797_axes_0 = const()[name = string("input_tensor_797_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_3_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_3_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15898304)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_3_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_3_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15898880)))];
            fp16 var_3200_to_fp16 = const()[name = string("op_3200_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 128, 256]> input_163_cast_fp16 = transpose(perm = var_3197, x = input_tensor_795_cast_fp16)[name = string("transpose_14")];
            tensor<fp16, [1, 128, 256]> input_tensor_797_cast_fp16 = layer_norm(axes = input_tensor_797_axes_0, beta = text_encoder_attn_encoder_norm_layers_1_3_norm_LayerNormalization_bias_to_fp16, epsilon = var_3200_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_1_3_norm_LayerNormalization_weight_to_fp16, x = input_163_cast_fp16)[name = string("input_tensor_797_cast_fp16")];
            tensor<int32, [3]> var_3209 = const()[name = string("op_3209"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 256, 128]> first_229_cast_fp16 = transpose(perm = var_3209, x = input_tensor_797_cast_fp16)[name = string("transpose_13")];
            tensor<fp16, [1, 256, 128]> input_165_cast_fp16 = mul(x = first_229_cast_fp16, y = text_mask)[name = string("input_165_cast_fp16")];
            string input_167_pad_type_0 = const()[name = string("input_167_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_167_strides_0 = const()[name = string("input_167_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_167_pad_0 = const()[name = string("input_167_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_167_dilations_0 = const()[name = string("input_167_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_167_groups_0 = const()[name = string("input_167_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_attn_encoder_ffn_layers_3_conv_1_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_3_conv_1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15899456)))];
            tensor<fp16, [1024]> text_encoder_attn_encoder_ffn_layers_3_conv_1_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_3_conv_1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16423808)))];
            tensor<fp16, [1, 1024, 128]> input_167_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_3_conv_1_Conv_bias_to_fp16, dilations = input_167_dilations_0, groups = input_167_groups_0, pad = input_167_pad_0, pad_type = input_167_pad_type_0, strides = input_167_strides_0, weight = text_encoder_attn_encoder_ffn_layers_3_conv_1_Conv_weight_to_fp16, x = input_165_cast_fp16)[name = string("input_167_cast_fp16")];
            tensor<fp16, [1, 1024, 128]> first_231_cast_fp16 = relu(x = input_167_cast_fp16)[name = string("first_231_cast_fp16")];
            tensor<fp16, [1, 1024, 128]> input_169_cast_fp16 = mul(x = first_231_cast_fp16, y = text_mask)[name = string("input_169_cast_fp16")];
            string first_233_pad_type_0 = const()[name = string("first_233_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_233_strides_0 = const()[name = string("first_233_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_233_pad_0 = const()[name = string("first_233_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_233_dilations_0 = const()[name = string("first_233_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_233_groups_0 = const()[name = string("first_233_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> text_encoder_attn_encoder_ffn_layers_3_conv_2_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_3_conv_2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16425920)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_ffn_layers_3_conv_2_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_3_conv_2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16950272)))];
            tensor<fp16, [1, 256, 128]> first_233_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_3_conv_2_Conv_bias_to_fp16, dilations = first_233_dilations_0, groups = first_233_groups_0, pad = first_233_pad_0, pad_type = first_233_pad_type_0, strides = first_233_strides_0, weight = text_encoder_attn_encoder_ffn_layers_3_conv_2_Conv_weight_to_fp16, x = input_169_cast_fp16)[name = string("first_233_cast_fp16")];
            tensor<fp16, [1, 256, 128]> second_241_cast_fp16 = mul(x = first_233_cast_fp16, y = text_mask)[name = string("second_241_cast_fp16")];
            tensor<fp16, [1, 256, 128]> input_tensor_799_cast_fp16 = add(x = first_229_cast_fp16, y = second_241_cast_fp16)[name = string("input_tensor_799_cast_fp16")];
            tensor<int32, [3]> var_3242 = const()[name = string("op_3242"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_801_axes_0 = const()[name = string("input_tensor_801_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_3_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_3_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16950848)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_3_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_3_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16951424)))];
            fp16 var_3245_to_fp16 = const()[name = string("op_3245_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 128, 256]> input_171_cast_fp16 = transpose(perm = var_3242, x = input_tensor_799_cast_fp16)[name = string("transpose_12")];
            tensor<fp16, [1, 128, 256]> input_tensor_801_cast_fp16 = layer_norm(axes = input_tensor_801_axes_0, beta = text_encoder_attn_encoder_norm_layers_2_3_norm_LayerNormalization_bias_to_fp16, epsilon = var_3245_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_2_3_norm_LayerNormalization_weight_to_fp16, x = input_171_cast_fp16)[name = string("input_tensor_801_cast_fp16")];
            tensor<int32, [3]> var_3254 = const()[name = string("op_3254"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 256, 128]> first_235_cast_fp16 = transpose(perm = var_3254, x = input_tensor_801_cast_fp16)[name = string("transpose_11")];
            tensor<fp16, [1, 256, 128]> first_237_cast_fp16 = mul(x = first_235_cast_fp16, y = text_mask)[name = string("first_237_cast_fp16")];
            tensor<fp16, [1, 256, 128]> first_239_cast_fp16 = add(x = first_237_cast_fp16, y = first_89_cast_fp16)[name = string("first_239_cast_fp16")];
            tensor<fp16, [1, 256, 128]> input_tensor_807_cast_fp16 = mul(x = first_239_cast_fp16, y = text_mask)[name = string("input_tensor_807_cast_fp16")];
            tensor<int32, [3]> var_3299 = const()[name = string("op_3299"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [3]> var_3304 = const()[name = string("op_3304"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [256, 256]> var_3308_weight_0_to_fp16 = const()[name = string("op_3308_weight_0_to_fp16"), val = tensor<fp16, [256, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16952000)))];
            tensor<fp16, [256]> var_3308_bias_0_to_fp16 = const()[name = string("op_3308_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17083136)))];
            tensor<fp16, [1, 128, 256]> x_195_cast_fp16 = transpose(perm = var_3299, x = input_tensor_807_cast_fp16)[name = string("transpose_10")];
            tensor<fp16, [1, 128, 256]> var_3308_cast_fp16 = linear(bias = var_3308_bias_0_to_fp16, weight = var_3308_weight_0_to_fp16, x = x_195_cast_fp16)[name = string("op_3308_cast_fp16")];
            tensor<fp16, [256, 256]> var_3314_weight_0_to_fp16 = const()[name = string("op_3314_weight_0_to_fp16"), val = tensor<fp16, [256, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17083712)))];
            tensor<fp16, [256]> var_3314_bias_0_to_fp16 = const()[name = string("op_3314_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17214848)))];
            tensor<fp16, [1, 50, 256]> var_3314_cast_fp16 = linear(bias = var_3314_bias_0_to_fp16, weight = var_3314_weight_0_to_fp16, x = style_ttl)[name = string("op_3314_cast_fp16")];
            tensor<int32, [2]> var_3317 = const()[name = string("op_3317"), val = tensor<int32, [2]>([128, 128])];
            int32 var_3318_axis_0 = const()[name = string("op_3318_axis_0"), val = int32(2)];
            tensor<fp16, [1, 128, 128]> var_3318_cast_fp16_0, tensor<fp16, [1, 128, 128]> var_3318_cast_fp16_1 = split(axis = var_3318_axis_0, split_sizes = var_3317, x = var_3308_cast_fp16)[name = string("op_3318_cast_fp16")];
            tensor<int32, [1]> var_3325_axes_0 = const()[name = string("op_3325_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 128, 128]> var_3325_cast_fp16 = expand_dims(axes = var_3325_axes_0, x = var_3318_cast_fp16_0)[name = string("op_3325_cast_fp16")];
            tensor<int32, [1]> var_3327_axes_0 = const()[name = string("op_3327_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 128, 128]> var_3327_cast_fp16 = expand_dims(axes = var_3327_axes_0, x = var_3318_cast_fp16_1)[name = string("op_3327_cast_fp16")];
            int32 var_3328 = const()[name = string("op_3328"), val = int32(0)];
            bool x_199_interleave_0 = const()[name = string("x_199_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 1, 128, 128]> x_199_cast_fp16 = concat(axis = var_3328, interleave = x_199_interleave_0, values = (var_3325_cast_fp16, var_3327_cast_fp16))[name = string("x_199_cast_fp16")];
            tensor<int32, [2]> var_3349 = const()[name = string("op_3349"), val = tensor<int32, [2]>([128, 128])];
            int32 var_3350_axis_0 = const()[name = string("op_3350_axis_0"), val = int32(2)];
            tensor<fp16, [1, 50, 128]> var_3350_cast_fp16_0, tensor<fp16, [1, 50, 128]> var_3350_cast_fp16_1 = split(axis = var_3350_axis_0, split_sizes = var_3349, x = var_3314_cast_fp16)[name = string("op_3350_cast_fp16")];
            tensor<int32, [1]> var_3357_axes_0 = const()[name = string("op_3357_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 50, 128]> var_3357_cast_fp16 = expand_dims(axes = var_3357_axes_0, x = var_3350_cast_fp16_0)[name = string("op_3357_cast_fp16")];
            tensor<int32, [1]> var_3359_axes_0 = const()[name = string("op_3359_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 50, 128]> var_3359_cast_fp16 = expand_dims(axes = var_3359_axes_0, x = var_3350_cast_fp16_1)[name = string("op_3359_cast_fp16")];
            int32 var_3360 = const()[name = string("op_3360"), val = int32(0)];
            bool y_55_interleave_0 = const()[name = string("y_55_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 1, 50, 128]> y_55_cast_fp16 = concat(axis = var_3360, interleave = y_55_interleave_0, values = (var_3357_cast_fp16, var_3359_cast_fp16))[name = string("y_55_cast_fp16")];
            bool first_247_transpose_x_0 = const()[name = string("first_247_transpose_x_0"), val = bool(false)];
            bool first_247_transpose_y_0 = const()[name = string("first_247_transpose_y_0"), val = bool(false)];
            tensor<fp16, [2, 1, 128, 50]> y_49_to_fp16 = const()[name = string("y_49_to_fp16"), val = tensor<fp16, [2, 1, 128, 50]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17215424)))];
            tensor<fp16, [2, 1, 128, 50]> first_247_cast_fp16 = matmul(transpose_x = first_247_transpose_x_0, transpose_y = first_247_transpose_y_0, x = x_199_cast_fp16, y = y_49_to_fp16)[name = string("first_247_cast_fp16")];
            fp16 _inversed_input_173_y_0_to_fp16 = const()[name = string("_inversed_input_173_y_0_to_fp16"), val = fp16(0x1p-4)];
            tensor<fp16, [2, 1, 128, 50]> _inversed_input_173_cast_fp16 = mul(x = first_247_cast_fp16, y = _inversed_input_173_y_0_to_fp16)[name = string("_inversed_input_173_cast_fp16")];
            int32 var_3373 = const()[name = string("op_3373"), val = int32(3)];
            tensor<fp16, [2, 1, 128, 50]> y_53_cast_fp16 = softmax(axis = var_3373, x = _inversed_input_173_cast_fp16)[name = string("y_53_cast_fp16")];
            tensor<int32, [1]> x_201_axes_0 = const()[name = string("x_201_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 128, 1]> input_tensor_825_cast_fp16 = transpose(perm = var_3304, x = text_mask)[name = string("transpose_9")];
            tensor<fp16, [1, 1, 128, 1]> x_201_cast_fp16 = expand_dims(axes = x_201_axes_0, x = input_tensor_825_cast_fp16)[name = string("x_201_cast_fp16")];
            fp16 speech_prompted_text_encoder_attention1_Constant_11_value_to_fp16 = const()[name = string("speech_prompted_text_encoder_attention1_Constant_11_value_to_fp16"), val = fp16(0x0p+0)];
            tensor<bool, [1, 1, 128, 1]> input_tensor_827_cast_fp16 = equal(x = x_201_cast_fp16, y = speech_prompted_text_encoder_attention1_Constant_11_value_to_fp16)[name = string("input_tensor_827_cast_fp16")];
            tensor<int32, [4]> condition_9_after_broadcast_reps_0 = const()[name = string("condition_9_after_broadcast_reps_0"), val = tensor<int32, [4]>([2, 1, 1, 50])];
            tensor<bool, [2, 1, 128, 50]> condition_9_after_broadcast = tile(reps = condition_9_after_broadcast_reps_0, x = input_tensor_827_cast_fp16)[name = string("condition_9_after_broadcast")];
            tensor<fp16, [2, 1, 128, 50]> speech_prompted_text_encoder_attention1_Constant_12_value_after_broadcast_to_fp16 = const()[name = string("speech_prompted_text_encoder_attention1_Constant_12_value_after_broadcast_to_fp16"), val = tensor<fp16, [2, 1, 128, 50]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(18446784)))];
            tensor<fp16, [2, 1, 128, 50]> x_205_cast_fp16 = select(a = speech_prompted_text_encoder_attention1_Constant_12_value_after_broadcast_to_fp16, b = y_53_cast_fp16, cond = condition_9_after_broadcast)[name = string("x_205_cast_fp16")];
            bool var_3383_transpose_x_0 = const()[name = string("op_3383_transpose_x_0"), val = bool(false)];
            bool var_3383_transpose_y_0 = const()[name = string("op_3383_transpose_y_0"), val = bool(false)];
            tensor<fp16, [2, 1, 128, 128]> var_3383_cast_fp16 = matmul(transpose_x = var_3383_transpose_x_0, transpose_y = var_3383_transpose_y_0, x = x_205_cast_fp16, y = y_55_cast_fp16)[name = string("op_3383_cast_fp16")];
            tensor<int32, [2]> var_3386 = const()[name = string("op_3386"), val = tensor<int32, [2]>([1, 1])];
            int32 var_3387_axis_0 = const()[name = string("op_3387_axis_0"), val = int32(0)];
            tensor<fp16, [1, 1, 128, 128]> var_3387_cast_fp16_0, tensor<fp16, [1, 1, 128, 128]> var_3387_cast_fp16_1 = split(axis = var_3387_axis_0, split_sizes = var_3386, x = var_3383_cast_fp16)[name = string("op_3387_cast_fp16")];
            int32 var_3393 = const()[name = string("op_3393"), val = int32(3)];
            bool result_1_interleave_0 = const()[name = string("result_1_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 1, 128, 256]> result_1_cast_fp16 = concat(axis = var_3393, interleave = result_1_interleave_0, values = (var_3387_cast_fp16_0, var_3387_cast_fp16_1))[name = string("result_1_cast_fp16")];
            tensor<int32, [1]> x_207_axes_0 = const()[name = string("x_207_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 128, 256]> x_207_cast_fp16 = squeeze(axes = x_207_axes_0, x = result_1_cast_fp16)[name = string("x_207_cast_fp16")];
            tensor<fp16, [256, 256]> first_251_weight_0_to_fp16 = const()[name = string("first_251_weight_0_to_fp16"), val = tensor<fp16, [256, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17244352)))];
            tensor<fp16, [256]> first_251_bias_0_to_fp16 = const()[name = string("first_251_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17375488)))];
            tensor<fp16, [1, 128, 256]> first_251_cast_fp16 = linear(bias = first_251_bias_0_to_fp16, weight = first_251_weight_0_to_fp16, x = x_207_cast_fp16)[name = string("first_251_cast_fp16")];
            tensor<fp16, [1, 128, 256]> first_253_cast_fp16 = mul(x = first_251_cast_fp16, y = input_tensor_825_cast_fp16)[name = string("first_253_cast_fp16")];
            tensor<fp16, [1, 128, 256]> x_209_cast_fp16 = add(x = first_253_cast_fp16, y = x_195_cast_fp16)[name = string("x_209_cast_fp16")];
            tensor<fp16, [256, 256]> var_3413_weight_0_to_fp16 = const()[name = string("op_3413_weight_0_to_fp16"), val = tensor<fp16, [256, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17376064)))];
            tensor<fp16, [256]> var_3413_bias_0_to_fp16 = const()[name = string("op_3413_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17507200)))];
            tensor<fp16, [1, 128, 256]> var_3413_cast_fp16 = linear(bias = var_3413_bias_0_to_fp16, weight = var_3413_weight_0_to_fp16, x = x_209_cast_fp16)[name = string("op_3413_cast_fp16")];
            tensor<fp16, [256, 256]> var_3419_weight_0_to_fp16 = const()[name = string("op_3419_weight_0_to_fp16"), val = tensor<fp16, [256, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17507776)))];
            tensor<fp16, [256]> var_3419_bias_0_to_fp16 = const()[name = string("op_3419_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17638912)))];
            tensor<fp16, [1, 50, 256]> var_3419_cast_fp16 = linear(bias = var_3419_bias_0_to_fp16, weight = var_3419_weight_0_to_fp16, x = style_ttl)[name = string("op_3419_cast_fp16")];
            tensor<int32, [2]> var_3422 = const()[name = string("op_3422"), val = tensor<int32, [2]>([128, 128])];
            int32 var_3423_axis_0 = const()[name = string("op_3423_axis_0"), val = int32(2)];
            tensor<fp16, [1, 128, 128]> var_3423_cast_fp16_0, tensor<fp16, [1, 128, 128]> var_3423_cast_fp16_1 = split(axis = var_3423_axis_0, split_sizes = var_3422, x = var_3413_cast_fp16)[name = string("op_3423_cast_fp16")];
            tensor<int32, [1]> var_3430_axes_0 = const()[name = string("op_3430_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 128, 128]> var_3430_cast_fp16 = expand_dims(axes = var_3430_axes_0, x = var_3423_cast_fp16_0)[name = string("op_3430_cast_fp16")];
            tensor<int32, [1]> var_3432_axes_0 = const()[name = string("op_3432_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 128, 128]> var_3432_cast_fp16 = expand_dims(axes = var_3432_axes_0, x = var_3423_cast_fp16_1)[name = string("op_3432_cast_fp16")];
            int32 var_3433 = const()[name = string("op_3433"), val = int32(0)];
            bool x_211_interleave_0 = const()[name = string("x_211_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 1, 128, 128]> x_211_cast_fp16 = concat(axis = var_3433, interleave = x_211_interleave_0, values = (var_3430_cast_fp16, var_3432_cast_fp16))[name = string("x_211_cast_fp16")];
            tensor<int32, [2]> var_3454 = const()[name = string("op_3454"), val = tensor<int32, [2]>([128, 128])];
            int32 var_3455_axis_0 = const()[name = string("op_3455_axis_0"), val = int32(2)];
            tensor<fp16, [1, 50, 128]> var_3455_cast_fp16_0, tensor<fp16, [1, 50, 128]> var_3455_cast_fp16_1 = split(axis = var_3455_axis_0, split_sizes = var_3454, x = var_3419_cast_fp16)[name = string("op_3455_cast_fp16")];
            tensor<int32, [1]> var_3462_axes_0 = const()[name = string("op_3462_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 50, 128]> var_3462_cast_fp16 = expand_dims(axes = var_3462_axes_0, x = var_3455_cast_fp16_0)[name = string("op_3462_cast_fp16")];
            tensor<int32, [1]> var_3464_axes_0 = const()[name = string("op_3464_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 50, 128]> var_3464_cast_fp16 = expand_dims(axes = var_3464_axes_0, x = var_3455_cast_fp16_1)[name = string("op_3464_cast_fp16")];
            int32 var_3465 = const()[name = string("op_3465"), val = int32(0)];
            bool y_69_interleave_0 = const()[name = string("y_69_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 1, 50, 128]> y_69_cast_fp16 = concat(axis = var_3465, interleave = y_69_interleave_0, values = (var_3462_cast_fp16, var_3464_cast_fp16))[name = string("y_69_cast_fp16")];
            bool first_261_transpose_x_0 = const()[name = string("first_261_transpose_x_0"), val = bool(false)];
            bool first_261_transpose_y_0 = const()[name = string("first_261_transpose_y_0"), val = bool(false)];
            tensor<fp16, [2, 1, 128, 50]> y_65_to_fp16 = const()[name = string("y_65_to_fp16"), val = tensor<fp16, [2, 1, 128, 50]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17639488)))];
            tensor<fp16, [2, 1, 128, 50]> first_261_cast_fp16 = matmul(transpose_x = first_261_transpose_x_0, transpose_y = first_261_transpose_y_0, x = x_211_cast_fp16, y = y_65_to_fp16)[name = string("first_261_cast_fp16")];
            fp16 _inversed_input_175_y_0_to_fp16 = const()[name = string("_inversed_input_175_y_0_to_fp16"), val = fp16(0x1p-4)];
            tensor<fp16, [2, 1, 128, 50]> _inversed_input_175_cast_fp16 = mul(x = first_261_cast_fp16, y = _inversed_input_175_y_0_to_fp16)[name = string("_inversed_input_175_cast_fp16")];
            int32 var_3478 = const()[name = string("op_3478"), val = int32(3)];
            tensor<fp16, [2, 1, 128, 50]> y_67_cast_fp16 = softmax(axis = var_3478, x = _inversed_input_175_cast_fp16)[name = string("y_67_cast_fp16")];
            tensor<fp16, [2, 1, 128, 50]> x_215_cast_fp16 = select(a = speech_prompted_text_encoder_attention1_Constant_12_value_after_broadcast_to_fp16, b = y_67_cast_fp16, cond = condition_9_after_broadcast)[name = string("x_215_cast_fp16")];
            bool var_3485_transpose_x_0 = const()[name = string("op_3485_transpose_x_0"), val = bool(false)];
            bool var_3485_transpose_y_0 = const()[name = string("op_3485_transpose_y_0"), val = bool(false)];
            tensor<fp16, [2, 1, 128, 128]> var_3485_cast_fp16 = matmul(transpose_x = var_3485_transpose_x_0, transpose_y = var_3485_transpose_y_0, x = x_215_cast_fp16, y = y_69_cast_fp16)[name = string("op_3485_cast_fp16")];
            tensor<int32, [2]> var_3488 = const()[name = string("op_3488"), val = tensor<int32, [2]>([1, 1])];
            int32 var_3489_axis_0 = const()[name = string("op_3489_axis_0"), val = int32(0)];
            tensor<fp16, [1, 1, 128, 128]> var_3489_cast_fp16_0, tensor<fp16, [1, 1, 128, 128]> var_3489_cast_fp16_1 = split(axis = var_3489_axis_0, split_sizes = var_3488, x = var_3485_cast_fp16)[name = string("op_3489_cast_fp16")];
            int32 var_3495 = const()[name = string("op_3495"), val = int32(3)];
            bool result_interleave_0 = const()[name = string("result_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 1, 128, 256]> result_cast_fp16 = concat(axis = var_3495, interleave = result_interleave_0, values = (var_3489_cast_fp16_0, var_3489_cast_fp16_1))[name = string("result_cast_fp16")];
            tensor<int32, [1]> x_axes_0 = const()[name = string("x_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 128, 256]> x_cast_fp16 = squeeze(axes = x_axes_0, x = result_cast_fp16)[name = string("x_cast_fp16")];
            tensor<fp16, [256, 256]> first_265_weight_0_to_fp16 = const()[name = string("first_265_weight_0_to_fp16"), val = tensor<fp16, [256, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17665152)))];
            tensor<fp16, [256]> first_265_bias_0_to_fp16 = const()[name = string("first_265_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17796288)))];
            tensor<fp16, [1, 128, 256]> first_265_cast_fp16 = linear(bias = first_265_bias_0_to_fp16, weight = first_265_weight_0_to_fp16, x = x_cast_fp16)[name = string("first_265_cast_fp16")];
            tensor<fp16, [1, 128, 256]> first_267_cast_fp16 = mul(x = first_265_cast_fp16, y = input_tensor_825_cast_fp16)[name = string("first_267_cast_fp16")];
            tensor<fp16, [1, 128, 256]> input_cast_fp16 = add(x = first_267_cast_fp16, y = x_195_cast_fp16)[name = string("input_cast_fp16")];
            tensor<int32, [1]> input_tensor_axes_0 = const()[name = string("input_tensor_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> speech_prompted_text_encoder_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("speech_prompted_text_encoder_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17796864)))];
            tensor<fp16, [256]> speech_prompted_text_encoder_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("speech_prompted_text_encoder_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17797440)))];
            fp16 var_3514_to_fp16 = const()[name = string("op_3514_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 128, 256]> input_tensor_cast_fp16 = layer_norm(axes = input_tensor_axes_0, beta = speech_prompted_text_encoder_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_3514_to_fp16, gamma = speech_prompted_text_encoder_norm_norm_LayerNormalization_weight_to_fp16, x = input_cast_fp16)[name = string("input_tensor_cast_fp16")];
            tensor<int32, [3]> var_3523 = const()[name = string("op_3523"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 256, 128]> first_cast_fp16 = transpose(perm = var_3523, x = input_tensor_cast_fp16)[name = string("transpose_8")];
            tensor<fp16, [1, 256, 128]> text_emb = mul(x = first_cast_fp16, y = text_mask)[name = string("op_3525_cast_fp16")];
        } -> (text_emb);
    func text_t16<ios18>(tensor<fp16, [1, 50, 256]> style_ttl, tensor<int32, [1, 16]> text_ids, tensor<fp16, [1, 1, 16]> text_mask) {
            int32 input_tensor_3_batch_dims_0 = const()[name = string("input_tensor_3_batch_dims_0"), val = int32(0)];
            bool input_tensor_3_validate_indices_0 = const()[name = string("input_tensor_3_validate_indices_0"), val = bool(false)];
            tensor<fp16, [8322, 256]> initializers_onnx_initializer_0_to_fp16 = const()[name = string("initializers_onnx_initializer_0_to_fp16"), val = tensor<fp16, [8322, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(64)))];
            string text_ids_to_int16_dtype_0 = const()[name = string("text_ids_to_int16_dtype_0"), val = string("int16")];
            string cast_59_dtype_0 = const()[name = string("cast_59_dtype_0"), val = string("int32")];
            int32 greater_equal_0_y_0 = const()[name = string("greater_equal_0_y_0"), val = int32(0)];
            tensor<int16, [1, 16]> text_ids_to_int16 = cast(dtype = text_ids_to_int16_dtype_0, x = text_ids)[name = string("cast_62")];
            tensor<int32, [1, 16]> cast_59 = cast(dtype = cast_59_dtype_0, x = text_ids_to_int16)[name = string("cast_61")];
            tensor<bool, [1, 16]> greater_equal_0 = greater_equal(x = cast_59, y = greater_equal_0_y_0)[name = string("greater_equal_0")];
            int32 slice_by_index_0 = const()[name = string("slice_by_index_0"), val = int32(8322)];
            tensor<int32, [1, 16]> add_0 = add(x = cast_59, y = slice_by_index_0)[name = string("add_0")];
            tensor<int32, [1, 16]> select_0 = select(a = cast_59, b = add_0, cond = greater_equal_0)[name = string("select_0")];
            int32 input_tensor_3_cast_fp16_cast_uint16_axis_0 = const()[name = string("input_tensor_3_cast_fp16_cast_uint16_axis_0"), val = int32(0)];
            string select_0_to_int16_dtype_0 = const()[name = string("select_0_to_int16_dtype_0"), val = string("int16")];
            tensor<int16, [1, 16]> select_0_to_int16 = cast(dtype = select_0_to_int16_dtype_0, x = select_0)[name = string("cast_60")];
            tensor<fp16, [1, 16, 256]> input_tensor_3_cast_fp16_cast_uint16_cast_uint16 = gather(axis = input_tensor_3_cast_fp16_cast_uint16_axis_0, batch_dims = input_tensor_3_batch_dims_0, indices = select_0_to_int16, validate_indices = input_tensor_3_validate_indices_0, x = initializers_onnx_initializer_0_to_fp16)[name = string("input_tensor_3_cast_fp16_cast_uint16_cast_uint16")];
            tensor<int32, [3]> var_446 = const()[name = string("op_446"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 256, 16]> first_1_cast_fp16 = transpose(perm = var_446, x = input_tensor_3_cast_fp16_cast_uint16_cast_uint16)[name = string("transpose_47")];
            tensor<fp16, [1, 256, 16]> first_3_cast_fp16 = mul(x = first_1_cast_fp16, y = text_mask)[name = string("first_3_cast_fp16")];
            tensor<fp16, [1, 256, 16]> input_1_cast_fp16 = mul(x = first_3_cast_fp16, y = text_mask)[name = string("input_1_cast_fp16")];
            tensor<int32, [6]> input_3_pad_0 = const()[name = string("input_3_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 2, 2])];
            string input_3_mode_0 = const()[name = string("input_3_mode_0"), val = string("replicate")];
            fp16 const_0_to_fp16 = const()[name = string("const_0_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 256, 20]> input_3_cast_fp16 = pad(constant_val = const_0_to_fp16, mode = input_3_mode_0, pad = input_3_pad_0, x = input_1_cast_fp16)[name = string("input_3_cast_fp16")];
            string first_5_pad_type_0 = const()[name = string("first_5_pad_type_0"), val = string("valid")];
            int32 first_5_groups_0 = const()[name = string("first_5_groups_0"), val = int32(256)];
            tensor<int32, [1]> first_5_strides_0 = const()[name = string("first_5_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_5_pad_0 = const()[name = string("first_5_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_5_dilations_0 = const()[name = string("first_5_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [256, 1, 5]> text_encoder_convnext_convnext_0_dwconv_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_0_dwconv_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4260992)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_0_dwconv_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_0_dwconv_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4263616)))];
            tensor<fp16, [1, 256, 16]> first_5_cast_fp16 = conv(bias = text_encoder_convnext_convnext_0_dwconv_Conv_bias_to_fp16, dilations = first_5_dilations_0, groups = first_5_groups_0, pad = first_5_pad_0, pad_type = first_5_pad_type_0, strides = first_5_strides_0, weight = text_encoder_convnext_convnext_0_dwconv_Conv_weight_to_fp16, x = input_3_cast_fp16)[name = string("first_5_cast_fp16")];
            tensor<fp16, [1, 256, 16]> input_tensor_13_cast_fp16 = mul(x = first_5_cast_fp16, y = text_mask)[name = string("input_tensor_13_cast_fp16")];
            tensor<int32, [3]> var_471 = const()[name = string("op_471"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_15_axes_0 = const()[name = string("input_tensor_15_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_convnext_convnext_0_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_0_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4264192)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_0_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_0_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4264768)))];
            fp16 var_474_to_fp16 = const()[name = string("op_474_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 16, 256]> input_5_cast_fp16 = transpose(perm = var_471, x = input_tensor_13_cast_fp16)[name = string("transpose_46")];
            tensor<fp16, [1, 16, 256]> input_tensor_15_cast_fp16 = layer_norm(axes = input_tensor_15_axes_0, beta = text_encoder_convnext_convnext_0_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_474_to_fp16, gamma = text_encoder_convnext_convnext_0_norm_norm_LayerNormalization_weight_to_fp16, x = input_5_cast_fp16)[name = string("input_tensor_15_cast_fp16")];
            tensor<int32, [3]> var_483 = const()[name = string("op_483"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_7_pad_type_0 = const()[name = string("first_7_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_7_strides_0 = const()[name = string("first_7_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_7_pad_0 = const()[name = string("first_7_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_7_dilations_0 = const()[name = string("first_7_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_7_groups_0 = const()[name = string("first_7_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_convnext_convnext_0_pwconv1_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_0_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4265344)))];
            tensor<fp16, [1024]> text_encoder_convnext_convnext_0_pwconv1_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_0_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4789696)))];
            tensor<fp16, [1, 256, 16]> input_7_cast_fp16 = transpose(perm = var_483, x = input_tensor_15_cast_fp16)[name = string("transpose_45")];
            tensor<fp16, [1, 1024, 16]> first_7_cast_fp16 = conv(bias = text_encoder_convnext_convnext_0_pwconv1_Conv_bias_to_fp16, dilations = first_7_dilations_0, groups = first_7_groups_0, pad = first_7_pad_0, pad_type = first_7_pad_type_0, strides = first_7_strides_0, weight = text_encoder_convnext_convnext_0_pwconv1_Conv_weight_to_fp16, x = input_7_cast_fp16)[name = string("first_7_cast_fp16")];
            string input_9_mode_0 = const()[name = string("input_9_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 1024, 16]> input_9_cast_fp16 = gelu(mode = input_9_mode_0, x = first_7_cast_fp16)[name = string("input_9_cast_fp16")];
            string second_9_pad_type_0 = const()[name = string("second_9_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_9_strides_0 = const()[name = string("second_9_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_9_pad_0 = const()[name = string("second_9_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_9_dilations_0 = const()[name = string("second_9_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_9_groups_0 = const()[name = string("second_9_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> second_11_weight_0_to_fp16 = const()[name = string("second_11_weight_0_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4791808)))];
            tensor<fp16, [256]> second_11_bias_0_to_fp16 = const()[name = string("second_11_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5316160)))];
            tensor<fp16, [1, 256, 16]> second_11_cast_fp16 = conv(bias = second_11_bias_0_to_fp16, dilations = second_9_dilations_0, groups = second_9_groups_0, pad = second_9_pad_0, pad_type = second_9_pad_type_0, strides = second_9_strides_0, weight = second_11_weight_0_to_fp16, x = input_9_cast_fp16)[name = string("second_11_cast_fp16")];
            tensor<fp16, [1, 256, 16]> first_15_cast_fp16 = add(x = input_1_cast_fp16, y = second_11_cast_fp16)[name = string("first_15_cast_fp16")];
            tensor<fp16, [1, 256, 16]> first_17_cast_fp16 = mul(x = first_15_cast_fp16, y = text_mask)[name = string("first_17_cast_fp16")];
            tensor<fp16, [1, 256, 16]> input_11_cast_fp16 = mul(x = first_17_cast_fp16, y = text_mask)[name = string("input_11_cast_fp16")];
            tensor<int32, [6]> input_13_pad_0 = const()[name = string("input_13_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 2, 2])];
            string input_13_mode_0 = const()[name = string("input_13_mode_0"), val = string("replicate")];
            fp16 const_1_to_fp16 = const()[name = string("const_1_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 256, 20]> input_13_cast_fp16 = pad(constant_val = const_1_to_fp16, mode = input_13_mode_0, pad = input_13_pad_0, x = input_11_cast_fp16)[name = string("input_13_cast_fp16")];
            string first_19_pad_type_0 = const()[name = string("first_19_pad_type_0"), val = string("valid")];
            int32 first_19_groups_0 = const()[name = string("first_19_groups_0"), val = int32(256)];
            tensor<int32, [1]> first_19_strides_0 = const()[name = string("first_19_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_19_pad_0 = const()[name = string("first_19_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_19_dilations_0 = const()[name = string("first_19_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [256, 1, 5]> text_encoder_convnext_convnext_1_dwconv_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_1_dwconv_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5316736)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_1_dwconv_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_1_dwconv_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5319360)))];
            tensor<fp16, [1, 256, 16]> first_19_cast_fp16 = conv(bias = text_encoder_convnext_convnext_1_dwconv_Conv_bias_to_fp16, dilations = first_19_dilations_0, groups = first_19_groups_0, pad = first_19_pad_0, pad_type = first_19_pad_type_0, strides = first_19_strides_0, weight = text_encoder_convnext_convnext_1_dwconv_Conv_weight_to_fp16, x = input_13_cast_fp16)[name = string("first_19_cast_fp16")];
            tensor<fp16, [1, 256, 16]> input_tensor_27_cast_fp16 = mul(x = first_19_cast_fp16, y = text_mask)[name = string("input_tensor_27_cast_fp16")];
            tensor<int32, [3]> var_539 = const()[name = string("op_539"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_29_axes_0 = const()[name = string("input_tensor_29_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_convnext_convnext_1_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_1_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5319936)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_1_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_1_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5320512)))];
            fp16 var_542_to_fp16 = const()[name = string("op_542_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 16, 256]> input_15_cast_fp16 = transpose(perm = var_539, x = input_tensor_27_cast_fp16)[name = string("transpose_44")];
            tensor<fp16, [1, 16, 256]> input_tensor_29_cast_fp16 = layer_norm(axes = input_tensor_29_axes_0, beta = text_encoder_convnext_convnext_1_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_542_to_fp16, gamma = text_encoder_convnext_convnext_1_norm_norm_LayerNormalization_weight_to_fp16, x = input_15_cast_fp16)[name = string("input_tensor_29_cast_fp16")];
            tensor<int32, [3]> var_551 = const()[name = string("op_551"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_21_pad_type_0 = const()[name = string("first_21_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_21_strides_0 = const()[name = string("first_21_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_21_pad_0 = const()[name = string("first_21_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_21_dilations_0 = const()[name = string("first_21_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_21_groups_0 = const()[name = string("first_21_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_convnext_convnext_1_pwconv1_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_1_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5321088)))];
            tensor<fp16, [1024]> text_encoder_convnext_convnext_1_pwconv1_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_1_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5845440)))];
            tensor<fp16, [1, 256, 16]> input_17_cast_fp16 = transpose(perm = var_551, x = input_tensor_29_cast_fp16)[name = string("transpose_43")];
            tensor<fp16, [1, 1024, 16]> first_21_cast_fp16 = conv(bias = text_encoder_convnext_convnext_1_pwconv1_Conv_bias_to_fp16, dilations = first_21_dilations_0, groups = first_21_groups_0, pad = first_21_pad_0, pad_type = first_21_pad_type_0, strides = first_21_strides_0, weight = text_encoder_convnext_convnext_1_pwconv1_Conv_weight_to_fp16, x = input_17_cast_fp16)[name = string("first_21_cast_fp16")];
            string input_19_mode_0 = const()[name = string("input_19_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 1024, 16]> input_19_cast_fp16 = gelu(mode = input_19_mode_0, x = first_21_cast_fp16)[name = string("input_19_cast_fp16")];
            string second_21_pad_type_0 = const()[name = string("second_21_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_21_strides_0 = const()[name = string("second_21_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_21_pad_0 = const()[name = string("second_21_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_21_dilations_0 = const()[name = string("second_21_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_21_groups_0 = const()[name = string("second_21_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> second_23_weight_0_to_fp16 = const()[name = string("second_23_weight_0_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5847552)))];
            tensor<fp16, [256]> second_23_bias_0_to_fp16 = const()[name = string("second_23_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6371904)))];
            tensor<fp16, [1, 256, 16]> second_23_cast_fp16 = conv(bias = second_23_bias_0_to_fp16, dilations = second_21_dilations_0, groups = second_21_groups_0, pad = second_21_pad_0, pad_type = second_21_pad_type_0, strides = second_21_strides_0, weight = second_23_weight_0_to_fp16, x = input_19_cast_fp16)[name = string("second_23_cast_fp16")];
            tensor<fp16, [1, 256, 16]> first_29_cast_fp16 = add(x = input_11_cast_fp16, y = second_23_cast_fp16)[name = string("first_29_cast_fp16")];
            tensor<fp16, [1, 256, 16]> first_31_cast_fp16 = mul(x = first_29_cast_fp16, y = text_mask)[name = string("first_31_cast_fp16")];
            tensor<fp16, [1, 256, 16]> input_21_cast_fp16 = mul(x = first_31_cast_fp16, y = text_mask)[name = string("input_21_cast_fp16")];
            tensor<int32, [6]> input_23_pad_0 = const()[name = string("input_23_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            string input_23_mode_0 = const()[name = string("input_23_mode_0"), val = string("replicate")];
            fp16 const_2_to_fp16 = const()[name = string("const_2_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 256, 24]> input_23_cast_fp16 = pad(constant_val = const_2_to_fp16, mode = input_23_mode_0, pad = input_23_pad_0, x = input_21_cast_fp16)[name = string("input_23_cast_fp16")];
            string first_33_pad_type_0 = const()[name = string("first_33_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_33_dilations_0 = const()[name = string("first_33_dilations_0"), val = tensor<int32, [1]>([2])];
            int32 first_33_groups_0 = const()[name = string("first_33_groups_0"), val = int32(256)];
            tensor<int32, [1]> first_33_strides_0 = const()[name = string("first_33_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_33_pad_0 = const()[name = string("first_33_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [256, 1, 5]> text_encoder_convnext_convnext_2_dwconv_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_2_dwconv_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6372480)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_2_dwconv_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_2_dwconv_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6375104)))];
            tensor<fp16, [1, 256, 16]> first_33_cast_fp16 = conv(bias = text_encoder_convnext_convnext_2_dwconv_Conv_bias_to_fp16, dilations = first_33_dilations_0, groups = first_33_groups_0, pad = first_33_pad_0, pad_type = first_33_pad_type_0, strides = first_33_strides_0, weight = text_encoder_convnext_convnext_2_dwconv_Conv_weight_to_fp16, x = input_23_cast_fp16)[name = string("first_33_cast_fp16")];
            tensor<fp16, [1, 256, 16]> input_tensor_41_cast_fp16 = mul(x = first_33_cast_fp16, y = text_mask)[name = string("input_tensor_41_cast_fp16")];
            tensor<int32, [3]> var_608 = const()[name = string("op_608"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_43_axes_0 = const()[name = string("input_tensor_43_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_convnext_convnext_2_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_2_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6375680)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_2_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_2_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6376256)))];
            fp16 var_611_to_fp16 = const()[name = string("op_611_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 16, 256]> input_25_cast_fp16 = transpose(perm = var_608, x = input_tensor_41_cast_fp16)[name = string("transpose_42")];
            tensor<fp16, [1, 16, 256]> input_tensor_43_cast_fp16 = layer_norm(axes = input_tensor_43_axes_0, beta = text_encoder_convnext_convnext_2_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_611_to_fp16, gamma = text_encoder_convnext_convnext_2_norm_norm_LayerNormalization_weight_to_fp16, x = input_25_cast_fp16)[name = string("input_tensor_43_cast_fp16")];
            tensor<int32, [3]> var_620 = const()[name = string("op_620"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_35_pad_type_0 = const()[name = string("first_35_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_35_strides_0 = const()[name = string("first_35_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_35_pad_0 = const()[name = string("first_35_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_35_dilations_0 = const()[name = string("first_35_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_35_groups_0 = const()[name = string("first_35_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_convnext_convnext_2_pwconv1_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_2_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6376832)))];
            tensor<fp16, [1024]> text_encoder_convnext_convnext_2_pwconv1_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_2_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6901184)))];
            tensor<fp16, [1, 256, 16]> input_27_cast_fp16 = transpose(perm = var_620, x = input_tensor_43_cast_fp16)[name = string("transpose_41")];
            tensor<fp16, [1, 1024, 16]> first_35_cast_fp16 = conv(bias = text_encoder_convnext_convnext_2_pwconv1_Conv_bias_to_fp16, dilations = first_35_dilations_0, groups = first_35_groups_0, pad = first_35_pad_0, pad_type = first_35_pad_type_0, strides = first_35_strides_0, weight = text_encoder_convnext_convnext_2_pwconv1_Conv_weight_to_fp16, x = input_27_cast_fp16)[name = string("first_35_cast_fp16")];
            string input_29_mode_0 = const()[name = string("input_29_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 1024, 16]> input_29_cast_fp16 = gelu(mode = input_29_mode_0, x = first_35_cast_fp16)[name = string("input_29_cast_fp16")];
            string second_33_pad_type_0 = const()[name = string("second_33_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_33_strides_0 = const()[name = string("second_33_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_33_pad_0 = const()[name = string("second_33_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_33_dilations_0 = const()[name = string("second_33_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_33_groups_0 = const()[name = string("second_33_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> second_35_weight_0_to_fp16 = const()[name = string("second_35_weight_0_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6903296)))];
            tensor<fp16, [256]> second_35_bias_0_to_fp16 = const()[name = string("second_35_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7427648)))];
            tensor<fp16, [1, 256, 16]> second_35_cast_fp16 = conv(bias = second_35_bias_0_to_fp16, dilations = second_33_dilations_0, groups = second_33_groups_0, pad = second_33_pad_0, pad_type = second_33_pad_type_0, strides = second_33_strides_0, weight = second_35_weight_0_to_fp16, x = input_29_cast_fp16)[name = string("second_35_cast_fp16")];
            tensor<fp16, [1, 256, 16]> first_43_cast_fp16 = add(x = input_21_cast_fp16, y = second_35_cast_fp16)[name = string("first_43_cast_fp16")];
            tensor<fp16, [1, 256, 16]> first_45_cast_fp16 = mul(x = first_43_cast_fp16, y = text_mask)[name = string("first_45_cast_fp16")];
            tensor<fp16, [1, 256, 16]> input_31_cast_fp16 = mul(x = first_45_cast_fp16, y = text_mask)[name = string("input_31_cast_fp16")];
            tensor<int32, [6]> input_33_pad_0 = const()[name = string("input_33_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            string input_33_mode_0 = const()[name = string("input_33_mode_0"), val = string("replicate")];
            fp16 const_3_to_fp16 = const()[name = string("const_3_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 256, 24]> input_33_cast_fp16 = pad(constant_val = const_3_to_fp16, mode = input_33_mode_0, pad = input_33_pad_0, x = input_31_cast_fp16)[name = string("input_33_cast_fp16")];
            string first_47_pad_type_0 = const()[name = string("first_47_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_47_dilations_0 = const()[name = string("first_47_dilations_0"), val = tensor<int32, [1]>([2])];
            int32 first_47_groups_0 = const()[name = string("first_47_groups_0"), val = int32(256)];
            tensor<int32, [1]> first_47_strides_0 = const()[name = string("first_47_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_47_pad_0 = const()[name = string("first_47_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [256, 1, 5]> text_encoder_convnext_convnext_3_dwconv_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_3_dwconv_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7428224)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_3_dwconv_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_3_dwconv_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7430848)))];
            tensor<fp16, [1, 256, 16]> first_47_cast_fp16 = conv(bias = text_encoder_convnext_convnext_3_dwconv_Conv_bias_to_fp16, dilations = first_47_dilations_0, groups = first_47_groups_0, pad = first_47_pad_0, pad_type = first_47_pad_type_0, strides = first_47_strides_0, weight = text_encoder_convnext_convnext_3_dwconv_Conv_weight_to_fp16, x = input_33_cast_fp16)[name = string("first_47_cast_fp16")];
            tensor<fp16, [1, 256, 16]> input_tensor_55_cast_fp16 = mul(x = first_47_cast_fp16, y = text_mask)[name = string("input_tensor_55_cast_fp16")];
            tensor<int32, [3]> var_677 = const()[name = string("op_677"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_57_axes_0 = const()[name = string("input_tensor_57_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_convnext_convnext_3_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_3_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7431424)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_3_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_3_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7432000)))];
            fp16 var_680_to_fp16 = const()[name = string("op_680_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 16, 256]> input_35_cast_fp16 = transpose(perm = var_677, x = input_tensor_55_cast_fp16)[name = string("transpose_40")];
            tensor<fp16, [1, 16, 256]> input_tensor_57_cast_fp16 = layer_norm(axes = input_tensor_57_axes_0, beta = text_encoder_convnext_convnext_3_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_680_to_fp16, gamma = text_encoder_convnext_convnext_3_norm_norm_LayerNormalization_weight_to_fp16, x = input_35_cast_fp16)[name = string("input_tensor_57_cast_fp16")];
            tensor<int32, [3]> var_689 = const()[name = string("op_689"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_49_pad_type_0 = const()[name = string("first_49_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_49_strides_0 = const()[name = string("first_49_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_49_pad_0 = const()[name = string("first_49_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_49_dilations_0 = const()[name = string("first_49_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_49_groups_0 = const()[name = string("first_49_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_convnext_convnext_3_pwconv1_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_3_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7432576)))];
            tensor<fp16, [1024]> text_encoder_convnext_convnext_3_pwconv1_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_3_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7956928)))];
            tensor<fp16, [1, 256, 16]> input_37_cast_fp16 = transpose(perm = var_689, x = input_tensor_57_cast_fp16)[name = string("transpose_39")];
            tensor<fp16, [1, 1024, 16]> first_49_cast_fp16 = conv(bias = text_encoder_convnext_convnext_3_pwconv1_Conv_bias_to_fp16, dilations = first_49_dilations_0, groups = first_49_groups_0, pad = first_49_pad_0, pad_type = first_49_pad_type_0, strides = first_49_strides_0, weight = text_encoder_convnext_convnext_3_pwconv1_Conv_weight_to_fp16, x = input_37_cast_fp16)[name = string("first_49_cast_fp16")];
            string input_39_mode_0 = const()[name = string("input_39_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 1024, 16]> input_39_cast_fp16 = gelu(mode = input_39_mode_0, x = first_49_cast_fp16)[name = string("input_39_cast_fp16")];
            string second_45_pad_type_0 = const()[name = string("second_45_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_45_strides_0 = const()[name = string("second_45_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_45_pad_0 = const()[name = string("second_45_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_45_dilations_0 = const()[name = string("second_45_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_45_groups_0 = const()[name = string("second_45_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> second_47_weight_0_to_fp16 = const()[name = string("second_47_weight_0_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7959040)))];
            tensor<fp16, [256]> second_47_bias_0_to_fp16 = const()[name = string("second_47_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8483392)))];
            tensor<fp16, [1, 256, 16]> second_47_cast_fp16 = conv(bias = second_47_bias_0_to_fp16, dilations = second_45_dilations_0, groups = second_45_groups_0, pad = second_45_pad_0, pad_type = second_45_pad_type_0, strides = second_45_strides_0, weight = second_47_weight_0_to_fp16, x = input_39_cast_fp16)[name = string("second_47_cast_fp16")];
            tensor<fp16, [1, 256, 16]> first_57_cast_fp16 = add(x = input_31_cast_fp16, y = second_47_cast_fp16)[name = string("first_57_cast_fp16")];
            tensor<fp16, [1, 256, 16]> first_59_cast_fp16 = mul(x = first_57_cast_fp16, y = text_mask)[name = string("first_59_cast_fp16")];
            tensor<fp16, [1, 256, 16]> input_41_cast_fp16 = mul(x = first_59_cast_fp16, y = text_mask)[name = string("input_41_cast_fp16")];
            tensor<int32, [6]> input_43_pad_0 = const()[name = string("input_43_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 8, 8])];
            string input_43_mode_0 = const()[name = string("input_43_mode_0"), val = string("replicate")];
            fp16 const_4_to_fp16 = const()[name = string("const_4_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 256, 32]> input_43_cast_fp16 = pad(constant_val = const_4_to_fp16, mode = input_43_mode_0, pad = input_43_pad_0, x = input_41_cast_fp16)[name = string("input_43_cast_fp16")];
            string first_61_pad_type_0 = const()[name = string("first_61_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_61_dilations_0 = const()[name = string("first_61_dilations_0"), val = tensor<int32, [1]>([4])];
            int32 first_61_groups_0 = const()[name = string("first_61_groups_0"), val = int32(256)];
            tensor<int32, [1]> first_61_strides_0 = const()[name = string("first_61_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_61_pad_0 = const()[name = string("first_61_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [256, 1, 5]> text_encoder_convnext_convnext_4_dwconv_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_4_dwconv_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8483968)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_4_dwconv_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_4_dwconv_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8486592)))];
            tensor<fp16, [1, 256, 16]> first_61_cast_fp16 = conv(bias = text_encoder_convnext_convnext_4_dwconv_Conv_bias_to_fp16, dilations = first_61_dilations_0, groups = first_61_groups_0, pad = first_61_pad_0, pad_type = first_61_pad_type_0, strides = first_61_strides_0, weight = text_encoder_convnext_convnext_4_dwconv_Conv_weight_to_fp16, x = input_43_cast_fp16)[name = string("first_61_cast_fp16")];
            tensor<fp16, [1, 256, 16]> input_tensor_69_cast_fp16 = mul(x = first_61_cast_fp16, y = text_mask)[name = string("input_tensor_69_cast_fp16")];
            tensor<int32, [3]> var_746 = const()[name = string("op_746"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_71_axes_0 = const()[name = string("input_tensor_71_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_convnext_convnext_4_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_4_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8487168)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_4_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_4_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8487744)))];
            fp16 var_749_to_fp16 = const()[name = string("op_749_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 16, 256]> input_45_cast_fp16 = transpose(perm = var_746, x = input_tensor_69_cast_fp16)[name = string("transpose_38")];
            tensor<fp16, [1, 16, 256]> input_tensor_71_cast_fp16 = layer_norm(axes = input_tensor_71_axes_0, beta = text_encoder_convnext_convnext_4_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_749_to_fp16, gamma = text_encoder_convnext_convnext_4_norm_norm_LayerNormalization_weight_to_fp16, x = input_45_cast_fp16)[name = string("input_tensor_71_cast_fp16")];
            tensor<int32, [3]> var_758 = const()[name = string("op_758"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_63_pad_type_0 = const()[name = string("first_63_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_63_strides_0 = const()[name = string("first_63_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_63_pad_0 = const()[name = string("first_63_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_63_dilations_0 = const()[name = string("first_63_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_63_groups_0 = const()[name = string("first_63_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_convnext_convnext_4_pwconv1_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_4_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8488320)))];
            tensor<fp16, [1024]> text_encoder_convnext_convnext_4_pwconv1_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_4_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9012672)))];
            tensor<fp16, [1, 256, 16]> input_47_cast_fp16 = transpose(perm = var_758, x = input_tensor_71_cast_fp16)[name = string("transpose_37")];
            tensor<fp16, [1, 1024, 16]> first_63_cast_fp16 = conv(bias = text_encoder_convnext_convnext_4_pwconv1_Conv_bias_to_fp16, dilations = first_63_dilations_0, groups = first_63_groups_0, pad = first_63_pad_0, pad_type = first_63_pad_type_0, strides = first_63_strides_0, weight = text_encoder_convnext_convnext_4_pwconv1_Conv_weight_to_fp16, x = input_47_cast_fp16)[name = string("first_63_cast_fp16")];
            string input_49_mode_0 = const()[name = string("input_49_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 1024, 16]> input_49_cast_fp16 = gelu(mode = input_49_mode_0, x = first_63_cast_fp16)[name = string("input_49_cast_fp16")];
            string second_57_pad_type_0 = const()[name = string("second_57_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_57_strides_0 = const()[name = string("second_57_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_57_pad_0 = const()[name = string("second_57_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_57_dilations_0 = const()[name = string("second_57_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_57_groups_0 = const()[name = string("second_57_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> second_59_weight_0_to_fp16 = const()[name = string("second_59_weight_0_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9014784)))];
            tensor<fp16, [256]> second_59_bias_0_to_fp16 = const()[name = string("second_59_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9539136)))];
            tensor<fp16, [1, 256, 16]> second_59_cast_fp16 = conv(bias = second_59_bias_0_to_fp16, dilations = second_57_dilations_0, groups = second_57_groups_0, pad = second_57_pad_0, pad_type = second_57_pad_type_0, strides = second_57_strides_0, weight = second_59_weight_0_to_fp16, x = input_49_cast_fp16)[name = string("second_59_cast_fp16")];
            tensor<fp16, [1, 256, 16]> first_71_cast_fp16 = add(x = input_41_cast_fp16, y = second_59_cast_fp16)[name = string("first_71_cast_fp16")];
            tensor<fp16, [1, 256, 16]> first_73_cast_fp16 = mul(x = first_71_cast_fp16, y = text_mask)[name = string("first_73_cast_fp16")];
            tensor<fp16, [1, 256, 16]> input_51_cast_fp16 = mul(x = first_73_cast_fp16, y = text_mask)[name = string("input_51_cast_fp16")];
            tensor<int32, [6]> input_53_pad_0 = const()[name = string("input_53_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 8, 8])];
            string input_53_mode_0 = const()[name = string("input_53_mode_0"), val = string("replicate")];
            fp16 const_5_to_fp16 = const()[name = string("const_5_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 256, 32]> input_53_cast_fp16 = pad(constant_val = const_5_to_fp16, mode = input_53_mode_0, pad = input_53_pad_0, x = input_51_cast_fp16)[name = string("input_53_cast_fp16")];
            string first_75_pad_type_0 = const()[name = string("first_75_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_75_dilations_0 = const()[name = string("first_75_dilations_0"), val = tensor<int32, [1]>([4])];
            int32 first_75_groups_0 = const()[name = string("first_75_groups_0"), val = int32(256)];
            tensor<int32, [1]> first_75_strides_0 = const()[name = string("first_75_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_75_pad_0 = const()[name = string("first_75_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [256, 1, 5]> text_encoder_convnext_convnext_5_dwconv_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_5_dwconv_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9539712)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_5_dwconv_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_5_dwconv_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9542336)))];
            tensor<fp16, [1, 256, 16]> first_75_cast_fp16 = conv(bias = text_encoder_convnext_convnext_5_dwconv_Conv_bias_to_fp16, dilations = first_75_dilations_0, groups = first_75_groups_0, pad = first_75_pad_0, pad_type = first_75_pad_type_0, strides = first_75_strides_0, weight = text_encoder_convnext_convnext_5_dwconv_Conv_weight_to_fp16, x = input_53_cast_fp16)[name = string("first_75_cast_fp16")];
            tensor<fp16, [1, 256, 16]> input_tensor_83_cast_fp16 = mul(x = first_75_cast_fp16, y = text_mask)[name = string("input_tensor_83_cast_fp16")];
            tensor<int32, [3]> var_815 = const()[name = string("op_815"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_85_axes_0 = const()[name = string("input_tensor_85_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_convnext_convnext_5_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_5_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9542912)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_5_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_5_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9543488)))];
            fp16 var_818_to_fp16 = const()[name = string("op_818_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 16, 256]> input_55_cast_fp16 = transpose(perm = var_815, x = input_tensor_83_cast_fp16)[name = string("transpose_36")];
            tensor<fp16, [1, 16, 256]> input_tensor_85_cast_fp16 = layer_norm(axes = input_tensor_85_axes_0, beta = text_encoder_convnext_convnext_5_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_818_to_fp16, gamma = text_encoder_convnext_convnext_5_norm_norm_LayerNormalization_weight_to_fp16, x = input_55_cast_fp16)[name = string("input_tensor_85_cast_fp16")];
            tensor<int32, [3]> var_827 = const()[name = string("op_827"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_77_pad_type_0 = const()[name = string("first_77_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_77_strides_0 = const()[name = string("first_77_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_77_pad_0 = const()[name = string("first_77_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_77_dilations_0 = const()[name = string("first_77_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_77_groups_0 = const()[name = string("first_77_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_convnext_convnext_5_pwconv1_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_5_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9544064)))];
            tensor<fp16, [1024]> text_encoder_convnext_convnext_5_pwconv1_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_5_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10068416)))];
            tensor<fp16, [1, 256, 16]> input_57_cast_fp16 = transpose(perm = var_827, x = input_tensor_85_cast_fp16)[name = string("transpose_35")];
            tensor<fp16, [1, 1024, 16]> first_77_cast_fp16 = conv(bias = text_encoder_convnext_convnext_5_pwconv1_Conv_bias_to_fp16, dilations = first_77_dilations_0, groups = first_77_groups_0, pad = first_77_pad_0, pad_type = first_77_pad_type_0, strides = first_77_strides_0, weight = text_encoder_convnext_convnext_5_pwconv1_Conv_weight_to_fp16, x = input_57_cast_fp16)[name = string("first_77_cast_fp16")];
            string input_59_mode_0 = const()[name = string("input_59_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 1024, 16]> input_59_cast_fp16 = gelu(mode = input_59_mode_0, x = first_77_cast_fp16)[name = string("input_59_cast_fp16")];
            string second_69_pad_type_0 = const()[name = string("second_69_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_69_strides_0 = const()[name = string("second_69_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_69_pad_0 = const()[name = string("second_69_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_69_dilations_0 = const()[name = string("second_69_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_69_groups_0 = const()[name = string("second_69_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> second_71_weight_0_to_fp16 = const()[name = string("second_71_weight_0_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10070528)))];
            tensor<fp16, [256]> second_71_bias_0_to_fp16 = const()[name = string("second_71_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10594880)))];
            tensor<fp16, [1, 256, 16]> second_71_cast_fp16 = conv(bias = second_71_bias_0_to_fp16, dilations = second_69_dilations_0, groups = second_69_groups_0, pad = second_69_pad_0, pad_type = second_69_pad_type_0, strides = second_69_strides_0, weight = second_71_weight_0_to_fp16, x = input_59_cast_fp16)[name = string("second_71_cast_fp16")];
            tensor<fp16, [1, 256, 16]> first_85_cast_fp16 = add(x = input_51_cast_fp16, y = second_71_cast_fp16)[name = string("first_85_cast_fp16")];
            tensor<fp16, [1, 256, 16]> first_89_cast_fp16 = mul(x = first_85_cast_fp16, y = text_mask)[name = string("first_89_cast_fp16")];
            tensor<int32, [1]> first_87_axes_0 = const()[name = string("first_87_axes_0"), val = tensor<int32, [1]>([2])];
            tensor<fp16, [1, 1, 1, 16]> first_87_cast_fp16 = expand_dims(axes = first_87_axes_0, x = text_mask)[name = string("first_87_cast_fp16")];
            tensor<int32, [1]> second_73_axes_0 = const()[name = string("second_73_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 1, 16, 1]> second_73_cast_fp16 = expand_dims(axes = second_73_axes_0, x = text_mask)[name = string("second_73_cast_fp16")];
            tensor<fp16, [1, 1, 16, 16]> x_45_cast_fp16 = mul(x = first_87_cast_fp16, y = second_73_cast_fp16)[name = string("x_45_cast_fp16")];
            tensor<fp16, [1, 256, 16]> input_61_cast_fp16 = mul(x = first_89_cast_fp16, y = text_mask)[name = string("input_61_cast_fp16")];
            string input_tensor_97_pad_type_0 = const()[name = string("input_tensor_97_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_97_strides_0 = const()[name = string("input_tensor_97_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_97_pad_0 = const()[name = string("input_tensor_97_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_97_dilations_0 = const()[name = string("input_tensor_97_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_97_groups_0 = const()[name = string("input_tensor_97_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_0_conv_q_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_q_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10595456)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_0_conv_q_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_q_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10726592)))];
            tensor<fp16, [1, 256, 16]> input_tensor_97_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_0_conv_q_Conv_bias_to_fp16, dilations = input_tensor_97_dilations_0, groups = input_tensor_97_groups_0, pad = input_tensor_97_pad_0, pad_type = input_tensor_97_pad_type_0, strides = input_tensor_97_strides_0, weight = text_encoder_attn_encoder_attn_layers_0_conv_q_Conv_weight_to_fp16, x = input_61_cast_fp16)[name = string("input_tensor_97_cast_fp16")];
            string input_tensor_89_pad_type_0 = const()[name = string("input_tensor_89_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_89_strides_0 = const()[name = string("input_tensor_89_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_89_pad_0 = const()[name = string("input_tensor_89_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_89_dilations_0 = const()[name = string("input_tensor_89_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_89_groups_0 = const()[name = string("input_tensor_89_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_0_conv_k_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_k_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10727168)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_0_conv_k_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_k_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10858304)))];
            tensor<fp16, [1, 256, 16]> input_tensor_89_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_0_conv_k_Conv_bias_to_fp16, dilations = input_tensor_89_dilations_0, groups = input_tensor_89_groups_0, pad = input_tensor_89_pad_0, pad_type = input_tensor_89_pad_type_0, strides = input_tensor_89_strides_0, weight = text_encoder_attn_encoder_attn_layers_0_conv_k_Conv_weight_to_fp16, x = input_61_cast_fp16)[name = string("input_tensor_89_cast_fp16")];
            string input_tensor_109_pad_type_0 = const()[name = string("input_tensor_109_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_109_strides_0 = const()[name = string("input_tensor_109_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_109_pad_0 = const()[name = string("input_tensor_109_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_109_dilations_0 = const()[name = string("input_tensor_109_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_109_groups_0 = const()[name = string("input_tensor_109_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_0_conv_v_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_v_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10858880)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_0_conv_v_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_v_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10990016)))];
            tensor<fp16, [1, 256, 16]> input_tensor_109_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_0_conv_v_Conv_bias_to_fp16, dilations = input_tensor_109_dilations_0, groups = input_tensor_109_groups_0, pad = input_tensor_109_pad_0, pad_type = input_tensor_109_pad_type_0, strides = input_tensor_109_strides_0, weight = text_encoder_attn_encoder_attn_layers_0_conv_v_Conv_weight_to_fp16, x = input_61_cast_fp16)[name = string("input_tensor_109_cast_fp16")];
            tensor<int32, [4]> var_973 = const()[name = string("op_973"), val = tensor<int32, [4]>([1, 4, 64, 16])];
            tensor<fp16, [1, 4, 64, 16]> input_tensor_105_cast_fp16 = reshape(shape = var_973, x = input_tensor_97_cast_fp16)[name = string("input_tensor_105_cast_fp16")];
            tensor<int32, [4]> var_979 = const()[name = string("op_979"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [4]> var_1005 = const()[name = string("op_1005"), val = tensor<int32, [4]>([1, 4, 64, 16])];
            tensor<fp16, [1, 4, 64, 16]> y_1_cast_fp16 = reshape(shape = var_1005, x = input_tensor_89_cast_fp16)[name = string("y_1_cast_fp16")];
            tensor<int32, [4]> var_1017 = const()[name = string("op_1017"), val = tensor<int32, [4]>([1, 4, 64, 16])];
            tensor<fp16, [1, 4, 64, 16]> input_tensor_111_cast_fp16 = reshape(shape = var_1017, x = input_tensor_109_cast_fp16)[name = string("input_tensor_111_cast_fp16")];
            fp16 _inversed_x_25_y_0_to_fp16 = const()[name = string("_inversed_x_25_y_0_to_fp16"), val = fp16(0x1p-3)];
            tensor<fp16, [1, 4, 16, 64]> first_91_cast_fp16 = transpose(perm = var_979, x = input_tensor_105_cast_fp16)[name = string("transpose_34")];
            tensor<fp16, [1, 4, 16, 64]> _inversed_x_25_cast_fp16 = mul(x = first_91_cast_fp16, y = _inversed_x_25_y_0_to_fp16)[name = string("_inversed_x_25_cast_fp16")];
            bool first_107_transpose_x_0 = const()[name = string("first_107_transpose_x_0"), val = bool(false)];
            bool first_107_transpose_y_0 = const()[name = string("first_107_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 4, 16, 16]> first_107_cast_fp16 = matmul(transpose_x = first_107_transpose_x_0, transpose_y = first_107_transpose_y_0, x = _inversed_x_25_cast_fp16, y = y_1_cast_fp16)[name = string("first_107_cast_fp16")];
            bool input_tensor_143_transpose_x_0 = const()[name = string("input_tensor_143_transpose_x_0"), val = bool(false)];
            bool input_tensor_143_transpose_y_0 = const()[name = string("input_tensor_143_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 64, 31]> y_3_to_fp16 = const()[name = string("y_3_to_fp16"), val = tensor<fp16, [1, 1, 64, 31]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10990592)))];
            tensor<fp16, [1, 4, 16, 31]> input_tensor_143_cast_fp16 = matmul(transpose_x = input_tensor_143_transpose_x_0, transpose_y = input_tensor_143_transpose_y_0, x = _inversed_x_25_cast_fp16, y = y_3_to_fp16)[name = string("input_tensor_143_cast_fp16")];
            tensor<int32, [8]> input_tensor_165_pad_0 = const()[name = string("input_tensor_165_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 1])];
            string input_tensor_165_mode_0 = const()[name = string("input_tensor_165_mode_0"), val = string("constant")];
            fp16 const_23_to_fp16 = const()[name = string("const_23_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 16, 32]> input_tensor_165_cast_fp16 = pad(constant_val = const_23_to_fp16, mode = input_tensor_165_mode_0, pad = input_tensor_165_pad_0, x = input_tensor_143_cast_fp16)[name = string("input_tensor_165_cast_fp16")];
            tensor<int32, [3]> var_1140 = const()[name = string("op_1140"), val = tensor<int32, [3]>([1, 4, 512])];
            tensor<fp16, [1, 4, 512]> input_69_cast_fp16 = reshape(shape = var_1140, x = input_tensor_165_cast_fp16)[name = string("input_69_cast_fp16")];
            tensor<int32, [6]> input_tensor_187_pad_0 = const()[name = string("input_tensor_187_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 0, 15])];
            string input_tensor_187_mode_0 = const()[name = string("input_tensor_187_mode_0"), val = string("constant")];
            fp16 const_24_to_fp16 = const()[name = string("const_24_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 527]> input_tensor_187_cast_fp16 = pad(constant_val = const_24_to_fp16, mode = input_tensor_187_mode_0, pad = input_tensor_187_pad_0, x = input_69_cast_fp16)[name = string("input_tensor_187_cast_fp16")];
            tensor<int32, [4]> var_1175 = const()[name = string("op_1175"), val = tensor<int32, [4]>([1, 4, 17, 31])];
            tensor<fp16, [1, 4, 17, 31]> x_41_cast_fp16 = reshape(shape = var_1175, x = input_tensor_187_cast_fp16)[name = string("x_41_cast_fp16")];
            tensor<int32, [4]> x_43_begin_0 = const()[name = string("x_43_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> x_43_end_0 = const()[name = string("x_43_end_0"), val = tensor<int32, [4]>([1, 4, 16, 31])];
            tensor<bool, [4]> x_43_end_mask_0 = const()[name = string("x_43_end_mask_0"), val = tensor<bool, [4]>([true, true, false, true])];
            tensor<fp16, [1, 4, 16, 31]> x_43_cast_fp16 = slice_by_index(begin = x_43_begin_0, end = x_43_end_0, end_mask = x_43_end_mask_0, x = x_41_cast_fp16)[name = string("x_43_cast_fp16")];
            tensor<int32, [4]> second_97_begin_0 = const()[name = string("second_97_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 15])];
            tensor<int32, [4]> second_97_end_0 = const()[name = string("second_97_end_0"), val = tensor<int32, [4]>([1, 4, 16, 1])];
            tensor<bool, [4]> second_97_end_mask_0 = const()[name = string("second_97_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 16, 16]> second_97_cast_fp16 = slice_by_index(begin = second_97_begin_0, end = second_97_end_0, end_mask = second_97_end_mask_0, x = x_43_cast_fp16)[name = string("second_97_cast_fp16")];
            tensor<fp16, [1, 4, 16, 16]> y_7_cast_fp16 = add(x = first_107_cast_fp16, y = second_97_cast_fp16)[name = string("y_7_cast_fp16")];
            fp16 text_encoder_attn_encoder_attn_layers_0_Constant_87_value_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_Constant_87_value_to_fp16"), val = fp16(0x0p+0)];
            tensor<bool, [1, 1, 16, 16]> input_tensor_189_cast_fp16 = equal(x = x_45_cast_fp16, y = text_encoder_attn_encoder_attn_layers_0_Constant_87_value_to_fp16)[name = string("input_tensor_189_cast_fp16")];
            tensor<int32, [4]> condition_1_after_broadcast_reps_0 = const()[name = string("condition_1_after_broadcast_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<bool, [1, 4, 16, 16]> condition_1_after_broadcast = tile(reps = condition_1_after_broadcast_reps_0, x = input_tensor_189_cast_fp16)[name = string("condition_1_after_broadcast")];
            tensor<fp16, [1, 4, 16, 16]> text_encoder_attn_encoder_attn_layers_0_Constant_88_value_after_broadcast_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_Constant_88_value_after_broadcast_to_fp16"), val = tensor<fp16, [1, 4, 16, 16]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10994624)))];
            tensor<fp16, [1, 4, 16, 16]> input_71_cast_fp16 = select(a = text_encoder_attn_encoder_attn_layers_0_Constant_88_value_after_broadcast_to_fp16, b = y_7_cast_fp16, cond = condition_1_after_broadcast)[name = string("input_71_cast_fp16")];
            int32 var_1218 = const()[name = string("op_1218"), val = int32(-1)];
            tensor<fp16, [1, 4, 16, 16]> x_49_cast_fp16 = softmax(axis = var_1218, x = input_71_cast_fp16)[name = string("x_49_cast_fp16")];
            bool first_119_transpose_x_1 = const()[name = string("first_119_transpose_x_1"), val = bool(false)];
            bool first_119_transpose_y_1 = const()[name = string("first_119_transpose_y_1"), val = bool(true)];
            tensor<fp16, [1, 4, 16, 64]> first_119_cast_fp16 = matmul(transpose_x = first_119_transpose_x_1, transpose_y = first_119_transpose_y_1, x = x_49_cast_fp16, y = input_tensor_111_cast_fp16)[name = string("first_119_cast_fp16")];
            tensor<int32, [8]> input_tensor_219_pad_0 = const()[name = string("input_tensor_219_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 15])];
            string input_tensor_219_mode_0 = const()[name = string("input_tensor_219_mode_0"), val = string("constant")];
            fp16 const_31_to_fp16 = const()[name = string("const_31_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 16, 31]> input_tensor_219_cast_fp16 = pad(constant_val = const_31_to_fp16, mode = input_tensor_219_mode_0, pad = input_tensor_219_pad_0, x = x_49_cast_fp16)[name = string("input_tensor_219_cast_fp16")];
            tensor<int32, [3]> var_1292 = const()[name = string("op_1292"), val = tensor<int32, [3]>([1, 4, 496])];
            tensor<fp16, [1, 4, 496]> input_73_cast_fp16 = reshape(shape = var_1292, x = input_tensor_219_cast_fp16)[name = string("input_73_cast_fp16")];
            tensor<int32, [6]> input_tensor_237_pad_0 = const()[name = string("input_tensor_237_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 16, 0])];
            string input_tensor_237_mode_0 = const()[name = string("input_tensor_237_mode_0"), val = string("constant")];
            fp16 const_32_to_fp16 = const()[name = string("const_32_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 512]> input_tensor_237_cast_fp16 = pad(constant_val = const_32_to_fp16, mode = input_tensor_237_mode_0, pad = input_tensor_237_pad_0, x = input_73_cast_fp16)[name = string("input_tensor_237_cast_fp16")];
            tensor<int32, [4]> var_1322 = const()[name = string("op_1322"), val = tensor<int32, [4]>([1, 4, 16, 32])];
            tensor<fp16, [1, 4, 16, 32]> x_59_cast_fp16 = reshape(shape = var_1322, x = input_tensor_237_cast_fp16)[name = string("x_59_cast_fp16")];
            tensor<int32, [4]> x_67_begin_0 = const()[name = string("x_67_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 1])];
            tensor<int32, [4]> x_67_end_0 = const()[name = string("x_67_end_0"), val = tensor<int32, [4]>([1, 4, 16, 1])];
            tensor<bool, [4]> x_67_end_mask_0 = const()[name = string("x_67_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 16, 31]> x_67_cast_fp16 = slice_by_index(begin = x_67_begin_0, end = x_67_end_0, end_mask = x_67_end_mask_0, x = x_59_cast_fp16)[name = string("x_67_cast_fp16")];
            bool second_111_transpose_x_0 = const()[name = string("second_111_transpose_x_0"), val = bool(false)];
            bool second_111_transpose_y_0 = const()[name = string("second_111_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 31, 64]> y_11_to_fp16 = const()[name = string("y_11_to_fp16"), val = tensor<fp16, [1, 1, 31, 64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10996736)))];
            tensor<fp16, [1, 4, 16, 64]> second_111_cast_fp16 = matmul(transpose_x = second_111_transpose_x_0, transpose_y = second_111_transpose_y_0, x = x_67_cast_fp16, y = y_11_to_fp16)[name = string("second_111_cast_fp16")];
            tensor<fp16, [1, 4, 16, 64]> input_tensor_255_cast_fp16 = add(x = first_119_cast_fp16, y = second_111_cast_fp16)[name = string("input_tensor_255_cast_fp16")];
            tensor<int32, [4]> var_1369 = const()[name = string("op_1369"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [3]> var_1388 = const()[name = string("op_1388"), val = tensor<int32, [3]>([1, 256, 16])];
            tensor<fp16, [1, 4, 64, 16]> input_tensor_259_cast_fp16 = transpose(perm = var_1369, x = input_tensor_255_cast_fp16)[name = string("transpose_33")];
            tensor<fp16, [1, 256, 16]> input_77_cast_fp16 = reshape(shape = var_1388, x = input_tensor_259_cast_fp16)[name = string("input_77_cast_fp16")];
            string second_113_pad_type_0 = const()[name = string("second_113_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_113_strides_0 = const()[name = string("second_113_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_113_pad_0 = const()[name = string("second_113_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_113_dilations_0 = const()[name = string("second_113_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_113_groups_0 = const()[name = string("second_113_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_0_conv_o_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_o_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11000768)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_0_conv_o_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_o_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11131904)))];
            tensor<fp16, [1, 256, 16]> second_113_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_0_conv_o_Conv_bias_to_fp16, dilations = second_113_dilations_0, groups = second_113_groups_0, pad = second_113_pad_0, pad_type = second_113_pad_type_0, strides = second_113_strides_0, weight = text_encoder_attn_encoder_attn_layers_0_conv_o_Conv_weight_to_fp16, x = input_77_cast_fp16)[name = string("second_113_cast_fp16")];
            tensor<fp16, [1, 256, 16]> input_tensor_261_cast_fp16 = add(x = input_61_cast_fp16, y = second_113_cast_fp16)[name = string("input_tensor_261_cast_fp16")];
            tensor<int32, [3]> var_1406 = const()[name = string("op_1406"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_263_axes_0 = const()[name = string("input_tensor_263_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_0_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_0_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11132480)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_0_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_0_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11133056)))];
            fp16 var_1409_to_fp16 = const()[name = string("op_1409_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 16, 256]> input_79_cast_fp16 = transpose(perm = var_1406, x = input_tensor_261_cast_fp16)[name = string("transpose_32")];
            tensor<fp16, [1, 16, 256]> input_tensor_263_cast_fp16 = layer_norm(axes = input_tensor_263_axes_0, beta = text_encoder_attn_encoder_norm_layers_1_0_norm_LayerNormalization_bias_to_fp16, epsilon = var_1409_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_1_0_norm_LayerNormalization_weight_to_fp16, x = input_79_cast_fp16)[name = string("input_tensor_263_cast_fp16")];
            tensor<int32, [3]> var_1418 = const()[name = string("op_1418"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 256, 16]> first_121_cast_fp16 = transpose(perm = var_1418, x = input_tensor_263_cast_fp16)[name = string("transpose_31")];
            tensor<fp16, [1, 256, 16]> input_81_cast_fp16 = mul(x = first_121_cast_fp16, y = text_mask)[name = string("input_81_cast_fp16")];
            string input_83_pad_type_0 = const()[name = string("input_83_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_83_strides_0 = const()[name = string("input_83_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_83_pad_0 = const()[name = string("input_83_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_83_dilations_0 = const()[name = string("input_83_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_83_groups_0 = const()[name = string("input_83_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_attn_encoder_ffn_layers_0_conv_1_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_0_conv_1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11133632)))];
            tensor<fp16, [1024]> text_encoder_attn_encoder_ffn_layers_0_conv_1_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_0_conv_1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11657984)))];
            tensor<fp16, [1, 1024, 16]> input_83_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_0_conv_1_Conv_bias_to_fp16, dilations = input_83_dilations_0, groups = input_83_groups_0, pad = input_83_pad_0, pad_type = input_83_pad_type_0, strides = input_83_strides_0, weight = text_encoder_attn_encoder_ffn_layers_0_conv_1_Conv_weight_to_fp16, x = input_81_cast_fp16)[name = string("input_83_cast_fp16")];
            tensor<fp16, [1, 1024, 16]> first_123_cast_fp16 = relu(x = input_83_cast_fp16)[name = string("first_123_cast_fp16")];
            tensor<fp16, [1, 1024, 16]> input_85_cast_fp16 = mul(x = first_123_cast_fp16, y = text_mask)[name = string("input_85_cast_fp16")];
            string first_125_pad_type_0 = const()[name = string("first_125_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_125_strides_0 = const()[name = string("first_125_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_125_pad_0 = const()[name = string("first_125_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_125_dilations_0 = const()[name = string("first_125_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_125_groups_0 = const()[name = string("first_125_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> text_encoder_attn_encoder_ffn_layers_0_conv_2_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_0_conv_2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11660096)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_ffn_layers_0_conv_2_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_0_conv_2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12184448)))];
            tensor<fp16, [1, 256, 16]> first_125_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_0_conv_2_Conv_bias_to_fp16, dilations = first_125_dilations_0, groups = first_125_groups_0, pad = first_125_pad_0, pad_type = first_125_pad_type_0, strides = first_125_strides_0, weight = text_encoder_attn_encoder_ffn_layers_0_conv_2_Conv_weight_to_fp16, x = input_85_cast_fp16)[name = string("first_125_cast_fp16")];
            tensor<fp16, [1, 256, 16]> second_115_cast_fp16 = mul(x = first_125_cast_fp16, y = text_mask)[name = string("second_115_cast_fp16")];
            tensor<fp16, [1, 256, 16]> input_tensor_265_cast_fp16 = add(x = first_121_cast_fp16, y = second_115_cast_fp16)[name = string("input_tensor_265_cast_fp16")];
            tensor<int32, [3]> var_1451 = const()[name = string("op_1451"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_267_axes_0 = const()[name = string("input_tensor_267_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_0_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_0_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12185024)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_0_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_0_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12185600)))];
            fp16 var_1454_to_fp16 = const()[name = string("op_1454_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 16, 256]> input_87_cast_fp16 = transpose(perm = var_1451, x = input_tensor_265_cast_fp16)[name = string("transpose_30")];
            tensor<fp16, [1, 16, 256]> input_tensor_267_cast_fp16 = layer_norm(axes = input_tensor_267_axes_0, beta = text_encoder_attn_encoder_norm_layers_2_0_norm_LayerNormalization_bias_to_fp16, epsilon = var_1454_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_2_0_norm_LayerNormalization_weight_to_fp16, x = input_87_cast_fp16)[name = string("input_tensor_267_cast_fp16")];
            tensor<int32, [3]> var_1463 = const()[name = string("op_1463"), val = tensor<int32, [3]>([0, 2, 1])];
            string input_tensor_277_pad_type_0 = const()[name = string("input_tensor_277_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_277_strides_0 = const()[name = string("input_tensor_277_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_277_pad_0 = const()[name = string("input_tensor_277_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_277_dilations_0 = const()[name = string("input_tensor_277_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_277_groups_0 = const()[name = string("input_tensor_277_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_1_conv_q_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_q_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12186176)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_1_conv_q_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_q_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12317312)))];
            tensor<fp16, [1, 256, 16]> input_89_cast_fp16 = transpose(perm = var_1463, x = input_tensor_267_cast_fp16)[name = string("transpose_29")];
            tensor<fp16, [1, 256, 16]> input_tensor_277_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_1_conv_q_Conv_bias_to_fp16, dilations = input_tensor_277_dilations_0, groups = input_tensor_277_groups_0, pad = input_tensor_277_pad_0, pad_type = input_tensor_277_pad_type_0, strides = input_tensor_277_strides_0, weight = text_encoder_attn_encoder_attn_layers_1_conv_q_Conv_weight_to_fp16, x = input_89_cast_fp16)[name = string("input_tensor_277_cast_fp16")];
            string input_tensor_269_pad_type_0 = const()[name = string("input_tensor_269_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_269_strides_0 = const()[name = string("input_tensor_269_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_269_pad_0 = const()[name = string("input_tensor_269_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_269_dilations_0 = const()[name = string("input_tensor_269_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_269_groups_0 = const()[name = string("input_tensor_269_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_1_conv_k_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_k_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12317888)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_1_conv_k_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_k_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12449024)))];
            tensor<fp16, [1, 256, 16]> input_tensor_269_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_1_conv_k_Conv_bias_to_fp16, dilations = input_tensor_269_dilations_0, groups = input_tensor_269_groups_0, pad = input_tensor_269_pad_0, pad_type = input_tensor_269_pad_type_0, strides = input_tensor_269_strides_0, weight = text_encoder_attn_encoder_attn_layers_1_conv_k_Conv_weight_to_fp16, x = input_89_cast_fp16)[name = string("input_tensor_269_cast_fp16")];
            string input_tensor_289_pad_type_0 = const()[name = string("input_tensor_289_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_289_strides_0 = const()[name = string("input_tensor_289_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_289_pad_0 = const()[name = string("input_tensor_289_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_289_dilations_0 = const()[name = string("input_tensor_289_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_289_groups_0 = const()[name = string("input_tensor_289_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_1_conv_v_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_v_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12449600)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_1_conv_v_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_v_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12580736)))];
            tensor<fp16, [1, 256, 16]> input_tensor_289_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_1_conv_v_Conv_bias_to_fp16, dilations = input_tensor_289_dilations_0, groups = input_tensor_289_groups_0, pad = input_tensor_289_pad_0, pad_type = input_tensor_289_pad_type_0, strides = input_tensor_289_strides_0, weight = text_encoder_attn_encoder_attn_layers_1_conv_v_Conv_weight_to_fp16, x = input_89_cast_fp16)[name = string("input_tensor_289_cast_fp16")];
            tensor<int32, [4]> var_1571 = const()[name = string("op_1571"), val = tensor<int32, [4]>([1, 4, 64, 16])];
            tensor<fp16, [1, 4, 64, 16]> input_tensor_285_cast_fp16 = reshape(shape = var_1571, x = input_tensor_277_cast_fp16)[name = string("input_tensor_285_cast_fp16")];
            tensor<int32, [4]> var_1577 = const()[name = string("op_1577"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [4]> var_1603 = const()[name = string("op_1603"), val = tensor<int32, [4]>([1, 4, 64, 16])];
            tensor<fp16, [1, 4, 64, 16]> y_13_cast_fp16 = reshape(shape = var_1603, x = input_tensor_269_cast_fp16)[name = string("y_13_cast_fp16")];
            tensor<int32, [4]> var_1615 = const()[name = string("op_1615"), val = tensor<int32, [4]>([1, 4, 64, 16])];
            tensor<fp16, [1, 4, 64, 16]> input_tensor_291_cast_fp16 = reshape(shape = var_1615, x = input_tensor_289_cast_fp16)[name = string("input_tensor_291_cast_fp16")];
            fp16 _inversed_x_69_y_0_to_fp16 = const()[name = string("_inversed_x_69_y_0_to_fp16"), val = fp16(0x1p-3)];
            tensor<fp16, [1, 4, 16, 64]> first_127_cast_fp16 = transpose(perm = var_1577, x = input_tensor_285_cast_fp16)[name = string("transpose_28")];
            tensor<fp16, [1, 4, 16, 64]> _inversed_x_69_cast_fp16 = mul(x = first_127_cast_fp16, y = _inversed_x_69_y_0_to_fp16)[name = string("_inversed_x_69_cast_fp16")];
            bool first_143_transpose_x_0 = const()[name = string("first_143_transpose_x_0"), val = bool(false)];
            bool first_143_transpose_y_0 = const()[name = string("first_143_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 4, 16, 16]> first_143_cast_fp16 = matmul(transpose_x = first_143_transpose_x_0, transpose_y = first_143_transpose_y_0, x = _inversed_x_69_cast_fp16, y = y_13_cast_fp16)[name = string("first_143_cast_fp16")];
            bool input_tensor_323_transpose_x_0 = const()[name = string("input_tensor_323_transpose_x_0"), val = bool(false)];
            bool input_tensor_323_transpose_y_0 = const()[name = string("input_tensor_323_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 64, 31]> y_15_to_fp16 = const()[name = string("y_15_to_fp16"), val = tensor<fp16, [1, 1, 64, 31]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12581312)))];
            tensor<fp16, [1, 4, 16, 31]> input_tensor_323_cast_fp16 = matmul(transpose_x = input_tensor_323_transpose_x_0, transpose_y = input_tensor_323_transpose_y_0, x = _inversed_x_69_cast_fp16, y = y_15_to_fp16)[name = string("input_tensor_323_cast_fp16")];
            tensor<int32, [8]> input_tensor_345_pad_0 = const()[name = string("input_tensor_345_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 1])];
            string input_tensor_345_mode_0 = const()[name = string("input_tensor_345_mode_0"), val = string("constant")];
            fp16 const_51_to_fp16 = const()[name = string("const_51_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 16, 32]> input_tensor_345_cast_fp16 = pad(constant_val = const_51_to_fp16, mode = input_tensor_345_mode_0, pad = input_tensor_345_pad_0, x = input_tensor_323_cast_fp16)[name = string("input_tensor_345_cast_fp16")];
            tensor<int32, [3]> var_1738 = const()[name = string("op_1738"), val = tensor<int32, [3]>([1, 4, 512])];
            tensor<fp16, [1, 4, 512]> input_97_cast_fp16 = reshape(shape = var_1738, x = input_tensor_345_cast_fp16)[name = string("input_97_cast_fp16")];
            tensor<int32, [6]> input_tensor_367_pad_0 = const()[name = string("input_tensor_367_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 0, 15])];
            string input_tensor_367_mode_0 = const()[name = string("input_tensor_367_mode_0"), val = string("constant")];
            fp16 const_52_to_fp16 = const()[name = string("const_52_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 527]> input_tensor_367_cast_fp16 = pad(constant_val = const_52_to_fp16, mode = input_tensor_367_mode_0, pad = input_tensor_367_pad_0, x = input_97_cast_fp16)[name = string("input_tensor_367_cast_fp16")];
            tensor<int32, [4]> var_1773 = const()[name = string("op_1773"), val = tensor<int32, [4]>([1, 4, 17, 31])];
            tensor<fp16, [1, 4, 17, 31]> x_85_cast_fp16 = reshape(shape = var_1773, x = input_tensor_367_cast_fp16)[name = string("x_85_cast_fp16")];
            tensor<int32, [4]> x_87_begin_0 = const()[name = string("x_87_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> x_87_end_0 = const()[name = string("x_87_end_0"), val = tensor<int32, [4]>([1, 4, 16, 31])];
            tensor<bool, [4]> x_87_end_mask_0 = const()[name = string("x_87_end_mask_0"), val = tensor<bool, [4]>([true, true, false, true])];
            tensor<fp16, [1, 4, 16, 31]> x_87_cast_fp16 = slice_by_index(begin = x_87_begin_0, end = x_87_end_0, end_mask = x_87_end_mask_0, x = x_85_cast_fp16)[name = string("x_87_cast_fp16")];
            tensor<int32, [4]> second_139_begin_0 = const()[name = string("second_139_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 15])];
            tensor<int32, [4]> second_139_end_0 = const()[name = string("second_139_end_0"), val = tensor<int32, [4]>([1, 4, 16, 1])];
            tensor<bool, [4]> second_139_end_mask_0 = const()[name = string("second_139_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 16, 16]> second_139_cast_fp16 = slice_by_index(begin = second_139_begin_0, end = second_139_end_0, end_mask = second_139_end_mask_0, x = x_87_cast_fp16)[name = string("second_139_cast_fp16")];
            tensor<fp16, [1, 4, 16, 16]> y_17_cast_fp16 = add(x = first_143_cast_fp16, y = second_139_cast_fp16)[name = string("y_17_cast_fp16")];
            tensor<fp16, [1, 4, 16, 16]> input_99_cast_fp16 = select(a = text_encoder_attn_encoder_attn_layers_0_Constant_88_value_after_broadcast_to_fp16, b = y_17_cast_fp16, cond = condition_1_after_broadcast)[name = string("input_99_cast_fp16")];
            int32 var_1815 = const()[name = string("op_1815"), val = int32(-1)];
            tensor<fp16, [1, 4, 16, 16]> x_91_cast_fp16 = softmax(axis = var_1815, x = input_99_cast_fp16)[name = string("x_91_cast_fp16")];
            bool first_155_transpose_x_1 = const()[name = string("first_155_transpose_x_1"), val = bool(false)];
            bool first_155_transpose_y_1 = const()[name = string("first_155_transpose_y_1"), val = bool(true)];
            tensor<fp16, [1, 4, 16, 64]> first_155_cast_fp16 = matmul(transpose_x = first_155_transpose_x_1, transpose_y = first_155_transpose_y_1, x = x_91_cast_fp16, y = input_tensor_291_cast_fp16)[name = string("first_155_cast_fp16")];
            tensor<int32, [8]> input_tensor_397_pad_0 = const()[name = string("input_tensor_397_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 15])];
            string input_tensor_397_mode_0 = const()[name = string("input_tensor_397_mode_0"), val = string("constant")];
            fp16 const_59_to_fp16 = const()[name = string("const_59_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 16, 31]> input_tensor_397_cast_fp16 = pad(constant_val = const_59_to_fp16, mode = input_tensor_397_mode_0, pad = input_tensor_397_pad_0, x = x_91_cast_fp16)[name = string("input_tensor_397_cast_fp16")];
            tensor<int32, [3]> var_1889 = const()[name = string("op_1889"), val = tensor<int32, [3]>([1, 4, 496])];
            tensor<fp16, [1, 4, 496]> input_101_cast_fp16 = reshape(shape = var_1889, x = input_tensor_397_cast_fp16)[name = string("input_101_cast_fp16")];
            tensor<int32, [6]> input_tensor_415_pad_0 = const()[name = string("input_tensor_415_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 16, 0])];
            string input_tensor_415_mode_0 = const()[name = string("input_tensor_415_mode_0"), val = string("constant")];
            fp16 const_60_to_fp16 = const()[name = string("const_60_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 512]> input_tensor_415_cast_fp16 = pad(constant_val = const_60_to_fp16, mode = input_tensor_415_mode_0, pad = input_tensor_415_pad_0, x = input_101_cast_fp16)[name = string("input_tensor_415_cast_fp16")];
            tensor<int32, [4]> var_1919 = const()[name = string("op_1919"), val = tensor<int32, [4]>([1, 4, 16, 32])];
            tensor<fp16, [1, 4, 16, 32]> x_101_cast_fp16 = reshape(shape = var_1919, x = input_tensor_415_cast_fp16)[name = string("x_101_cast_fp16")];
            tensor<int32, [4]> x_109_begin_0 = const()[name = string("x_109_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 1])];
            tensor<int32, [4]> x_109_end_0 = const()[name = string("x_109_end_0"), val = tensor<int32, [4]>([1, 4, 16, 1])];
            tensor<bool, [4]> x_109_end_mask_0 = const()[name = string("x_109_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 16, 31]> x_109_cast_fp16 = slice_by_index(begin = x_109_begin_0, end = x_109_end_0, end_mask = x_109_end_mask_0, x = x_101_cast_fp16)[name = string("x_109_cast_fp16")];
            bool second_153_transpose_x_0 = const()[name = string("second_153_transpose_x_0"), val = bool(false)];
            bool second_153_transpose_y_0 = const()[name = string("second_153_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 31, 64]> y_21_to_fp16 = const()[name = string("y_21_to_fp16"), val = tensor<fp16, [1, 1, 31, 64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12585344)))];
            tensor<fp16, [1, 4, 16, 64]> second_153_cast_fp16 = matmul(transpose_x = second_153_transpose_x_0, transpose_y = second_153_transpose_y_0, x = x_109_cast_fp16, y = y_21_to_fp16)[name = string("second_153_cast_fp16")];
            tensor<fp16, [1, 4, 16, 64]> input_tensor_433_cast_fp16 = add(x = first_155_cast_fp16, y = second_153_cast_fp16)[name = string("input_tensor_433_cast_fp16")];
            tensor<int32, [4]> var_1966 = const()[name = string("op_1966"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [3]> var_1985 = const()[name = string("op_1985"), val = tensor<int32, [3]>([1, 256, 16])];
            tensor<fp16, [1, 4, 64, 16]> input_tensor_437_cast_fp16 = transpose(perm = var_1966, x = input_tensor_433_cast_fp16)[name = string("transpose_27")];
            tensor<fp16, [1, 256, 16]> input_105_cast_fp16 = reshape(shape = var_1985, x = input_tensor_437_cast_fp16)[name = string("input_105_cast_fp16")];
            string second_155_pad_type_0 = const()[name = string("second_155_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_155_strides_0 = const()[name = string("second_155_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_155_pad_0 = const()[name = string("second_155_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_155_dilations_0 = const()[name = string("second_155_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_155_groups_0 = const()[name = string("second_155_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_1_conv_o_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_o_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12589376)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_1_conv_o_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_o_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12720512)))];
            tensor<fp16, [1, 256, 16]> second_155_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_1_conv_o_Conv_bias_to_fp16, dilations = second_155_dilations_0, groups = second_155_groups_0, pad = second_155_pad_0, pad_type = second_155_pad_type_0, strides = second_155_strides_0, weight = text_encoder_attn_encoder_attn_layers_1_conv_o_Conv_weight_to_fp16, x = input_105_cast_fp16)[name = string("second_155_cast_fp16")];
            tensor<fp16, [1, 256, 16]> input_tensor_439_cast_fp16 = add(x = input_89_cast_fp16, y = second_155_cast_fp16)[name = string("input_tensor_439_cast_fp16")];
            tensor<int32, [3]> var_2003 = const()[name = string("op_2003"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_441_axes_0 = const()[name = string("input_tensor_441_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_1_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_1_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12721088)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_1_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_1_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12721664)))];
            fp16 var_2006_to_fp16 = const()[name = string("op_2006_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 16, 256]> input_107_cast_fp16 = transpose(perm = var_2003, x = input_tensor_439_cast_fp16)[name = string("transpose_26")];
            tensor<fp16, [1, 16, 256]> input_tensor_441_cast_fp16 = layer_norm(axes = input_tensor_441_axes_0, beta = text_encoder_attn_encoder_norm_layers_1_1_norm_LayerNormalization_bias_to_fp16, epsilon = var_2006_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_1_1_norm_LayerNormalization_weight_to_fp16, x = input_107_cast_fp16)[name = string("input_tensor_441_cast_fp16")];
            tensor<int32, [3]> var_2015 = const()[name = string("op_2015"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 256, 16]> first_157_cast_fp16 = transpose(perm = var_2015, x = input_tensor_441_cast_fp16)[name = string("transpose_25")];
            tensor<fp16, [1, 256, 16]> input_109_cast_fp16 = mul(x = first_157_cast_fp16, y = text_mask)[name = string("input_109_cast_fp16")];
            string input_111_pad_type_0 = const()[name = string("input_111_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_111_strides_0 = const()[name = string("input_111_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_111_pad_0 = const()[name = string("input_111_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_111_dilations_0 = const()[name = string("input_111_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_111_groups_0 = const()[name = string("input_111_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_attn_encoder_ffn_layers_1_conv_1_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_1_conv_1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12722240)))];
            tensor<fp16, [1024]> text_encoder_attn_encoder_ffn_layers_1_conv_1_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_1_conv_1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13246592)))];
            tensor<fp16, [1, 1024, 16]> input_111_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_1_conv_1_Conv_bias_to_fp16, dilations = input_111_dilations_0, groups = input_111_groups_0, pad = input_111_pad_0, pad_type = input_111_pad_type_0, strides = input_111_strides_0, weight = text_encoder_attn_encoder_ffn_layers_1_conv_1_Conv_weight_to_fp16, x = input_109_cast_fp16)[name = string("input_111_cast_fp16")];
            tensor<fp16, [1, 1024, 16]> first_159_cast_fp16 = relu(x = input_111_cast_fp16)[name = string("first_159_cast_fp16")];
            tensor<fp16, [1, 1024, 16]> input_113_cast_fp16 = mul(x = first_159_cast_fp16, y = text_mask)[name = string("input_113_cast_fp16")];
            string first_161_pad_type_0 = const()[name = string("first_161_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_161_strides_0 = const()[name = string("first_161_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_161_pad_0 = const()[name = string("first_161_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_161_dilations_0 = const()[name = string("first_161_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_161_groups_0 = const()[name = string("first_161_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> text_encoder_attn_encoder_ffn_layers_1_conv_2_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_1_conv_2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13248704)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_ffn_layers_1_conv_2_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_1_conv_2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13773056)))];
            tensor<fp16, [1, 256, 16]> first_161_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_1_conv_2_Conv_bias_to_fp16, dilations = first_161_dilations_0, groups = first_161_groups_0, pad = first_161_pad_0, pad_type = first_161_pad_type_0, strides = first_161_strides_0, weight = text_encoder_attn_encoder_ffn_layers_1_conv_2_Conv_weight_to_fp16, x = input_113_cast_fp16)[name = string("first_161_cast_fp16")];
            tensor<fp16, [1, 256, 16]> second_157_cast_fp16 = mul(x = first_161_cast_fp16, y = text_mask)[name = string("second_157_cast_fp16")];
            tensor<fp16, [1, 256, 16]> input_tensor_443_cast_fp16 = add(x = first_157_cast_fp16, y = second_157_cast_fp16)[name = string("input_tensor_443_cast_fp16")];
            tensor<int32, [3]> var_2048 = const()[name = string("op_2048"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_445_axes_0 = const()[name = string("input_tensor_445_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_1_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_1_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13773632)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_1_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_1_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13774208)))];
            fp16 var_2051_to_fp16 = const()[name = string("op_2051_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 16, 256]> input_115_cast_fp16 = transpose(perm = var_2048, x = input_tensor_443_cast_fp16)[name = string("transpose_24")];
            tensor<fp16, [1, 16, 256]> input_tensor_445_cast_fp16 = layer_norm(axes = input_tensor_445_axes_0, beta = text_encoder_attn_encoder_norm_layers_2_1_norm_LayerNormalization_bias_to_fp16, epsilon = var_2051_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_2_1_norm_LayerNormalization_weight_to_fp16, x = input_115_cast_fp16)[name = string("input_tensor_445_cast_fp16")];
            tensor<int32, [3]> var_2060 = const()[name = string("op_2060"), val = tensor<int32, [3]>([0, 2, 1])];
            string input_tensor_455_pad_type_0 = const()[name = string("input_tensor_455_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_455_strides_0 = const()[name = string("input_tensor_455_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_455_pad_0 = const()[name = string("input_tensor_455_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_455_dilations_0 = const()[name = string("input_tensor_455_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_455_groups_0 = const()[name = string("input_tensor_455_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_2_conv_q_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_q_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13774784)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_2_conv_q_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_q_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13905920)))];
            tensor<fp16, [1, 256, 16]> input_117_cast_fp16 = transpose(perm = var_2060, x = input_tensor_445_cast_fp16)[name = string("transpose_23")];
            tensor<fp16, [1, 256, 16]> input_tensor_455_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_2_conv_q_Conv_bias_to_fp16, dilations = input_tensor_455_dilations_0, groups = input_tensor_455_groups_0, pad = input_tensor_455_pad_0, pad_type = input_tensor_455_pad_type_0, strides = input_tensor_455_strides_0, weight = text_encoder_attn_encoder_attn_layers_2_conv_q_Conv_weight_to_fp16, x = input_117_cast_fp16)[name = string("input_tensor_455_cast_fp16")];
            string input_tensor_447_pad_type_0 = const()[name = string("input_tensor_447_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_447_strides_0 = const()[name = string("input_tensor_447_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_447_pad_0 = const()[name = string("input_tensor_447_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_447_dilations_0 = const()[name = string("input_tensor_447_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_447_groups_0 = const()[name = string("input_tensor_447_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_2_conv_k_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_k_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13906496)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_2_conv_k_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_k_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14037632)))];
            tensor<fp16, [1, 256, 16]> input_tensor_447_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_2_conv_k_Conv_bias_to_fp16, dilations = input_tensor_447_dilations_0, groups = input_tensor_447_groups_0, pad = input_tensor_447_pad_0, pad_type = input_tensor_447_pad_type_0, strides = input_tensor_447_strides_0, weight = text_encoder_attn_encoder_attn_layers_2_conv_k_Conv_weight_to_fp16, x = input_117_cast_fp16)[name = string("input_tensor_447_cast_fp16")];
            string input_tensor_467_pad_type_0 = const()[name = string("input_tensor_467_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_467_strides_0 = const()[name = string("input_tensor_467_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_467_pad_0 = const()[name = string("input_tensor_467_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_467_dilations_0 = const()[name = string("input_tensor_467_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_467_groups_0 = const()[name = string("input_tensor_467_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_2_conv_v_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_v_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14038208)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_2_conv_v_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_v_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14169344)))];
            tensor<fp16, [1, 256, 16]> input_tensor_467_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_2_conv_v_Conv_bias_to_fp16, dilations = input_tensor_467_dilations_0, groups = input_tensor_467_groups_0, pad = input_tensor_467_pad_0, pad_type = input_tensor_467_pad_type_0, strides = input_tensor_467_strides_0, weight = text_encoder_attn_encoder_attn_layers_2_conv_v_Conv_weight_to_fp16, x = input_117_cast_fp16)[name = string("input_tensor_467_cast_fp16")];
            tensor<int32, [4]> var_2168 = const()[name = string("op_2168"), val = tensor<int32, [4]>([1, 4, 64, 16])];
            tensor<fp16, [1, 4, 64, 16]> input_tensor_463_cast_fp16 = reshape(shape = var_2168, x = input_tensor_455_cast_fp16)[name = string("input_tensor_463_cast_fp16")];
            tensor<int32, [4]> var_2174 = const()[name = string("op_2174"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [4]> var_2200 = const()[name = string("op_2200"), val = tensor<int32, [4]>([1, 4, 64, 16])];
            tensor<fp16, [1, 4, 64, 16]> y_23_cast_fp16 = reshape(shape = var_2200, x = input_tensor_447_cast_fp16)[name = string("y_23_cast_fp16")];
            tensor<int32, [4]> var_2212 = const()[name = string("op_2212"), val = tensor<int32, [4]>([1, 4, 64, 16])];
            tensor<fp16, [1, 4, 64, 16]> input_tensor_469_cast_fp16 = reshape(shape = var_2212, x = input_tensor_467_cast_fp16)[name = string("input_tensor_469_cast_fp16")];
            fp16 _inversed_x_111_y_0_to_fp16 = const()[name = string("_inversed_x_111_y_0_to_fp16"), val = fp16(0x1p-3)];
            tensor<fp16, [1, 4, 16, 64]> first_163_cast_fp16 = transpose(perm = var_2174, x = input_tensor_463_cast_fp16)[name = string("transpose_22")];
            tensor<fp16, [1, 4, 16, 64]> _inversed_x_111_cast_fp16 = mul(x = first_163_cast_fp16, y = _inversed_x_111_y_0_to_fp16)[name = string("_inversed_x_111_cast_fp16")];
            bool first_179_transpose_x_0 = const()[name = string("first_179_transpose_x_0"), val = bool(false)];
            bool first_179_transpose_y_0 = const()[name = string("first_179_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 4, 16, 16]> first_179_cast_fp16 = matmul(transpose_x = first_179_transpose_x_0, transpose_y = first_179_transpose_y_0, x = _inversed_x_111_cast_fp16, y = y_23_cast_fp16)[name = string("first_179_cast_fp16")];
            bool input_tensor_501_transpose_x_0 = const()[name = string("input_tensor_501_transpose_x_0"), val = bool(false)];
            bool input_tensor_501_transpose_y_0 = const()[name = string("input_tensor_501_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 64, 31]> y_25_to_fp16 = const()[name = string("y_25_to_fp16"), val = tensor<fp16, [1, 1, 64, 31]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14169920)))];
            tensor<fp16, [1, 4, 16, 31]> input_tensor_501_cast_fp16 = matmul(transpose_x = input_tensor_501_transpose_x_0, transpose_y = input_tensor_501_transpose_y_0, x = _inversed_x_111_cast_fp16, y = y_25_to_fp16)[name = string("input_tensor_501_cast_fp16")];
            tensor<int32, [8]> input_tensor_523_pad_0 = const()[name = string("input_tensor_523_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 1])];
            string input_tensor_523_mode_0 = const()[name = string("input_tensor_523_mode_0"), val = string("constant")];
            fp16 const_79_to_fp16 = const()[name = string("const_79_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 16, 32]> input_tensor_523_cast_fp16 = pad(constant_val = const_79_to_fp16, mode = input_tensor_523_mode_0, pad = input_tensor_523_pad_0, x = input_tensor_501_cast_fp16)[name = string("input_tensor_523_cast_fp16")];
            tensor<int32, [3]> var_2335 = const()[name = string("op_2335"), val = tensor<int32, [3]>([1, 4, 512])];
            tensor<fp16, [1, 4, 512]> input_125_cast_fp16 = reshape(shape = var_2335, x = input_tensor_523_cast_fp16)[name = string("input_125_cast_fp16")];
            tensor<int32, [6]> input_tensor_545_pad_0 = const()[name = string("input_tensor_545_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 0, 15])];
            string input_tensor_545_mode_0 = const()[name = string("input_tensor_545_mode_0"), val = string("constant")];
            fp16 const_80_to_fp16 = const()[name = string("const_80_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 527]> input_tensor_545_cast_fp16 = pad(constant_val = const_80_to_fp16, mode = input_tensor_545_mode_0, pad = input_tensor_545_pad_0, x = input_125_cast_fp16)[name = string("input_tensor_545_cast_fp16")];
            tensor<int32, [4]> var_2370 = const()[name = string("op_2370"), val = tensor<int32, [4]>([1, 4, 17, 31])];
            tensor<fp16, [1, 4, 17, 31]> x_127_cast_fp16 = reshape(shape = var_2370, x = input_tensor_545_cast_fp16)[name = string("x_127_cast_fp16")];
            tensor<int32, [4]> x_129_begin_0 = const()[name = string("x_129_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> x_129_end_0 = const()[name = string("x_129_end_0"), val = tensor<int32, [4]>([1, 4, 16, 31])];
            tensor<bool, [4]> x_129_end_mask_0 = const()[name = string("x_129_end_mask_0"), val = tensor<bool, [4]>([true, true, false, true])];
            tensor<fp16, [1, 4, 16, 31]> x_129_cast_fp16 = slice_by_index(begin = x_129_begin_0, end = x_129_end_0, end_mask = x_129_end_mask_0, x = x_127_cast_fp16)[name = string("x_129_cast_fp16")];
            tensor<int32, [4]> second_181_begin_0 = const()[name = string("second_181_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 15])];
            tensor<int32, [4]> second_181_end_0 = const()[name = string("second_181_end_0"), val = tensor<int32, [4]>([1, 4, 16, 1])];
            tensor<bool, [4]> second_181_end_mask_0 = const()[name = string("second_181_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 16, 16]> second_181_cast_fp16 = slice_by_index(begin = second_181_begin_0, end = second_181_end_0, end_mask = second_181_end_mask_0, x = x_129_cast_fp16)[name = string("second_181_cast_fp16")];
            tensor<fp16, [1, 4, 16, 16]> y_27_cast_fp16 = add(x = first_179_cast_fp16, y = second_181_cast_fp16)[name = string("y_27_cast_fp16")];
            tensor<fp16, [1, 4, 16, 16]> input_127_cast_fp16 = select(a = text_encoder_attn_encoder_attn_layers_0_Constant_88_value_after_broadcast_to_fp16, b = y_27_cast_fp16, cond = condition_1_after_broadcast)[name = string("input_127_cast_fp16")];
            int32 var_2412 = const()[name = string("op_2412"), val = int32(-1)];
            tensor<fp16, [1, 4, 16, 16]> x_133_cast_fp16 = softmax(axis = var_2412, x = input_127_cast_fp16)[name = string("x_133_cast_fp16")];
            bool first_191_transpose_x_1 = const()[name = string("first_191_transpose_x_1"), val = bool(false)];
            bool first_191_transpose_y_1 = const()[name = string("first_191_transpose_y_1"), val = bool(true)];
            tensor<fp16, [1, 4, 16, 64]> first_191_cast_fp16 = matmul(transpose_x = first_191_transpose_x_1, transpose_y = first_191_transpose_y_1, x = x_133_cast_fp16, y = input_tensor_469_cast_fp16)[name = string("first_191_cast_fp16")];
            tensor<int32, [8]> input_tensor_575_pad_0 = const()[name = string("input_tensor_575_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 15])];
            string input_tensor_575_mode_0 = const()[name = string("input_tensor_575_mode_0"), val = string("constant")];
            fp16 const_87_to_fp16 = const()[name = string("const_87_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 16, 31]> input_tensor_575_cast_fp16 = pad(constant_val = const_87_to_fp16, mode = input_tensor_575_mode_0, pad = input_tensor_575_pad_0, x = x_133_cast_fp16)[name = string("input_tensor_575_cast_fp16")];
            tensor<int32, [3]> var_2486 = const()[name = string("op_2486"), val = tensor<int32, [3]>([1, 4, 496])];
            tensor<fp16, [1, 4, 496]> input_129_cast_fp16 = reshape(shape = var_2486, x = input_tensor_575_cast_fp16)[name = string("input_129_cast_fp16")];
            tensor<int32, [6]> input_tensor_593_pad_0 = const()[name = string("input_tensor_593_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 16, 0])];
            string input_tensor_593_mode_0 = const()[name = string("input_tensor_593_mode_0"), val = string("constant")];
            fp16 const_88_to_fp16 = const()[name = string("const_88_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 512]> input_tensor_593_cast_fp16 = pad(constant_val = const_88_to_fp16, mode = input_tensor_593_mode_0, pad = input_tensor_593_pad_0, x = input_129_cast_fp16)[name = string("input_tensor_593_cast_fp16")];
            tensor<int32, [4]> var_2516 = const()[name = string("op_2516"), val = tensor<int32, [4]>([1, 4, 16, 32])];
            tensor<fp16, [1, 4, 16, 32]> x_143_cast_fp16 = reshape(shape = var_2516, x = input_tensor_593_cast_fp16)[name = string("x_143_cast_fp16")];
            tensor<int32, [4]> x_151_begin_0 = const()[name = string("x_151_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 1])];
            tensor<int32, [4]> x_151_end_0 = const()[name = string("x_151_end_0"), val = tensor<int32, [4]>([1, 4, 16, 1])];
            tensor<bool, [4]> x_151_end_mask_0 = const()[name = string("x_151_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 16, 31]> x_151_cast_fp16 = slice_by_index(begin = x_151_begin_0, end = x_151_end_0, end_mask = x_151_end_mask_0, x = x_143_cast_fp16)[name = string("x_151_cast_fp16")];
            bool second_195_transpose_x_0 = const()[name = string("second_195_transpose_x_0"), val = bool(false)];
            bool second_195_transpose_y_0 = const()[name = string("second_195_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 31, 64]> y_31_to_fp16 = const()[name = string("y_31_to_fp16"), val = tensor<fp16, [1, 1, 31, 64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14173952)))];
            tensor<fp16, [1, 4, 16, 64]> second_195_cast_fp16 = matmul(transpose_x = second_195_transpose_x_0, transpose_y = second_195_transpose_y_0, x = x_151_cast_fp16, y = y_31_to_fp16)[name = string("second_195_cast_fp16")];
            tensor<fp16, [1, 4, 16, 64]> input_tensor_611_cast_fp16 = add(x = first_191_cast_fp16, y = second_195_cast_fp16)[name = string("input_tensor_611_cast_fp16")];
            tensor<int32, [4]> var_2563 = const()[name = string("op_2563"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [3]> var_2582 = const()[name = string("op_2582"), val = tensor<int32, [3]>([1, 256, 16])];
            tensor<fp16, [1, 4, 64, 16]> input_tensor_615_cast_fp16 = transpose(perm = var_2563, x = input_tensor_611_cast_fp16)[name = string("transpose_21")];
            tensor<fp16, [1, 256, 16]> input_133_cast_fp16 = reshape(shape = var_2582, x = input_tensor_615_cast_fp16)[name = string("input_133_cast_fp16")];
            string second_197_pad_type_0 = const()[name = string("second_197_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_197_strides_0 = const()[name = string("second_197_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_197_pad_0 = const()[name = string("second_197_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_197_dilations_0 = const()[name = string("second_197_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_197_groups_0 = const()[name = string("second_197_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_2_conv_o_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_o_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14177984)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_2_conv_o_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_o_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14309120)))];
            tensor<fp16, [1, 256, 16]> second_197_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_2_conv_o_Conv_bias_to_fp16, dilations = second_197_dilations_0, groups = second_197_groups_0, pad = second_197_pad_0, pad_type = second_197_pad_type_0, strides = second_197_strides_0, weight = text_encoder_attn_encoder_attn_layers_2_conv_o_Conv_weight_to_fp16, x = input_133_cast_fp16)[name = string("second_197_cast_fp16")];
            tensor<fp16, [1, 256, 16]> input_tensor_617_cast_fp16 = add(x = input_117_cast_fp16, y = second_197_cast_fp16)[name = string("input_tensor_617_cast_fp16")];
            tensor<int32, [3]> var_2600 = const()[name = string("op_2600"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_619_axes_0 = const()[name = string("input_tensor_619_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_2_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_2_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14309696)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_2_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_2_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14310272)))];
            fp16 var_2603_to_fp16 = const()[name = string("op_2603_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 16, 256]> input_135_cast_fp16 = transpose(perm = var_2600, x = input_tensor_617_cast_fp16)[name = string("transpose_20")];
            tensor<fp16, [1, 16, 256]> input_tensor_619_cast_fp16 = layer_norm(axes = input_tensor_619_axes_0, beta = text_encoder_attn_encoder_norm_layers_1_2_norm_LayerNormalization_bias_to_fp16, epsilon = var_2603_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_1_2_norm_LayerNormalization_weight_to_fp16, x = input_135_cast_fp16)[name = string("input_tensor_619_cast_fp16")];
            tensor<int32, [3]> var_2612 = const()[name = string("op_2612"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 256, 16]> first_193_cast_fp16 = transpose(perm = var_2612, x = input_tensor_619_cast_fp16)[name = string("transpose_19")];
            tensor<fp16, [1, 256, 16]> input_137_cast_fp16 = mul(x = first_193_cast_fp16, y = text_mask)[name = string("input_137_cast_fp16")];
            string input_139_pad_type_0 = const()[name = string("input_139_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_139_strides_0 = const()[name = string("input_139_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_139_pad_0 = const()[name = string("input_139_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_139_dilations_0 = const()[name = string("input_139_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_139_groups_0 = const()[name = string("input_139_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_attn_encoder_ffn_layers_2_conv_1_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_2_conv_1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14310848)))];
            tensor<fp16, [1024]> text_encoder_attn_encoder_ffn_layers_2_conv_1_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_2_conv_1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14835200)))];
            tensor<fp16, [1, 1024, 16]> input_139_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_2_conv_1_Conv_bias_to_fp16, dilations = input_139_dilations_0, groups = input_139_groups_0, pad = input_139_pad_0, pad_type = input_139_pad_type_0, strides = input_139_strides_0, weight = text_encoder_attn_encoder_ffn_layers_2_conv_1_Conv_weight_to_fp16, x = input_137_cast_fp16)[name = string("input_139_cast_fp16")];
            tensor<fp16, [1, 1024, 16]> first_195_cast_fp16 = relu(x = input_139_cast_fp16)[name = string("first_195_cast_fp16")];
            tensor<fp16, [1, 1024, 16]> input_141_cast_fp16 = mul(x = first_195_cast_fp16, y = text_mask)[name = string("input_141_cast_fp16")];
            string first_197_pad_type_0 = const()[name = string("first_197_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_197_strides_0 = const()[name = string("first_197_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_197_pad_0 = const()[name = string("first_197_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_197_dilations_0 = const()[name = string("first_197_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_197_groups_0 = const()[name = string("first_197_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> text_encoder_attn_encoder_ffn_layers_2_conv_2_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_2_conv_2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14837312)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_ffn_layers_2_conv_2_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_2_conv_2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15361664)))];
            tensor<fp16, [1, 256, 16]> first_197_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_2_conv_2_Conv_bias_to_fp16, dilations = first_197_dilations_0, groups = first_197_groups_0, pad = first_197_pad_0, pad_type = first_197_pad_type_0, strides = first_197_strides_0, weight = text_encoder_attn_encoder_ffn_layers_2_conv_2_Conv_weight_to_fp16, x = input_141_cast_fp16)[name = string("first_197_cast_fp16")];
            tensor<fp16, [1, 256, 16]> second_199_cast_fp16 = mul(x = first_197_cast_fp16, y = text_mask)[name = string("second_199_cast_fp16")];
            tensor<fp16, [1, 256, 16]> input_tensor_621_cast_fp16 = add(x = first_193_cast_fp16, y = second_199_cast_fp16)[name = string("input_tensor_621_cast_fp16")];
            tensor<int32, [3]> var_2645 = const()[name = string("op_2645"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_623_axes_0 = const()[name = string("input_tensor_623_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_2_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_2_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15362240)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_2_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_2_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15362816)))];
            fp16 var_2648_to_fp16 = const()[name = string("op_2648_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 16, 256]> input_143_cast_fp16 = transpose(perm = var_2645, x = input_tensor_621_cast_fp16)[name = string("transpose_18")];
            tensor<fp16, [1, 16, 256]> input_tensor_623_cast_fp16 = layer_norm(axes = input_tensor_623_axes_0, beta = text_encoder_attn_encoder_norm_layers_2_2_norm_LayerNormalization_bias_to_fp16, epsilon = var_2648_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_2_2_norm_LayerNormalization_weight_to_fp16, x = input_143_cast_fp16)[name = string("input_tensor_623_cast_fp16")];
            tensor<int32, [3]> var_2657 = const()[name = string("op_2657"), val = tensor<int32, [3]>([0, 2, 1])];
            string input_tensor_633_pad_type_0 = const()[name = string("input_tensor_633_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_633_strides_0 = const()[name = string("input_tensor_633_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_633_pad_0 = const()[name = string("input_tensor_633_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_633_dilations_0 = const()[name = string("input_tensor_633_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_633_groups_0 = const()[name = string("input_tensor_633_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_3_conv_q_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_q_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15363392)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_3_conv_q_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_q_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15494528)))];
            tensor<fp16, [1, 256, 16]> input_145_cast_fp16 = transpose(perm = var_2657, x = input_tensor_623_cast_fp16)[name = string("transpose_17")];
            tensor<fp16, [1, 256, 16]> input_tensor_633_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_3_conv_q_Conv_bias_to_fp16, dilations = input_tensor_633_dilations_0, groups = input_tensor_633_groups_0, pad = input_tensor_633_pad_0, pad_type = input_tensor_633_pad_type_0, strides = input_tensor_633_strides_0, weight = text_encoder_attn_encoder_attn_layers_3_conv_q_Conv_weight_to_fp16, x = input_145_cast_fp16)[name = string("input_tensor_633_cast_fp16")];
            string input_tensor_625_pad_type_0 = const()[name = string("input_tensor_625_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_625_strides_0 = const()[name = string("input_tensor_625_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_625_pad_0 = const()[name = string("input_tensor_625_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_625_dilations_0 = const()[name = string("input_tensor_625_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_625_groups_0 = const()[name = string("input_tensor_625_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_3_conv_k_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_k_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15495104)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_3_conv_k_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_k_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15626240)))];
            tensor<fp16, [1, 256, 16]> input_tensor_625_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_3_conv_k_Conv_bias_to_fp16, dilations = input_tensor_625_dilations_0, groups = input_tensor_625_groups_0, pad = input_tensor_625_pad_0, pad_type = input_tensor_625_pad_type_0, strides = input_tensor_625_strides_0, weight = text_encoder_attn_encoder_attn_layers_3_conv_k_Conv_weight_to_fp16, x = input_145_cast_fp16)[name = string("input_tensor_625_cast_fp16")];
            string input_tensor_645_pad_type_0 = const()[name = string("input_tensor_645_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_645_strides_0 = const()[name = string("input_tensor_645_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_645_pad_0 = const()[name = string("input_tensor_645_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_645_dilations_0 = const()[name = string("input_tensor_645_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_645_groups_0 = const()[name = string("input_tensor_645_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_3_conv_v_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_v_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15626816)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_3_conv_v_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_v_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15757952)))];
            tensor<fp16, [1, 256, 16]> input_tensor_645_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_3_conv_v_Conv_bias_to_fp16, dilations = input_tensor_645_dilations_0, groups = input_tensor_645_groups_0, pad = input_tensor_645_pad_0, pad_type = input_tensor_645_pad_type_0, strides = input_tensor_645_strides_0, weight = text_encoder_attn_encoder_attn_layers_3_conv_v_Conv_weight_to_fp16, x = input_145_cast_fp16)[name = string("input_tensor_645_cast_fp16")];
            tensor<int32, [4]> var_2765 = const()[name = string("op_2765"), val = tensor<int32, [4]>([1, 4, 64, 16])];
            tensor<fp16, [1, 4, 64, 16]> input_tensor_641_cast_fp16 = reshape(shape = var_2765, x = input_tensor_633_cast_fp16)[name = string("input_tensor_641_cast_fp16")];
            tensor<int32, [4]> var_2771 = const()[name = string("op_2771"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [4]> var_2797 = const()[name = string("op_2797"), val = tensor<int32, [4]>([1, 4, 64, 16])];
            tensor<fp16, [1, 4, 64, 16]> y_33_cast_fp16 = reshape(shape = var_2797, x = input_tensor_625_cast_fp16)[name = string("y_33_cast_fp16")];
            tensor<int32, [4]> var_2809 = const()[name = string("op_2809"), val = tensor<int32, [4]>([1, 4, 64, 16])];
            tensor<fp16, [1, 4, 64, 16]> input_tensor_647_cast_fp16 = reshape(shape = var_2809, x = input_tensor_645_cast_fp16)[name = string("input_tensor_647_cast_fp16")];
            fp16 _inversed_x_153_y_0_to_fp16 = const()[name = string("_inversed_x_153_y_0_to_fp16"), val = fp16(0x1p-3)];
            tensor<fp16, [1, 4, 16, 64]> first_199_cast_fp16 = transpose(perm = var_2771, x = input_tensor_641_cast_fp16)[name = string("transpose_16")];
            tensor<fp16, [1, 4, 16, 64]> _inversed_x_153_cast_fp16 = mul(x = first_199_cast_fp16, y = _inversed_x_153_y_0_to_fp16)[name = string("_inversed_x_153_cast_fp16")];
            bool first_215_transpose_x_0 = const()[name = string("first_215_transpose_x_0"), val = bool(false)];
            bool first_215_transpose_y_0 = const()[name = string("first_215_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 4, 16, 16]> first_215_cast_fp16 = matmul(transpose_x = first_215_transpose_x_0, transpose_y = first_215_transpose_y_0, x = _inversed_x_153_cast_fp16, y = y_33_cast_fp16)[name = string("first_215_cast_fp16")];
            bool input_tensor_679_transpose_x_0 = const()[name = string("input_tensor_679_transpose_x_0"), val = bool(false)];
            bool input_tensor_679_transpose_y_0 = const()[name = string("input_tensor_679_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 64, 31]> y_35_to_fp16 = const()[name = string("y_35_to_fp16"), val = tensor<fp16, [1, 1, 64, 31]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15758528)))];
            tensor<fp16, [1, 4, 16, 31]> input_tensor_679_cast_fp16 = matmul(transpose_x = input_tensor_679_transpose_x_0, transpose_y = input_tensor_679_transpose_y_0, x = _inversed_x_153_cast_fp16, y = y_35_to_fp16)[name = string("input_tensor_679_cast_fp16")];
            tensor<int32, [8]> input_tensor_701_pad_0 = const()[name = string("input_tensor_701_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 1])];
            string input_tensor_701_mode_0 = const()[name = string("input_tensor_701_mode_0"), val = string("constant")];
            fp16 const_107_to_fp16 = const()[name = string("const_107_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 16, 32]> input_tensor_701_cast_fp16 = pad(constant_val = const_107_to_fp16, mode = input_tensor_701_mode_0, pad = input_tensor_701_pad_0, x = input_tensor_679_cast_fp16)[name = string("input_tensor_701_cast_fp16")];
            tensor<int32, [3]> var_2932 = const()[name = string("op_2932"), val = tensor<int32, [3]>([1, 4, 512])];
            tensor<fp16, [1, 4, 512]> input_153_cast_fp16 = reshape(shape = var_2932, x = input_tensor_701_cast_fp16)[name = string("input_153_cast_fp16")];
            tensor<int32, [6]> input_tensor_723_pad_0 = const()[name = string("input_tensor_723_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 0, 15])];
            string input_tensor_723_mode_0 = const()[name = string("input_tensor_723_mode_0"), val = string("constant")];
            fp16 const_108_to_fp16 = const()[name = string("const_108_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 527]> input_tensor_723_cast_fp16 = pad(constant_val = const_108_to_fp16, mode = input_tensor_723_mode_0, pad = input_tensor_723_pad_0, x = input_153_cast_fp16)[name = string("input_tensor_723_cast_fp16")];
            tensor<int32, [4]> var_2967 = const()[name = string("op_2967"), val = tensor<int32, [4]>([1, 4, 17, 31])];
            tensor<fp16, [1, 4, 17, 31]> x_169_cast_fp16 = reshape(shape = var_2967, x = input_tensor_723_cast_fp16)[name = string("x_169_cast_fp16")];
            tensor<int32, [4]> x_171_begin_0 = const()[name = string("x_171_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> x_171_end_0 = const()[name = string("x_171_end_0"), val = tensor<int32, [4]>([1, 4, 16, 31])];
            tensor<bool, [4]> x_171_end_mask_0 = const()[name = string("x_171_end_mask_0"), val = tensor<bool, [4]>([true, true, false, true])];
            tensor<fp16, [1, 4, 16, 31]> x_171_cast_fp16 = slice_by_index(begin = x_171_begin_0, end = x_171_end_0, end_mask = x_171_end_mask_0, x = x_169_cast_fp16)[name = string("x_171_cast_fp16")];
            tensor<int32, [4]> second_223_begin_0 = const()[name = string("second_223_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 15])];
            tensor<int32, [4]> second_223_end_0 = const()[name = string("second_223_end_0"), val = tensor<int32, [4]>([1, 4, 16, 1])];
            tensor<bool, [4]> second_223_end_mask_0 = const()[name = string("second_223_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 16, 16]> second_223_cast_fp16 = slice_by_index(begin = second_223_begin_0, end = second_223_end_0, end_mask = second_223_end_mask_0, x = x_171_cast_fp16)[name = string("second_223_cast_fp16")];
            tensor<fp16, [1, 4, 16, 16]> y_37_cast_fp16 = add(x = first_215_cast_fp16, y = second_223_cast_fp16)[name = string("y_37_cast_fp16")];
            tensor<fp16, [1, 4, 16, 16]> input_155_cast_fp16 = select(a = text_encoder_attn_encoder_attn_layers_0_Constant_88_value_after_broadcast_to_fp16, b = y_37_cast_fp16, cond = condition_1_after_broadcast)[name = string("input_155_cast_fp16")];
            int32 var_3009 = const()[name = string("op_3009"), val = int32(-1)];
            tensor<fp16, [1, 4, 16, 16]> x_175_cast_fp16 = softmax(axis = var_3009, x = input_155_cast_fp16)[name = string("x_175_cast_fp16")];
            bool first_227_transpose_x_1 = const()[name = string("first_227_transpose_x_1"), val = bool(false)];
            bool first_227_transpose_y_1 = const()[name = string("first_227_transpose_y_1"), val = bool(true)];
            tensor<fp16, [1, 4, 16, 64]> first_227_cast_fp16 = matmul(transpose_x = first_227_transpose_x_1, transpose_y = first_227_transpose_y_1, x = x_175_cast_fp16, y = input_tensor_647_cast_fp16)[name = string("first_227_cast_fp16")];
            tensor<int32, [8]> input_tensor_753_pad_0 = const()[name = string("input_tensor_753_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 15])];
            string input_tensor_753_mode_0 = const()[name = string("input_tensor_753_mode_0"), val = string("constant")];
            fp16 const_115_to_fp16 = const()[name = string("const_115_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 16, 31]> input_tensor_753_cast_fp16 = pad(constant_val = const_115_to_fp16, mode = input_tensor_753_mode_0, pad = input_tensor_753_pad_0, x = x_175_cast_fp16)[name = string("input_tensor_753_cast_fp16")];
            tensor<int32, [3]> var_3083 = const()[name = string("op_3083"), val = tensor<int32, [3]>([1, 4, 496])];
            tensor<fp16, [1, 4, 496]> input_157_cast_fp16 = reshape(shape = var_3083, x = input_tensor_753_cast_fp16)[name = string("input_157_cast_fp16")];
            tensor<int32, [6]> input_tensor_771_pad_0 = const()[name = string("input_tensor_771_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 16, 0])];
            string input_tensor_771_mode_0 = const()[name = string("input_tensor_771_mode_0"), val = string("constant")];
            fp16 const_116_to_fp16 = const()[name = string("const_116_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 512]> input_tensor_771_cast_fp16 = pad(constant_val = const_116_to_fp16, mode = input_tensor_771_mode_0, pad = input_tensor_771_pad_0, x = input_157_cast_fp16)[name = string("input_tensor_771_cast_fp16")];
            tensor<int32, [4]> var_3113 = const()[name = string("op_3113"), val = tensor<int32, [4]>([1, 4, 16, 32])];
            tensor<fp16, [1, 4, 16, 32]> x_185_cast_fp16 = reshape(shape = var_3113, x = input_tensor_771_cast_fp16)[name = string("x_185_cast_fp16")];
            tensor<int32, [4]> x_193_begin_0 = const()[name = string("x_193_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 1])];
            tensor<int32, [4]> x_193_end_0 = const()[name = string("x_193_end_0"), val = tensor<int32, [4]>([1, 4, 16, 1])];
            tensor<bool, [4]> x_193_end_mask_0 = const()[name = string("x_193_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 16, 31]> x_193_cast_fp16 = slice_by_index(begin = x_193_begin_0, end = x_193_end_0, end_mask = x_193_end_mask_0, x = x_185_cast_fp16)[name = string("x_193_cast_fp16")];
            bool second_237_transpose_x_0 = const()[name = string("second_237_transpose_x_0"), val = bool(false)];
            bool second_237_transpose_y_0 = const()[name = string("second_237_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 31, 64]> y_41_to_fp16 = const()[name = string("y_41_to_fp16"), val = tensor<fp16, [1, 1, 31, 64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15762560)))];
            tensor<fp16, [1, 4, 16, 64]> second_237_cast_fp16 = matmul(transpose_x = second_237_transpose_x_0, transpose_y = second_237_transpose_y_0, x = x_193_cast_fp16, y = y_41_to_fp16)[name = string("second_237_cast_fp16")];
            tensor<fp16, [1, 4, 16, 64]> input_tensor_789_cast_fp16 = add(x = first_227_cast_fp16, y = second_237_cast_fp16)[name = string("input_tensor_789_cast_fp16")];
            tensor<int32, [4]> var_3160 = const()[name = string("op_3160"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [3]> var_3179 = const()[name = string("op_3179"), val = tensor<int32, [3]>([1, 256, 16])];
            tensor<fp16, [1, 4, 64, 16]> input_tensor_793_cast_fp16 = transpose(perm = var_3160, x = input_tensor_789_cast_fp16)[name = string("transpose_15")];
            tensor<fp16, [1, 256, 16]> input_161_cast_fp16 = reshape(shape = var_3179, x = input_tensor_793_cast_fp16)[name = string("input_161_cast_fp16")];
            string second_239_pad_type_0 = const()[name = string("second_239_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_239_strides_0 = const()[name = string("second_239_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_239_pad_0 = const()[name = string("second_239_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_239_dilations_0 = const()[name = string("second_239_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_239_groups_0 = const()[name = string("second_239_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_3_conv_o_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_o_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15766592)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_3_conv_o_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_o_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15897728)))];
            tensor<fp16, [1, 256, 16]> second_239_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_3_conv_o_Conv_bias_to_fp16, dilations = second_239_dilations_0, groups = second_239_groups_0, pad = second_239_pad_0, pad_type = second_239_pad_type_0, strides = second_239_strides_0, weight = text_encoder_attn_encoder_attn_layers_3_conv_o_Conv_weight_to_fp16, x = input_161_cast_fp16)[name = string("second_239_cast_fp16")];
            tensor<fp16, [1, 256, 16]> input_tensor_795_cast_fp16 = add(x = input_145_cast_fp16, y = second_239_cast_fp16)[name = string("input_tensor_795_cast_fp16")];
            tensor<int32, [3]> var_3197 = const()[name = string("op_3197"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_797_axes_0 = const()[name = string("input_tensor_797_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_3_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_3_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15898304)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_3_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_3_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15898880)))];
            fp16 var_3200_to_fp16 = const()[name = string("op_3200_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 16, 256]> input_163_cast_fp16 = transpose(perm = var_3197, x = input_tensor_795_cast_fp16)[name = string("transpose_14")];
            tensor<fp16, [1, 16, 256]> input_tensor_797_cast_fp16 = layer_norm(axes = input_tensor_797_axes_0, beta = text_encoder_attn_encoder_norm_layers_1_3_norm_LayerNormalization_bias_to_fp16, epsilon = var_3200_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_1_3_norm_LayerNormalization_weight_to_fp16, x = input_163_cast_fp16)[name = string("input_tensor_797_cast_fp16")];
            tensor<int32, [3]> var_3209 = const()[name = string("op_3209"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 256, 16]> first_229_cast_fp16 = transpose(perm = var_3209, x = input_tensor_797_cast_fp16)[name = string("transpose_13")];
            tensor<fp16, [1, 256, 16]> input_165_cast_fp16 = mul(x = first_229_cast_fp16, y = text_mask)[name = string("input_165_cast_fp16")];
            string input_167_pad_type_0 = const()[name = string("input_167_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_167_strides_0 = const()[name = string("input_167_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_167_pad_0 = const()[name = string("input_167_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_167_dilations_0 = const()[name = string("input_167_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_167_groups_0 = const()[name = string("input_167_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_attn_encoder_ffn_layers_3_conv_1_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_3_conv_1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15899456)))];
            tensor<fp16, [1024]> text_encoder_attn_encoder_ffn_layers_3_conv_1_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_3_conv_1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16423808)))];
            tensor<fp16, [1, 1024, 16]> input_167_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_3_conv_1_Conv_bias_to_fp16, dilations = input_167_dilations_0, groups = input_167_groups_0, pad = input_167_pad_0, pad_type = input_167_pad_type_0, strides = input_167_strides_0, weight = text_encoder_attn_encoder_ffn_layers_3_conv_1_Conv_weight_to_fp16, x = input_165_cast_fp16)[name = string("input_167_cast_fp16")];
            tensor<fp16, [1, 1024, 16]> first_231_cast_fp16 = relu(x = input_167_cast_fp16)[name = string("first_231_cast_fp16")];
            tensor<fp16, [1, 1024, 16]> input_169_cast_fp16 = mul(x = first_231_cast_fp16, y = text_mask)[name = string("input_169_cast_fp16")];
            string first_233_pad_type_0 = const()[name = string("first_233_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_233_strides_0 = const()[name = string("first_233_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_233_pad_0 = const()[name = string("first_233_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_233_dilations_0 = const()[name = string("first_233_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_233_groups_0 = const()[name = string("first_233_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> text_encoder_attn_encoder_ffn_layers_3_conv_2_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_3_conv_2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16425920)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_ffn_layers_3_conv_2_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_3_conv_2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16950272)))];
            tensor<fp16, [1, 256, 16]> first_233_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_3_conv_2_Conv_bias_to_fp16, dilations = first_233_dilations_0, groups = first_233_groups_0, pad = first_233_pad_0, pad_type = first_233_pad_type_0, strides = first_233_strides_0, weight = text_encoder_attn_encoder_ffn_layers_3_conv_2_Conv_weight_to_fp16, x = input_169_cast_fp16)[name = string("first_233_cast_fp16")];
            tensor<fp16, [1, 256, 16]> second_241_cast_fp16 = mul(x = first_233_cast_fp16, y = text_mask)[name = string("second_241_cast_fp16")];
            tensor<fp16, [1, 256, 16]> input_tensor_799_cast_fp16 = add(x = first_229_cast_fp16, y = second_241_cast_fp16)[name = string("input_tensor_799_cast_fp16")];
            tensor<int32, [3]> var_3242 = const()[name = string("op_3242"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_801_axes_0 = const()[name = string("input_tensor_801_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_3_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_3_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16950848)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_3_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_3_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16951424)))];
            fp16 var_3245_to_fp16 = const()[name = string("op_3245_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 16, 256]> input_171_cast_fp16 = transpose(perm = var_3242, x = input_tensor_799_cast_fp16)[name = string("transpose_12")];
            tensor<fp16, [1, 16, 256]> input_tensor_801_cast_fp16 = layer_norm(axes = input_tensor_801_axes_0, beta = text_encoder_attn_encoder_norm_layers_2_3_norm_LayerNormalization_bias_to_fp16, epsilon = var_3245_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_2_3_norm_LayerNormalization_weight_to_fp16, x = input_171_cast_fp16)[name = string("input_tensor_801_cast_fp16")];
            tensor<int32, [3]> var_3254 = const()[name = string("op_3254"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 256, 16]> first_235_cast_fp16 = transpose(perm = var_3254, x = input_tensor_801_cast_fp16)[name = string("transpose_11")];
            tensor<fp16, [1, 256, 16]> first_237_cast_fp16 = mul(x = first_235_cast_fp16, y = text_mask)[name = string("first_237_cast_fp16")];
            tensor<fp16, [1, 256, 16]> first_239_cast_fp16 = add(x = first_237_cast_fp16, y = first_89_cast_fp16)[name = string("first_239_cast_fp16")];
            tensor<fp16, [1, 256, 16]> input_tensor_807_cast_fp16 = mul(x = first_239_cast_fp16, y = text_mask)[name = string("input_tensor_807_cast_fp16")];
            tensor<int32, [3]> var_3299 = const()[name = string("op_3299"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [3]> var_3304 = const()[name = string("op_3304"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [256, 256]> var_3308_weight_0_to_fp16 = const()[name = string("op_3308_weight_0_to_fp16"), val = tensor<fp16, [256, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16952000)))];
            tensor<fp16, [256]> var_3308_bias_0_to_fp16 = const()[name = string("op_3308_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17083136)))];
            tensor<fp16, [1, 16, 256]> x_195_cast_fp16 = transpose(perm = var_3299, x = input_tensor_807_cast_fp16)[name = string("transpose_10")];
            tensor<fp16, [1, 16, 256]> var_3308_cast_fp16 = linear(bias = var_3308_bias_0_to_fp16, weight = var_3308_weight_0_to_fp16, x = x_195_cast_fp16)[name = string("op_3308_cast_fp16")];
            tensor<fp16, [256, 256]> var_3314_weight_0_to_fp16 = const()[name = string("op_3314_weight_0_to_fp16"), val = tensor<fp16, [256, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17083712)))];
            tensor<fp16, [256]> var_3314_bias_0_to_fp16 = const()[name = string("op_3314_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17214848)))];
            tensor<fp16, [1, 50, 256]> var_3314_cast_fp16 = linear(bias = var_3314_bias_0_to_fp16, weight = var_3314_weight_0_to_fp16, x = style_ttl)[name = string("op_3314_cast_fp16")];
            tensor<int32, [2]> var_3317 = const()[name = string("op_3317"), val = tensor<int32, [2]>([128, 128])];
            int32 var_3318_axis_0 = const()[name = string("op_3318_axis_0"), val = int32(2)];
            tensor<fp16, [1, 16, 128]> var_3318_cast_fp16_0, tensor<fp16, [1, 16, 128]> var_3318_cast_fp16_1 = split(axis = var_3318_axis_0, split_sizes = var_3317, x = var_3308_cast_fp16)[name = string("op_3318_cast_fp16")];
            tensor<int32, [1]> var_3325_axes_0 = const()[name = string("op_3325_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 16, 128]> var_3325_cast_fp16 = expand_dims(axes = var_3325_axes_0, x = var_3318_cast_fp16_0)[name = string("op_3325_cast_fp16")];
            tensor<int32, [1]> var_3327_axes_0 = const()[name = string("op_3327_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 16, 128]> var_3327_cast_fp16 = expand_dims(axes = var_3327_axes_0, x = var_3318_cast_fp16_1)[name = string("op_3327_cast_fp16")];
            int32 var_3328 = const()[name = string("op_3328"), val = int32(0)];
            bool x_199_interleave_0 = const()[name = string("x_199_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 1, 16, 128]> x_199_cast_fp16 = concat(axis = var_3328, interleave = x_199_interleave_0, values = (var_3325_cast_fp16, var_3327_cast_fp16))[name = string("x_199_cast_fp16")];
            tensor<int32, [2]> var_3349 = const()[name = string("op_3349"), val = tensor<int32, [2]>([128, 128])];
            int32 var_3350_axis_0 = const()[name = string("op_3350_axis_0"), val = int32(2)];
            tensor<fp16, [1, 50, 128]> var_3350_cast_fp16_0, tensor<fp16, [1, 50, 128]> var_3350_cast_fp16_1 = split(axis = var_3350_axis_0, split_sizes = var_3349, x = var_3314_cast_fp16)[name = string("op_3350_cast_fp16")];
            tensor<int32, [1]> var_3357_axes_0 = const()[name = string("op_3357_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 50, 128]> var_3357_cast_fp16 = expand_dims(axes = var_3357_axes_0, x = var_3350_cast_fp16_0)[name = string("op_3357_cast_fp16")];
            tensor<int32, [1]> var_3359_axes_0 = const()[name = string("op_3359_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 50, 128]> var_3359_cast_fp16 = expand_dims(axes = var_3359_axes_0, x = var_3350_cast_fp16_1)[name = string("op_3359_cast_fp16")];
            int32 var_3360 = const()[name = string("op_3360"), val = int32(0)];
            bool y_55_interleave_0 = const()[name = string("y_55_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 1, 50, 128]> y_55_cast_fp16 = concat(axis = var_3360, interleave = y_55_interleave_0, values = (var_3357_cast_fp16, var_3359_cast_fp16))[name = string("y_55_cast_fp16")];
            bool first_247_transpose_x_0 = const()[name = string("first_247_transpose_x_0"), val = bool(false)];
            bool first_247_transpose_y_0 = const()[name = string("first_247_transpose_y_0"), val = bool(false)];
            tensor<fp16, [2, 1, 128, 50]> y_49_to_fp16 = const()[name = string("y_49_to_fp16"), val = tensor<fp16, [2, 1, 128, 50]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17215424)))];
            tensor<fp16, [2, 1, 16, 50]> first_247_cast_fp16 = matmul(transpose_x = first_247_transpose_x_0, transpose_y = first_247_transpose_y_0, x = x_199_cast_fp16, y = y_49_to_fp16)[name = string("first_247_cast_fp16")];
            fp16 _inversed_input_173_y_0_to_fp16 = const()[name = string("_inversed_input_173_y_0_to_fp16"), val = fp16(0x1p-4)];
            tensor<fp16, [2, 1, 16, 50]> _inversed_input_173_cast_fp16 = mul(x = first_247_cast_fp16, y = _inversed_input_173_y_0_to_fp16)[name = string("_inversed_input_173_cast_fp16")];
            int32 var_3373 = const()[name = string("op_3373"), val = int32(3)];
            tensor<fp16, [2, 1, 16, 50]> y_53_cast_fp16 = softmax(axis = var_3373, x = _inversed_input_173_cast_fp16)[name = string("y_53_cast_fp16")];
            tensor<int32, [1]> x_201_axes_0 = const()[name = string("x_201_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 16, 1]> input_tensor_825_cast_fp16 = transpose(perm = var_3304, x = text_mask)[name = string("transpose_9")];
            tensor<fp16, [1, 1, 16, 1]> x_201_cast_fp16 = expand_dims(axes = x_201_axes_0, x = input_tensor_825_cast_fp16)[name = string("x_201_cast_fp16")];
            fp16 speech_prompted_text_encoder_attention1_Constant_11_value_to_fp16 = const()[name = string("speech_prompted_text_encoder_attention1_Constant_11_value_to_fp16"), val = fp16(0x0p+0)];
            tensor<bool, [1, 1, 16, 1]> input_tensor_827_cast_fp16 = equal(x = x_201_cast_fp16, y = speech_prompted_text_encoder_attention1_Constant_11_value_to_fp16)[name = string("input_tensor_827_cast_fp16")];
            tensor<int32, [4]> condition_9_after_broadcast_reps_0 = const()[name = string("condition_9_after_broadcast_reps_0"), val = tensor<int32, [4]>([2, 1, 1, 50])];
            tensor<bool, [2, 1, 16, 50]> condition_9_after_broadcast = tile(reps = condition_9_after_broadcast_reps_0, x = input_tensor_827_cast_fp16)[name = string("condition_9_after_broadcast")];
            tensor<fp16, [2, 1, 16, 50]> speech_prompted_text_encoder_attention1_Constant_12_value_after_broadcast_to_fp16 = const()[name = string("speech_prompted_text_encoder_attention1_Constant_12_value_after_broadcast_to_fp16"), val = tensor<fp16, [2, 1, 16, 50]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17241088)))];
            tensor<fp16, [2, 1, 16, 50]> x_205_cast_fp16 = select(a = speech_prompted_text_encoder_attention1_Constant_12_value_after_broadcast_to_fp16, b = y_53_cast_fp16, cond = condition_9_after_broadcast)[name = string("x_205_cast_fp16")];
            bool var_3383_transpose_x_0 = const()[name = string("op_3383_transpose_x_0"), val = bool(false)];
            bool var_3383_transpose_y_0 = const()[name = string("op_3383_transpose_y_0"), val = bool(false)];
            tensor<fp16, [2, 1, 16, 128]> var_3383_cast_fp16 = matmul(transpose_x = var_3383_transpose_x_0, transpose_y = var_3383_transpose_y_0, x = x_205_cast_fp16, y = y_55_cast_fp16)[name = string("op_3383_cast_fp16")];
            tensor<int32, [2]> var_3386 = const()[name = string("op_3386"), val = tensor<int32, [2]>([1, 1])];
            int32 var_3387_axis_0 = const()[name = string("op_3387_axis_0"), val = int32(0)];
            tensor<fp16, [1, 1, 16, 128]> var_3387_cast_fp16_0, tensor<fp16, [1, 1, 16, 128]> var_3387_cast_fp16_1 = split(axis = var_3387_axis_0, split_sizes = var_3386, x = var_3383_cast_fp16)[name = string("op_3387_cast_fp16")];
            int32 var_3393 = const()[name = string("op_3393"), val = int32(3)];
            bool result_1_interleave_0 = const()[name = string("result_1_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 1, 16, 256]> result_1_cast_fp16 = concat(axis = var_3393, interleave = result_1_interleave_0, values = (var_3387_cast_fp16_0, var_3387_cast_fp16_1))[name = string("result_1_cast_fp16")];
            tensor<int32, [1]> x_207_axes_0 = const()[name = string("x_207_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 16, 256]> x_207_cast_fp16 = squeeze(axes = x_207_axes_0, x = result_1_cast_fp16)[name = string("x_207_cast_fp16")];
            tensor<fp16, [256, 256]> first_251_weight_0_to_fp16 = const()[name = string("first_251_weight_0_to_fp16"), val = tensor<fp16, [256, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17244352)))];
            tensor<fp16, [256]> first_251_bias_0_to_fp16 = const()[name = string("first_251_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17375488)))];
            tensor<fp16, [1, 16, 256]> first_251_cast_fp16 = linear(bias = first_251_bias_0_to_fp16, weight = first_251_weight_0_to_fp16, x = x_207_cast_fp16)[name = string("first_251_cast_fp16")];
            tensor<fp16, [1, 16, 256]> first_253_cast_fp16 = mul(x = first_251_cast_fp16, y = input_tensor_825_cast_fp16)[name = string("first_253_cast_fp16")];
            tensor<fp16, [1, 16, 256]> x_209_cast_fp16 = add(x = first_253_cast_fp16, y = x_195_cast_fp16)[name = string("x_209_cast_fp16")];
            tensor<fp16, [256, 256]> var_3413_weight_0_to_fp16 = const()[name = string("op_3413_weight_0_to_fp16"), val = tensor<fp16, [256, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17376064)))];
            tensor<fp16, [256]> var_3413_bias_0_to_fp16 = const()[name = string("op_3413_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17507200)))];
            tensor<fp16, [1, 16, 256]> var_3413_cast_fp16 = linear(bias = var_3413_bias_0_to_fp16, weight = var_3413_weight_0_to_fp16, x = x_209_cast_fp16)[name = string("op_3413_cast_fp16")];
            tensor<fp16, [256, 256]> var_3419_weight_0_to_fp16 = const()[name = string("op_3419_weight_0_to_fp16"), val = tensor<fp16, [256, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17507776)))];
            tensor<fp16, [256]> var_3419_bias_0_to_fp16 = const()[name = string("op_3419_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17638912)))];
            tensor<fp16, [1, 50, 256]> var_3419_cast_fp16 = linear(bias = var_3419_bias_0_to_fp16, weight = var_3419_weight_0_to_fp16, x = style_ttl)[name = string("op_3419_cast_fp16")];
            tensor<int32, [2]> var_3422 = const()[name = string("op_3422"), val = tensor<int32, [2]>([128, 128])];
            int32 var_3423_axis_0 = const()[name = string("op_3423_axis_0"), val = int32(2)];
            tensor<fp16, [1, 16, 128]> var_3423_cast_fp16_0, tensor<fp16, [1, 16, 128]> var_3423_cast_fp16_1 = split(axis = var_3423_axis_0, split_sizes = var_3422, x = var_3413_cast_fp16)[name = string("op_3423_cast_fp16")];
            tensor<int32, [1]> var_3430_axes_0 = const()[name = string("op_3430_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 16, 128]> var_3430_cast_fp16 = expand_dims(axes = var_3430_axes_0, x = var_3423_cast_fp16_0)[name = string("op_3430_cast_fp16")];
            tensor<int32, [1]> var_3432_axes_0 = const()[name = string("op_3432_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 16, 128]> var_3432_cast_fp16 = expand_dims(axes = var_3432_axes_0, x = var_3423_cast_fp16_1)[name = string("op_3432_cast_fp16")];
            int32 var_3433 = const()[name = string("op_3433"), val = int32(0)];
            bool x_211_interleave_0 = const()[name = string("x_211_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 1, 16, 128]> x_211_cast_fp16 = concat(axis = var_3433, interleave = x_211_interleave_0, values = (var_3430_cast_fp16, var_3432_cast_fp16))[name = string("x_211_cast_fp16")];
            tensor<int32, [2]> var_3454 = const()[name = string("op_3454"), val = tensor<int32, [2]>([128, 128])];
            int32 var_3455_axis_0 = const()[name = string("op_3455_axis_0"), val = int32(2)];
            tensor<fp16, [1, 50, 128]> var_3455_cast_fp16_0, tensor<fp16, [1, 50, 128]> var_3455_cast_fp16_1 = split(axis = var_3455_axis_0, split_sizes = var_3454, x = var_3419_cast_fp16)[name = string("op_3455_cast_fp16")];
            tensor<int32, [1]> var_3462_axes_0 = const()[name = string("op_3462_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 50, 128]> var_3462_cast_fp16 = expand_dims(axes = var_3462_axes_0, x = var_3455_cast_fp16_0)[name = string("op_3462_cast_fp16")];
            tensor<int32, [1]> var_3464_axes_0 = const()[name = string("op_3464_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 50, 128]> var_3464_cast_fp16 = expand_dims(axes = var_3464_axes_0, x = var_3455_cast_fp16_1)[name = string("op_3464_cast_fp16")];
            int32 var_3465 = const()[name = string("op_3465"), val = int32(0)];
            bool y_69_interleave_0 = const()[name = string("y_69_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 1, 50, 128]> y_69_cast_fp16 = concat(axis = var_3465, interleave = y_69_interleave_0, values = (var_3462_cast_fp16, var_3464_cast_fp16))[name = string("y_69_cast_fp16")];
            bool first_261_transpose_x_0 = const()[name = string("first_261_transpose_x_0"), val = bool(false)];
            bool first_261_transpose_y_0 = const()[name = string("first_261_transpose_y_0"), val = bool(false)];
            tensor<fp16, [2, 1, 128, 50]> y_65_to_fp16 = const()[name = string("y_65_to_fp16"), val = tensor<fp16, [2, 1, 128, 50]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17639488)))];
            tensor<fp16, [2, 1, 16, 50]> first_261_cast_fp16 = matmul(transpose_x = first_261_transpose_x_0, transpose_y = first_261_transpose_y_0, x = x_211_cast_fp16, y = y_65_to_fp16)[name = string("first_261_cast_fp16")];
            fp16 _inversed_input_175_y_0_to_fp16 = const()[name = string("_inversed_input_175_y_0_to_fp16"), val = fp16(0x1p-4)];
            tensor<fp16, [2, 1, 16, 50]> _inversed_input_175_cast_fp16 = mul(x = first_261_cast_fp16, y = _inversed_input_175_y_0_to_fp16)[name = string("_inversed_input_175_cast_fp16")];
            int32 var_3478 = const()[name = string("op_3478"), val = int32(3)];
            tensor<fp16, [2, 1, 16, 50]> y_67_cast_fp16 = softmax(axis = var_3478, x = _inversed_input_175_cast_fp16)[name = string("y_67_cast_fp16")];
            tensor<fp16, [2, 1, 16, 50]> x_215_cast_fp16 = select(a = speech_prompted_text_encoder_attention1_Constant_12_value_after_broadcast_to_fp16, b = y_67_cast_fp16, cond = condition_9_after_broadcast)[name = string("x_215_cast_fp16")];
            bool var_3485_transpose_x_0 = const()[name = string("op_3485_transpose_x_0"), val = bool(false)];
            bool var_3485_transpose_y_0 = const()[name = string("op_3485_transpose_y_0"), val = bool(false)];
            tensor<fp16, [2, 1, 16, 128]> var_3485_cast_fp16 = matmul(transpose_x = var_3485_transpose_x_0, transpose_y = var_3485_transpose_y_0, x = x_215_cast_fp16, y = y_69_cast_fp16)[name = string("op_3485_cast_fp16")];
            tensor<int32, [2]> var_3488 = const()[name = string("op_3488"), val = tensor<int32, [2]>([1, 1])];
            int32 var_3489_axis_0 = const()[name = string("op_3489_axis_0"), val = int32(0)];
            tensor<fp16, [1, 1, 16, 128]> var_3489_cast_fp16_0, tensor<fp16, [1, 1, 16, 128]> var_3489_cast_fp16_1 = split(axis = var_3489_axis_0, split_sizes = var_3488, x = var_3485_cast_fp16)[name = string("op_3489_cast_fp16")];
            int32 var_3495 = const()[name = string("op_3495"), val = int32(3)];
            bool result_interleave_0 = const()[name = string("result_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 1, 16, 256]> result_cast_fp16 = concat(axis = var_3495, interleave = result_interleave_0, values = (var_3489_cast_fp16_0, var_3489_cast_fp16_1))[name = string("result_cast_fp16")];
            tensor<int32, [1]> x_axes_0 = const()[name = string("x_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 16, 256]> x_cast_fp16 = squeeze(axes = x_axes_0, x = result_cast_fp16)[name = string("x_cast_fp16")];
            tensor<fp16, [256, 256]> first_265_weight_0_to_fp16 = const()[name = string("first_265_weight_0_to_fp16"), val = tensor<fp16, [256, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17665152)))];
            tensor<fp16, [256]> first_265_bias_0_to_fp16 = const()[name = string("first_265_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17796288)))];
            tensor<fp16, [1, 16, 256]> first_265_cast_fp16 = linear(bias = first_265_bias_0_to_fp16, weight = first_265_weight_0_to_fp16, x = x_cast_fp16)[name = string("first_265_cast_fp16")];
            tensor<fp16, [1, 16, 256]> first_267_cast_fp16 = mul(x = first_265_cast_fp16, y = input_tensor_825_cast_fp16)[name = string("first_267_cast_fp16")];
            tensor<fp16, [1, 16, 256]> input_cast_fp16 = add(x = first_267_cast_fp16, y = x_195_cast_fp16)[name = string("input_cast_fp16")];
            tensor<int32, [1]> input_tensor_axes_0 = const()[name = string("input_tensor_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> speech_prompted_text_encoder_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("speech_prompted_text_encoder_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17796864)))];
            tensor<fp16, [256]> speech_prompted_text_encoder_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("speech_prompted_text_encoder_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17797440)))];
            fp16 var_3514_to_fp16 = const()[name = string("op_3514_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 16, 256]> input_tensor_cast_fp16 = layer_norm(axes = input_tensor_axes_0, beta = speech_prompted_text_encoder_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_3514_to_fp16, gamma = speech_prompted_text_encoder_norm_norm_LayerNormalization_weight_to_fp16, x = input_cast_fp16)[name = string("input_tensor_cast_fp16")];
            tensor<int32, [3]> var_3523 = const()[name = string("op_3523"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 256, 16]> first_cast_fp16 = transpose(perm = var_3523, x = input_tensor_cast_fp16)[name = string("transpose_8")];
            tensor<fp16, [1, 256, 16]> text_emb = mul(x = first_cast_fp16, y = text_mask)[name = string("op_3525_cast_fp16")];
        } -> (text_emb);
    func text_t192<ios18>(tensor<fp16, [1, 50, 256]> style_ttl, tensor<int32, [1, 192]> text_ids, tensor<fp16, [1, 1, 192]> text_mask) {
            int32 input_tensor_3_batch_dims_0 = const()[name = string("input_tensor_3_batch_dims_0"), val = int32(0)];
            bool input_tensor_3_validate_indices_0 = const()[name = string("input_tensor_3_validate_indices_0"), val = bool(false)];
            tensor<fp16, [8322, 256]> initializers_onnx_initializer_0_to_fp16 = const()[name = string("initializers_onnx_initializer_0_to_fp16"), val = tensor<fp16, [8322, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(64)))];
            string text_ids_to_int16_dtype_0 = const()[name = string("text_ids_to_int16_dtype_0"), val = string("int16")];
            string cast_59_dtype_0 = const()[name = string("cast_59_dtype_0"), val = string("int32")];
            int32 greater_equal_0_y_0 = const()[name = string("greater_equal_0_y_0"), val = int32(0)];
            tensor<int16, [1, 192]> text_ids_to_int16 = cast(dtype = text_ids_to_int16_dtype_0, x = text_ids)[name = string("cast_62")];
            tensor<int32, [1, 192]> cast_59 = cast(dtype = cast_59_dtype_0, x = text_ids_to_int16)[name = string("cast_61")];
            tensor<bool, [1, 192]> greater_equal_0 = greater_equal(x = cast_59, y = greater_equal_0_y_0)[name = string("greater_equal_0")];
            int32 slice_by_index_0 = const()[name = string("slice_by_index_0"), val = int32(8322)];
            tensor<int32, [1, 192]> add_0 = add(x = cast_59, y = slice_by_index_0)[name = string("add_0")];
            tensor<int32, [1, 192]> select_0 = select(a = cast_59, b = add_0, cond = greater_equal_0)[name = string("select_0")];
            int32 input_tensor_3_cast_fp16_cast_uint16_axis_0 = const()[name = string("input_tensor_3_cast_fp16_cast_uint16_axis_0"), val = int32(0)];
            string select_0_to_int16_dtype_0 = const()[name = string("select_0_to_int16_dtype_0"), val = string("int16")];
            tensor<int16, [1, 192]> select_0_to_int16 = cast(dtype = select_0_to_int16_dtype_0, x = select_0)[name = string("cast_60")];
            tensor<fp16, [1, 192, 256]> input_tensor_3_cast_fp16_cast_uint16_cast_uint16 = gather(axis = input_tensor_3_cast_fp16_cast_uint16_axis_0, batch_dims = input_tensor_3_batch_dims_0, indices = select_0_to_int16, validate_indices = input_tensor_3_validate_indices_0, x = initializers_onnx_initializer_0_to_fp16)[name = string("input_tensor_3_cast_fp16_cast_uint16_cast_uint16")];
            tensor<int32, [3]> var_446 = const()[name = string("op_446"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 256, 192]> first_1_cast_fp16 = transpose(perm = var_446, x = input_tensor_3_cast_fp16_cast_uint16_cast_uint16)[name = string("transpose_47")];
            tensor<fp16, [1, 256, 192]> first_3_cast_fp16 = mul(x = first_1_cast_fp16, y = text_mask)[name = string("first_3_cast_fp16")];
            tensor<fp16, [1, 256, 192]> input_1_cast_fp16 = mul(x = first_3_cast_fp16, y = text_mask)[name = string("input_1_cast_fp16")];
            tensor<int32, [6]> input_3_pad_0 = const()[name = string("input_3_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 2, 2])];
            string input_3_mode_0 = const()[name = string("input_3_mode_0"), val = string("replicate")];
            fp16 const_0_to_fp16 = const()[name = string("const_0_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 256, 196]> input_3_cast_fp16 = pad(constant_val = const_0_to_fp16, mode = input_3_mode_0, pad = input_3_pad_0, x = input_1_cast_fp16)[name = string("input_3_cast_fp16")];
            string first_5_pad_type_0 = const()[name = string("first_5_pad_type_0"), val = string("valid")];
            int32 first_5_groups_0 = const()[name = string("first_5_groups_0"), val = int32(256)];
            tensor<int32, [1]> first_5_strides_0 = const()[name = string("first_5_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_5_pad_0 = const()[name = string("first_5_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_5_dilations_0 = const()[name = string("first_5_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [256, 1, 5]> text_encoder_convnext_convnext_0_dwconv_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_0_dwconv_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4260992)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_0_dwconv_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_0_dwconv_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4263616)))];
            tensor<fp16, [1, 256, 192]> first_5_cast_fp16 = conv(bias = text_encoder_convnext_convnext_0_dwconv_Conv_bias_to_fp16, dilations = first_5_dilations_0, groups = first_5_groups_0, pad = first_5_pad_0, pad_type = first_5_pad_type_0, strides = first_5_strides_0, weight = text_encoder_convnext_convnext_0_dwconv_Conv_weight_to_fp16, x = input_3_cast_fp16)[name = string("first_5_cast_fp16")];
            tensor<fp16, [1, 256, 192]> input_tensor_13_cast_fp16 = mul(x = first_5_cast_fp16, y = text_mask)[name = string("input_tensor_13_cast_fp16")];
            tensor<int32, [3]> var_471 = const()[name = string("op_471"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_15_axes_0 = const()[name = string("input_tensor_15_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_convnext_convnext_0_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_0_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4264192)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_0_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_0_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4264768)))];
            fp16 var_474_to_fp16 = const()[name = string("op_474_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 192, 256]> input_5_cast_fp16 = transpose(perm = var_471, x = input_tensor_13_cast_fp16)[name = string("transpose_46")];
            tensor<fp16, [1, 192, 256]> input_tensor_15_cast_fp16 = layer_norm(axes = input_tensor_15_axes_0, beta = text_encoder_convnext_convnext_0_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_474_to_fp16, gamma = text_encoder_convnext_convnext_0_norm_norm_LayerNormalization_weight_to_fp16, x = input_5_cast_fp16)[name = string("input_tensor_15_cast_fp16")];
            tensor<int32, [3]> var_483 = const()[name = string("op_483"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_7_pad_type_0 = const()[name = string("first_7_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_7_strides_0 = const()[name = string("first_7_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_7_pad_0 = const()[name = string("first_7_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_7_dilations_0 = const()[name = string("first_7_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_7_groups_0 = const()[name = string("first_7_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_convnext_convnext_0_pwconv1_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_0_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4265344)))];
            tensor<fp16, [1024]> text_encoder_convnext_convnext_0_pwconv1_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_0_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4789696)))];
            tensor<fp16, [1, 256, 192]> input_7_cast_fp16 = transpose(perm = var_483, x = input_tensor_15_cast_fp16)[name = string("transpose_45")];
            tensor<fp16, [1, 1024, 192]> first_7_cast_fp16 = conv(bias = text_encoder_convnext_convnext_0_pwconv1_Conv_bias_to_fp16, dilations = first_7_dilations_0, groups = first_7_groups_0, pad = first_7_pad_0, pad_type = first_7_pad_type_0, strides = first_7_strides_0, weight = text_encoder_convnext_convnext_0_pwconv1_Conv_weight_to_fp16, x = input_7_cast_fp16)[name = string("first_7_cast_fp16")];
            string input_9_mode_0 = const()[name = string("input_9_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 1024, 192]> input_9_cast_fp16 = gelu(mode = input_9_mode_0, x = first_7_cast_fp16)[name = string("input_9_cast_fp16")];
            string second_9_pad_type_0 = const()[name = string("second_9_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_9_strides_0 = const()[name = string("second_9_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_9_pad_0 = const()[name = string("second_9_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_9_dilations_0 = const()[name = string("second_9_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_9_groups_0 = const()[name = string("second_9_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> second_11_weight_0_to_fp16 = const()[name = string("second_11_weight_0_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4791808)))];
            tensor<fp16, [256]> second_11_bias_0_to_fp16 = const()[name = string("second_11_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5316160)))];
            tensor<fp16, [1, 256, 192]> second_11_cast_fp16 = conv(bias = second_11_bias_0_to_fp16, dilations = second_9_dilations_0, groups = second_9_groups_0, pad = second_9_pad_0, pad_type = second_9_pad_type_0, strides = second_9_strides_0, weight = second_11_weight_0_to_fp16, x = input_9_cast_fp16)[name = string("second_11_cast_fp16")];
            tensor<fp16, [1, 256, 192]> first_15_cast_fp16 = add(x = input_1_cast_fp16, y = second_11_cast_fp16)[name = string("first_15_cast_fp16")];
            tensor<fp16, [1, 256, 192]> first_17_cast_fp16 = mul(x = first_15_cast_fp16, y = text_mask)[name = string("first_17_cast_fp16")];
            tensor<fp16, [1, 256, 192]> input_11_cast_fp16 = mul(x = first_17_cast_fp16, y = text_mask)[name = string("input_11_cast_fp16")];
            tensor<int32, [6]> input_13_pad_0 = const()[name = string("input_13_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 2, 2])];
            string input_13_mode_0 = const()[name = string("input_13_mode_0"), val = string("replicate")];
            fp16 const_1_to_fp16 = const()[name = string("const_1_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 256, 196]> input_13_cast_fp16 = pad(constant_val = const_1_to_fp16, mode = input_13_mode_0, pad = input_13_pad_0, x = input_11_cast_fp16)[name = string("input_13_cast_fp16")];
            string first_19_pad_type_0 = const()[name = string("first_19_pad_type_0"), val = string("valid")];
            int32 first_19_groups_0 = const()[name = string("first_19_groups_0"), val = int32(256)];
            tensor<int32, [1]> first_19_strides_0 = const()[name = string("first_19_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_19_pad_0 = const()[name = string("first_19_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_19_dilations_0 = const()[name = string("first_19_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [256, 1, 5]> text_encoder_convnext_convnext_1_dwconv_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_1_dwconv_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5316736)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_1_dwconv_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_1_dwconv_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5319360)))];
            tensor<fp16, [1, 256, 192]> first_19_cast_fp16 = conv(bias = text_encoder_convnext_convnext_1_dwconv_Conv_bias_to_fp16, dilations = first_19_dilations_0, groups = first_19_groups_0, pad = first_19_pad_0, pad_type = first_19_pad_type_0, strides = first_19_strides_0, weight = text_encoder_convnext_convnext_1_dwconv_Conv_weight_to_fp16, x = input_13_cast_fp16)[name = string("first_19_cast_fp16")];
            tensor<fp16, [1, 256, 192]> input_tensor_27_cast_fp16 = mul(x = first_19_cast_fp16, y = text_mask)[name = string("input_tensor_27_cast_fp16")];
            tensor<int32, [3]> var_539 = const()[name = string("op_539"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_29_axes_0 = const()[name = string("input_tensor_29_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_convnext_convnext_1_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_1_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5319936)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_1_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_1_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5320512)))];
            fp16 var_542_to_fp16 = const()[name = string("op_542_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 192, 256]> input_15_cast_fp16 = transpose(perm = var_539, x = input_tensor_27_cast_fp16)[name = string("transpose_44")];
            tensor<fp16, [1, 192, 256]> input_tensor_29_cast_fp16 = layer_norm(axes = input_tensor_29_axes_0, beta = text_encoder_convnext_convnext_1_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_542_to_fp16, gamma = text_encoder_convnext_convnext_1_norm_norm_LayerNormalization_weight_to_fp16, x = input_15_cast_fp16)[name = string("input_tensor_29_cast_fp16")];
            tensor<int32, [3]> var_551 = const()[name = string("op_551"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_21_pad_type_0 = const()[name = string("first_21_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_21_strides_0 = const()[name = string("first_21_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_21_pad_0 = const()[name = string("first_21_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_21_dilations_0 = const()[name = string("first_21_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_21_groups_0 = const()[name = string("first_21_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_convnext_convnext_1_pwconv1_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_1_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5321088)))];
            tensor<fp16, [1024]> text_encoder_convnext_convnext_1_pwconv1_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_1_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5845440)))];
            tensor<fp16, [1, 256, 192]> input_17_cast_fp16 = transpose(perm = var_551, x = input_tensor_29_cast_fp16)[name = string("transpose_43")];
            tensor<fp16, [1, 1024, 192]> first_21_cast_fp16 = conv(bias = text_encoder_convnext_convnext_1_pwconv1_Conv_bias_to_fp16, dilations = first_21_dilations_0, groups = first_21_groups_0, pad = first_21_pad_0, pad_type = first_21_pad_type_0, strides = first_21_strides_0, weight = text_encoder_convnext_convnext_1_pwconv1_Conv_weight_to_fp16, x = input_17_cast_fp16)[name = string("first_21_cast_fp16")];
            string input_19_mode_0 = const()[name = string("input_19_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 1024, 192]> input_19_cast_fp16 = gelu(mode = input_19_mode_0, x = first_21_cast_fp16)[name = string("input_19_cast_fp16")];
            string second_21_pad_type_0 = const()[name = string("second_21_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_21_strides_0 = const()[name = string("second_21_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_21_pad_0 = const()[name = string("second_21_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_21_dilations_0 = const()[name = string("second_21_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_21_groups_0 = const()[name = string("second_21_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> second_23_weight_0_to_fp16 = const()[name = string("second_23_weight_0_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5847552)))];
            tensor<fp16, [256]> second_23_bias_0_to_fp16 = const()[name = string("second_23_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6371904)))];
            tensor<fp16, [1, 256, 192]> second_23_cast_fp16 = conv(bias = second_23_bias_0_to_fp16, dilations = second_21_dilations_0, groups = second_21_groups_0, pad = second_21_pad_0, pad_type = second_21_pad_type_0, strides = second_21_strides_0, weight = second_23_weight_0_to_fp16, x = input_19_cast_fp16)[name = string("second_23_cast_fp16")];
            tensor<fp16, [1, 256, 192]> first_29_cast_fp16 = add(x = input_11_cast_fp16, y = second_23_cast_fp16)[name = string("first_29_cast_fp16")];
            tensor<fp16, [1, 256, 192]> first_31_cast_fp16 = mul(x = first_29_cast_fp16, y = text_mask)[name = string("first_31_cast_fp16")];
            tensor<fp16, [1, 256, 192]> input_21_cast_fp16 = mul(x = first_31_cast_fp16, y = text_mask)[name = string("input_21_cast_fp16")];
            tensor<int32, [6]> input_23_pad_0 = const()[name = string("input_23_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            string input_23_mode_0 = const()[name = string("input_23_mode_0"), val = string("replicate")];
            fp16 const_2_to_fp16 = const()[name = string("const_2_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 256, 200]> input_23_cast_fp16 = pad(constant_val = const_2_to_fp16, mode = input_23_mode_0, pad = input_23_pad_0, x = input_21_cast_fp16)[name = string("input_23_cast_fp16")];
            string first_33_pad_type_0 = const()[name = string("first_33_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_33_dilations_0 = const()[name = string("first_33_dilations_0"), val = tensor<int32, [1]>([2])];
            int32 first_33_groups_0 = const()[name = string("first_33_groups_0"), val = int32(256)];
            tensor<int32, [1]> first_33_strides_0 = const()[name = string("first_33_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_33_pad_0 = const()[name = string("first_33_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [256, 1, 5]> text_encoder_convnext_convnext_2_dwconv_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_2_dwconv_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6372480)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_2_dwconv_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_2_dwconv_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6375104)))];
            tensor<fp16, [1, 256, 192]> first_33_cast_fp16 = conv(bias = text_encoder_convnext_convnext_2_dwconv_Conv_bias_to_fp16, dilations = first_33_dilations_0, groups = first_33_groups_0, pad = first_33_pad_0, pad_type = first_33_pad_type_0, strides = first_33_strides_0, weight = text_encoder_convnext_convnext_2_dwconv_Conv_weight_to_fp16, x = input_23_cast_fp16)[name = string("first_33_cast_fp16")];
            tensor<fp16, [1, 256, 192]> input_tensor_41_cast_fp16 = mul(x = first_33_cast_fp16, y = text_mask)[name = string("input_tensor_41_cast_fp16")];
            tensor<int32, [3]> var_608 = const()[name = string("op_608"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_43_axes_0 = const()[name = string("input_tensor_43_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_convnext_convnext_2_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_2_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6375680)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_2_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_2_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6376256)))];
            fp16 var_611_to_fp16 = const()[name = string("op_611_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 192, 256]> input_25_cast_fp16 = transpose(perm = var_608, x = input_tensor_41_cast_fp16)[name = string("transpose_42")];
            tensor<fp16, [1, 192, 256]> input_tensor_43_cast_fp16 = layer_norm(axes = input_tensor_43_axes_0, beta = text_encoder_convnext_convnext_2_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_611_to_fp16, gamma = text_encoder_convnext_convnext_2_norm_norm_LayerNormalization_weight_to_fp16, x = input_25_cast_fp16)[name = string("input_tensor_43_cast_fp16")];
            tensor<int32, [3]> var_620 = const()[name = string("op_620"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_35_pad_type_0 = const()[name = string("first_35_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_35_strides_0 = const()[name = string("first_35_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_35_pad_0 = const()[name = string("first_35_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_35_dilations_0 = const()[name = string("first_35_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_35_groups_0 = const()[name = string("first_35_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_convnext_convnext_2_pwconv1_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_2_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6376832)))];
            tensor<fp16, [1024]> text_encoder_convnext_convnext_2_pwconv1_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_2_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6901184)))];
            tensor<fp16, [1, 256, 192]> input_27_cast_fp16 = transpose(perm = var_620, x = input_tensor_43_cast_fp16)[name = string("transpose_41")];
            tensor<fp16, [1, 1024, 192]> first_35_cast_fp16 = conv(bias = text_encoder_convnext_convnext_2_pwconv1_Conv_bias_to_fp16, dilations = first_35_dilations_0, groups = first_35_groups_0, pad = first_35_pad_0, pad_type = first_35_pad_type_0, strides = first_35_strides_0, weight = text_encoder_convnext_convnext_2_pwconv1_Conv_weight_to_fp16, x = input_27_cast_fp16)[name = string("first_35_cast_fp16")];
            string input_29_mode_0 = const()[name = string("input_29_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 1024, 192]> input_29_cast_fp16 = gelu(mode = input_29_mode_0, x = first_35_cast_fp16)[name = string("input_29_cast_fp16")];
            string second_33_pad_type_0 = const()[name = string("second_33_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_33_strides_0 = const()[name = string("second_33_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_33_pad_0 = const()[name = string("second_33_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_33_dilations_0 = const()[name = string("second_33_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_33_groups_0 = const()[name = string("second_33_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> second_35_weight_0_to_fp16 = const()[name = string("second_35_weight_0_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6903296)))];
            tensor<fp16, [256]> second_35_bias_0_to_fp16 = const()[name = string("second_35_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7427648)))];
            tensor<fp16, [1, 256, 192]> second_35_cast_fp16 = conv(bias = second_35_bias_0_to_fp16, dilations = second_33_dilations_0, groups = second_33_groups_0, pad = second_33_pad_0, pad_type = second_33_pad_type_0, strides = second_33_strides_0, weight = second_35_weight_0_to_fp16, x = input_29_cast_fp16)[name = string("second_35_cast_fp16")];
            tensor<fp16, [1, 256, 192]> first_43_cast_fp16 = add(x = input_21_cast_fp16, y = second_35_cast_fp16)[name = string("first_43_cast_fp16")];
            tensor<fp16, [1, 256, 192]> first_45_cast_fp16 = mul(x = first_43_cast_fp16, y = text_mask)[name = string("first_45_cast_fp16")];
            tensor<fp16, [1, 256, 192]> input_31_cast_fp16 = mul(x = first_45_cast_fp16, y = text_mask)[name = string("input_31_cast_fp16")];
            tensor<int32, [6]> input_33_pad_0 = const()[name = string("input_33_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            string input_33_mode_0 = const()[name = string("input_33_mode_0"), val = string("replicate")];
            fp16 const_3_to_fp16 = const()[name = string("const_3_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 256, 200]> input_33_cast_fp16 = pad(constant_val = const_3_to_fp16, mode = input_33_mode_0, pad = input_33_pad_0, x = input_31_cast_fp16)[name = string("input_33_cast_fp16")];
            string first_47_pad_type_0 = const()[name = string("first_47_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_47_dilations_0 = const()[name = string("first_47_dilations_0"), val = tensor<int32, [1]>([2])];
            int32 first_47_groups_0 = const()[name = string("first_47_groups_0"), val = int32(256)];
            tensor<int32, [1]> first_47_strides_0 = const()[name = string("first_47_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_47_pad_0 = const()[name = string("first_47_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [256, 1, 5]> text_encoder_convnext_convnext_3_dwconv_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_3_dwconv_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7428224)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_3_dwconv_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_3_dwconv_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7430848)))];
            tensor<fp16, [1, 256, 192]> first_47_cast_fp16 = conv(bias = text_encoder_convnext_convnext_3_dwconv_Conv_bias_to_fp16, dilations = first_47_dilations_0, groups = first_47_groups_0, pad = first_47_pad_0, pad_type = first_47_pad_type_0, strides = first_47_strides_0, weight = text_encoder_convnext_convnext_3_dwconv_Conv_weight_to_fp16, x = input_33_cast_fp16)[name = string("first_47_cast_fp16")];
            tensor<fp16, [1, 256, 192]> input_tensor_55_cast_fp16 = mul(x = first_47_cast_fp16, y = text_mask)[name = string("input_tensor_55_cast_fp16")];
            tensor<int32, [3]> var_677 = const()[name = string("op_677"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_57_axes_0 = const()[name = string("input_tensor_57_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_convnext_convnext_3_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_3_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7431424)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_3_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_3_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7432000)))];
            fp16 var_680_to_fp16 = const()[name = string("op_680_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 192, 256]> input_35_cast_fp16 = transpose(perm = var_677, x = input_tensor_55_cast_fp16)[name = string("transpose_40")];
            tensor<fp16, [1, 192, 256]> input_tensor_57_cast_fp16 = layer_norm(axes = input_tensor_57_axes_0, beta = text_encoder_convnext_convnext_3_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_680_to_fp16, gamma = text_encoder_convnext_convnext_3_norm_norm_LayerNormalization_weight_to_fp16, x = input_35_cast_fp16)[name = string("input_tensor_57_cast_fp16")];
            tensor<int32, [3]> var_689 = const()[name = string("op_689"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_49_pad_type_0 = const()[name = string("first_49_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_49_strides_0 = const()[name = string("first_49_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_49_pad_0 = const()[name = string("first_49_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_49_dilations_0 = const()[name = string("first_49_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_49_groups_0 = const()[name = string("first_49_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_convnext_convnext_3_pwconv1_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_3_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7432576)))];
            tensor<fp16, [1024]> text_encoder_convnext_convnext_3_pwconv1_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_3_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7956928)))];
            tensor<fp16, [1, 256, 192]> input_37_cast_fp16 = transpose(perm = var_689, x = input_tensor_57_cast_fp16)[name = string("transpose_39")];
            tensor<fp16, [1, 1024, 192]> first_49_cast_fp16 = conv(bias = text_encoder_convnext_convnext_3_pwconv1_Conv_bias_to_fp16, dilations = first_49_dilations_0, groups = first_49_groups_0, pad = first_49_pad_0, pad_type = first_49_pad_type_0, strides = first_49_strides_0, weight = text_encoder_convnext_convnext_3_pwconv1_Conv_weight_to_fp16, x = input_37_cast_fp16)[name = string("first_49_cast_fp16")];
            string input_39_mode_0 = const()[name = string("input_39_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 1024, 192]> input_39_cast_fp16 = gelu(mode = input_39_mode_0, x = first_49_cast_fp16)[name = string("input_39_cast_fp16")];
            string second_45_pad_type_0 = const()[name = string("second_45_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_45_strides_0 = const()[name = string("second_45_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_45_pad_0 = const()[name = string("second_45_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_45_dilations_0 = const()[name = string("second_45_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_45_groups_0 = const()[name = string("second_45_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> second_47_weight_0_to_fp16 = const()[name = string("second_47_weight_0_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7959040)))];
            tensor<fp16, [256]> second_47_bias_0_to_fp16 = const()[name = string("second_47_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8483392)))];
            tensor<fp16, [1, 256, 192]> second_47_cast_fp16 = conv(bias = second_47_bias_0_to_fp16, dilations = second_45_dilations_0, groups = second_45_groups_0, pad = second_45_pad_0, pad_type = second_45_pad_type_0, strides = second_45_strides_0, weight = second_47_weight_0_to_fp16, x = input_39_cast_fp16)[name = string("second_47_cast_fp16")];
            tensor<fp16, [1, 256, 192]> first_57_cast_fp16 = add(x = input_31_cast_fp16, y = second_47_cast_fp16)[name = string("first_57_cast_fp16")];
            tensor<fp16, [1, 256, 192]> first_59_cast_fp16 = mul(x = first_57_cast_fp16, y = text_mask)[name = string("first_59_cast_fp16")];
            tensor<fp16, [1, 256, 192]> input_41_cast_fp16 = mul(x = first_59_cast_fp16, y = text_mask)[name = string("input_41_cast_fp16")];
            tensor<int32, [6]> input_43_pad_0 = const()[name = string("input_43_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 8, 8])];
            string input_43_mode_0 = const()[name = string("input_43_mode_0"), val = string("replicate")];
            fp16 const_4_to_fp16 = const()[name = string("const_4_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 256, 208]> input_43_cast_fp16 = pad(constant_val = const_4_to_fp16, mode = input_43_mode_0, pad = input_43_pad_0, x = input_41_cast_fp16)[name = string("input_43_cast_fp16")];
            string first_61_pad_type_0 = const()[name = string("first_61_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_61_dilations_0 = const()[name = string("first_61_dilations_0"), val = tensor<int32, [1]>([4])];
            int32 first_61_groups_0 = const()[name = string("first_61_groups_0"), val = int32(256)];
            tensor<int32, [1]> first_61_strides_0 = const()[name = string("first_61_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_61_pad_0 = const()[name = string("first_61_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [256, 1, 5]> text_encoder_convnext_convnext_4_dwconv_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_4_dwconv_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8483968)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_4_dwconv_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_4_dwconv_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8486592)))];
            tensor<fp16, [1, 256, 192]> first_61_cast_fp16 = conv(bias = text_encoder_convnext_convnext_4_dwconv_Conv_bias_to_fp16, dilations = first_61_dilations_0, groups = first_61_groups_0, pad = first_61_pad_0, pad_type = first_61_pad_type_0, strides = first_61_strides_0, weight = text_encoder_convnext_convnext_4_dwconv_Conv_weight_to_fp16, x = input_43_cast_fp16)[name = string("first_61_cast_fp16")];
            tensor<fp16, [1, 256, 192]> input_tensor_69_cast_fp16 = mul(x = first_61_cast_fp16, y = text_mask)[name = string("input_tensor_69_cast_fp16")];
            tensor<int32, [3]> var_746 = const()[name = string("op_746"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_71_axes_0 = const()[name = string("input_tensor_71_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_convnext_convnext_4_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_4_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8487168)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_4_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_4_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8487744)))];
            fp16 var_749_to_fp16 = const()[name = string("op_749_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 192, 256]> input_45_cast_fp16 = transpose(perm = var_746, x = input_tensor_69_cast_fp16)[name = string("transpose_38")];
            tensor<fp16, [1, 192, 256]> input_tensor_71_cast_fp16 = layer_norm(axes = input_tensor_71_axes_0, beta = text_encoder_convnext_convnext_4_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_749_to_fp16, gamma = text_encoder_convnext_convnext_4_norm_norm_LayerNormalization_weight_to_fp16, x = input_45_cast_fp16)[name = string("input_tensor_71_cast_fp16")];
            tensor<int32, [3]> var_758 = const()[name = string("op_758"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_63_pad_type_0 = const()[name = string("first_63_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_63_strides_0 = const()[name = string("first_63_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_63_pad_0 = const()[name = string("first_63_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_63_dilations_0 = const()[name = string("first_63_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_63_groups_0 = const()[name = string("first_63_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_convnext_convnext_4_pwconv1_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_4_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8488320)))];
            tensor<fp16, [1024]> text_encoder_convnext_convnext_4_pwconv1_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_4_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9012672)))];
            tensor<fp16, [1, 256, 192]> input_47_cast_fp16 = transpose(perm = var_758, x = input_tensor_71_cast_fp16)[name = string("transpose_37")];
            tensor<fp16, [1, 1024, 192]> first_63_cast_fp16 = conv(bias = text_encoder_convnext_convnext_4_pwconv1_Conv_bias_to_fp16, dilations = first_63_dilations_0, groups = first_63_groups_0, pad = first_63_pad_0, pad_type = first_63_pad_type_0, strides = first_63_strides_0, weight = text_encoder_convnext_convnext_4_pwconv1_Conv_weight_to_fp16, x = input_47_cast_fp16)[name = string("first_63_cast_fp16")];
            string input_49_mode_0 = const()[name = string("input_49_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 1024, 192]> input_49_cast_fp16 = gelu(mode = input_49_mode_0, x = first_63_cast_fp16)[name = string("input_49_cast_fp16")];
            string second_57_pad_type_0 = const()[name = string("second_57_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_57_strides_0 = const()[name = string("second_57_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_57_pad_0 = const()[name = string("second_57_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_57_dilations_0 = const()[name = string("second_57_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_57_groups_0 = const()[name = string("second_57_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> second_59_weight_0_to_fp16 = const()[name = string("second_59_weight_0_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9014784)))];
            tensor<fp16, [256]> second_59_bias_0_to_fp16 = const()[name = string("second_59_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9539136)))];
            tensor<fp16, [1, 256, 192]> second_59_cast_fp16 = conv(bias = second_59_bias_0_to_fp16, dilations = second_57_dilations_0, groups = second_57_groups_0, pad = second_57_pad_0, pad_type = second_57_pad_type_0, strides = second_57_strides_0, weight = second_59_weight_0_to_fp16, x = input_49_cast_fp16)[name = string("second_59_cast_fp16")];
            tensor<fp16, [1, 256, 192]> first_71_cast_fp16 = add(x = input_41_cast_fp16, y = second_59_cast_fp16)[name = string("first_71_cast_fp16")];
            tensor<fp16, [1, 256, 192]> first_73_cast_fp16 = mul(x = first_71_cast_fp16, y = text_mask)[name = string("first_73_cast_fp16")];
            tensor<fp16, [1, 256, 192]> input_51_cast_fp16 = mul(x = first_73_cast_fp16, y = text_mask)[name = string("input_51_cast_fp16")];
            tensor<int32, [6]> input_53_pad_0 = const()[name = string("input_53_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 8, 8])];
            string input_53_mode_0 = const()[name = string("input_53_mode_0"), val = string("replicate")];
            fp16 const_5_to_fp16 = const()[name = string("const_5_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 256, 208]> input_53_cast_fp16 = pad(constant_val = const_5_to_fp16, mode = input_53_mode_0, pad = input_53_pad_0, x = input_51_cast_fp16)[name = string("input_53_cast_fp16")];
            string first_75_pad_type_0 = const()[name = string("first_75_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_75_dilations_0 = const()[name = string("first_75_dilations_0"), val = tensor<int32, [1]>([4])];
            int32 first_75_groups_0 = const()[name = string("first_75_groups_0"), val = int32(256)];
            tensor<int32, [1]> first_75_strides_0 = const()[name = string("first_75_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_75_pad_0 = const()[name = string("first_75_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [256, 1, 5]> text_encoder_convnext_convnext_5_dwconv_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_5_dwconv_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9539712)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_5_dwconv_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_5_dwconv_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9542336)))];
            tensor<fp16, [1, 256, 192]> first_75_cast_fp16 = conv(bias = text_encoder_convnext_convnext_5_dwconv_Conv_bias_to_fp16, dilations = first_75_dilations_0, groups = first_75_groups_0, pad = first_75_pad_0, pad_type = first_75_pad_type_0, strides = first_75_strides_0, weight = text_encoder_convnext_convnext_5_dwconv_Conv_weight_to_fp16, x = input_53_cast_fp16)[name = string("first_75_cast_fp16")];
            tensor<fp16, [1, 256, 192]> input_tensor_83_cast_fp16 = mul(x = first_75_cast_fp16, y = text_mask)[name = string("input_tensor_83_cast_fp16")];
            tensor<int32, [3]> var_815 = const()[name = string("op_815"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_85_axes_0 = const()[name = string("input_tensor_85_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_convnext_convnext_5_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_5_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9542912)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_5_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_5_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9543488)))];
            fp16 var_818_to_fp16 = const()[name = string("op_818_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 192, 256]> input_55_cast_fp16 = transpose(perm = var_815, x = input_tensor_83_cast_fp16)[name = string("transpose_36")];
            tensor<fp16, [1, 192, 256]> input_tensor_85_cast_fp16 = layer_norm(axes = input_tensor_85_axes_0, beta = text_encoder_convnext_convnext_5_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_818_to_fp16, gamma = text_encoder_convnext_convnext_5_norm_norm_LayerNormalization_weight_to_fp16, x = input_55_cast_fp16)[name = string("input_tensor_85_cast_fp16")];
            tensor<int32, [3]> var_827 = const()[name = string("op_827"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_77_pad_type_0 = const()[name = string("first_77_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_77_strides_0 = const()[name = string("first_77_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_77_pad_0 = const()[name = string("first_77_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_77_dilations_0 = const()[name = string("first_77_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_77_groups_0 = const()[name = string("first_77_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_convnext_convnext_5_pwconv1_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_5_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9544064)))];
            tensor<fp16, [1024]> text_encoder_convnext_convnext_5_pwconv1_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_5_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10068416)))];
            tensor<fp16, [1, 256, 192]> input_57_cast_fp16 = transpose(perm = var_827, x = input_tensor_85_cast_fp16)[name = string("transpose_35")];
            tensor<fp16, [1, 1024, 192]> first_77_cast_fp16 = conv(bias = text_encoder_convnext_convnext_5_pwconv1_Conv_bias_to_fp16, dilations = first_77_dilations_0, groups = first_77_groups_0, pad = first_77_pad_0, pad_type = first_77_pad_type_0, strides = first_77_strides_0, weight = text_encoder_convnext_convnext_5_pwconv1_Conv_weight_to_fp16, x = input_57_cast_fp16)[name = string("first_77_cast_fp16")];
            string input_59_mode_0 = const()[name = string("input_59_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 1024, 192]> input_59_cast_fp16 = gelu(mode = input_59_mode_0, x = first_77_cast_fp16)[name = string("input_59_cast_fp16")];
            string second_69_pad_type_0 = const()[name = string("second_69_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_69_strides_0 = const()[name = string("second_69_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_69_pad_0 = const()[name = string("second_69_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_69_dilations_0 = const()[name = string("second_69_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_69_groups_0 = const()[name = string("second_69_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> second_71_weight_0_to_fp16 = const()[name = string("second_71_weight_0_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10070528)))];
            tensor<fp16, [256]> second_71_bias_0_to_fp16 = const()[name = string("second_71_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10594880)))];
            tensor<fp16, [1, 256, 192]> second_71_cast_fp16 = conv(bias = second_71_bias_0_to_fp16, dilations = second_69_dilations_0, groups = second_69_groups_0, pad = second_69_pad_0, pad_type = second_69_pad_type_0, strides = second_69_strides_0, weight = second_71_weight_0_to_fp16, x = input_59_cast_fp16)[name = string("second_71_cast_fp16")];
            tensor<fp16, [1, 256, 192]> first_85_cast_fp16 = add(x = input_51_cast_fp16, y = second_71_cast_fp16)[name = string("first_85_cast_fp16")];
            tensor<fp16, [1, 256, 192]> first_89_cast_fp16 = mul(x = first_85_cast_fp16, y = text_mask)[name = string("first_89_cast_fp16")];
            tensor<int32, [1]> first_87_axes_0 = const()[name = string("first_87_axes_0"), val = tensor<int32, [1]>([2])];
            tensor<fp16, [1, 1, 1, 192]> first_87_cast_fp16 = expand_dims(axes = first_87_axes_0, x = text_mask)[name = string("first_87_cast_fp16")];
            tensor<int32, [1]> second_73_axes_0 = const()[name = string("second_73_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 1, 192, 1]> second_73_cast_fp16 = expand_dims(axes = second_73_axes_0, x = text_mask)[name = string("second_73_cast_fp16")];
            tensor<fp16, [1, 1, 192, 192]> x_45_cast_fp16 = mul(x = first_87_cast_fp16, y = second_73_cast_fp16)[name = string("x_45_cast_fp16")];
            tensor<fp16, [1, 256, 192]> input_61_cast_fp16 = mul(x = first_89_cast_fp16, y = text_mask)[name = string("input_61_cast_fp16")];
            string input_tensor_97_pad_type_0 = const()[name = string("input_tensor_97_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_97_strides_0 = const()[name = string("input_tensor_97_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_97_pad_0 = const()[name = string("input_tensor_97_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_97_dilations_0 = const()[name = string("input_tensor_97_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_97_groups_0 = const()[name = string("input_tensor_97_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_0_conv_q_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_q_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10595456)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_0_conv_q_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_q_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10726592)))];
            tensor<fp16, [1, 256, 192]> input_tensor_97_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_0_conv_q_Conv_bias_to_fp16, dilations = input_tensor_97_dilations_0, groups = input_tensor_97_groups_0, pad = input_tensor_97_pad_0, pad_type = input_tensor_97_pad_type_0, strides = input_tensor_97_strides_0, weight = text_encoder_attn_encoder_attn_layers_0_conv_q_Conv_weight_to_fp16, x = input_61_cast_fp16)[name = string("input_tensor_97_cast_fp16")];
            string input_tensor_89_pad_type_0 = const()[name = string("input_tensor_89_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_89_strides_0 = const()[name = string("input_tensor_89_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_89_pad_0 = const()[name = string("input_tensor_89_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_89_dilations_0 = const()[name = string("input_tensor_89_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_89_groups_0 = const()[name = string("input_tensor_89_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_0_conv_k_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_k_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10727168)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_0_conv_k_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_k_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10858304)))];
            tensor<fp16, [1, 256, 192]> input_tensor_89_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_0_conv_k_Conv_bias_to_fp16, dilations = input_tensor_89_dilations_0, groups = input_tensor_89_groups_0, pad = input_tensor_89_pad_0, pad_type = input_tensor_89_pad_type_0, strides = input_tensor_89_strides_0, weight = text_encoder_attn_encoder_attn_layers_0_conv_k_Conv_weight_to_fp16, x = input_61_cast_fp16)[name = string("input_tensor_89_cast_fp16")];
            string input_tensor_109_pad_type_0 = const()[name = string("input_tensor_109_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_109_strides_0 = const()[name = string("input_tensor_109_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_109_pad_0 = const()[name = string("input_tensor_109_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_109_dilations_0 = const()[name = string("input_tensor_109_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_109_groups_0 = const()[name = string("input_tensor_109_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_0_conv_v_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_v_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10858880)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_0_conv_v_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_v_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10990016)))];
            tensor<fp16, [1, 256, 192]> input_tensor_109_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_0_conv_v_Conv_bias_to_fp16, dilations = input_tensor_109_dilations_0, groups = input_tensor_109_groups_0, pad = input_tensor_109_pad_0, pad_type = input_tensor_109_pad_type_0, strides = input_tensor_109_strides_0, weight = text_encoder_attn_encoder_attn_layers_0_conv_v_Conv_weight_to_fp16, x = input_61_cast_fp16)[name = string("input_tensor_109_cast_fp16")];
            tensor<int32, [4]> var_973 = const()[name = string("op_973"), val = tensor<int32, [4]>([1, 4, 64, 192])];
            tensor<fp16, [1, 4, 64, 192]> input_tensor_105_cast_fp16 = reshape(shape = var_973, x = input_tensor_97_cast_fp16)[name = string("input_tensor_105_cast_fp16")];
            tensor<int32, [4]> var_979 = const()[name = string("op_979"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [4]> var_1005 = const()[name = string("op_1005"), val = tensor<int32, [4]>([1, 4, 64, 192])];
            tensor<fp16, [1, 4, 64, 192]> y_1_cast_fp16 = reshape(shape = var_1005, x = input_tensor_89_cast_fp16)[name = string("y_1_cast_fp16")];
            tensor<int32, [4]> var_1017 = const()[name = string("op_1017"), val = tensor<int32, [4]>([1, 4, 64, 192])];
            tensor<fp16, [1, 4, 64, 192]> input_tensor_111_cast_fp16 = reshape(shape = var_1017, x = input_tensor_109_cast_fp16)[name = string("input_tensor_111_cast_fp16")];
            fp16 _inversed_x_25_y_0_to_fp16 = const()[name = string("_inversed_x_25_y_0_to_fp16"), val = fp16(0x1p-3)];
            tensor<fp16, [1, 4, 192, 64]> first_91_cast_fp16 = transpose(perm = var_979, x = input_tensor_105_cast_fp16)[name = string("transpose_34")];
            tensor<fp16, [1, 4, 192, 64]> _inversed_x_25_cast_fp16 = mul(x = first_91_cast_fp16, y = _inversed_x_25_y_0_to_fp16)[name = string("_inversed_x_25_cast_fp16")];
            bool first_107_transpose_x_0 = const()[name = string("first_107_transpose_x_0"), val = bool(false)];
            bool first_107_transpose_y_0 = const()[name = string("first_107_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 4, 192, 192]> first_107_cast_fp16 = matmul(transpose_x = first_107_transpose_x_0, transpose_y = first_107_transpose_y_0, x = _inversed_x_25_cast_fp16, y = y_1_cast_fp16)[name = string("first_107_cast_fp16")];
            bool input_tensor_143_transpose_x_0 = const()[name = string("input_tensor_143_transpose_x_0"), val = bool(false)];
            bool input_tensor_143_transpose_y_0 = const()[name = string("input_tensor_143_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 64, 383]> y_3_to_fp16 = const()[name = string("y_3_to_fp16"), val = tensor<fp16, [1, 1, 64, 383]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(18472448)))];
            tensor<fp16, [1, 4, 192, 383]> input_tensor_143_cast_fp16 = matmul(transpose_x = input_tensor_143_transpose_x_0, transpose_y = input_tensor_143_transpose_y_0, x = _inversed_x_25_cast_fp16, y = y_3_to_fp16)[name = string("input_tensor_143_cast_fp16")];
            tensor<int32, [8]> input_tensor_165_pad_0 = const()[name = string("input_tensor_165_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 1])];
            string input_tensor_165_mode_0 = const()[name = string("input_tensor_165_mode_0"), val = string("constant")];
            fp16 const_23_to_fp16 = const()[name = string("const_23_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 192, 384]> input_tensor_165_cast_fp16 = pad(constant_val = const_23_to_fp16, mode = input_tensor_165_mode_0, pad = input_tensor_165_pad_0, x = input_tensor_143_cast_fp16)[name = string("input_tensor_165_cast_fp16")];
            tensor<int32, [3]> var_1140 = const()[name = string("op_1140"), val = tensor<int32, [3]>([1, 4, 73728])];
            tensor<fp16, [1, 4, 73728]> input_69_cast_fp16 = reshape(shape = var_1140, x = input_tensor_165_cast_fp16)[name = string("input_69_cast_fp16")];
            tensor<int32, [6]> input_tensor_187_pad_0 = const()[name = string("input_tensor_187_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 0, 191])];
            string input_tensor_187_mode_0 = const()[name = string("input_tensor_187_mode_0"), val = string("constant")];
            fp16 const_24_to_fp16 = const()[name = string("const_24_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 73919]> input_tensor_187_cast_fp16 = pad(constant_val = const_24_to_fp16, mode = input_tensor_187_mode_0, pad = input_tensor_187_pad_0, x = input_69_cast_fp16)[name = string("input_tensor_187_cast_fp16")];
            tensor<int32, [4]> var_1175 = const()[name = string("op_1175"), val = tensor<int32, [4]>([1, 4, 193, 383])];
            tensor<fp16, [1, 4, 193, 383]> x_41_cast_fp16 = reshape(shape = var_1175, x = input_tensor_187_cast_fp16)[name = string("x_41_cast_fp16")];
            tensor<int32, [4]> x_43_begin_0 = const()[name = string("x_43_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> x_43_end_0 = const()[name = string("x_43_end_0"), val = tensor<int32, [4]>([1, 4, 192, 383])];
            tensor<bool, [4]> x_43_end_mask_0 = const()[name = string("x_43_end_mask_0"), val = tensor<bool, [4]>([true, true, false, true])];
            tensor<fp16, [1, 4, 192, 383]> x_43_cast_fp16 = slice_by_index(begin = x_43_begin_0, end = x_43_end_0, end_mask = x_43_end_mask_0, x = x_41_cast_fp16)[name = string("x_43_cast_fp16")];
            tensor<int32, [4]> second_97_begin_0 = const()[name = string("second_97_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 191])];
            tensor<int32, [4]> second_97_end_0 = const()[name = string("second_97_end_0"), val = tensor<int32, [4]>([1, 4, 192, 1])];
            tensor<bool, [4]> second_97_end_mask_0 = const()[name = string("second_97_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 192, 192]> second_97_cast_fp16 = slice_by_index(begin = second_97_begin_0, end = second_97_end_0, end_mask = second_97_end_mask_0, x = x_43_cast_fp16)[name = string("second_97_cast_fp16")];
            tensor<fp16, [1, 4, 192, 192]> y_7_cast_fp16 = add(x = first_107_cast_fp16, y = second_97_cast_fp16)[name = string("y_7_cast_fp16")];
            fp16 text_encoder_attn_encoder_attn_layers_0_Constant_87_value_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_Constant_87_value_to_fp16"), val = fp16(0x0p+0)];
            tensor<bool, [1, 1, 192, 192]> input_tensor_189_cast_fp16 = equal(x = x_45_cast_fp16, y = text_encoder_attn_encoder_attn_layers_0_Constant_87_value_to_fp16)[name = string("input_tensor_189_cast_fp16")];
            tensor<int32, [4]> condition_1_after_broadcast_reps_0 = const()[name = string("condition_1_after_broadcast_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<bool, [1, 4, 192, 192]> condition_1_after_broadcast = tile(reps = condition_1_after_broadcast_reps_0, x = input_tensor_189_cast_fp16)[name = string("condition_1_after_broadcast")];
            tensor<fp16, [1, 4, 192, 192]> text_encoder_attn_encoder_attn_layers_0_Constant_88_value_after_broadcast_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_Constant_88_value_after_broadcast_to_fp16"), val = tensor<fp16, [1, 4, 192, 192]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(18521536)))];
            tensor<fp16, [1, 4, 192, 192]> input_71_cast_fp16 = select(a = text_encoder_attn_encoder_attn_layers_0_Constant_88_value_after_broadcast_to_fp16, b = y_7_cast_fp16, cond = condition_1_after_broadcast)[name = string("input_71_cast_fp16")];
            int32 var_1218 = const()[name = string("op_1218"), val = int32(-1)];
            tensor<fp16, [1, 4, 192, 192]> x_49_cast_fp16 = softmax(axis = var_1218, x = input_71_cast_fp16)[name = string("x_49_cast_fp16")];
            bool first_119_transpose_x_1 = const()[name = string("first_119_transpose_x_1"), val = bool(false)];
            bool first_119_transpose_y_1 = const()[name = string("first_119_transpose_y_1"), val = bool(true)];
            tensor<fp16, [1, 4, 192, 64]> first_119_cast_fp16 = matmul(transpose_x = first_119_transpose_x_1, transpose_y = first_119_transpose_y_1, x = x_49_cast_fp16, y = input_tensor_111_cast_fp16)[name = string("first_119_cast_fp16")];
            tensor<int32, [8]> input_tensor_219_pad_0 = const()[name = string("input_tensor_219_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 191])];
            string input_tensor_219_mode_0 = const()[name = string("input_tensor_219_mode_0"), val = string("constant")];
            fp16 const_31_to_fp16 = const()[name = string("const_31_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 192, 383]> input_tensor_219_cast_fp16 = pad(constant_val = const_31_to_fp16, mode = input_tensor_219_mode_0, pad = input_tensor_219_pad_0, x = x_49_cast_fp16)[name = string("input_tensor_219_cast_fp16")];
            tensor<int32, [3]> var_1292 = const()[name = string("op_1292"), val = tensor<int32, [3]>([1, 4, 73536])];
            tensor<fp16, [1, 4, 73536]> input_73_cast_fp16 = reshape(shape = var_1292, x = input_tensor_219_cast_fp16)[name = string("input_73_cast_fp16")];
            tensor<int32, [6]> input_tensor_237_pad_0 = const()[name = string("input_tensor_237_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 192, 0])];
            string input_tensor_237_mode_0 = const()[name = string("input_tensor_237_mode_0"), val = string("constant")];
            fp16 const_32_to_fp16 = const()[name = string("const_32_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 73728]> input_tensor_237_cast_fp16 = pad(constant_val = const_32_to_fp16, mode = input_tensor_237_mode_0, pad = input_tensor_237_pad_0, x = input_73_cast_fp16)[name = string("input_tensor_237_cast_fp16")];
            tensor<int32, [4]> var_1322 = const()[name = string("op_1322"), val = tensor<int32, [4]>([1, 4, 192, 384])];
            tensor<fp16, [1, 4, 192, 384]> x_59_cast_fp16 = reshape(shape = var_1322, x = input_tensor_237_cast_fp16)[name = string("x_59_cast_fp16")];
            tensor<int32, [4]> x_67_begin_0 = const()[name = string("x_67_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 1])];
            tensor<int32, [4]> x_67_end_0 = const()[name = string("x_67_end_0"), val = tensor<int32, [4]>([1, 4, 192, 1])];
            tensor<bool, [4]> x_67_end_mask_0 = const()[name = string("x_67_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 192, 383]> x_67_cast_fp16 = slice_by_index(begin = x_67_begin_0, end = x_67_end_0, end_mask = x_67_end_mask_0, x = x_59_cast_fp16)[name = string("x_67_cast_fp16")];
            bool second_111_transpose_x_0 = const()[name = string("second_111_transpose_x_0"), val = bool(false)];
            bool second_111_transpose_y_0 = const()[name = string("second_111_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 383, 64]> y_11_to_fp16 = const()[name = string("y_11_to_fp16"), val = tensor<fp16, [1, 1, 383, 64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(18816512)))];
            tensor<fp16, [1, 4, 192, 64]> second_111_cast_fp16 = matmul(transpose_x = second_111_transpose_x_0, transpose_y = second_111_transpose_y_0, x = x_67_cast_fp16, y = y_11_to_fp16)[name = string("second_111_cast_fp16")];
            tensor<fp16, [1, 4, 192, 64]> input_tensor_255_cast_fp16 = add(x = first_119_cast_fp16, y = second_111_cast_fp16)[name = string("input_tensor_255_cast_fp16")];
            tensor<int32, [4]> var_1369 = const()[name = string("op_1369"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [3]> var_1388 = const()[name = string("op_1388"), val = tensor<int32, [3]>([1, 256, 192])];
            tensor<fp16, [1, 4, 64, 192]> input_tensor_259_cast_fp16 = transpose(perm = var_1369, x = input_tensor_255_cast_fp16)[name = string("transpose_33")];
            tensor<fp16, [1, 256, 192]> input_77_cast_fp16 = reshape(shape = var_1388, x = input_tensor_259_cast_fp16)[name = string("input_77_cast_fp16")];
            string second_113_pad_type_0 = const()[name = string("second_113_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_113_strides_0 = const()[name = string("second_113_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_113_pad_0 = const()[name = string("second_113_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_113_dilations_0 = const()[name = string("second_113_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_113_groups_0 = const()[name = string("second_113_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_0_conv_o_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_o_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11000768)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_0_conv_o_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_o_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11131904)))];
            tensor<fp16, [1, 256, 192]> second_113_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_0_conv_o_Conv_bias_to_fp16, dilations = second_113_dilations_0, groups = second_113_groups_0, pad = second_113_pad_0, pad_type = second_113_pad_type_0, strides = second_113_strides_0, weight = text_encoder_attn_encoder_attn_layers_0_conv_o_Conv_weight_to_fp16, x = input_77_cast_fp16)[name = string("second_113_cast_fp16")];
            tensor<fp16, [1, 256, 192]> input_tensor_261_cast_fp16 = add(x = input_61_cast_fp16, y = second_113_cast_fp16)[name = string("input_tensor_261_cast_fp16")];
            tensor<int32, [3]> var_1406 = const()[name = string("op_1406"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_263_axes_0 = const()[name = string("input_tensor_263_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_0_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_0_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11132480)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_0_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_0_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11133056)))];
            fp16 var_1409_to_fp16 = const()[name = string("op_1409_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 192, 256]> input_79_cast_fp16 = transpose(perm = var_1406, x = input_tensor_261_cast_fp16)[name = string("transpose_32")];
            tensor<fp16, [1, 192, 256]> input_tensor_263_cast_fp16 = layer_norm(axes = input_tensor_263_axes_0, beta = text_encoder_attn_encoder_norm_layers_1_0_norm_LayerNormalization_bias_to_fp16, epsilon = var_1409_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_1_0_norm_LayerNormalization_weight_to_fp16, x = input_79_cast_fp16)[name = string("input_tensor_263_cast_fp16")];
            tensor<int32, [3]> var_1418 = const()[name = string("op_1418"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 256, 192]> first_121_cast_fp16 = transpose(perm = var_1418, x = input_tensor_263_cast_fp16)[name = string("transpose_31")];
            tensor<fp16, [1, 256, 192]> input_81_cast_fp16 = mul(x = first_121_cast_fp16, y = text_mask)[name = string("input_81_cast_fp16")];
            string input_83_pad_type_0 = const()[name = string("input_83_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_83_strides_0 = const()[name = string("input_83_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_83_pad_0 = const()[name = string("input_83_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_83_dilations_0 = const()[name = string("input_83_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_83_groups_0 = const()[name = string("input_83_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_attn_encoder_ffn_layers_0_conv_1_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_0_conv_1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11133632)))];
            tensor<fp16, [1024]> text_encoder_attn_encoder_ffn_layers_0_conv_1_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_0_conv_1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11657984)))];
            tensor<fp16, [1, 1024, 192]> input_83_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_0_conv_1_Conv_bias_to_fp16, dilations = input_83_dilations_0, groups = input_83_groups_0, pad = input_83_pad_0, pad_type = input_83_pad_type_0, strides = input_83_strides_0, weight = text_encoder_attn_encoder_ffn_layers_0_conv_1_Conv_weight_to_fp16, x = input_81_cast_fp16)[name = string("input_83_cast_fp16")];
            tensor<fp16, [1, 1024, 192]> first_123_cast_fp16 = relu(x = input_83_cast_fp16)[name = string("first_123_cast_fp16")];
            tensor<fp16, [1, 1024, 192]> input_85_cast_fp16 = mul(x = first_123_cast_fp16, y = text_mask)[name = string("input_85_cast_fp16")];
            string first_125_pad_type_0 = const()[name = string("first_125_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_125_strides_0 = const()[name = string("first_125_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_125_pad_0 = const()[name = string("first_125_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_125_dilations_0 = const()[name = string("first_125_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_125_groups_0 = const()[name = string("first_125_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> text_encoder_attn_encoder_ffn_layers_0_conv_2_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_0_conv_2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11660096)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_ffn_layers_0_conv_2_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_0_conv_2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12184448)))];
            tensor<fp16, [1, 256, 192]> first_125_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_0_conv_2_Conv_bias_to_fp16, dilations = first_125_dilations_0, groups = first_125_groups_0, pad = first_125_pad_0, pad_type = first_125_pad_type_0, strides = first_125_strides_0, weight = text_encoder_attn_encoder_ffn_layers_0_conv_2_Conv_weight_to_fp16, x = input_85_cast_fp16)[name = string("first_125_cast_fp16")];
            tensor<fp16, [1, 256, 192]> second_115_cast_fp16 = mul(x = first_125_cast_fp16, y = text_mask)[name = string("second_115_cast_fp16")];
            tensor<fp16, [1, 256, 192]> input_tensor_265_cast_fp16 = add(x = first_121_cast_fp16, y = second_115_cast_fp16)[name = string("input_tensor_265_cast_fp16")];
            tensor<int32, [3]> var_1451 = const()[name = string("op_1451"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_267_axes_0 = const()[name = string("input_tensor_267_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_0_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_0_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12185024)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_0_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_0_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12185600)))];
            fp16 var_1454_to_fp16 = const()[name = string("op_1454_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 192, 256]> input_87_cast_fp16 = transpose(perm = var_1451, x = input_tensor_265_cast_fp16)[name = string("transpose_30")];
            tensor<fp16, [1, 192, 256]> input_tensor_267_cast_fp16 = layer_norm(axes = input_tensor_267_axes_0, beta = text_encoder_attn_encoder_norm_layers_2_0_norm_LayerNormalization_bias_to_fp16, epsilon = var_1454_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_2_0_norm_LayerNormalization_weight_to_fp16, x = input_87_cast_fp16)[name = string("input_tensor_267_cast_fp16")];
            tensor<int32, [3]> var_1463 = const()[name = string("op_1463"), val = tensor<int32, [3]>([0, 2, 1])];
            string input_tensor_277_pad_type_0 = const()[name = string("input_tensor_277_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_277_strides_0 = const()[name = string("input_tensor_277_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_277_pad_0 = const()[name = string("input_tensor_277_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_277_dilations_0 = const()[name = string("input_tensor_277_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_277_groups_0 = const()[name = string("input_tensor_277_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_1_conv_q_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_q_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12186176)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_1_conv_q_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_q_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12317312)))];
            tensor<fp16, [1, 256, 192]> input_89_cast_fp16 = transpose(perm = var_1463, x = input_tensor_267_cast_fp16)[name = string("transpose_29")];
            tensor<fp16, [1, 256, 192]> input_tensor_277_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_1_conv_q_Conv_bias_to_fp16, dilations = input_tensor_277_dilations_0, groups = input_tensor_277_groups_0, pad = input_tensor_277_pad_0, pad_type = input_tensor_277_pad_type_0, strides = input_tensor_277_strides_0, weight = text_encoder_attn_encoder_attn_layers_1_conv_q_Conv_weight_to_fp16, x = input_89_cast_fp16)[name = string("input_tensor_277_cast_fp16")];
            string input_tensor_269_pad_type_0 = const()[name = string("input_tensor_269_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_269_strides_0 = const()[name = string("input_tensor_269_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_269_pad_0 = const()[name = string("input_tensor_269_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_269_dilations_0 = const()[name = string("input_tensor_269_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_269_groups_0 = const()[name = string("input_tensor_269_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_1_conv_k_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_k_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12317888)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_1_conv_k_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_k_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12449024)))];
            tensor<fp16, [1, 256, 192]> input_tensor_269_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_1_conv_k_Conv_bias_to_fp16, dilations = input_tensor_269_dilations_0, groups = input_tensor_269_groups_0, pad = input_tensor_269_pad_0, pad_type = input_tensor_269_pad_type_0, strides = input_tensor_269_strides_0, weight = text_encoder_attn_encoder_attn_layers_1_conv_k_Conv_weight_to_fp16, x = input_89_cast_fp16)[name = string("input_tensor_269_cast_fp16")];
            string input_tensor_289_pad_type_0 = const()[name = string("input_tensor_289_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_289_strides_0 = const()[name = string("input_tensor_289_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_289_pad_0 = const()[name = string("input_tensor_289_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_289_dilations_0 = const()[name = string("input_tensor_289_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_289_groups_0 = const()[name = string("input_tensor_289_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_1_conv_v_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_v_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12449600)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_1_conv_v_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_v_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12580736)))];
            tensor<fp16, [1, 256, 192]> input_tensor_289_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_1_conv_v_Conv_bias_to_fp16, dilations = input_tensor_289_dilations_0, groups = input_tensor_289_groups_0, pad = input_tensor_289_pad_0, pad_type = input_tensor_289_pad_type_0, strides = input_tensor_289_strides_0, weight = text_encoder_attn_encoder_attn_layers_1_conv_v_Conv_weight_to_fp16, x = input_89_cast_fp16)[name = string("input_tensor_289_cast_fp16")];
            tensor<int32, [4]> var_1571 = const()[name = string("op_1571"), val = tensor<int32, [4]>([1, 4, 64, 192])];
            tensor<fp16, [1, 4, 64, 192]> input_tensor_285_cast_fp16 = reshape(shape = var_1571, x = input_tensor_277_cast_fp16)[name = string("input_tensor_285_cast_fp16")];
            tensor<int32, [4]> var_1577 = const()[name = string("op_1577"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [4]> var_1603 = const()[name = string("op_1603"), val = tensor<int32, [4]>([1, 4, 64, 192])];
            tensor<fp16, [1, 4, 64, 192]> y_13_cast_fp16 = reshape(shape = var_1603, x = input_tensor_269_cast_fp16)[name = string("y_13_cast_fp16")];
            tensor<int32, [4]> var_1615 = const()[name = string("op_1615"), val = tensor<int32, [4]>([1, 4, 64, 192])];
            tensor<fp16, [1, 4, 64, 192]> input_tensor_291_cast_fp16 = reshape(shape = var_1615, x = input_tensor_289_cast_fp16)[name = string("input_tensor_291_cast_fp16")];
            fp16 _inversed_x_69_y_0_to_fp16 = const()[name = string("_inversed_x_69_y_0_to_fp16"), val = fp16(0x1p-3)];
            tensor<fp16, [1, 4, 192, 64]> first_127_cast_fp16 = transpose(perm = var_1577, x = input_tensor_285_cast_fp16)[name = string("transpose_28")];
            tensor<fp16, [1, 4, 192, 64]> _inversed_x_69_cast_fp16 = mul(x = first_127_cast_fp16, y = _inversed_x_69_y_0_to_fp16)[name = string("_inversed_x_69_cast_fp16")];
            bool first_143_transpose_x_0 = const()[name = string("first_143_transpose_x_0"), val = bool(false)];
            bool first_143_transpose_y_0 = const()[name = string("first_143_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 4, 192, 192]> first_143_cast_fp16 = matmul(transpose_x = first_143_transpose_x_0, transpose_y = first_143_transpose_y_0, x = _inversed_x_69_cast_fp16, y = y_13_cast_fp16)[name = string("first_143_cast_fp16")];
            bool input_tensor_323_transpose_x_0 = const()[name = string("input_tensor_323_transpose_x_0"), val = bool(false)];
            bool input_tensor_323_transpose_y_0 = const()[name = string("input_tensor_323_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 64, 383]> y_15_to_fp16 = const()[name = string("y_15_to_fp16"), val = tensor<fp16, [1, 1, 64, 383]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(18865600)))];
            tensor<fp16, [1, 4, 192, 383]> input_tensor_323_cast_fp16 = matmul(transpose_x = input_tensor_323_transpose_x_0, transpose_y = input_tensor_323_transpose_y_0, x = _inversed_x_69_cast_fp16, y = y_15_to_fp16)[name = string("input_tensor_323_cast_fp16")];
            tensor<int32, [8]> input_tensor_345_pad_0 = const()[name = string("input_tensor_345_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 1])];
            string input_tensor_345_mode_0 = const()[name = string("input_tensor_345_mode_0"), val = string("constant")];
            fp16 const_51_to_fp16 = const()[name = string("const_51_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 192, 384]> input_tensor_345_cast_fp16 = pad(constant_val = const_51_to_fp16, mode = input_tensor_345_mode_0, pad = input_tensor_345_pad_0, x = input_tensor_323_cast_fp16)[name = string("input_tensor_345_cast_fp16")];
            tensor<int32, [3]> var_1738 = const()[name = string("op_1738"), val = tensor<int32, [3]>([1, 4, 73728])];
            tensor<fp16, [1, 4, 73728]> input_97_cast_fp16 = reshape(shape = var_1738, x = input_tensor_345_cast_fp16)[name = string("input_97_cast_fp16")];
            tensor<int32, [6]> input_tensor_367_pad_0 = const()[name = string("input_tensor_367_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 0, 191])];
            string input_tensor_367_mode_0 = const()[name = string("input_tensor_367_mode_0"), val = string("constant")];
            fp16 const_52_to_fp16 = const()[name = string("const_52_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 73919]> input_tensor_367_cast_fp16 = pad(constant_val = const_52_to_fp16, mode = input_tensor_367_mode_0, pad = input_tensor_367_pad_0, x = input_97_cast_fp16)[name = string("input_tensor_367_cast_fp16")];
            tensor<int32, [4]> var_1773 = const()[name = string("op_1773"), val = tensor<int32, [4]>([1, 4, 193, 383])];
            tensor<fp16, [1, 4, 193, 383]> x_85_cast_fp16 = reshape(shape = var_1773, x = input_tensor_367_cast_fp16)[name = string("x_85_cast_fp16")];
            tensor<int32, [4]> x_87_begin_0 = const()[name = string("x_87_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> x_87_end_0 = const()[name = string("x_87_end_0"), val = tensor<int32, [4]>([1, 4, 192, 383])];
            tensor<bool, [4]> x_87_end_mask_0 = const()[name = string("x_87_end_mask_0"), val = tensor<bool, [4]>([true, true, false, true])];
            tensor<fp16, [1, 4, 192, 383]> x_87_cast_fp16 = slice_by_index(begin = x_87_begin_0, end = x_87_end_0, end_mask = x_87_end_mask_0, x = x_85_cast_fp16)[name = string("x_87_cast_fp16")];
            tensor<int32, [4]> second_139_begin_0 = const()[name = string("second_139_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 191])];
            tensor<int32, [4]> second_139_end_0 = const()[name = string("second_139_end_0"), val = tensor<int32, [4]>([1, 4, 192, 1])];
            tensor<bool, [4]> second_139_end_mask_0 = const()[name = string("second_139_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 192, 192]> second_139_cast_fp16 = slice_by_index(begin = second_139_begin_0, end = second_139_end_0, end_mask = second_139_end_mask_0, x = x_87_cast_fp16)[name = string("second_139_cast_fp16")];
            tensor<fp16, [1, 4, 192, 192]> y_17_cast_fp16 = add(x = first_143_cast_fp16, y = second_139_cast_fp16)[name = string("y_17_cast_fp16")];
            tensor<fp16, [1, 4, 192, 192]> input_99_cast_fp16 = select(a = text_encoder_attn_encoder_attn_layers_0_Constant_88_value_after_broadcast_to_fp16, b = y_17_cast_fp16, cond = condition_1_after_broadcast)[name = string("input_99_cast_fp16")];
            int32 var_1815 = const()[name = string("op_1815"), val = int32(-1)];
            tensor<fp16, [1, 4, 192, 192]> x_91_cast_fp16 = softmax(axis = var_1815, x = input_99_cast_fp16)[name = string("x_91_cast_fp16")];
            bool first_155_transpose_x_1 = const()[name = string("first_155_transpose_x_1"), val = bool(false)];
            bool first_155_transpose_y_1 = const()[name = string("first_155_transpose_y_1"), val = bool(true)];
            tensor<fp16, [1, 4, 192, 64]> first_155_cast_fp16 = matmul(transpose_x = first_155_transpose_x_1, transpose_y = first_155_transpose_y_1, x = x_91_cast_fp16, y = input_tensor_291_cast_fp16)[name = string("first_155_cast_fp16")];
            tensor<int32, [8]> input_tensor_397_pad_0 = const()[name = string("input_tensor_397_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 191])];
            string input_tensor_397_mode_0 = const()[name = string("input_tensor_397_mode_0"), val = string("constant")];
            fp16 const_59_to_fp16 = const()[name = string("const_59_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 192, 383]> input_tensor_397_cast_fp16 = pad(constant_val = const_59_to_fp16, mode = input_tensor_397_mode_0, pad = input_tensor_397_pad_0, x = x_91_cast_fp16)[name = string("input_tensor_397_cast_fp16")];
            tensor<int32, [3]> var_1889 = const()[name = string("op_1889"), val = tensor<int32, [3]>([1, 4, 73536])];
            tensor<fp16, [1, 4, 73536]> input_101_cast_fp16 = reshape(shape = var_1889, x = input_tensor_397_cast_fp16)[name = string("input_101_cast_fp16")];
            tensor<int32, [6]> input_tensor_415_pad_0 = const()[name = string("input_tensor_415_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 192, 0])];
            string input_tensor_415_mode_0 = const()[name = string("input_tensor_415_mode_0"), val = string("constant")];
            fp16 const_60_to_fp16 = const()[name = string("const_60_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 73728]> input_tensor_415_cast_fp16 = pad(constant_val = const_60_to_fp16, mode = input_tensor_415_mode_0, pad = input_tensor_415_pad_0, x = input_101_cast_fp16)[name = string("input_tensor_415_cast_fp16")];
            tensor<int32, [4]> var_1919 = const()[name = string("op_1919"), val = tensor<int32, [4]>([1, 4, 192, 384])];
            tensor<fp16, [1, 4, 192, 384]> x_101_cast_fp16 = reshape(shape = var_1919, x = input_tensor_415_cast_fp16)[name = string("x_101_cast_fp16")];
            tensor<int32, [4]> x_109_begin_0 = const()[name = string("x_109_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 1])];
            tensor<int32, [4]> x_109_end_0 = const()[name = string("x_109_end_0"), val = tensor<int32, [4]>([1, 4, 192, 1])];
            tensor<bool, [4]> x_109_end_mask_0 = const()[name = string("x_109_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 192, 383]> x_109_cast_fp16 = slice_by_index(begin = x_109_begin_0, end = x_109_end_0, end_mask = x_109_end_mask_0, x = x_101_cast_fp16)[name = string("x_109_cast_fp16")];
            bool second_153_transpose_x_0 = const()[name = string("second_153_transpose_x_0"), val = bool(false)];
            bool second_153_transpose_y_0 = const()[name = string("second_153_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 383, 64]> y_21_to_fp16 = const()[name = string("y_21_to_fp16"), val = tensor<fp16, [1, 1, 383, 64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(18914688)))];
            tensor<fp16, [1, 4, 192, 64]> second_153_cast_fp16 = matmul(transpose_x = second_153_transpose_x_0, transpose_y = second_153_transpose_y_0, x = x_109_cast_fp16, y = y_21_to_fp16)[name = string("second_153_cast_fp16")];
            tensor<fp16, [1, 4, 192, 64]> input_tensor_433_cast_fp16 = add(x = first_155_cast_fp16, y = second_153_cast_fp16)[name = string("input_tensor_433_cast_fp16")];
            tensor<int32, [4]> var_1966 = const()[name = string("op_1966"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [3]> var_1985 = const()[name = string("op_1985"), val = tensor<int32, [3]>([1, 256, 192])];
            tensor<fp16, [1, 4, 64, 192]> input_tensor_437_cast_fp16 = transpose(perm = var_1966, x = input_tensor_433_cast_fp16)[name = string("transpose_27")];
            tensor<fp16, [1, 256, 192]> input_105_cast_fp16 = reshape(shape = var_1985, x = input_tensor_437_cast_fp16)[name = string("input_105_cast_fp16")];
            string second_155_pad_type_0 = const()[name = string("second_155_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_155_strides_0 = const()[name = string("second_155_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_155_pad_0 = const()[name = string("second_155_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_155_dilations_0 = const()[name = string("second_155_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_155_groups_0 = const()[name = string("second_155_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_1_conv_o_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_o_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12589376)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_1_conv_o_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_o_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12720512)))];
            tensor<fp16, [1, 256, 192]> second_155_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_1_conv_o_Conv_bias_to_fp16, dilations = second_155_dilations_0, groups = second_155_groups_0, pad = second_155_pad_0, pad_type = second_155_pad_type_0, strides = second_155_strides_0, weight = text_encoder_attn_encoder_attn_layers_1_conv_o_Conv_weight_to_fp16, x = input_105_cast_fp16)[name = string("second_155_cast_fp16")];
            tensor<fp16, [1, 256, 192]> input_tensor_439_cast_fp16 = add(x = input_89_cast_fp16, y = second_155_cast_fp16)[name = string("input_tensor_439_cast_fp16")];
            tensor<int32, [3]> var_2003 = const()[name = string("op_2003"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_441_axes_0 = const()[name = string("input_tensor_441_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_1_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_1_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12721088)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_1_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_1_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12721664)))];
            fp16 var_2006_to_fp16 = const()[name = string("op_2006_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 192, 256]> input_107_cast_fp16 = transpose(perm = var_2003, x = input_tensor_439_cast_fp16)[name = string("transpose_26")];
            tensor<fp16, [1, 192, 256]> input_tensor_441_cast_fp16 = layer_norm(axes = input_tensor_441_axes_0, beta = text_encoder_attn_encoder_norm_layers_1_1_norm_LayerNormalization_bias_to_fp16, epsilon = var_2006_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_1_1_norm_LayerNormalization_weight_to_fp16, x = input_107_cast_fp16)[name = string("input_tensor_441_cast_fp16")];
            tensor<int32, [3]> var_2015 = const()[name = string("op_2015"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 256, 192]> first_157_cast_fp16 = transpose(perm = var_2015, x = input_tensor_441_cast_fp16)[name = string("transpose_25")];
            tensor<fp16, [1, 256, 192]> input_109_cast_fp16 = mul(x = first_157_cast_fp16, y = text_mask)[name = string("input_109_cast_fp16")];
            string input_111_pad_type_0 = const()[name = string("input_111_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_111_strides_0 = const()[name = string("input_111_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_111_pad_0 = const()[name = string("input_111_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_111_dilations_0 = const()[name = string("input_111_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_111_groups_0 = const()[name = string("input_111_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_attn_encoder_ffn_layers_1_conv_1_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_1_conv_1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12722240)))];
            tensor<fp16, [1024]> text_encoder_attn_encoder_ffn_layers_1_conv_1_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_1_conv_1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13246592)))];
            tensor<fp16, [1, 1024, 192]> input_111_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_1_conv_1_Conv_bias_to_fp16, dilations = input_111_dilations_0, groups = input_111_groups_0, pad = input_111_pad_0, pad_type = input_111_pad_type_0, strides = input_111_strides_0, weight = text_encoder_attn_encoder_ffn_layers_1_conv_1_Conv_weight_to_fp16, x = input_109_cast_fp16)[name = string("input_111_cast_fp16")];
            tensor<fp16, [1, 1024, 192]> first_159_cast_fp16 = relu(x = input_111_cast_fp16)[name = string("first_159_cast_fp16")];
            tensor<fp16, [1, 1024, 192]> input_113_cast_fp16 = mul(x = first_159_cast_fp16, y = text_mask)[name = string("input_113_cast_fp16")];
            string first_161_pad_type_0 = const()[name = string("first_161_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_161_strides_0 = const()[name = string("first_161_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_161_pad_0 = const()[name = string("first_161_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_161_dilations_0 = const()[name = string("first_161_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_161_groups_0 = const()[name = string("first_161_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> text_encoder_attn_encoder_ffn_layers_1_conv_2_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_1_conv_2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13248704)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_ffn_layers_1_conv_2_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_1_conv_2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13773056)))];
            tensor<fp16, [1, 256, 192]> first_161_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_1_conv_2_Conv_bias_to_fp16, dilations = first_161_dilations_0, groups = first_161_groups_0, pad = first_161_pad_0, pad_type = first_161_pad_type_0, strides = first_161_strides_0, weight = text_encoder_attn_encoder_ffn_layers_1_conv_2_Conv_weight_to_fp16, x = input_113_cast_fp16)[name = string("first_161_cast_fp16")];
            tensor<fp16, [1, 256, 192]> second_157_cast_fp16 = mul(x = first_161_cast_fp16, y = text_mask)[name = string("second_157_cast_fp16")];
            tensor<fp16, [1, 256, 192]> input_tensor_443_cast_fp16 = add(x = first_157_cast_fp16, y = second_157_cast_fp16)[name = string("input_tensor_443_cast_fp16")];
            tensor<int32, [3]> var_2048 = const()[name = string("op_2048"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_445_axes_0 = const()[name = string("input_tensor_445_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_1_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_1_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13773632)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_1_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_1_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13774208)))];
            fp16 var_2051_to_fp16 = const()[name = string("op_2051_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 192, 256]> input_115_cast_fp16 = transpose(perm = var_2048, x = input_tensor_443_cast_fp16)[name = string("transpose_24")];
            tensor<fp16, [1, 192, 256]> input_tensor_445_cast_fp16 = layer_norm(axes = input_tensor_445_axes_0, beta = text_encoder_attn_encoder_norm_layers_2_1_norm_LayerNormalization_bias_to_fp16, epsilon = var_2051_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_2_1_norm_LayerNormalization_weight_to_fp16, x = input_115_cast_fp16)[name = string("input_tensor_445_cast_fp16")];
            tensor<int32, [3]> var_2060 = const()[name = string("op_2060"), val = tensor<int32, [3]>([0, 2, 1])];
            string input_tensor_455_pad_type_0 = const()[name = string("input_tensor_455_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_455_strides_0 = const()[name = string("input_tensor_455_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_455_pad_0 = const()[name = string("input_tensor_455_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_455_dilations_0 = const()[name = string("input_tensor_455_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_455_groups_0 = const()[name = string("input_tensor_455_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_2_conv_q_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_q_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13774784)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_2_conv_q_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_q_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13905920)))];
            tensor<fp16, [1, 256, 192]> input_117_cast_fp16 = transpose(perm = var_2060, x = input_tensor_445_cast_fp16)[name = string("transpose_23")];
            tensor<fp16, [1, 256, 192]> input_tensor_455_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_2_conv_q_Conv_bias_to_fp16, dilations = input_tensor_455_dilations_0, groups = input_tensor_455_groups_0, pad = input_tensor_455_pad_0, pad_type = input_tensor_455_pad_type_0, strides = input_tensor_455_strides_0, weight = text_encoder_attn_encoder_attn_layers_2_conv_q_Conv_weight_to_fp16, x = input_117_cast_fp16)[name = string("input_tensor_455_cast_fp16")];
            string input_tensor_447_pad_type_0 = const()[name = string("input_tensor_447_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_447_strides_0 = const()[name = string("input_tensor_447_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_447_pad_0 = const()[name = string("input_tensor_447_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_447_dilations_0 = const()[name = string("input_tensor_447_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_447_groups_0 = const()[name = string("input_tensor_447_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_2_conv_k_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_k_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13906496)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_2_conv_k_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_k_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14037632)))];
            tensor<fp16, [1, 256, 192]> input_tensor_447_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_2_conv_k_Conv_bias_to_fp16, dilations = input_tensor_447_dilations_0, groups = input_tensor_447_groups_0, pad = input_tensor_447_pad_0, pad_type = input_tensor_447_pad_type_0, strides = input_tensor_447_strides_0, weight = text_encoder_attn_encoder_attn_layers_2_conv_k_Conv_weight_to_fp16, x = input_117_cast_fp16)[name = string("input_tensor_447_cast_fp16")];
            string input_tensor_467_pad_type_0 = const()[name = string("input_tensor_467_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_467_strides_0 = const()[name = string("input_tensor_467_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_467_pad_0 = const()[name = string("input_tensor_467_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_467_dilations_0 = const()[name = string("input_tensor_467_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_467_groups_0 = const()[name = string("input_tensor_467_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_2_conv_v_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_v_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14038208)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_2_conv_v_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_v_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14169344)))];
            tensor<fp16, [1, 256, 192]> input_tensor_467_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_2_conv_v_Conv_bias_to_fp16, dilations = input_tensor_467_dilations_0, groups = input_tensor_467_groups_0, pad = input_tensor_467_pad_0, pad_type = input_tensor_467_pad_type_0, strides = input_tensor_467_strides_0, weight = text_encoder_attn_encoder_attn_layers_2_conv_v_Conv_weight_to_fp16, x = input_117_cast_fp16)[name = string("input_tensor_467_cast_fp16")];
            tensor<int32, [4]> var_2168 = const()[name = string("op_2168"), val = tensor<int32, [4]>([1, 4, 64, 192])];
            tensor<fp16, [1, 4, 64, 192]> input_tensor_463_cast_fp16 = reshape(shape = var_2168, x = input_tensor_455_cast_fp16)[name = string("input_tensor_463_cast_fp16")];
            tensor<int32, [4]> var_2174 = const()[name = string("op_2174"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [4]> var_2200 = const()[name = string("op_2200"), val = tensor<int32, [4]>([1, 4, 64, 192])];
            tensor<fp16, [1, 4, 64, 192]> y_23_cast_fp16 = reshape(shape = var_2200, x = input_tensor_447_cast_fp16)[name = string("y_23_cast_fp16")];
            tensor<int32, [4]> var_2212 = const()[name = string("op_2212"), val = tensor<int32, [4]>([1, 4, 64, 192])];
            tensor<fp16, [1, 4, 64, 192]> input_tensor_469_cast_fp16 = reshape(shape = var_2212, x = input_tensor_467_cast_fp16)[name = string("input_tensor_469_cast_fp16")];
            fp16 _inversed_x_111_y_0_to_fp16 = const()[name = string("_inversed_x_111_y_0_to_fp16"), val = fp16(0x1p-3)];
            tensor<fp16, [1, 4, 192, 64]> first_163_cast_fp16 = transpose(perm = var_2174, x = input_tensor_463_cast_fp16)[name = string("transpose_22")];
            tensor<fp16, [1, 4, 192, 64]> _inversed_x_111_cast_fp16 = mul(x = first_163_cast_fp16, y = _inversed_x_111_y_0_to_fp16)[name = string("_inversed_x_111_cast_fp16")];
            bool first_179_transpose_x_0 = const()[name = string("first_179_transpose_x_0"), val = bool(false)];
            bool first_179_transpose_y_0 = const()[name = string("first_179_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 4, 192, 192]> first_179_cast_fp16 = matmul(transpose_x = first_179_transpose_x_0, transpose_y = first_179_transpose_y_0, x = _inversed_x_111_cast_fp16, y = y_23_cast_fp16)[name = string("first_179_cast_fp16")];
            bool input_tensor_501_transpose_x_0 = const()[name = string("input_tensor_501_transpose_x_0"), val = bool(false)];
            bool input_tensor_501_transpose_y_0 = const()[name = string("input_tensor_501_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 64, 383]> y_25_to_fp16 = const()[name = string("y_25_to_fp16"), val = tensor<fp16, [1, 1, 64, 383]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(18963776)))];
            tensor<fp16, [1, 4, 192, 383]> input_tensor_501_cast_fp16 = matmul(transpose_x = input_tensor_501_transpose_x_0, transpose_y = input_tensor_501_transpose_y_0, x = _inversed_x_111_cast_fp16, y = y_25_to_fp16)[name = string("input_tensor_501_cast_fp16")];
            tensor<int32, [8]> input_tensor_523_pad_0 = const()[name = string("input_tensor_523_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 1])];
            string input_tensor_523_mode_0 = const()[name = string("input_tensor_523_mode_0"), val = string("constant")];
            fp16 const_79_to_fp16 = const()[name = string("const_79_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 192, 384]> input_tensor_523_cast_fp16 = pad(constant_val = const_79_to_fp16, mode = input_tensor_523_mode_0, pad = input_tensor_523_pad_0, x = input_tensor_501_cast_fp16)[name = string("input_tensor_523_cast_fp16")];
            tensor<int32, [3]> var_2335 = const()[name = string("op_2335"), val = tensor<int32, [3]>([1, 4, 73728])];
            tensor<fp16, [1, 4, 73728]> input_125_cast_fp16 = reshape(shape = var_2335, x = input_tensor_523_cast_fp16)[name = string("input_125_cast_fp16")];
            tensor<int32, [6]> input_tensor_545_pad_0 = const()[name = string("input_tensor_545_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 0, 191])];
            string input_tensor_545_mode_0 = const()[name = string("input_tensor_545_mode_0"), val = string("constant")];
            fp16 const_80_to_fp16 = const()[name = string("const_80_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 73919]> input_tensor_545_cast_fp16 = pad(constant_val = const_80_to_fp16, mode = input_tensor_545_mode_0, pad = input_tensor_545_pad_0, x = input_125_cast_fp16)[name = string("input_tensor_545_cast_fp16")];
            tensor<int32, [4]> var_2370 = const()[name = string("op_2370"), val = tensor<int32, [4]>([1, 4, 193, 383])];
            tensor<fp16, [1, 4, 193, 383]> x_127_cast_fp16 = reshape(shape = var_2370, x = input_tensor_545_cast_fp16)[name = string("x_127_cast_fp16")];
            tensor<int32, [4]> x_129_begin_0 = const()[name = string("x_129_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> x_129_end_0 = const()[name = string("x_129_end_0"), val = tensor<int32, [4]>([1, 4, 192, 383])];
            tensor<bool, [4]> x_129_end_mask_0 = const()[name = string("x_129_end_mask_0"), val = tensor<bool, [4]>([true, true, false, true])];
            tensor<fp16, [1, 4, 192, 383]> x_129_cast_fp16 = slice_by_index(begin = x_129_begin_0, end = x_129_end_0, end_mask = x_129_end_mask_0, x = x_127_cast_fp16)[name = string("x_129_cast_fp16")];
            tensor<int32, [4]> second_181_begin_0 = const()[name = string("second_181_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 191])];
            tensor<int32, [4]> second_181_end_0 = const()[name = string("second_181_end_0"), val = tensor<int32, [4]>([1, 4, 192, 1])];
            tensor<bool, [4]> second_181_end_mask_0 = const()[name = string("second_181_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 192, 192]> second_181_cast_fp16 = slice_by_index(begin = second_181_begin_0, end = second_181_end_0, end_mask = second_181_end_mask_0, x = x_129_cast_fp16)[name = string("second_181_cast_fp16")];
            tensor<fp16, [1, 4, 192, 192]> y_27_cast_fp16 = add(x = first_179_cast_fp16, y = second_181_cast_fp16)[name = string("y_27_cast_fp16")];
            tensor<fp16, [1, 4, 192, 192]> input_127_cast_fp16 = select(a = text_encoder_attn_encoder_attn_layers_0_Constant_88_value_after_broadcast_to_fp16, b = y_27_cast_fp16, cond = condition_1_after_broadcast)[name = string("input_127_cast_fp16")];
            int32 var_2412 = const()[name = string("op_2412"), val = int32(-1)];
            tensor<fp16, [1, 4, 192, 192]> x_133_cast_fp16 = softmax(axis = var_2412, x = input_127_cast_fp16)[name = string("x_133_cast_fp16")];
            bool first_191_transpose_x_1 = const()[name = string("first_191_transpose_x_1"), val = bool(false)];
            bool first_191_transpose_y_1 = const()[name = string("first_191_transpose_y_1"), val = bool(true)];
            tensor<fp16, [1, 4, 192, 64]> first_191_cast_fp16 = matmul(transpose_x = first_191_transpose_x_1, transpose_y = first_191_transpose_y_1, x = x_133_cast_fp16, y = input_tensor_469_cast_fp16)[name = string("first_191_cast_fp16")];
            tensor<int32, [8]> input_tensor_575_pad_0 = const()[name = string("input_tensor_575_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 191])];
            string input_tensor_575_mode_0 = const()[name = string("input_tensor_575_mode_0"), val = string("constant")];
            fp16 const_87_to_fp16 = const()[name = string("const_87_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 192, 383]> input_tensor_575_cast_fp16 = pad(constant_val = const_87_to_fp16, mode = input_tensor_575_mode_0, pad = input_tensor_575_pad_0, x = x_133_cast_fp16)[name = string("input_tensor_575_cast_fp16")];
            tensor<int32, [3]> var_2486 = const()[name = string("op_2486"), val = tensor<int32, [3]>([1, 4, 73536])];
            tensor<fp16, [1, 4, 73536]> input_129_cast_fp16 = reshape(shape = var_2486, x = input_tensor_575_cast_fp16)[name = string("input_129_cast_fp16")];
            tensor<int32, [6]> input_tensor_593_pad_0 = const()[name = string("input_tensor_593_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 192, 0])];
            string input_tensor_593_mode_0 = const()[name = string("input_tensor_593_mode_0"), val = string("constant")];
            fp16 const_88_to_fp16 = const()[name = string("const_88_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 73728]> input_tensor_593_cast_fp16 = pad(constant_val = const_88_to_fp16, mode = input_tensor_593_mode_0, pad = input_tensor_593_pad_0, x = input_129_cast_fp16)[name = string("input_tensor_593_cast_fp16")];
            tensor<int32, [4]> var_2516 = const()[name = string("op_2516"), val = tensor<int32, [4]>([1, 4, 192, 384])];
            tensor<fp16, [1, 4, 192, 384]> x_143_cast_fp16 = reshape(shape = var_2516, x = input_tensor_593_cast_fp16)[name = string("x_143_cast_fp16")];
            tensor<int32, [4]> x_151_begin_0 = const()[name = string("x_151_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 1])];
            tensor<int32, [4]> x_151_end_0 = const()[name = string("x_151_end_0"), val = tensor<int32, [4]>([1, 4, 192, 1])];
            tensor<bool, [4]> x_151_end_mask_0 = const()[name = string("x_151_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 192, 383]> x_151_cast_fp16 = slice_by_index(begin = x_151_begin_0, end = x_151_end_0, end_mask = x_151_end_mask_0, x = x_143_cast_fp16)[name = string("x_151_cast_fp16")];
            bool second_195_transpose_x_0 = const()[name = string("second_195_transpose_x_0"), val = bool(false)];
            bool second_195_transpose_y_0 = const()[name = string("second_195_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 383, 64]> y_31_to_fp16 = const()[name = string("y_31_to_fp16"), val = tensor<fp16, [1, 1, 383, 64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(19012864)))];
            tensor<fp16, [1, 4, 192, 64]> second_195_cast_fp16 = matmul(transpose_x = second_195_transpose_x_0, transpose_y = second_195_transpose_y_0, x = x_151_cast_fp16, y = y_31_to_fp16)[name = string("second_195_cast_fp16")];
            tensor<fp16, [1, 4, 192, 64]> input_tensor_611_cast_fp16 = add(x = first_191_cast_fp16, y = second_195_cast_fp16)[name = string("input_tensor_611_cast_fp16")];
            tensor<int32, [4]> var_2563 = const()[name = string("op_2563"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [3]> var_2582 = const()[name = string("op_2582"), val = tensor<int32, [3]>([1, 256, 192])];
            tensor<fp16, [1, 4, 64, 192]> input_tensor_615_cast_fp16 = transpose(perm = var_2563, x = input_tensor_611_cast_fp16)[name = string("transpose_21")];
            tensor<fp16, [1, 256, 192]> input_133_cast_fp16 = reshape(shape = var_2582, x = input_tensor_615_cast_fp16)[name = string("input_133_cast_fp16")];
            string second_197_pad_type_0 = const()[name = string("second_197_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_197_strides_0 = const()[name = string("second_197_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_197_pad_0 = const()[name = string("second_197_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_197_dilations_0 = const()[name = string("second_197_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_197_groups_0 = const()[name = string("second_197_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_2_conv_o_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_o_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14177984)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_2_conv_o_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_o_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14309120)))];
            tensor<fp16, [1, 256, 192]> second_197_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_2_conv_o_Conv_bias_to_fp16, dilations = second_197_dilations_0, groups = second_197_groups_0, pad = second_197_pad_0, pad_type = second_197_pad_type_0, strides = second_197_strides_0, weight = text_encoder_attn_encoder_attn_layers_2_conv_o_Conv_weight_to_fp16, x = input_133_cast_fp16)[name = string("second_197_cast_fp16")];
            tensor<fp16, [1, 256, 192]> input_tensor_617_cast_fp16 = add(x = input_117_cast_fp16, y = second_197_cast_fp16)[name = string("input_tensor_617_cast_fp16")];
            tensor<int32, [3]> var_2600 = const()[name = string("op_2600"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_619_axes_0 = const()[name = string("input_tensor_619_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_2_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_2_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14309696)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_2_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_2_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14310272)))];
            fp16 var_2603_to_fp16 = const()[name = string("op_2603_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 192, 256]> input_135_cast_fp16 = transpose(perm = var_2600, x = input_tensor_617_cast_fp16)[name = string("transpose_20")];
            tensor<fp16, [1, 192, 256]> input_tensor_619_cast_fp16 = layer_norm(axes = input_tensor_619_axes_0, beta = text_encoder_attn_encoder_norm_layers_1_2_norm_LayerNormalization_bias_to_fp16, epsilon = var_2603_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_1_2_norm_LayerNormalization_weight_to_fp16, x = input_135_cast_fp16)[name = string("input_tensor_619_cast_fp16")];
            tensor<int32, [3]> var_2612 = const()[name = string("op_2612"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 256, 192]> first_193_cast_fp16 = transpose(perm = var_2612, x = input_tensor_619_cast_fp16)[name = string("transpose_19")];
            tensor<fp16, [1, 256, 192]> input_137_cast_fp16 = mul(x = first_193_cast_fp16, y = text_mask)[name = string("input_137_cast_fp16")];
            string input_139_pad_type_0 = const()[name = string("input_139_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_139_strides_0 = const()[name = string("input_139_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_139_pad_0 = const()[name = string("input_139_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_139_dilations_0 = const()[name = string("input_139_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_139_groups_0 = const()[name = string("input_139_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_attn_encoder_ffn_layers_2_conv_1_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_2_conv_1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14310848)))];
            tensor<fp16, [1024]> text_encoder_attn_encoder_ffn_layers_2_conv_1_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_2_conv_1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14835200)))];
            tensor<fp16, [1, 1024, 192]> input_139_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_2_conv_1_Conv_bias_to_fp16, dilations = input_139_dilations_0, groups = input_139_groups_0, pad = input_139_pad_0, pad_type = input_139_pad_type_0, strides = input_139_strides_0, weight = text_encoder_attn_encoder_ffn_layers_2_conv_1_Conv_weight_to_fp16, x = input_137_cast_fp16)[name = string("input_139_cast_fp16")];
            tensor<fp16, [1, 1024, 192]> first_195_cast_fp16 = relu(x = input_139_cast_fp16)[name = string("first_195_cast_fp16")];
            tensor<fp16, [1, 1024, 192]> input_141_cast_fp16 = mul(x = first_195_cast_fp16, y = text_mask)[name = string("input_141_cast_fp16")];
            string first_197_pad_type_0 = const()[name = string("first_197_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_197_strides_0 = const()[name = string("first_197_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_197_pad_0 = const()[name = string("first_197_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_197_dilations_0 = const()[name = string("first_197_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_197_groups_0 = const()[name = string("first_197_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> text_encoder_attn_encoder_ffn_layers_2_conv_2_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_2_conv_2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14837312)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_ffn_layers_2_conv_2_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_2_conv_2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15361664)))];
            tensor<fp16, [1, 256, 192]> first_197_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_2_conv_2_Conv_bias_to_fp16, dilations = first_197_dilations_0, groups = first_197_groups_0, pad = first_197_pad_0, pad_type = first_197_pad_type_0, strides = first_197_strides_0, weight = text_encoder_attn_encoder_ffn_layers_2_conv_2_Conv_weight_to_fp16, x = input_141_cast_fp16)[name = string("first_197_cast_fp16")];
            tensor<fp16, [1, 256, 192]> second_199_cast_fp16 = mul(x = first_197_cast_fp16, y = text_mask)[name = string("second_199_cast_fp16")];
            tensor<fp16, [1, 256, 192]> input_tensor_621_cast_fp16 = add(x = first_193_cast_fp16, y = second_199_cast_fp16)[name = string("input_tensor_621_cast_fp16")];
            tensor<int32, [3]> var_2645 = const()[name = string("op_2645"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_623_axes_0 = const()[name = string("input_tensor_623_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_2_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_2_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15362240)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_2_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_2_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15362816)))];
            fp16 var_2648_to_fp16 = const()[name = string("op_2648_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 192, 256]> input_143_cast_fp16 = transpose(perm = var_2645, x = input_tensor_621_cast_fp16)[name = string("transpose_18")];
            tensor<fp16, [1, 192, 256]> input_tensor_623_cast_fp16 = layer_norm(axes = input_tensor_623_axes_0, beta = text_encoder_attn_encoder_norm_layers_2_2_norm_LayerNormalization_bias_to_fp16, epsilon = var_2648_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_2_2_norm_LayerNormalization_weight_to_fp16, x = input_143_cast_fp16)[name = string("input_tensor_623_cast_fp16")];
            tensor<int32, [3]> var_2657 = const()[name = string("op_2657"), val = tensor<int32, [3]>([0, 2, 1])];
            string input_tensor_633_pad_type_0 = const()[name = string("input_tensor_633_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_633_strides_0 = const()[name = string("input_tensor_633_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_633_pad_0 = const()[name = string("input_tensor_633_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_633_dilations_0 = const()[name = string("input_tensor_633_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_633_groups_0 = const()[name = string("input_tensor_633_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_3_conv_q_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_q_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15363392)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_3_conv_q_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_q_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15494528)))];
            tensor<fp16, [1, 256, 192]> input_145_cast_fp16 = transpose(perm = var_2657, x = input_tensor_623_cast_fp16)[name = string("transpose_17")];
            tensor<fp16, [1, 256, 192]> input_tensor_633_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_3_conv_q_Conv_bias_to_fp16, dilations = input_tensor_633_dilations_0, groups = input_tensor_633_groups_0, pad = input_tensor_633_pad_0, pad_type = input_tensor_633_pad_type_0, strides = input_tensor_633_strides_0, weight = text_encoder_attn_encoder_attn_layers_3_conv_q_Conv_weight_to_fp16, x = input_145_cast_fp16)[name = string("input_tensor_633_cast_fp16")];
            string input_tensor_625_pad_type_0 = const()[name = string("input_tensor_625_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_625_strides_0 = const()[name = string("input_tensor_625_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_625_pad_0 = const()[name = string("input_tensor_625_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_625_dilations_0 = const()[name = string("input_tensor_625_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_625_groups_0 = const()[name = string("input_tensor_625_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_3_conv_k_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_k_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15495104)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_3_conv_k_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_k_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15626240)))];
            tensor<fp16, [1, 256, 192]> input_tensor_625_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_3_conv_k_Conv_bias_to_fp16, dilations = input_tensor_625_dilations_0, groups = input_tensor_625_groups_0, pad = input_tensor_625_pad_0, pad_type = input_tensor_625_pad_type_0, strides = input_tensor_625_strides_0, weight = text_encoder_attn_encoder_attn_layers_3_conv_k_Conv_weight_to_fp16, x = input_145_cast_fp16)[name = string("input_tensor_625_cast_fp16")];
            string input_tensor_645_pad_type_0 = const()[name = string("input_tensor_645_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_645_strides_0 = const()[name = string("input_tensor_645_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_645_pad_0 = const()[name = string("input_tensor_645_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_645_dilations_0 = const()[name = string("input_tensor_645_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_645_groups_0 = const()[name = string("input_tensor_645_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_3_conv_v_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_v_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15626816)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_3_conv_v_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_v_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15757952)))];
            tensor<fp16, [1, 256, 192]> input_tensor_645_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_3_conv_v_Conv_bias_to_fp16, dilations = input_tensor_645_dilations_0, groups = input_tensor_645_groups_0, pad = input_tensor_645_pad_0, pad_type = input_tensor_645_pad_type_0, strides = input_tensor_645_strides_0, weight = text_encoder_attn_encoder_attn_layers_3_conv_v_Conv_weight_to_fp16, x = input_145_cast_fp16)[name = string("input_tensor_645_cast_fp16")];
            tensor<int32, [4]> var_2765 = const()[name = string("op_2765"), val = tensor<int32, [4]>([1, 4, 64, 192])];
            tensor<fp16, [1, 4, 64, 192]> input_tensor_641_cast_fp16 = reshape(shape = var_2765, x = input_tensor_633_cast_fp16)[name = string("input_tensor_641_cast_fp16")];
            tensor<int32, [4]> var_2771 = const()[name = string("op_2771"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [4]> var_2797 = const()[name = string("op_2797"), val = tensor<int32, [4]>([1, 4, 64, 192])];
            tensor<fp16, [1, 4, 64, 192]> y_33_cast_fp16 = reshape(shape = var_2797, x = input_tensor_625_cast_fp16)[name = string("y_33_cast_fp16")];
            tensor<int32, [4]> var_2809 = const()[name = string("op_2809"), val = tensor<int32, [4]>([1, 4, 64, 192])];
            tensor<fp16, [1, 4, 64, 192]> input_tensor_647_cast_fp16 = reshape(shape = var_2809, x = input_tensor_645_cast_fp16)[name = string("input_tensor_647_cast_fp16")];
            fp16 _inversed_x_153_y_0_to_fp16 = const()[name = string("_inversed_x_153_y_0_to_fp16"), val = fp16(0x1p-3)];
            tensor<fp16, [1, 4, 192, 64]> first_199_cast_fp16 = transpose(perm = var_2771, x = input_tensor_641_cast_fp16)[name = string("transpose_16")];
            tensor<fp16, [1, 4, 192, 64]> _inversed_x_153_cast_fp16 = mul(x = first_199_cast_fp16, y = _inversed_x_153_y_0_to_fp16)[name = string("_inversed_x_153_cast_fp16")];
            bool first_215_transpose_x_0 = const()[name = string("first_215_transpose_x_0"), val = bool(false)];
            bool first_215_transpose_y_0 = const()[name = string("first_215_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 4, 192, 192]> first_215_cast_fp16 = matmul(transpose_x = first_215_transpose_x_0, transpose_y = first_215_transpose_y_0, x = _inversed_x_153_cast_fp16, y = y_33_cast_fp16)[name = string("first_215_cast_fp16")];
            bool input_tensor_679_transpose_x_0 = const()[name = string("input_tensor_679_transpose_x_0"), val = bool(false)];
            bool input_tensor_679_transpose_y_0 = const()[name = string("input_tensor_679_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 64, 383]> y_35_to_fp16 = const()[name = string("y_35_to_fp16"), val = tensor<fp16, [1, 1, 64, 383]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(19061952)))];
            tensor<fp16, [1, 4, 192, 383]> input_tensor_679_cast_fp16 = matmul(transpose_x = input_tensor_679_transpose_x_0, transpose_y = input_tensor_679_transpose_y_0, x = _inversed_x_153_cast_fp16, y = y_35_to_fp16)[name = string("input_tensor_679_cast_fp16")];
            tensor<int32, [8]> input_tensor_701_pad_0 = const()[name = string("input_tensor_701_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 1])];
            string input_tensor_701_mode_0 = const()[name = string("input_tensor_701_mode_0"), val = string("constant")];
            fp16 const_107_to_fp16 = const()[name = string("const_107_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 192, 384]> input_tensor_701_cast_fp16 = pad(constant_val = const_107_to_fp16, mode = input_tensor_701_mode_0, pad = input_tensor_701_pad_0, x = input_tensor_679_cast_fp16)[name = string("input_tensor_701_cast_fp16")];
            tensor<int32, [3]> var_2932 = const()[name = string("op_2932"), val = tensor<int32, [3]>([1, 4, 73728])];
            tensor<fp16, [1, 4, 73728]> input_153_cast_fp16 = reshape(shape = var_2932, x = input_tensor_701_cast_fp16)[name = string("input_153_cast_fp16")];
            tensor<int32, [6]> input_tensor_723_pad_0 = const()[name = string("input_tensor_723_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 0, 191])];
            string input_tensor_723_mode_0 = const()[name = string("input_tensor_723_mode_0"), val = string("constant")];
            fp16 const_108_to_fp16 = const()[name = string("const_108_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 73919]> input_tensor_723_cast_fp16 = pad(constant_val = const_108_to_fp16, mode = input_tensor_723_mode_0, pad = input_tensor_723_pad_0, x = input_153_cast_fp16)[name = string("input_tensor_723_cast_fp16")];
            tensor<int32, [4]> var_2967 = const()[name = string("op_2967"), val = tensor<int32, [4]>([1, 4, 193, 383])];
            tensor<fp16, [1, 4, 193, 383]> x_169_cast_fp16 = reshape(shape = var_2967, x = input_tensor_723_cast_fp16)[name = string("x_169_cast_fp16")];
            tensor<int32, [4]> x_171_begin_0 = const()[name = string("x_171_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> x_171_end_0 = const()[name = string("x_171_end_0"), val = tensor<int32, [4]>([1, 4, 192, 383])];
            tensor<bool, [4]> x_171_end_mask_0 = const()[name = string("x_171_end_mask_0"), val = tensor<bool, [4]>([true, true, false, true])];
            tensor<fp16, [1, 4, 192, 383]> x_171_cast_fp16 = slice_by_index(begin = x_171_begin_0, end = x_171_end_0, end_mask = x_171_end_mask_0, x = x_169_cast_fp16)[name = string("x_171_cast_fp16")];
            tensor<int32, [4]> second_223_begin_0 = const()[name = string("second_223_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 191])];
            tensor<int32, [4]> second_223_end_0 = const()[name = string("second_223_end_0"), val = tensor<int32, [4]>([1, 4, 192, 1])];
            tensor<bool, [4]> second_223_end_mask_0 = const()[name = string("second_223_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 192, 192]> second_223_cast_fp16 = slice_by_index(begin = second_223_begin_0, end = second_223_end_0, end_mask = second_223_end_mask_0, x = x_171_cast_fp16)[name = string("second_223_cast_fp16")];
            tensor<fp16, [1, 4, 192, 192]> y_37_cast_fp16 = add(x = first_215_cast_fp16, y = second_223_cast_fp16)[name = string("y_37_cast_fp16")];
            tensor<fp16, [1, 4, 192, 192]> input_155_cast_fp16 = select(a = text_encoder_attn_encoder_attn_layers_0_Constant_88_value_after_broadcast_to_fp16, b = y_37_cast_fp16, cond = condition_1_after_broadcast)[name = string("input_155_cast_fp16")];
            int32 var_3009 = const()[name = string("op_3009"), val = int32(-1)];
            tensor<fp16, [1, 4, 192, 192]> x_175_cast_fp16 = softmax(axis = var_3009, x = input_155_cast_fp16)[name = string("x_175_cast_fp16")];
            bool first_227_transpose_x_1 = const()[name = string("first_227_transpose_x_1"), val = bool(false)];
            bool first_227_transpose_y_1 = const()[name = string("first_227_transpose_y_1"), val = bool(true)];
            tensor<fp16, [1, 4, 192, 64]> first_227_cast_fp16 = matmul(transpose_x = first_227_transpose_x_1, transpose_y = first_227_transpose_y_1, x = x_175_cast_fp16, y = input_tensor_647_cast_fp16)[name = string("first_227_cast_fp16")];
            tensor<int32, [8]> input_tensor_753_pad_0 = const()[name = string("input_tensor_753_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 191])];
            string input_tensor_753_mode_0 = const()[name = string("input_tensor_753_mode_0"), val = string("constant")];
            fp16 const_115_to_fp16 = const()[name = string("const_115_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 192, 383]> input_tensor_753_cast_fp16 = pad(constant_val = const_115_to_fp16, mode = input_tensor_753_mode_0, pad = input_tensor_753_pad_0, x = x_175_cast_fp16)[name = string("input_tensor_753_cast_fp16")];
            tensor<int32, [3]> var_3083 = const()[name = string("op_3083"), val = tensor<int32, [3]>([1, 4, 73536])];
            tensor<fp16, [1, 4, 73536]> input_157_cast_fp16 = reshape(shape = var_3083, x = input_tensor_753_cast_fp16)[name = string("input_157_cast_fp16")];
            tensor<int32, [6]> input_tensor_771_pad_0 = const()[name = string("input_tensor_771_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 192, 0])];
            string input_tensor_771_mode_0 = const()[name = string("input_tensor_771_mode_0"), val = string("constant")];
            fp16 const_116_to_fp16 = const()[name = string("const_116_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 73728]> input_tensor_771_cast_fp16 = pad(constant_val = const_116_to_fp16, mode = input_tensor_771_mode_0, pad = input_tensor_771_pad_0, x = input_157_cast_fp16)[name = string("input_tensor_771_cast_fp16")];
            tensor<int32, [4]> var_3113 = const()[name = string("op_3113"), val = tensor<int32, [4]>([1, 4, 192, 384])];
            tensor<fp16, [1, 4, 192, 384]> x_185_cast_fp16 = reshape(shape = var_3113, x = input_tensor_771_cast_fp16)[name = string("x_185_cast_fp16")];
            tensor<int32, [4]> x_193_begin_0 = const()[name = string("x_193_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 1])];
            tensor<int32, [4]> x_193_end_0 = const()[name = string("x_193_end_0"), val = tensor<int32, [4]>([1, 4, 192, 1])];
            tensor<bool, [4]> x_193_end_mask_0 = const()[name = string("x_193_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 192, 383]> x_193_cast_fp16 = slice_by_index(begin = x_193_begin_0, end = x_193_end_0, end_mask = x_193_end_mask_0, x = x_185_cast_fp16)[name = string("x_193_cast_fp16")];
            bool second_237_transpose_x_0 = const()[name = string("second_237_transpose_x_0"), val = bool(false)];
            bool second_237_transpose_y_0 = const()[name = string("second_237_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 383, 64]> y_41_to_fp16 = const()[name = string("y_41_to_fp16"), val = tensor<fp16, [1, 1, 383, 64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(19111040)))];
            tensor<fp16, [1, 4, 192, 64]> second_237_cast_fp16 = matmul(transpose_x = second_237_transpose_x_0, transpose_y = second_237_transpose_y_0, x = x_193_cast_fp16, y = y_41_to_fp16)[name = string("second_237_cast_fp16")];
            tensor<fp16, [1, 4, 192, 64]> input_tensor_789_cast_fp16 = add(x = first_227_cast_fp16, y = second_237_cast_fp16)[name = string("input_tensor_789_cast_fp16")];
            tensor<int32, [4]> var_3160 = const()[name = string("op_3160"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [3]> var_3179 = const()[name = string("op_3179"), val = tensor<int32, [3]>([1, 256, 192])];
            tensor<fp16, [1, 4, 64, 192]> input_tensor_793_cast_fp16 = transpose(perm = var_3160, x = input_tensor_789_cast_fp16)[name = string("transpose_15")];
            tensor<fp16, [1, 256, 192]> input_161_cast_fp16 = reshape(shape = var_3179, x = input_tensor_793_cast_fp16)[name = string("input_161_cast_fp16")];
            string second_239_pad_type_0 = const()[name = string("second_239_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_239_strides_0 = const()[name = string("second_239_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_239_pad_0 = const()[name = string("second_239_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_239_dilations_0 = const()[name = string("second_239_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_239_groups_0 = const()[name = string("second_239_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_3_conv_o_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_o_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15766592)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_3_conv_o_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_o_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15897728)))];
            tensor<fp16, [1, 256, 192]> second_239_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_3_conv_o_Conv_bias_to_fp16, dilations = second_239_dilations_0, groups = second_239_groups_0, pad = second_239_pad_0, pad_type = second_239_pad_type_0, strides = second_239_strides_0, weight = text_encoder_attn_encoder_attn_layers_3_conv_o_Conv_weight_to_fp16, x = input_161_cast_fp16)[name = string("second_239_cast_fp16")];
            tensor<fp16, [1, 256, 192]> input_tensor_795_cast_fp16 = add(x = input_145_cast_fp16, y = second_239_cast_fp16)[name = string("input_tensor_795_cast_fp16")];
            tensor<int32, [3]> var_3197 = const()[name = string("op_3197"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_797_axes_0 = const()[name = string("input_tensor_797_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_3_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_3_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15898304)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_3_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_3_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15898880)))];
            fp16 var_3200_to_fp16 = const()[name = string("op_3200_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 192, 256]> input_163_cast_fp16 = transpose(perm = var_3197, x = input_tensor_795_cast_fp16)[name = string("transpose_14")];
            tensor<fp16, [1, 192, 256]> input_tensor_797_cast_fp16 = layer_norm(axes = input_tensor_797_axes_0, beta = text_encoder_attn_encoder_norm_layers_1_3_norm_LayerNormalization_bias_to_fp16, epsilon = var_3200_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_1_3_norm_LayerNormalization_weight_to_fp16, x = input_163_cast_fp16)[name = string("input_tensor_797_cast_fp16")];
            tensor<int32, [3]> var_3209 = const()[name = string("op_3209"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 256, 192]> first_229_cast_fp16 = transpose(perm = var_3209, x = input_tensor_797_cast_fp16)[name = string("transpose_13")];
            tensor<fp16, [1, 256, 192]> input_165_cast_fp16 = mul(x = first_229_cast_fp16, y = text_mask)[name = string("input_165_cast_fp16")];
            string input_167_pad_type_0 = const()[name = string("input_167_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_167_strides_0 = const()[name = string("input_167_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_167_pad_0 = const()[name = string("input_167_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_167_dilations_0 = const()[name = string("input_167_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_167_groups_0 = const()[name = string("input_167_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_attn_encoder_ffn_layers_3_conv_1_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_3_conv_1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15899456)))];
            tensor<fp16, [1024]> text_encoder_attn_encoder_ffn_layers_3_conv_1_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_3_conv_1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16423808)))];
            tensor<fp16, [1, 1024, 192]> input_167_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_3_conv_1_Conv_bias_to_fp16, dilations = input_167_dilations_0, groups = input_167_groups_0, pad = input_167_pad_0, pad_type = input_167_pad_type_0, strides = input_167_strides_0, weight = text_encoder_attn_encoder_ffn_layers_3_conv_1_Conv_weight_to_fp16, x = input_165_cast_fp16)[name = string("input_167_cast_fp16")];
            tensor<fp16, [1, 1024, 192]> first_231_cast_fp16 = relu(x = input_167_cast_fp16)[name = string("first_231_cast_fp16")];
            tensor<fp16, [1, 1024, 192]> input_169_cast_fp16 = mul(x = first_231_cast_fp16, y = text_mask)[name = string("input_169_cast_fp16")];
            string first_233_pad_type_0 = const()[name = string("first_233_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_233_strides_0 = const()[name = string("first_233_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_233_pad_0 = const()[name = string("first_233_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_233_dilations_0 = const()[name = string("first_233_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_233_groups_0 = const()[name = string("first_233_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> text_encoder_attn_encoder_ffn_layers_3_conv_2_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_3_conv_2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16425920)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_ffn_layers_3_conv_2_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_3_conv_2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16950272)))];
            tensor<fp16, [1, 256, 192]> first_233_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_3_conv_2_Conv_bias_to_fp16, dilations = first_233_dilations_0, groups = first_233_groups_0, pad = first_233_pad_0, pad_type = first_233_pad_type_0, strides = first_233_strides_0, weight = text_encoder_attn_encoder_ffn_layers_3_conv_2_Conv_weight_to_fp16, x = input_169_cast_fp16)[name = string("first_233_cast_fp16")];
            tensor<fp16, [1, 256, 192]> second_241_cast_fp16 = mul(x = first_233_cast_fp16, y = text_mask)[name = string("second_241_cast_fp16")];
            tensor<fp16, [1, 256, 192]> input_tensor_799_cast_fp16 = add(x = first_229_cast_fp16, y = second_241_cast_fp16)[name = string("input_tensor_799_cast_fp16")];
            tensor<int32, [3]> var_3242 = const()[name = string("op_3242"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_801_axes_0 = const()[name = string("input_tensor_801_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_3_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_3_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16950848)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_3_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_3_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16951424)))];
            fp16 var_3245_to_fp16 = const()[name = string("op_3245_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 192, 256]> input_171_cast_fp16 = transpose(perm = var_3242, x = input_tensor_799_cast_fp16)[name = string("transpose_12")];
            tensor<fp16, [1, 192, 256]> input_tensor_801_cast_fp16 = layer_norm(axes = input_tensor_801_axes_0, beta = text_encoder_attn_encoder_norm_layers_2_3_norm_LayerNormalization_bias_to_fp16, epsilon = var_3245_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_2_3_norm_LayerNormalization_weight_to_fp16, x = input_171_cast_fp16)[name = string("input_tensor_801_cast_fp16")];
            tensor<int32, [3]> var_3254 = const()[name = string("op_3254"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 256, 192]> first_235_cast_fp16 = transpose(perm = var_3254, x = input_tensor_801_cast_fp16)[name = string("transpose_11")];
            tensor<fp16, [1, 256, 192]> first_237_cast_fp16 = mul(x = first_235_cast_fp16, y = text_mask)[name = string("first_237_cast_fp16")];
            tensor<fp16, [1, 256, 192]> first_239_cast_fp16 = add(x = first_237_cast_fp16, y = first_89_cast_fp16)[name = string("first_239_cast_fp16")];
            tensor<fp16, [1, 256, 192]> input_tensor_807_cast_fp16 = mul(x = first_239_cast_fp16, y = text_mask)[name = string("input_tensor_807_cast_fp16")];
            tensor<int32, [3]> var_3299 = const()[name = string("op_3299"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [3]> var_3304 = const()[name = string("op_3304"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [256, 256]> var_3308_weight_0_to_fp16 = const()[name = string("op_3308_weight_0_to_fp16"), val = tensor<fp16, [256, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16952000)))];
            tensor<fp16, [256]> var_3308_bias_0_to_fp16 = const()[name = string("op_3308_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17083136)))];
            tensor<fp16, [1, 192, 256]> x_195_cast_fp16 = transpose(perm = var_3299, x = input_tensor_807_cast_fp16)[name = string("transpose_10")];
            tensor<fp16, [1, 192, 256]> var_3308_cast_fp16 = linear(bias = var_3308_bias_0_to_fp16, weight = var_3308_weight_0_to_fp16, x = x_195_cast_fp16)[name = string("op_3308_cast_fp16")];
            tensor<fp16, [256, 256]> var_3314_weight_0_to_fp16 = const()[name = string("op_3314_weight_0_to_fp16"), val = tensor<fp16, [256, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17083712)))];
            tensor<fp16, [256]> var_3314_bias_0_to_fp16 = const()[name = string("op_3314_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17214848)))];
            tensor<fp16, [1, 50, 256]> var_3314_cast_fp16 = linear(bias = var_3314_bias_0_to_fp16, weight = var_3314_weight_0_to_fp16, x = style_ttl)[name = string("op_3314_cast_fp16")];
            tensor<int32, [2]> var_3317 = const()[name = string("op_3317"), val = tensor<int32, [2]>([128, 128])];
            int32 var_3318_axis_0 = const()[name = string("op_3318_axis_0"), val = int32(2)];
            tensor<fp16, [1, 192, 128]> var_3318_cast_fp16_0, tensor<fp16, [1, 192, 128]> var_3318_cast_fp16_1 = split(axis = var_3318_axis_0, split_sizes = var_3317, x = var_3308_cast_fp16)[name = string("op_3318_cast_fp16")];
            tensor<int32, [1]> var_3325_axes_0 = const()[name = string("op_3325_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 192, 128]> var_3325_cast_fp16 = expand_dims(axes = var_3325_axes_0, x = var_3318_cast_fp16_0)[name = string("op_3325_cast_fp16")];
            tensor<int32, [1]> var_3327_axes_0 = const()[name = string("op_3327_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 192, 128]> var_3327_cast_fp16 = expand_dims(axes = var_3327_axes_0, x = var_3318_cast_fp16_1)[name = string("op_3327_cast_fp16")];
            int32 var_3328 = const()[name = string("op_3328"), val = int32(0)];
            bool x_199_interleave_0 = const()[name = string("x_199_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 1, 192, 128]> x_199_cast_fp16 = concat(axis = var_3328, interleave = x_199_interleave_0, values = (var_3325_cast_fp16, var_3327_cast_fp16))[name = string("x_199_cast_fp16")];
            tensor<int32, [2]> var_3349 = const()[name = string("op_3349"), val = tensor<int32, [2]>([128, 128])];
            int32 var_3350_axis_0 = const()[name = string("op_3350_axis_0"), val = int32(2)];
            tensor<fp16, [1, 50, 128]> var_3350_cast_fp16_0, tensor<fp16, [1, 50, 128]> var_3350_cast_fp16_1 = split(axis = var_3350_axis_0, split_sizes = var_3349, x = var_3314_cast_fp16)[name = string("op_3350_cast_fp16")];
            tensor<int32, [1]> var_3357_axes_0 = const()[name = string("op_3357_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 50, 128]> var_3357_cast_fp16 = expand_dims(axes = var_3357_axes_0, x = var_3350_cast_fp16_0)[name = string("op_3357_cast_fp16")];
            tensor<int32, [1]> var_3359_axes_0 = const()[name = string("op_3359_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 50, 128]> var_3359_cast_fp16 = expand_dims(axes = var_3359_axes_0, x = var_3350_cast_fp16_1)[name = string("op_3359_cast_fp16")];
            int32 var_3360 = const()[name = string("op_3360"), val = int32(0)];
            bool y_55_interleave_0 = const()[name = string("y_55_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 1, 50, 128]> y_55_cast_fp16 = concat(axis = var_3360, interleave = y_55_interleave_0, values = (var_3357_cast_fp16, var_3359_cast_fp16))[name = string("y_55_cast_fp16")];
            bool first_247_transpose_x_0 = const()[name = string("first_247_transpose_x_0"), val = bool(false)];
            bool first_247_transpose_y_0 = const()[name = string("first_247_transpose_y_0"), val = bool(false)];
            tensor<fp16, [2, 1, 128, 50]> y_49_to_fp16 = const()[name = string("y_49_to_fp16"), val = tensor<fp16, [2, 1, 128, 50]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17215424)))];
            tensor<fp16, [2, 1, 192, 50]> first_247_cast_fp16 = matmul(transpose_x = first_247_transpose_x_0, transpose_y = first_247_transpose_y_0, x = x_199_cast_fp16, y = y_49_to_fp16)[name = string("first_247_cast_fp16")];
            fp16 _inversed_input_173_y_0_to_fp16 = const()[name = string("_inversed_input_173_y_0_to_fp16"), val = fp16(0x1p-4)];
            tensor<fp16, [2, 1, 192, 50]> _inversed_input_173_cast_fp16 = mul(x = first_247_cast_fp16, y = _inversed_input_173_y_0_to_fp16)[name = string("_inversed_input_173_cast_fp16")];
            int32 var_3373 = const()[name = string("op_3373"), val = int32(3)];
            tensor<fp16, [2, 1, 192, 50]> y_53_cast_fp16 = softmax(axis = var_3373, x = _inversed_input_173_cast_fp16)[name = string("y_53_cast_fp16")];
            tensor<int32, [1]> x_201_axes_0 = const()[name = string("x_201_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 192, 1]> input_tensor_825_cast_fp16 = transpose(perm = var_3304, x = text_mask)[name = string("transpose_9")];
            tensor<fp16, [1, 1, 192, 1]> x_201_cast_fp16 = expand_dims(axes = x_201_axes_0, x = input_tensor_825_cast_fp16)[name = string("x_201_cast_fp16")];
            fp16 speech_prompted_text_encoder_attention1_Constant_11_value_to_fp16 = const()[name = string("speech_prompted_text_encoder_attention1_Constant_11_value_to_fp16"), val = fp16(0x0p+0)];
            tensor<bool, [1, 1, 192, 1]> input_tensor_827_cast_fp16 = equal(x = x_201_cast_fp16, y = speech_prompted_text_encoder_attention1_Constant_11_value_to_fp16)[name = string("input_tensor_827_cast_fp16")];
            tensor<int32, [4]> condition_9_after_broadcast_reps_0 = const()[name = string("condition_9_after_broadcast_reps_0"), val = tensor<int32, [4]>([2, 1, 1, 50])];
            tensor<bool, [2, 1, 192, 50]> condition_9_after_broadcast = tile(reps = condition_9_after_broadcast_reps_0, x = input_tensor_827_cast_fp16)[name = string("condition_9_after_broadcast")];
            tensor<fp16, [2, 1, 192, 50]> speech_prompted_text_encoder_attention1_Constant_12_value_after_broadcast_to_fp16 = const()[name = string("speech_prompted_text_encoder_attention1_Constant_12_value_after_broadcast_to_fp16"), val = tensor<fp16, [2, 1, 192, 50]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(19160128)))];
            tensor<fp16, [2, 1, 192, 50]> x_205_cast_fp16 = select(a = speech_prompted_text_encoder_attention1_Constant_12_value_after_broadcast_to_fp16, b = y_53_cast_fp16, cond = condition_9_after_broadcast)[name = string("x_205_cast_fp16")];
            bool var_3383_transpose_x_0 = const()[name = string("op_3383_transpose_x_0"), val = bool(false)];
            bool var_3383_transpose_y_0 = const()[name = string("op_3383_transpose_y_0"), val = bool(false)];
            tensor<fp16, [2, 1, 192, 128]> var_3383_cast_fp16 = matmul(transpose_x = var_3383_transpose_x_0, transpose_y = var_3383_transpose_y_0, x = x_205_cast_fp16, y = y_55_cast_fp16)[name = string("op_3383_cast_fp16")];
            tensor<int32, [2]> var_3386 = const()[name = string("op_3386"), val = tensor<int32, [2]>([1, 1])];
            int32 var_3387_axis_0 = const()[name = string("op_3387_axis_0"), val = int32(0)];
            tensor<fp16, [1, 1, 192, 128]> var_3387_cast_fp16_0, tensor<fp16, [1, 1, 192, 128]> var_3387_cast_fp16_1 = split(axis = var_3387_axis_0, split_sizes = var_3386, x = var_3383_cast_fp16)[name = string("op_3387_cast_fp16")];
            int32 var_3393 = const()[name = string("op_3393"), val = int32(3)];
            bool result_1_interleave_0 = const()[name = string("result_1_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 1, 192, 256]> result_1_cast_fp16 = concat(axis = var_3393, interleave = result_1_interleave_0, values = (var_3387_cast_fp16_0, var_3387_cast_fp16_1))[name = string("result_1_cast_fp16")];
            tensor<int32, [1]> x_207_axes_0 = const()[name = string("x_207_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 192, 256]> x_207_cast_fp16 = squeeze(axes = x_207_axes_0, x = result_1_cast_fp16)[name = string("x_207_cast_fp16")];
            tensor<fp16, [256, 256]> first_251_weight_0_to_fp16 = const()[name = string("first_251_weight_0_to_fp16"), val = tensor<fp16, [256, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17244352)))];
            tensor<fp16, [256]> first_251_bias_0_to_fp16 = const()[name = string("first_251_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17375488)))];
            tensor<fp16, [1, 192, 256]> first_251_cast_fp16 = linear(bias = first_251_bias_0_to_fp16, weight = first_251_weight_0_to_fp16, x = x_207_cast_fp16)[name = string("first_251_cast_fp16")];
            tensor<fp16, [1, 192, 256]> first_253_cast_fp16 = mul(x = first_251_cast_fp16, y = input_tensor_825_cast_fp16)[name = string("first_253_cast_fp16")];
            tensor<fp16, [1, 192, 256]> x_209_cast_fp16 = add(x = first_253_cast_fp16, y = x_195_cast_fp16)[name = string("x_209_cast_fp16")];
            tensor<fp16, [256, 256]> var_3413_weight_0_to_fp16 = const()[name = string("op_3413_weight_0_to_fp16"), val = tensor<fp16, [256, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17376064)))];
            tensor<fp16, [256]> var_3413_bias_0_to_fp16 = const()[name = string("op_3413_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17507200)))];
            tensor<fp16, [1, 192, 256]> var_3413_cast_fp16 = linear(bias = var_3413_bias_0_to_fp16, weight = var_3413_weight_0_to_fp16, x = x_209_cast_fp16)[name = string("op_3413_cast_fp16")];
            tensor<fp16, [256, 256]> var_3419_weight_0_to_fp16 = const()[name = string("op_3419_weight_0_to_fp16"), val = tensor<fp16, [256, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17507776)))];
            tensor<fp16, [256]> var_3419_bias_0_to_fp16 = const()[name = string("op_3419_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17638912)))];
            tensor<fp16, [1, 50, 256]> var_3419_cast_fp16 = linear(bias = var_3419_bias_0_to_fp16, weight = var_3419_weight_0_to_fp16, x = style_ttl)[name = string("op_3419_cast_fp16")];
            tensor<int32, [2]> var_3422 = const()[name = string("op_3422"), val = tensor<int32, [2]>([128, 128])];
            int32 var_3423_axis_0 = const()[name = string("op_3423_axis_0"), val = int32(2)];
            tensor<fp16, [1, 192, 128]> var_3423_cast_fp16_0, tensor<fp16, [1, 192, 128]> var_3423_cast_fp16_1 = split(axis = var_3423_axis_0, split_sizes = var_3422, x = var_3413_cast_fp16)[name = string("op_3423_cast_fp16")];
            tensor<int32, [1]> var_3430_axes_0 = const()[name = string("op_3430_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 192, 128]> var_3430_cast_fp16 = expand_dims(axes = var_3430_axes_0, x = var_3423_cast_fp16_0)[name = string("op_3430_cast_fp16")];
            tensor<int32, [1]> var_3432_axes_0 = const()[name = string("op_3432_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 192, 128]> var_3432_cast_fp16 = expand_dims(axes = var_3432_axes_0, x = var_3423_cast_fp16_1)[name = string("op_3432_cast_fp16")];
            int32 var_3433 = const()[name = string("op_3433"), val = int32(0)];
            bool x_211_interleave_0 = const()[name = string("x_211_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 1, 192, 128]> x_211_cast_fp16 = concat(axis = var_3433, interleave = x_211_interleave_0, values = (var_3430_cast_fp16, var_3432_cast_fp16))[name = string("x_211_cast_fp16")];
            tensor<int32, [2]> var_3454 = const()[name = string("op_3454"), val = tensor<int32, [2]>([128, 128])];
            int32 var_3455_axis_0 = const()[name = string("op_3455_axis_0"), val = int32(2)];
            tensor<fp16, [1, 50, 128]> var_3455_cast_fp16_0, tensor<fp16, [1, 50, 128]> var_3455_cast_fp16_1 = split(axis = var_3455_axis_0, split_sizes = var_3454, x = var_3419_cast_fp16)[name = string("op_3455_cast_fp16")];
            tensor<int32, [1]> var_3462_axes_0 = const()[name = string("op_3462_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 50, 128]> var_3462_cast_fp16 = expand_dims(axes = var_3462_axes_0, x = var_3455_cast_fp16_0)[name = string("op_3462_cast_fp16")];
            tensor<int32, [1]> var_3464_axes_0 = const()[name = string("op_3464_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 50, 128]> var_3464_cast_fp16 = expand_dims(axes = var_3464_axes_0, x = var_3455_cast_fp16_1)[name = string("op_3464_cast_fp16")];
            int32 var_3465 = const()[name = string("op_3465"), val = int32(0)];
            bool y_69_interleave_0 = const()[name = string("y_69_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 1, 50, 128]> y_69_cast_fp16 = concat(axis = var_3465, interleave = y_69_interleave_0, values = (var_3462_cast_fp16, var_3464_cast_fp16))[name = string("y_69_cast_fp16")];
            bool first_261_transpose_x_0 = const()[name = string("first_261_transpose_x_0"), val = bool(false)];
            bool first_261_transpose_y_0 = const()[name = string("first_261_transpose_y_0"), val = bool(false)];
            tensor<fp16, [2, 1, 128, 50]> y_65_to_fp16 = const()[name = string("y_65_to_fp16"), val = tensor<fp16, [2, 1, 128, 50]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17639488)))];
            tensor<fp16, [2, 1, 192, 50]> first_261_cast_fp16 = matmul(transpose_x = first_261_transpose_x_0, transpose_y = first_261_transpose_y_0, x = x_211_cast_fp16, y = y_65_to_fp16)[name = string("first_261_cast_fp16")];
            fp16 _inversed_input_175_y_0_to_fp16 = const()[name = string("_inversed_input_175_y_0_to_fp16"), val = fp16(0x1p-4)];
            tensor<fp16, [2, 1, 192, 50]> _inversed_input_175_cast_fp16 = mul(x = first_261_cast_fp16, y = _inversed_input_175_y_0_to_fp16)[name = string("_inversed_input_175_cast_fp16")];
            int32 var_3478 = const()[name = string("op_3478"), val = int32(3)];
            tensor<fp16, [2, 1, 192, 50]> y_67_cast_fp16 = softmax(axis = var_3478, x = _inversed_input_175_cast_fp16)[name = string("y_67_cast_fp16")];
            tensor<fp16, [2, 1, 192, 50]> x_215_cast_fp16 = select(a = speech_prompted_text_encoder_attention1_Constant_12_value_after_broadcast_to_fp16, b = y_67_cast_fp16, cond = condition_9_after_broadcast)[name = string("x_215_cast_fp16")];
            bool var_3485_transpose_x_0 = const()[name = string("op_3485_transpose_x_0"), val = bool(false)];
            bool var_3485_transpose_y_0 = const()[name = string("op_3485_transpose_y_0"), val = bool(false)];
            tensor<fp16, [2, 1, 192, 128]> var_3485_cast_fp16 = matmul(transpose_x = var_3485_transpose_x_0, transpose_y = var_3485_transpose_y_0, x = x_215_cast_fp16, y = y_69_cast_fp16)[name = string("op_3485_cast_fp16")];
            tensor<int32, [2]> var_3488 = const()[name = string("op_3488"), val = tensor<int32, [2]>([1, 1])];
            int32 var_3489_axis_0 = const()[name = string("op_3489_axis_0"), val = int32(0)];
            tensor<fp16, [1, 1, 192, 128]> var_3489_cast_fp16_0, tensor<fp16, [1, 1, 192, 128]> var_3489_cast_fp16_1 = split(axis = var_3489_axis_0, split_sizes = var_3488, x = var_3485_cast_fp16)[name = string("op_3489_cast_fp16")];
            int32 var_3495 = const()[name = string("op_3495"), val = int32(3)];
            bool result_interleave_0 = const()[name = string("result_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 1, 192, 256]> result_cast_fp16 = concat(axis = var_3495, interleave = result_interleave_0, values = (var_3489_cast_fp16_0, var_3489_cast_fp16_1))[name = string("result_cast_fp16")];
            tensor<int32, [1]> x_axes_0 = const()[name = string("x_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 192, 256]> x_cast_fp16 = squeeze(axes = x_axes_0, x = result_cast_fp16)[name = string("x_cast_fp16")];
            tensor<fp16, [256, 256]> first_265_weight_0_to_fp16 = const()[name = string("first_265_weight_0_to_fp16"), val = tensor<fp16, [256, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17665152)))];
            tensor<fp16, [256]> first_265_bias_0_to_fp16 = const()[name = string("first_265_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17796288)))];
            tensor<fp16, [1, 192, 256]> first_265_cast_fp16 = linear(bias = first_265_bias_0_to_fp16, weight = first_265_weight_0_to_fp16, x = x_cast_fp16)[name = string("first_265_cast_fp16")];
            tensor<fp16, [1, 192, 256]> first_267_cast_fp16 = mul(x = first_265_cast_fp16, y = input_tensor_825_cast_fp16)[name = string("first_267_cast_fp16")];
            tensor<fp16, [1, 192, 256]> input_cast_fp16 = add(x = first_267_cast_fp16, y = x_195_cast_fp16)[name = string("input_cast_fp16")];
            tensor<int32, [1]> input_tensor_axes_0 = const()[name = string("input_tensor_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> speech_prompted_text_encoder_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("speech_prompted_text_encoder_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17796864)))];
            tensor<fp16, [256]> speech_prompted_text_encoder_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("speech_prompted_text_encoder_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17797440)))];
            fp16 var_3514_to_fp16 = const()[name = string("op_3514_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 192, 256]> input_tensor_cast_fp16 = layer_norm(axes = input_tensor_axes_0, beta = speech_prompted_text_encoder_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_3514_to_fp16, gamma = speech_prompted_text_encoder_norm_norm_LayerNormalization_weight_to_fp16, x = input_cast_fp16)[name = string("input_tensor_cast_fp16")];
            tensor<int32, [3]> var_3523 = const()[name = string("op_3523"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 256, 192]> first_cast_fp16 = transpose(perm = var_3523, x = input_tensor_cast_fp16)[name = string("transpose_8")];
            tensor<fp16, [1, 256, 192]> text_emb = mul(x = first_cast_fp16, y = text_mask)[name = string("op_3525_cast_fp16")];
        } -> (text_emb);
    func text_t256<ios18>(tensor<fp16, [1, 50, 256]> style_ttl, tensor<int32, [1, 256]> text_ids, tensor<fp16, [1, 1, 256]> text_mask) {
            int32 input_tensor_3_batch_dims_0 = const()[name = string("input_tensor_3_batch_dims_0"), val = int32(0)];
            bool input_tensor_3_validate_indices_0 = const()[name = string("input_tensor_3_validate_indices_0"), val = bool(false)];
            tensor<fp16, [8322, 256]> initializers_onnx_initializer_0_to_fp16 = const()[name = string("initializers_onnx_initializer_0_to_fp16"), val = tensor<fp16, [8322, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(64)))];
            string text_ids_to_int16_dtype_0 = const()[name = string("text_ids_to_int16_dtype_0"), val = string("int16")];
            string cast_59_dtype_0 = const()[name = string("cast_59_dtype_0"), val = string("int32")];
            int32 greater_equal_0_y_0 = const()[name = string("greater_equal_0_y_0"), val = int32(0)];
            tensor<int16, [1, 256]> text_ids_to_int16 = cast(dtype = text_ids_to_int16_dtype_0, x = text_ids)[name = string("cast_62")];
            tensor<int32, [1, 256]> cast_59 = cast(dtype = cast_59_dtype_0, x = text_ids_to_int16)[name = string("cast_61")];
            tensor<bool, [1, 256]> greater_equal_0 = greater_equal(x = cast_59, y = greater_equal_0_y_0)[name = string("greater_equal_0")];
            int32 slice_by_index_0 = const()[name = string("slice_by_index_0"), val = int32(8322)];
            tensor<int32, [1, 256]> add_0 = add(x = cast_59, y = slice_by_index_0)[name = string("add_0")];
            tensor<int32, [1, 256]> select_0 = select(a = cast_59, b = add_0, cond = greater_equal_0)[name = string("select_0")];
            int32 input_tensor_3_cast_fp16_cast_uint16_axis_0 = const()[name = string("input_tensor_3_cast_fp16_cast_uint16_axis_0"), val = int32(0)];
            string select_0_to_int16_dtype_0 = const()[name = string("select_0_to_int16_dtype_0"), val = string("int16")];
            tensor<int16, [1, 256]> select_0_to_int16 = cast(dtype = select_0_to_int16_dtype_0, x = select_0)[name = string("cast_60")];
            tensor<fp16, [1, 256, 256]> input_tensor_3_cast_fp16_cast_uint16_cast_uint16 = gather(axis = input_tensor_3_cast_fp16_cast_uint16_axis_0, batch_dims = input_tensor_3_batch_dims_0, indices = select_0_to_int16, validate_indices = input_tensor_3_validate_indices_0, x = initializers_onnx_initializer_0_to_fp16)[name = string("input_tensor_3_cast_fp16_cast_uint16_cast_uint16")];
            tensor<int32, [3]> var_446 = const()[name = string("op_446"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 256, 256]> first_1_cast_fp16 = transpose(perm = var_446, x = input_tensor_3_cast_fp16_cast_uint16_cast_uint16)[name = string("transpose_47")];
            tensor<fp16, [1, 256, 256]> first_3_cast_fp16 = mul(x = first_1_cast_fp16, y = text_mask)[name = string("first_3_cast_fp16")];
            tensor<fp16, [1, 256, 256]> input_1_cast_fp16 = mul(x = first_3_cast_fp16, y = text_mask)[name = string("input_1_cast_fp16")];
            tensor<int32, [6]> input_3_pad_0 = const()[name = string("input_3_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 2, 2])];
            string input_3_mode_0 = const()[name = string("input_3_mode_0"), val = string("replicate")];
            fp16 const_0_to_fp16 = const()[name = string("const_0_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 256, 260]> input_3_cast_fp16 = pad(constant_val = const_0_to_fp16, mode = input_3_mode_0, pad = input_3_pad_0, x = input_1_cast_fp16)[name = string("input_3_cast_fp16")];
            string first_5_pad_type_0 = const()[name = string("first_5_pad_type_0"), val = string("valid")];
            int32 first_5_groups_0 = const()[name = string("first_5_groups_0"), val = int32(256)];
            tensor<int32, [1]> first_5_strides_0 = const()[name = string("first_5_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_5_pad_0 = const()[name = string("first_5_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_5_dilations_0 = const()[name = string("first_5_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [256, 1, 5]> text_encoder_convnext_convnext_0_dwconv_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_0_dwconv_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4260992)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_0_dwconv_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_0_dwconv_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4263616)))];
            tensor<fp16, [1, 256, 256]> first_5_cast_fp16 = conv(bias = text_encoder_convnext_convnext_0_dwconv_Conv_bias_to_fp16, dilations = first_5_dilations_0, groups = first_5_groups_0, pad = first_5_pad_0, pad_type = first_5_pad_type_0, strides = first_5_strides_0, weight = text_encoder_convnext_convnext_0_dwconv_Conv_weight_to_fp16, x = input_3_cast_fp16)[name = string("first_5_cast_fp16")];
            tensor<fp16, [1, 256, 256]> input_tensor_13_cast_fp16 = mul(x = first_5_cast_fp16, y = text_mask)[name = string("input_tensor_13_cast_fp16")];
            tensor<int32, [3]> var_471 = const()[name = string("op_471"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_15_axes_0 = const()[name = string("input_tensor_15_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_convnext_convnext_0_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_0_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4264192)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_0_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_0_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4264768)))];
            fp16 var_474_to_fp16 = const()[name = string("op_474_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 256, 256]> input_5_cast_fp16 = transpose(perm = var_471, x = input_tensor_13_cast_fp16)[name = string("transpose_46")];
            tensor<fp16, [1, 256, 256]> input_tensor_15_cast_fp16 = layer_norm(axes = input_tensor_15_axes_0, beta = text_encoder_convnext_convnext_0_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_474_to_fp16, gamma = text_encoder_convnext_convnext_0_norm_norm_LayerNormalization_weight_to_fp16, x = input_5_cast_fp16)[name = string("input_tensor_15_cast_fp16")];
            tensor<int32, [3]> var_483 = const()[name = string("op_483"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_7_pad_type_0 = const()[name = string("first_7_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_7_strides_0 = const()[name = string("first_7_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_7_pad_0 = const()[name = string("first_7_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_7_dilations_0 = const()[name = string("first_7_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_7_groups_0 = const()[name = string("first_7_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_convnext_convnext_0_pwconv1_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_0_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4265344)))];
            tensor<fp16, [1024]> text_encoder_convnext_convnext_0_pwconv1_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_0_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4789696)))];
            tensor<fp16, [1, 256, 256]> input_7_cast_fp16 = transpose(perm = var_483, x = input_tensor_15_cast_fp16)[name = string("transpose_45")];
            tensor<fp16, [1, 1024, 256]> first_7_cast_fp16 = conv(bias = text_encoder_convnext_convnext_0_pwconv1_Conv_bias_to_fp16, dilations = first_7_dilations_0, groups = first_7_groups_0, pad = first_7_pad_0, pad_type = first_7_pad_type_0, strides = first_7_strides_0, weight = text_encoder_convnext_convnext_0_pwconv1_Conv_weight_to_fp16, x = input_7_cast_fp16)[name = string("first_7_cast_fp16")];
            string input_9_mode_0 = const()[name = string("input_9_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 1024, 256]> input_9_cast_fp16 = gelu(mode = input_9_mode_0, x = first_7_cast_fp16)[name = string("input_9_cast_fp16")];
            string second_9_pad_type_0 = const()[name = string("second_9_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_9_strides_0 = const()[name = string("second_9_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_9_pad_0 = const()[name = string("second_9_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_9_dilations_0 = const()[name = string("second_9_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_9_groups_0 = const()[name = string("second_9_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> second_11_weight_0_to_fp16 = const()[name = string("second_11_weight_0_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4791808)))];
            tensor<fp16, [256]> second_11_bias_0_to_fp16 = const()[name = string("second_11_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5316160)))];
            tensor<fp16, [1, 256, 256]> second_11_cast_fp16 = conv(bias = second_11_bias_0_to_fp16, dilations = second_9_dilations_0, groups = second_9_groups_0, pad = second_9_pad_0, pad_type = second_9_pad_type_0, strides = second_9_strides_0, weight = second_11_weight_0_to_fp16, x = input_9_cast_fp16)[name = string("second_11_cast_fp16")];
            tensor<fp16, [1, 256, 256]> first_15_cast_fp16 = add(x = input_1_cast_fp16, y = second_11_cast_fp16)[name = string("first_15_cast_fp16")];
            tensor<fp16, [1, 256, 256]> first_17_cast_fp16 = mul(x = first_15_cast_fp16, y = text_mask)[name = string("first_17_cast_fp16")];
            tensor<fp16, [1, 256, 256]> input_11_cast_fp16 = mul(x = first_17_cast_fp16, y = text_mask)[name = string("input_11_cast_fp16")];
            tensor<int32, [6]> input_13_pad_0 = const()[name = string("input_13_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 2, 2])];
            string input_13_mode_0 = const()[name = string("input_13_mode_0"), val = string("replicate")];
            fp16 const_1_to_fp16 = const()[name = string("const_1_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 256, 260]> input_13_cast_fp16 = pad(constant_val = const_1_to_fp16, mode = input_13_mode_0, pad = input_13_pad_0, x = input_11_cast_fp16)[name = string("input_13_cast_fp16")];
            string first_19_pad_type_0 = const()[name = string("first_19_pad_type_0"), val = string("valid")];
            int32 first_19_groups_0 = const()[name = string("first_19_groups_0"), val = int32(256)];
            tensor<int32, [1]> first_19_strides_0 = const()[name = string("first_19_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_19_pad_0 = const()[name = string("first_19_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_19_dilations_0 = const()[name = string("first_19_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [256, 1, 5]> text_encoder_convnext_convnext_1_dwconv_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_1_dwconv_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5316736)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_1_dwconv_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_1_dwconv_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5319360)))];
            tensor<fp16, [1, 256, 256]> first_19_cast_fp16 = conv(bias = text_encoder_convnext_convnext_1_dwconv_Conv_bias_to_fp16, dilations = first_19_dilations_0, groups = first_19_groups_0, pad = first_19_pad_0, pad_type = first_19_pad_type_0, strides = first_19_strides_0, weight = text_encoder_convnext_convnext_1_dwconv_Conv_weight_to_fp16, x = input_13_cast_fp16)[name = string("first_19_cast_fp16")];
            tensor<fp16, [1, 256, 256]> input_tensor_27_cast_fp16 = mul(x = first_19_cast_fp16, y = text_mask)[name = string("input_tensor_27_cast_fp16")];
            tensor<int32, [3]> var_539 = const()[name = string("op_539"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_29_axes_0 = const()[name = string("input_tensor_29_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_convnext_convnext_1_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_1_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5319936)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_1_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_1_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5320512)))];
            fp16 var_542_to_fp16 = const()[name = string("op_542_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 256, 256]> input_15_cast_fp16 = transpose(perm = var_539, x = input_tensor_27_cast_fp16)[name = string("transpose_44")];
            tensor<fp16, [1, 256, 256]> input_tensor_29_cast_fp16 = layer_norm(axes = input_tensor_29_axes_0, beta = text_encoder_convnext_convnext_1_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_542_to_fp16, gamma = text_encoder_convnext_convnext_1_norm_norm_LayerNormalization_weight_to_fp16, x = input_15_cast_fp16)[name = string("input_tensor_29_cast_fp16")];
            tensor<int32, [3]> var_551 = const()[name = string("op_551"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_21_pad_type_0 = const()[name = string("first_21_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_21_strides_0 = const()[name = string("first_21_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_21_pad_0 = const()[name = string("first_21_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_21_dilations_0 = const()[name = string("first_21_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_21_groups_0 = const()[name = string("first_21_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_convnext_convnext_1_pwconv1_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_1_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5321088)))];
            tensor<fp16, [1024]> text_encoder_convnext_convnext_1_pwconv1_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_1_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5845440)))];
            tensor<fp16, [1, 256, 256]> input_17_cast_fp16 = transpose(perm = var_551, x = input_tensor_29_cast_fp16)[name = string("transpose_43")];
            tensor<fp16, [1, 1024, 256]> first_21_cast_fp16 = conv(bias = text_encoder_convnext_convnext_1_pwconv1_Conv_bias_to_fp16, dilations = first_21_dilations_0, groups = first_21_groups_0, pad = first_21_pad_0, pad_type = first_21_pad_type_0, strides = first_21_strides_0, weight = text_encoder_convnext_convnext_1_pwconv1_Conv_weight_to_fp16, x = input_17_cast_fp16)[name = string("first_21_cast_fp16")];
            string input_19_mode_0 = const()[name = string("input_19_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 1024, 256]> input_19_cast_fp16 = gelu(mode = input_19_mode_0, x = first_21_cast_fp16)[name = string("input_19_cast_fp16")];
            string second_21_pad_type_0 = const()[name = string("second_21_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_21_strides_0 = const()[name = string("second_21_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_21_pad_0 = const()[name = string("second_21_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_21_dilations_0 = const()[name = string("second_21_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_21_groups_0 = const()[name = string("second_21_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> second_23_weight_0_to_fp16 = const()[name = string("second_23_weight_0_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5847552)))];
            tensor<fp16, [256]> second_23_bias_0_to_fp16 = const()[name = string("second_23_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6371904)))];
            tensor<fp16, [1, 256, 256]> second_23_cast_fp16 = conv(bias = second_23_bias_0_to_fp16, dilations = second_21_dilations_0, groups = second_21_groups_0, pad = second_21_pad_0, pad_type = second_21_pad_type_0, strides = second_21_strides_0, weight = second_23_weight_0_to_fp16, x = input_19_cast_fp16)[name = string("second_23_cast_fp16")];
            tensor<fp16, [1, 256, 256]> first_29_cast_fp16 = add(x = input_11_cast_fp16, y = second_23_cast_fp16)[name = string("first_29_cast_fp16")];
            tensor<fp16, [1, 256, 256]> first_31_cast_fp16 = mul(x = first_29_cast_fp16, y = text_mask)[name = string("first_31_cast_fp16")];
            tensor<fp16, [1, 256, 256]> input_21_cast_fp16 = mul(x = first_31_cast_fp16, y = text_mask)[name = string("input_21_cast_fp16")];
            tensor<int32, [6]> input_23_pad_0 = const()[name = string("input_23_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            string input_23_mode_0 = const()[name = string("input_23_mode_0"), val = string("replicate")];
            fp16 const_2_to_fp16 = const()[name = string("const_2_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 256, 264]> input_23_cast_fp16 = pad(constant_val = const_2_to_fp16, mode = input_23_mode_0, pad = input_23_pad_0, x = input_21_cast_fp16)[name = string("input_23_cast_fp16")];
            string first_33_pad_type_0 = const()[name = string("first_33_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_33_dilations_0 = const()[name = string("first_33_dilations_0"), val = tensor<int32, [1]>([2])];
            int32 first_33_groups_0 = const()[name = string("first_33_groups_0"), val = int32(256)];
            tensor<int32, [1]> first_33_strides_0 = const()[name = string("first_33_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_33_pad_0 = const()[name = string("first_33_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [256, 1, 5]> text_encoder_convnext_convnext_2_dwconv_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_2_dwconv_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6372480)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_2_dwconv_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_2_dwconv_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6375104)))];
            tensor<fp16, [1, 256, 256]> first_33_cast_fp16 = conv(bias = text_encoder_convnext_convnext_2_dwconv_Conv_bias_to_fp16, dilations = first_33_dilations_0, groups = first_33_groups_0, pad = first_33_pad_0, pad_type = first_33_pad_type_0, strides = first_33_strides_0, weight = text_encoder_convnext_convnext_2_dwconv_Conv_weight_to_fp16, x = input_23_cast_fp16)[name = string("first_33_cast_fp16")];
            tensor<fp16, [1, 256, 256]> input_tensor_41_cast_fp16 = mul(x = first_33_cast_fp16, y = text_mask)[name = string("input_tensor_41_cast_fp16")];
            tensor<int32, [3]> var_608 = const()[name = string("op_608"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_43_axes_0 = const()[name = string("input_tensor_43_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_convnext_convnext_2_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_2_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6375680)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_2_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_2_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6376256)))];
            fp16 var_611_to_fp16 = const()[name = string("op_611_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 256, 256]> input_25_cast_fp16 = transpose(perm = var_608, x = input_tensor_41_cast_fp16)[name = string("transpose_42")];
            tensor<fp16, [1, 256, 256]> input_tensor_43_cast_fp16 = layer_norm(axes = input_tensor_43_axes_0, beta = text_encoder_convnext_convnext_2_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_611_to_fp16, gamma = text_encoder_convnext_convnext_2_norm_norm_LayerNormalization_weight_to_fp16, x = input_25_cast_fp16)[name = string("input_tensor_43_cast_fp16")];
            tensor<int32, [3]> var_620 = const()[name = string("op_620"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_35_pad_type_0 = const()[name = string("first_35_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_35_strides_0 = const()[name = string("first_35_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_35_pad_0 = const()[name = string("first_35_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_35_dilations_0 = const()[name = string("first_35_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_35_groups_0 = const()[name = string("first_35_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_convnext_convnext_2_pwconv1_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_2_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6376832)))];
            tensor<fp16, [1024]> text_encoder_convnext_convnext_2_pwconv1_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_2_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6901184)))];
            tensor<fp16, [1, 256, 256]> input_27_cast_fp16 = transpose(perm = var_620, x = input_tensor_43_cast_fp16)[name = string("transpose_41")];
            tensor<fp16, [1, 1024, 256]> first_35_cast_fp16 = conv(bias = text_encoder_convnext_convnext_2_pwconv1_Conv_bias_to_fp16, dilations = first_35_dilations_0, groups = first_35_groups_0, pad = first_35_pad_0, pad_type = first_35_pad_type_0, strides = first_35_strides_0, weight = text_encoder_convnext_convnext_2_pwconv1_Conv_weight_to_fp16, x = input_27_cast_fp16)[name = string("first_35_cast_fp16")];
            string input_29_mode_0 = const()[name = string("input_29_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 1024, 256]> input_29_cast_fp16 = gelu(mode = input_29_mode_0, x = first_35_cast_fp16)[name = string("input_29_cast_fp16")];
            string second_33_pad_type_0 = const()[name = string("second_33_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_33_strides_0 = const()[name = string("second_33_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_33_pad_0 = const()[name = string("second_33_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_33_dilations_0 = const()[name = string("second_33_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_33_groups_0 = const()[name = string("second_33_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> second_35_weight_0_to_fp16 = const()[name = string("second_35_weight_0_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6903296)))];
            tensor<fp16, [256]> second_35_bias_0_to_fp16 = const()[name = string("second_35_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7427648)))];
            tensor<fp16, [1, 256, 256]> second_35_cast_fp16 = conv(bias = second_35_bias_0_to_fp16, dilations = second_33_dilations_0, groups = second_33_groups_0, pad = second_33_pad_0, pad_type = second_33_pad_type_0, strides = second_33_strides_0, weight = second_35_weight_0_to_fp16, x = input_29_cast_fp16)[name = string("second_35_cast_fp16")];
            tensor<fp16, [1, 256, 256]> first_43_cast_fp16 = add(x = input_21_cast_fp16, y = second_35_cast_fp16)[name = string("first_43_cast_fp16")];
            tensor<fp16, [1, 256, 256]> first_45_cast_fp16 = mul(x = first_43_cast_fp16, y = text_mask)[name = string("first_45_cast_fp16")];
            tensor<fp16, [1, 256, 256]> input_31_cast_fp16 = mul(x = first_45_cast_fp16, y = text_mask)[name = string("input_31_cast_fp16")];
            tensor<int32, [6]> input_33_pad_0 = const()[name = string("input_33_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            string input_33_mode_0 = const()[name = string("input_33_mode_0"), val = string("replicate")];
            fp16 const_3_to_fp16 = const()[name = string("const_3_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 256, 264]> input_33_cast_fp16 = pad(constant_val = const_3_to_fp16, mode = input_33_mode_0, pad = input_33_pad_0, x = input_31_cast_fp16)[name = string("input_33_cast_fp16")];
            string first_47_pad_type_0 = const()[name = string("first_47_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_47_dilations_0 = const()[name = string("first_47_dilations_0"), val = tensor<int32, [1]>([2])];
            int32 first_47_groups_0 = const()[name = string("first_47_groups_0"), val = int32(256)];
            tensor<int32, [1]> first_47_strides_0 = const()[name = string("first_47_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_47_pad_0 = const()[name = string("first_47_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [256, 1, 5]> text_encoder_convnext_convnext_3_dwconv_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_3_dwconv_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7428224)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_3_dwconv_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_3_dwconv_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7430848)))];
            tensor<fp16, [1, 256, 256]> first_47_cast_fp16 = conv(bias = text_encoder_convnext_convnext_3_dwconv_Conv_bias_to_fp16, dilations = first_47_dilations_0, groups = first_47_groups_0, pad = first_47_pad_0, pad_type = first_47_pad_type_0, strides = first_47_strides_0, weight = text_encoder_convnext_convnext_3_dwconv_Conv_weight_to_fp16, x = input_33_cast_fp16)[name = string("first_47_cast_fp16")];
            tensor<fp16, [1, 256, 256]> input_tensor_55_cast_fp16 = mul(x = first_47_cast_fp16, y = text_mask)[name = string("input_tensor_55_cast_fp16")];
            tensor<int32, [3]> var_677 = const()[name = string("op_677"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_57_axes_0 = const()[name = string("input_tensor_57_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_convnext_convnext_3_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_3_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7431424)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_3_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_3_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7432000)))];
            fp16 var_680_to_fp16 = const()[name = string("op_680_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 256, 256]> input_35_cast_fp16 = transpose(perm = var_677, x = input_tensor_55_cast_fp16)[name = string("transpose_40")];
            tensor<fp16, [1, 256, 256]> input_tensor_57_cast_fp16 = layer_norm(axes = input_tensor_57_axes_0, beta = text_encoder_convnext_convnext_3_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_680_to_fp16, gamma = text_encoder_convnext_convnext_3_norm_norm_LayerNormalization_weight_to_fp16, x = input_35_cast_fp16)[name = string("input_tensor_57_cast_fp16")];
            tensor<int32, [3]> var_689 = const()[name = string("op_689"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_49_pad_type_0 = const()[name = string("first_49_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_49_strides_0 = const()[name = string("first_49_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_49_pad_0 = const()[name = string("first_49_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_49_dilations_0 = const()[name = string("first_49_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_49_groups_0 = const()[name = string("first_49_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_convnext_convnext_3_pwconv1_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_3_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7432576)))];
            tensor<fp16, [1024]> text_encoder_convnext_convnext_3_pwconv1_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_3_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7956928)))];
            tensor<fp16, [1, 256, 256]> input_37_cast_fp16 = transpose(perm = var_689, x = input_tensor_57_cast_fp16)[name = string("transpose_39")];
            tensor<fp16, [1, 1024, 256]> first_49_cast_fp16 = conv(bias = text_encoder_convnext_convnext_3_pwconv1_Conv_bias_to_fp16, dilations = first_49_dilations_0, groups = first_49_groups_0, pad = first_49_pad_0, pad_type = first_49_pad_type_0, strides = first_49_strides_0, weight = text_encoder_convnext_convnext_3_pwconv1_Conv_weight_to_fp16, x = input_37_cast_fp16)[name = string("first_49_cast_fp16")];
            string input_39_mode_0 = const()[name = string("input_39_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 1024, 256]> input_39_cast_fp16 = gelu(mode = input_39_mode_0, x = first_49_cast_fp16)[name = string("input_39_cast_fp16")];
            string second_45_pad_type_0 = const()[name = string("second_45_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_45_strides_0 = const()[name = string("second_45_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_45_pad_0 = const()[name = string("second_45_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_45_dilations_0 = const()[name = string("second_45_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_45_groups_0 = const()[name = string("second_45_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> second_47_weight_0_to_fp16 = const()[name = string("second_47_weight_0_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7959040)))];
            tensor<fp16, [256]> second_47_bias_0_to_fp16 = const()[name = string("second_47_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8483392)))];
            tensor<fp16, [1, 256, 256]> second_47_cast_fp16 = conv(bias = second_47_bias_0_to_fp16, dilations = second_45_dilations_0, groups = second_45_groups_0, pad = second_45_pad_0, pad_type = second_45_pad_type_0, strides = second_45_strides_0, weight = second_47_weight_0_to_fp16, x = input_39_cast_fp16)[name = string("second_47_cast_fp16")];
            tensor<fp16, [1, 256, 256]> first_57_cast_fp16 = add(x = input_31_cast_fp16, y = second_47_cast_fp16)[name = string("first_57_cast_fp16")];
            tensor<fp16, [1, 256, 256]> first_59_cast_fp16 = mul(x = first_57_cast_fp16, y = text_mask)[name = string("first_59_cast_fp16")];
            tensor<fp16, [1, 256, 256]> input_41_cast_fp16 = mul(x = first_59_cast_fp16, y = text_mask)[name = string("input_41_cast_fp16")];
            tensor<int32, [6]> input_43_pad_0 = const()[name = string("input_43_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 8, 8])];
            string input_43_mode_0 = const()[name = string("input_43_mode_0"), val = string("replicate")];
            fp16 const_4_to_fp16 = const()[name = string("const_4_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 256, 272]> input_43_cast_fp16 = pad(constant_val = const_4_to_fp16, mode = input_43_mode_0, pad = input_43_pad_0, x = input_41_cast_fp16)[name = string("input_43_cast_fp16")];
            string first_61_pad_type_0 = const()[name = string("first_61_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_61_dilations_0 = const()[name = string("first_61_dilations_0"), val = tensor<int32, [1]>([4])];
            int32 first_61_groups_0 = const()[name = string("first_61_groups_0"), val = int32(256)];
            tensor<int32, [1]> first_61_strides_0 = const()[name = string("first_61_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_61_pad_0 = const()[name = string("first_61_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [256, 1, 5]> text_encoder_convnext_convnext_4_dwconv_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_4_dwconv_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8483968)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_4_dwconv_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_4_dwconv_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8486592)))];
            tensor<fp16, [1, 256, 256]> first_61_cast_fp16 = conv(bias = text_encoder_convnext_convnext_4_dwconv_Conv_bias_to_fp16, dilations = first_61_dilations_0, groups = first_61_groups_0, pad = first_61_pad_0, pad_type = first_61_pad_type_0, strides = first_61_strides_0, weight = text_encoder_convnext_convnext_4_dwconv_Conv_weight_to_fp16, x = input_43_cast_fp16)[name = string("first_61_cast_fp16")];
            tensor<fp16, [1, 256, 256]> input_tensor_69_cast_fp16 = mul(x = first_61_cast_fp16, y = text_mask)[name = string("input_tensor_69_cast_fp16")];
            tensor<int32, [3]> var_746 = const()[name = string("op_746"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_71_axes_0 = const()[name = string("input_tensor_71_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_convnext_convnext_4_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_4_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8487168)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_4_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_4_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8487744)))];
            fp16 var_749_to_fp16 = const()[name = string("op_749_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 256, 256]> input_45_cast_fp16 = transpose(perm = var_746, x = input_tensor_69_cast_fp16)[name = string("transpose_38")];
            tensor<fp16, [1, 256, 256]> input_tensor_71_cast_fp16 = layer_norm(axes = input_tensor_71_axes_0, beta = text_encoder_convnext_convnext_4_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_749_to_fp16, gamma = text_encoder_convnext_convnext_4_norm_norm_LayerNormalization_weight_to_fp16, x = input_45_cast_fp16)[name = string("input_tensor_71_cast_fp16")];
            tensor<int32, [3]> var_758 = const()[name = string("op_758"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_63_pad_type_0 = const()[name = string("first_63_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_63_strides_0 = const()[name = string("first_63_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_63_pad_0 = const()[name = string("first_63_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_63_dilations_0 = const()[name = string("first_63_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_63_groups_0 = const()[name = string("first_63_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_convnext_convnext_4_pwconv1_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_4_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8488320)))];
            tensor<fp16, [1024]> text_encoder_convnext_convnext_4_pwconv1_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_4_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9012672)))];
            tensor<fp16, [1, 256, 256]> input_47_cast_fp16 = transpose(perm = var_758, x = input_tensor_71_cast_fp16)[name = string("transpose_37")];
            tensor<fp16, [1, 1024, 256]> first_63_cast_fp16 = conv(bias = text_encoder_convnext_convnext_4_pwconv1_Conv_bias_to_fp16, dilations = first_63_dilations_0, groups = first_63_groups_0, pad = first_63_pad_0, pad_type = first_63_pad_type_0, strides = first_63_strides_0, weight = text_encoder_convnext_convnext_4_pwconv1_Conv_weight_to_fp16, x = input_47_cast_fp16)[name = string("first_63_cast_fp16")];
            string input_49_mode_0 = const()[name = string("input_49_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 1024, 256]> input_49_cast_fp16 = gelu(mode = input_49_mode_0, x = first_63_cast_fp16)[name = string("input_49_cast_fp16")];
            string second_57_pad_type_0 = const()[name = string("second_57_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_57_strides_0 = const()[name = string("second_57_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_57_pad_0 = const()[name = string("second_57_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_57_dilations_0 = const()[name = string("second_57_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_57_groups_0 = const()[name = string("second_57_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> second_59_weight_0_to_fp16 = const()[name = string("second_59_weight_0_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9014784)))];
            tensor<fp16, [256]> second_59_bias_0_to_fp16 = const()[name = string("second_59_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9539136)))];
            tensor<fp16, [1, 256, 256]> second_59_cast_fp16 = conv(bias = second_59_bias_0_to_fp16, dilations = second_57_dilations_0, groups = second_57_groups_0, pad = second_57_pad_0, pad_type = second_57_pad_type_0, strides = second_57_strides_0, weight = second_59_weight_0_to_fp16, x = input_49_cast_fp16)[name = string("second_59_cast_fp16")];
            tensor<fp16, [1, 256, 256]> first_71_cast_fp16 = add(x = input_41_cast_fp16, y = second_59_cast_fp16)[name = string("first_71_cast_fp16")];
            tensor<fp16, [1, 256, 256]> first_73_cast_fp16 = mul(x = first_71_cast_fp16, y = text_mask)[name = string("first_73_cast_fp16")];
            tensor<fp16, [1, 256, 256]> input_51_cast_fp16 = mul(x = first_73_cast_fp16, y = text_mask)[name = string("input_51_cast_fp16")];
            tensor<int32, [6]> input_53_pad_0 = const()[name = string("input_53_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 8, 8])];
            string input_53_mode_0 = const()[name = string("input_53_mode_0"), val = string("replicate")];
            fp16 const_5_to_fp16 = const()[name = string("const_5_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 256, 272]> input_53_cast_fp16 = pad(constant_val = const_5_to_fp16, mode = input_53_mode_0, pad = input_53_pad_0, x = input_51_cast_fp16)[name = string("input_53_cast_fp16")];
            string first_75_pad_type_0 = const()[name = string("first_75_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_75_dilations_0 = const()[name = string("first_75_dilations_0"), val = tensor<int32, [1]>([4])];
            int32 first_75_groups_0 = const()[name = string("first_75_groups_0"), val = int32(256)];
            tensor<int32, [1]> first_75_strides_0 = const()[name = string("first_75_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_75_pad_0 = const()[name = string("first_75_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [256, 1, 5]> text_encoder_convnext_convnext_5_dwconv_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_5_dwconv_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9539712)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_5_dwconv_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_5_dwconv_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9542336)))];
            tensor<fp16, [1, 256, 256]> first_75_cast_fp16 = conv(bias = text_encoder_convnext_convnext_5_dwconv_Conv_bias_to_fp16, dilations = first_75_dilations_0, groups = first_75_groups_0, pad = first_75_pad_0, pad_type = first_75_pad_type_0, strides = first_75_strides_0, weight = text_encoder_convnext_convnext_5_dwconv_Conv_weight_to_fp16, x = input_53_cast_fp16)[name = string("first_75_cast_fp16")];
            tensor<fp16, [1, 256, 256]> input_tensor_83_cast_fp16 = mul(x = first_75_cast_fp16, y = text_mask)[name = string("input_tensor_83_cast_fp16")];
            tensor<int32, [3]> var_815 = const()[name = string("op_815"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_85_axes_0 = const()[name = string("input_tensor_85_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_convnext_convnext_5_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_5_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9542912)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_5_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_5_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9543488)))];
            fp16 var_818_to_fp16 = const()[name = string("op_818_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 256, 256]> input_55_cast_fp16 = transpose(perm = var_815, x = input_tensor_83_cast_fp16)[name = string("transpose_36")];
            tensor<fp16, [1, 256, 256]> input_tensor_85_cast_fp16 = layer_norm(axes = input_tensor_85_axes_0, beta = text_encoder_convnext_convnext_5_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_818_to_fp16, gamma = text_encoder_convnext_convnext_5_norm_norm_LayerNormalization_weight_to_fp16, x = input_55_cast_fp16)[name = string("input_tensor_85_cast_fp16")];
            tensor<int32, [3]> var_827 = const()[name = string("op_827"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_77_pad_type_0 = const()[name = string("first_77_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_77_strides_0 = const()[name = string("first_77_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_77_pad_0 = const()[name = string("first_77_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_77_dilations_0 = const()[name = string("first_77_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_77_groups_0 = const()[name = string("first_77_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_convnext_convnext_5_pwconv1_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_5_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9544064)))];
            tensor<fp16, [1024]> text_encoder_convnext_convnext_5_pwconv1_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_5_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10068416)))];
            tensor<fp16, [1, 256, 256]> input_57_cast_fp16 = transpose(perm = var_827, x = input_tensor_85_cast_fp16)[name = string("transpose_35")];
            tensor<fp16, [1, 1024, 256]> first_77_cast_fp16 = conv(bias = text_encoder_convnext_convnext_5_pwconv1_Conv_bias_to_fp16, dilations = first_77_dilations_0, groups = first_77_groups_0, pad = first_77_pad_0, pad_type = first_77_pad_type_0, strides = first_77_strides_0, weight = text_encoder_convnext_convnext_5_pwconv1_Conv_weight_to_fp16, x = input_57_cast_fp16)[name = string("first_77_cast_fp16")];
            string input_59_mode_0 = const()[name = string("input_59_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 1024, 256]> input_59_cast_fp16 = gelu(mode = input_59_mode_0, x = first_77_cast_fp16)[name = string("input_59_cast_fp16")];
            string second_69_pad_type_0 = const()[name = string("second_69_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_69_strides_0 = const()[name = string("second_69_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_69_pad_0 = const()[name = string("second_69_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_69_dilations_0 = const()[name = string("second_69_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_69_groups_0 = const()[name = string("second_69_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> second_71_weight_0_to_fp16 = const()[name = string("second_71_weight_0_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10070528)))];
            tensor<fp16, [256]> second_71_bias_0_to_fp16 = const()[name = string("second_71_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10594880)))];
            tensor<fp16, [1, 256, 256]> second_71_cast_fp16 = conv(bias = second_71_bias_0_to_fp16, dilations = second_69_dilations_0, groups = second_69_groups_0, pad = second_69_pad_0, pad_type = second_69_pad_type_0, strides = second_69_strides_0, weight = second_71_weight_0_to_fp16, x = input_59_cast_fp16)[name = string("second_71_cast_fp16")];
            tensor<fp16, [1, 256, 256]> first_85_cast_fp16 = add(x = input_51_cast_fp16, y = second_71_cast_fp16)[name = string("first_85_cast_fp16")];
            tensor<fp16, [1, 256, 256]> first_89_cast_fp16 = mul(x = first_85_cast_fp16, y = text_mask)[name = string("first_89_cast_fp16")];
            tensor<int32, [1]> first_87_axes_0 = const()[name = string("first_87_axes_0"), val = tensor<int32, [1]>([2])];
            tensor<fp16, [1, 1, 1, 256]> first_87_cast_fp16 = expand_dims(axes = first_87_axes_0, x = text_mask)[name = string("first_87_cast_fp16")];
            tensor<int32, [1]> second_73_axes_0 = const()[name = string("second_73_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 1, 256, 1]> second_73_cast_fp16 = expand_dims(axes = second_73_axes_0, x = text_mask)[name = string("second_73_cast_fp16")];
            tensor<fp16, [1, 1, 256, 256]> x_45_cast_fp16 = mul(x = first_87_cast_fp16, y = second_73_cast_fp16)[name = string("x_45_cast_fp16")];
            tensor<fp16, [1, 256, 256]> input_61_cast_fp16 = mul(x = first_89_cast_fp16, y = text_mask)[name = string("input_61_cast_fp16")];
            string input_tensor_97_pad_type_0 = const()[name = string("input_tensor_97_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_97_strides_0 = const()[name = string("input_tensor_97_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_97_pad_0 = const()[name = string("input_tensor_97_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_97_dilations_0 = const()[name = string("input_tensor_97_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_97_groups_0 = const()[name = string("input_tensor_97_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_0_conv_q_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_q_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10595456)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_0_conv_q_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_q_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10726592)))];
            tensor<fp16, [1, 256, 256]> input_tensor_97_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_0_conv_q_Conv_bias_to_fp16, dilations = input_tensor_97_dilations_0, groups = input_tensor_97_groups_0, pad = input_tensor_97_pad_0, pad_type = input_tensor_97_pad_type_0, strides = input_tensor_97_strides_0, weight = text_encoder_attn_encoder_attn_layers_0_conv_q_Conv_weight_to_fp16, x = input_61_cast_fp16)[name = string("input_tensor_97_cast_fp16")];
            string input_tensor_89_pad_type_0 = const()[name = string("input_tensor_89_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_89_strides_0 = const()[name = string("input_tensor_89_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_89_pad_0 = const()[name = string("input_tensor_89_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_89_dilations_0 = const()[name = string("input_tensor_89_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_89_groups_0 = const()[name = string("input_tensor_89_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_0_conv_k_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_k_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10727168)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_0_conv_k_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_k_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10858304)))];
            tensor<fp16, [1, 256, 256]> input_tensor_89_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_0_conv_k_Conv_bias_to_fp16, dilations = input_tensor_89_dilations_0, groups = input_tensor_89_groups_0, pad = input_tensor_89_pad_0, pad_type = input_tensor_89_pad_type_0, strides = input_tensor_89_strides_0, weight = text_encoder_attn_encoder_attn_layers_0_conv_k_Conv_weight_to_fp16, x = input_61_cast_fp16)[name = string("input_tensor_89_cast_fp16")];
            string input_tensor_109_pad_type_0 = const()[name = string("input_tensor_109_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_109_strides_0 = const()[name = string("input_tensor_109_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_109_pad_0 = const()[name = string("input_tensor_109_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_109_dilations_0 = const()[name = string("input_tensor_109_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_109_groups_0 = const()[name = string("input_tensor_109_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_0_conv_v_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_v_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10858880)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_0_conv_v_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_v_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10990016)))];
            tensor<fp16, [1, 256, 256]> input_tensor_109_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_0_conv_v_Conv_bias_to_fp16, dilations = input_tensor_109_dilations_0, groups = input_tensor_109_groups_0, pad = input_tensor_109_pad_0, pad_type = input_tensor_109_pad_type_0, strides = input_tensor_109_strides_0, weight = text_encoder_attn_encoder_attn_layers_0_conv_v_Conv_weight_to_fp16, x = input_61_cast_fp16)[name = string("input_tensor_109_cast_fp16")];
            tensor<int32, [4]> var_973 = const()[name = string("op_973"), val = tensor<int32, [4]>([1, 4, 64, 256])];
            tensor<fp16, [1, 4, 64, 256]> input_tensor_105_cast_fp16 = reshape(shape = var_973, x = input_tensor_97_cast_fp16)[name = string("input_tensor_105_cast_fp16")];
            tensor<int32, [4]> var_979 = const()[name = string("op_979"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [4]> var_1005 = const()[name = string("op_1005"), val = tensor<int32, [4]>([1, 4, 64, 256])];
            tensor<fp16, [1, 4, 64, 256]> y_1_cast_fp16 = reshape(shape = var_1005, x = input_tensor_89_cast_fp16)[name = string("y_1_cast_fp16")];
            tensor<int32, [4]> var_1017 = const()[name = string("op_1017"), val = tensor<int32, [4]>([1, 4, 64, 256])];
            tensor<fp16, [1, 4, 64, 256]> input_tensor_111_cast_fp16 = reshape(shape = var_1017, x = input_tensor_109_cast_fp16)[name = string("input_tensor_111_cast_fp16")];
            fp16 _inversed_x_25_y_0_to_fp16 = const()[name = string("_inversed_x_25_y_0_to_fp16"), val = fp16(0x1p-3)];
            tensor<fp16, [1, 4, 256, 64]> first_91_cast_fp16 = transpose(perm = var_979, x = input_tensor_105_cast_fp16)[name = string("transpose_34")];
            tensor<fp16, [1, 4, 256, 64]> _inversed_x_25_cast_fp16 = mul(x = first_91_cast_fp16, y = _inversed_x_25_y_0_to_fp16)[name = string("_inversed_x_25_cast_fp16")];
            bool first_107_transpose_x_0 = const()[name = string("first_107_transpose_x_0"), val = bool(false)];
            bool first_107_transpose_y_0 = const()[name = string("first_107_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 4, 256, 256]> first_107_cast_fp16 = matmul(transpose_x = first_107_transpose_x_0, transpose_y = first_107_transpose_y_0, x = _inversed_x_25_cast_fp16, y = y_1_cast_fp16)[name = string("first_107_cast_fp16")];
            bool input_tensor_143_transpose_x_0 = const()[name = string("input_tensor_143_transpose_x_0"), val = bool(false)];
            bool input_tensor_143_transpose_y_0 = const()[name = string("input_tensor_143_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 64, 511]> y_3_to_fp16 = const()[name = string("y_3_to_fp16"), val = tensor<fp16, [1, 1, 64, 511]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(19198592)))];
            tensor<fp16, [1, 4, 256, 511]> input_tensor_143_cast_fp16 = matmul(transpose_x = input_tensor_143_transpose_x_0, transpose_y = input_tensor_143_transpose_y_0, x = _inversed_x_25_cast_fp16, y = y_3_to_fp16)[name = string("input_tensor_143_cast_fp16")];
            tensor<int32, [8]> input_tensor_165_pad_0 = const()[name = string("input_tensor_165_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 1])];
            string input_tensor_165_mode_0 = const()[name = string("input_tensor_165_mode_0"), val = string("constant")];
            fp16 const_23_to_fp16 = const()[name = string("const_23_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 256, 512]> input_tensor_165_cast_fp16 = pad(constant_val = const_23_to_fp16, mode = input_tensor_165_mode_0, pad = input_tensor_165_pad_0, x = input_tensor_143_cast_fp16)[name = string("input_tensor_165_cast_fp16")];
            tensor<int32, [3]> var_1140 = const()[name = string("op_1140"), val = tensor<int32, [3]>([1, 4, 131072])];
            tensor<fp16, [1, 4, 131072]> input_69_cast_fp16 = reshape(shape = var_1140, x = input_tensor_165_cast_fp16)[name = string("input_69_cast_fp16")];
            tensor<int32, [6]> input_tensor_187_pad_0 = const()[name = string("input_tensor_187_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 0, 255])];
            string input_tensor_187_mode_0 = const()[name = string("input_tensor_187_mode_0"), val = string("constant")];
            fp16 const_24_to_fp16 = const()[name = string("const_24_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 131327]> input_tensor_187_cast_fp16 = pad(constant_val = const_24_to_fp16, mode = input_tensor_187_mode_0, pad = input_tensor_187_pad_0, x = input_69_cast_fp16)[name = string("input_tensor_187_cast_fp16")];
            tensor<int32, [4]> var_1175 = const()[name = string("op_1175"), val = tensor<int32, [4]>([1, 4, 257, 511])];
            tensor<fp16, [1, 4, 257, 511]> x_41_cast_fp16 = reshape(shape = var_1175, x = input_tensor_187_cast_fp16)[name = string("x_41_cast_fp16")];
            tensor<int32, [4]> x_43_begin_0 = const()[name = string("x_43_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> x_43_end_0 = const()[name = string("x_43_end_0"), val = tensor<int32, [4]>([1, 4, 256, 511])];
            tensor<bool, [4]> x_43_end_mask_0 = const()[name = string("x_43_end_mask_0"), val = tensor<bool, [4]>([true, true, false, true])];
            tensor<fp16, [1, 4, 256, 511]> x_43_cast_fp16 = slice_by_index(begin = x_43_begin_0, end = x_43_end_0, end_mask = x_43_end_mask_0, x = x_41_cast_fp16)[name = string("x_43_cast_fp16")];
            tensor<int32, [4]> second_97_begin_0 = const()[name = string("second_97_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 255])];
            tensor<int32, [4]> second_97_end_0 = const()[name = string("second_97_end_0"), val = tensor<int32, [4]>([1, 4, 256, 1])];
            tensor<bool, [4]> second_97_end_mask_0 = const()[name = string("second_97_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 256, 256]> second_97_cast_fp16 = slice_by_index(begin = second_97_begin_0, end = second_97_end_0, end_mask = second_97_end_mask_0, x = x_43_cast_fp16)[name = string("second_97_cast_fp16")];
            tensor<fp16, [1, 4, 256, 256]> y_7_cast_fp16 = add(x = first_107_cast_fp16, y = second_97_cast_fp16)[name = string("y_7_cast_fp16")];
            fp16 text_encoder_attn_encoder_attn_layers_0_Constant_87_value_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_Constant_87_value_to_fp16"), val = fp16(0x0p+0)];
            tensor<bool, [1, 1, 256, 256]> input_tensor_189_cast_fp16 = equal(x = x_45_cast_fp16, y = text_encoder_attn_encoder_attn_layers_0_Constant_87_value_to_fp16)[name = string("input_tensor_189_cast_fp16")];
            tensor<int32, [4]> condition_1_after_broadcast_reps_0 = const()[name = string("condition_1_after_broadcast_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<bool, [1, 4, 256, 256]> condition_1_after_broadcast = tile(reps = condition_1_after_broadcast_reps_0, x = input_tensor_189_cast_fp16)[name = string("condition_1_after_broadcast")];
            tensor<fp16, [1, 4, 256, 256]> text_encoder_attn_encoder_attn_layers_0_Constant_88_value_after_broadcast_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_Constant_88_value_after_broadcast_to_fp16"), val = tensor<fp16, [1, 4, 256, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(19264064)))];
            tensor<fp16, [1, 4, 256, 256]> input_71_cast_fp16 = select(a = text_encoder_attn_encoder_attn_layers_0_Constant_88_value_after_broadcast_to_fp16, b = y_7_cast_fp16, cond = condition_1_after_broadcast)[name = string("input_71_cast_fp16")];
            int32 var_1218 = const()[name = string("op_1218"), val = int32(-1)];
            tensor<fp16, [1, 4, 256, 256]> x_49_cast_fp16 = softmax(axis = var_1218, x = input_71_cast_fp16)[name = string("x_49_cast_fp16")];
            bool first_119_transpose_x_1 = const()[name = string("first_119_transpose_x_1"), val = bool(false)];
            bool first_119_transpose_y_1 = const()[name = string("first_119_transpose_y_1"), val = bool(true)];
            tensor<fp16, [1, 4, 256, 64]> first_119_cast_fp16 = matmul(transpose_x = first_119_transpose_x_1, transpose_y = first_119_transpose_y_1, x = x_49_cast_fp16, y = input_tensor_111_cast_fp16)[name = string("first_119_cast_fp16")];
            tensor<int32, [8]> input_tensor_219_pad_0 = const()[name = string("input_tensor_219_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 255])];
            string input_tensor_219_mode_0 = const()[name = string("input_tensor_219_mode_0"), val = string("constant")];
            fp16 const_31_to_fp16 = const()[name = string("const_31_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 256, 511]> input_tensor_219_cast_fp16 = pad(constant_val = const_31_to_fp16, mode = input_tensor_219_mode_0, pad = input_tensor_219_pad_0, x = x_49_cast_fp16)[name = string("input_tensor_219_cast_fp16")];
            tensor<int32, [3]> var_1292 = const()[name = string("op_1292"), val = tensor<int32, [3]>([1, 4, 130816])];
            tensor<fp16, [1, 4, 130816]> input_73_cast_fp16 = reshape(shape = var_1292, x = input_tensor_219_cast_fp16)[name = string("input_73_cast_fp16")];
            tensor<int32, [6]> input_tensor_237_pad_0 = const()[name = string("input_tensor_237_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 256, 0])];
            string input_tensor_237_mode_0 = const()[name = string("input_tensor_237_mode_0"), val = string("constant")];
            fp16 const_32_to_fp16 = const()[name = string("const_32_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 131072]> input_tensor_237_cast_fp16 = pad(constant_val = const_32_to_fp16, mode = input_tensor_237_mode_0, pad = input_tensor_237_pad_0, x = input_73_cast_fp16)[name = string("input_tensor_237_cast_fp16")];
            tensor<int32, [4]> var_1322 = const()[name = string("op_1322"), val = tensor<int32, [4]>([1, 4, 256, 512])];
            tensor<fp16, [1, 4, 256, 512]> x_59_cast_fp16 = reshape(shape = var_1322, x = input_tensor_237_cast_fp16)[name = string("x_59_cast_fp16")];
            tensor<int32, [4]> x_67_begin_0 = const()[name = string("x_67_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 1])];
            tensor<int32, [4]> x_67_end_0 = const()[name = string("x_67_end_0"), val = tensor<int32, [4]>([1, 4, 256, 1])];
            tensor<bool, [4]> x_67_end_mask_0 = const()[name = string("x_67_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 256, 511]> x_67_cast_fp16 = slice_by_index(begin = x_67_begin_0, end = x_67_end_0, end_mask = x_67_end_mask_0, x = x_59_cast_fp16)[name = string("x_67_cast_fp16")];
            bool second_111_transpose_x_0 = const()[name = string("second_111_transpose_x_0"), val = bool(false)];
            bool second_111_transpose_y_0 = const()[name = string("second_111_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 511, 64]> y_11_to_fp16 = const()[name = string("y_11_to_fp16"), val = tensor<fp16, [1, 1, 511, 64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(19788416)))];
            tensor<fp16, [1, 4, 256, 64]> second_111_cast_fp16 = matmul(transpose_x = second_111_transpose_x_0, transpose_y = second_111_transpose_y_0, x = x_67_cast_fp16, y = y_11_to_fp16)[name = string("second_111_cast_fp16")];
            tensor<fp16, [1, 4, 256, 64]> input_tensor_255_cast_fp16 = add(x = first_119_cast_fp16, y = second_111_cast_fp16)[name = string("input_tensor_255_cast_fp16")];
            tensor<int32, [4]> var_1369 = const()[name = string("op_1369"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [3]> var_1388 = const()[name = string("op_1388"), val = tensor<int32, [3]>([1, 256, 256])];
            tensor<fp16, [1, 4, 64, 256]> input_tensor_259_cast_fp16 = transpose(perm = var_1369, x = input_tensor_255_cast_fp16)[name = string("transpose_33")];
            tensor<fp16, [1, 256, 256]> input_77_cast_fp16 = reshape(shape = var_1388, x = input_tensor_259_cast_fp16)[name = string("input_77_cast_fp16")];
            string second_113_pad_type_0 = const()[name = string("second_113_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_113_strides_0 = const()[name = string("second_113_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_113_pad_0 = const()[name = string("second_113_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_113_dilations_0 = const()[name = string("second_113_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_113_groups_0 = const()[name = string("second_113_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_0_conv_o_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_o_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11000768)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_0_conv_o_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_o_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11131904)))];
            tensor<fp16, [1, 256, 256]> second_113_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_0_conv_o_Conv_bias_to_fp16, dilations = second_113_dilations_0, groups = second_113_groups_0, pad = second_113_pad_0, pad_type = second_113_pad_type_0, strides = second_113_strides_0, weight = text_encoder_attn_encoder_attn_layers_0_conv_o_Conv_weight_to_fp16, x = input_77_cast_fp16)[name = string("second_113_cast_fp16")];
            tensor<fp16, [1, 256, 256]> input_tensor_261_cast_fp16 = add(x = input_61_cast_fp16, y = second_113_cast_fp16)[name = string("input_tensor_261_cast_fp16")];
            tensor<int32, [3]> var_1406 = const()[name = string("op_1406"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_263_axes_0 = const()[name = string("input_tensor_263_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_0_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_0_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11132480)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_0_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_0_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11133056)))];
            fp16 var_1409_to_fp16 = const()[name = string("op_1409_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 256, 256]> input_79_cast_fp16 = transpose(perm = var_1406, x = input_tensor_261_cast_fp16)[name = string("transpose_32")];
            tensor<fp16, [1, 256, 256]> input_tensor_263_cast_fp16 = layer_norm(axes = input_tensor_263_axes_0, beta = text_encoder_attn_encoder_norm_layers_1_0_norm_LayerNormalization_bias_to_fp16, epsilon = var_1409_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_1_0_norm_LayerNormalization_weight_to_fp16, x = input_79_cast_fp16)[name = string("input_tensor_263_cast_fp16")];
            tensor<int32, [3]> var_1418 = const()[name = string("op_1418"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 256, 256]> first_121_cast_fp16 = transpose(perm = var_1418, x = input_tensor_263_cast_fp16)[name = string("transpose_31")];
            tensor<fp16, [1, 256, 256]> input_81_cast_fp16 = mul(x = first_121_cast_fp16, y = text_mask)[name = string("input_81_cast_fp16")];
            string input_83_pad_type_0 = const()[name = string("input_83_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_83_strides_0 = const()[name = string("input_83_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_83_pad_0 = const()[name = string("input_83_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_83_dilations_0 = const()[name = string("input_83_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_83_groups_0 = const()[name = string("input_83_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_attn_encoder_ffn_layers_0_conv_1_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_0_conv_1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11133632)))];
            tensor<fp16, [1024]> text_encoder_attn_encoder_ffn_layers_0_conv_1_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_0_conv_1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11657984)))];
            tensor<fp16, [1, 1024, 256]> input_83_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_0_conv_1_Conv_bias_to_fp16, dilations = input_83_dilations_0, groups = input_83_groups_0, pad = input_83_pad_0, pad_type = input_83_pad_type_0, strides = input_83_strides_0, weight = text_encoder_attn_encoder_ffn_layers_0_conv_1_Conv_weight_to_fp16, x = input_81_cast_fp16)[name = string("input_83_cast_fp16")];
            tensor<fp16, [1, 1024, 256]> first_123_cast_fp16 = relu(x = input_83_cast_fp16)[name = string("first_123_cast_fp16")];
            tensor<fp16, [1, 1024, 256]> input_85_cast_fp16 = mul(x = first_123_cast_fp16, y = text_mask)[name = string("input_85_cast_fp16")];
            string first_125_pad_type_0 = const()[name = string("first_125_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_125_strides_0 = const()[name = string("first_125_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_125_pad_0 = const()[name = string("first_125_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_125_dilations_0 = const()[name = string("first_125_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_125_groups_0 = const()[name = string("first_125_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> text_encoder_attn_encoder_ffn_layers_0_conv_2_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_0_conv_2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11660096)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_ffn_layers_0_conv_2_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_0_conv_2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12184448)))];
            tensor<fp16, [1, 256, 256]> first_125_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_0_conv_2_Conv_bias_to_fp16, dilations = first_125_dilations_0, groups = first_125_groups_0, pad = first_125_pad_0, pad_type = first_125_pad_type_0, strides = first_125_strides_0, weight = text_encoder_attn_encoder_ffn_layers_0_conv_2_Conv_weight_to_fp16, x = input_85_cast_fp16)[name = string("first_125_cast_fp16")];
            tensor<fp16, [1, 256, 256]> second_115_cast_fp16 = mul(x = first_125_cast_fp16, y = text_mask)[name = string("second_115_cast_fp16")];
            tensor<fp16, [1, 256, 256]> input_tensor_265_cast_fp16 = add(x = first_121_cast_fp16, y = second_115_cast_fp16)[name = string("input_tensor_265_cast_fp16")];
            tensor<int32, [3]> var_1451 = const()[name = string("op_1451"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_267_axes_0 = const()[name = string("input_tensor_267_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_0_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_0_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12185024)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_0_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_0_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12185600)))];
            fp16 var_1454_to_fp16 = const()[name = string("op_1454_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 256, 256]> input_87_cast_fp16 = transpose(perm = var_1451, x = input_tensor_265_cast_fp16)[name = string("transpose_30")];
            tensor<fp16, [1, 256, 256]> input_tensor_267_cast_fp16 = layer_norm(axes = input_tensor_267_axes_0, beta = text_encoder_attn_encoder_norm_layers_2_0_norm_LayerNormalization_bias_to_fp16, epsilon = var_1454_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_2_0_norm_LayerNormalization_weight_to_fp16, x = input_87_cast_fp16)[name = string("input_tensor_267_cast_fp16")];
            tensor<int32, [3]> var_1463 = const()[name = string("op_1463"), val = tensor<int32, [3]>([0, 2, 1])];
            string input_tensor_277_pad_type_0 = const()[name = string("input_tensor_277_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_277_strides_0 = const()[name = string("input_tensor_277_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_277_pad_0 = const()[name = string("input_tensor_277_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_277_dilations_0 = const()[name = string("input_tensor_277_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_277_groups_0 = const()[name = string("input_tensor_277_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_1_conv_q_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_q_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12186176)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_1_conv_q_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_q_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12317312)))];
            tensor<fp16, [1, 256, 256]> input_89_cast_fp16 = transpose(perm = var_1463, x = input_tensor_267_cast_fp16)[name = string("transpose_29")];
            tensor<fp16, [1, 256, 256]> input_tensor_277_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_1_conv_q_Conv_bias_to_fp16, dilations = input_tensor_277_dilations_0, groups = input_tensor_277_groups_0, pad = input_tensor_277_pad_0, pad_type = input_tensor_277_pad_type_0, strides = input_tensor_277_strides_0, weight = text_encoder_attn_encoder_attn_layers_1_conv_q_Conv_weight_to_fp16, x = input_89_cast_fp16)[name = string("input_tensor_277_cast_fp16")];
            string input_tensor_269_pad_type_0 = const()[name = string("input_tensor_269_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_269_strides_0 = const()[name = string("input_tensor_269_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_269_pad_0 = const()[name = string("input_tensor_269_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_269_dilations_0 = const()[name = string("input_tensor_269_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_269_groups_0 = const()[name = string("input_tensor_269_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_1_conv_k_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_k_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12317888)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_1_conv_k_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_k_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12449024)))];
            tensor<fp16, [1, 256, 256]> input_tensor_269_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_1_conv_k_Conv_bias_to_fp16, dilations = input_tensor_269_dilations_0, groups = input_tensor_269_groups_0, pad = input_tensor_269_pad_0, pad_type = input_tensor_269_pad_type_0, strides = input_tensor_269_strides_0, weight = text_encoder_attn_encoder_attn_layers_1_conv_k_Conv_weight_to_fp16, x = input_89_cast_fp16)[name = string("input_tensor_269_cast_fp16")];
            string input_tensor_289_pad_type_0 = const()[name = string("input_tensor_289_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_289_strides_0 = const()[name = string("input_tensor_289_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_289_pad_0 = const()[name = string("input_tensor_289_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_289_dilations_0 = const()[name = string("input_tensor_289_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_289_groups_0 = const()[name = string("input_tensor_289_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_1_conv_v_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_v_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12449600)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_1_conv_v_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_v_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12580736)))];
            tensor<fp16, [1, 256, 256]> input_tensor_289_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_1_conv_v_Conv_bias_to_fp16, dilations = input_tensor_289_dilations_0, groups = input_tensor_289_groups_0, pad = input_tensor_289_pad_0, pad_type = input_tensor_289_pad_type_0, strides = input_tensor_289_strides_0, weight = text_encoder_attn_encoder_attn_layers_1_conv_v_Conv_weight_to_fp16, x = input_89_cast_fp16)[name = string("input_tensor_289_cast_fp16")];
            tensor<int32, [4]> var_1571 = const()[name = string("op_1571"), val = tensor<int32, [4]>([1, 4, 64, 256])];
            tensor<fp16, [1, 4, 64, 256]> input_tensor_285_cast_fp16 = reshape(shape = var_1571, x = input_tensor_277_cast_fp16)[name = string("input_tensor_285_cast_fp16")];
            tensor<int32, [4]> var_1577 = const()[name = string("op_1577"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [4]> var_1603 = const()[name = string("op_1603"), val = tensor<int32, [4]>([1, 4, 64, 256])];
            tensor<fp16, [1, 4, 64, 256]> y_13_cast_fp16 = reshape(shape = var_1603, x = input_tensor_269_cast_fp16)[name = string("y_13_cast_fp16")];
            tensor<int32, [4]> var_1615 = const()[name = string("op_1615"), val = tensor<int32, [4]>([1, 4, 64, 256])];
            tensor<fp16, [1, 4, 64, 256]> input_tensor_291_cast_fp16 = reshape(shape = var_1615, x = input_tensor_289_cast_fp16)[name = string("input_tensor_291_cast_fp16")];
            fp16 _inversed_x_69_y_0_to_fp16 = const()[name = string("_inversed_x_69_y_0_to_fp16"), val = fp16(0x1p-3)];
            tensor<fp16, [1, 4, 256, 64]> first_127_cast_fp16 = transpose(perm = var_1577, x = input_tensor_285_cast_fp16)[name = string("transpose_28")];
            tensor<fp16, [1, 4, 256, 64]> _inversed_x_69_cast_fp16 = mul(x = first_127_cast_fp16, y = _inversed_x_69_y_0_to_fp16)[name = string("_inversed_x_69_cast_fp16")];
            bool first_143_transpose_x_0 = const()[name = string("first_143_transpose_x_0"), val = bool(false)];
            bool first_143_transpose_y_0 = const()[name = string("first_143_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 4, 256, 256]> first_143_cast_fp16 = matmul(transpose_x = first_143_transpose_x_0, transpose_y = first_143_transpose_y_0, x = _inversed_x_69_cast_fp16, y = y_13_cast_fp16)[name = string("first_143_cast_fp16")];
            bool input_tensor_323_transpose_x_0 = const()[name = string("input_tensor_323_transpose_x_0"), val = bool(false)];
            bool input_tensor_323_transpose_y_0 = const()[name = string("input_tensor_323_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 64, 511]> y_15_to_fp16 = const()[name = string("y_15_to_fp16"), val = tensor<fp16, [1, 1, 64, 511]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(19853888)))];
            tensor<fp16, [1, 4, 256, 511]> input_tensor_323_cast_fp16 = matmul(transpose_x = input_tensor_323_transpose_x_0, transpose_y = input_tensor_323_transpose_y_0, x = _inversed_x_69_cast_fp16, y = y_15_to_fp16)[name = string("input_tensor_323_cast_fp16")];
            tensor<int32, [8]> input_tensor_345_pad_0 = const()[name = string("input_tensor_345_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 1])];
            string input_tensor_345_mode_0 = const()[name = string("input_tensor_345_mode_0"), val = string("constant")];
            fp16 const_51_to_fp16 = const()[name = string("const_51_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 256, 512]> input_tensor_345_cast_fp16 = pad(constant_val = const_51_to_fp16, mode = input_tensor_345_mode_0, pad = input_tensor_345_pad_0, x = input_tensor_323_cast_fp16)[name = string("input_tensor_345_cast_fp16")];
            tensor<int32, [3]> var_1738 = const()[name = string("op_1738"), val = tensor<int32, [3]>([1, 4, 131072])];
            tensor<fp16, [1, 4, 131072]> input_97_cast_fp16 = reshape(shape = var_1738, x = input_tensor_345_cast_fp16)[name = string("input_97_cast_fp16")];
            tensor<int32, [6]> input_tensor_367_pad_0 = const()[name = string("input_tensor_367_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 0, 255])];
            string input_tensor_367_mode_0 = const()[name = string("input_tensor_367_mode_0"), val = string("constant")];
            fp16 const_52_to_fp16 = const()[name = string("const_52_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 131327]> input_tensor_367_cast_fp16 = pad(constant_val = const_52_to_fp16, mode = input_tensor_367_mode_0, pad = input_tensor_367_pad_0, x = input_97_cast_fp16)[name = string("input_tensor_367_cast_fp16")];
            tensor<int32, [4]> var_1773 = const()[name = string("op_1773"), val = tensor<int32, [4]>([1, 4, 257, 511])];
            tensor<fp16, [1, 4, 257, 511]> x_85_cast_fp16 = reshape(shape = var_1773, x = input_tensor_367_cast_fp16)[name = string("x_85_cast_fp16")];
            tensor<int32, [4]> x_87_begin_0 = const()[name = string("x_87_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> x_87_end_0 = const()[name = string("x_87_end_0"), val = tensor<int32, [4]>([1, 4, 256, 511])];
            tensor<bool, [4]> x_87_end_mask_0 = const()[name = string("x_87_end_mask_0"), val = tensor<bool, [4]>([true, true, false, true])];
            tensor<fp16, [1, 4, 256, 511]> x_87_cast_fp16 = slice_by_index(begin = x_87_begin_0, end = x_87_end_0, end_mask = x_87_end_mask_0, x = x_85_cast_fp16)[name = string("x_87_cast_fp16")];
            tensor<int32, [4]> second_139_begin_0 = const()[name = string("second_139_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 255])];
            tensor<int32, [4]> second_139_end_0 = const()[name = string("second_139_end_0"), val = tensor<int32, [4]>([1, 4, 256, 1])];
            tensor<bool, [4]> second_139_end_mask_0 = const()[name = string("second_139_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 256, 256]> second_139_cast_fp16 = slice_by_index(begin = second_139_begin_0, end = second_139_end_0, end_mask = second_139_end_mask_0, x = x_87_cast_fp16)[name = string("second_139_cast_fp16")];
            tensor<fp16, [1, 4, 256, 256]> y_17_cast_fp16 = add(x = first_143_cast_fp16, y = second_139_cast_fp16)[name = string("y_17_cast_fp16")];
            tensor<fp16, [1, 4, 256, 256]> input_99_cast_fp16 = select(a = text_encoder_attn_encoder_attn_layers_0_Constant_88_value_after_broadcast_to_fp16, b = y_17_cast_fp16, cond = condition_1_after_broadcast)[name = string("input_99_cast_fp16")];
            int32 var_1815 = const()[name = string("op_1815"), val = int32(-1)];
            tensor<fp16, [1, 4, 256, 256]> x_91_cast_fp16 = softmax(axis = var_1815, x = input_99_cast_fp16)[name = string("x_91_cast_fp16")];
            bool first_155_transpose_x_1 = const()[name = string("first_155_transpose_x_1"), val = bool(false)];
            bool first_155_transpose_y_1 = const()[name = string("first_155_transpose_y_1"), val = bool(true)];
            tensor<fp16, [1, 4, 256, 64]> first_155_cast_fp16 = matmul(transpose_x = first_155_transpose_x_1, transpose_y = first_155_transpose_y_1, x = x_91_cast_fp16, y = input_tensor_291_cast_fp16)[name = string("first_155_cast_fp16")];
            tensor<int32, [8]> input_tensor_397_pad_0 = const()[name = string("input_tensor_397_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 255])];
            string input_tensor_397_mode_0 = const()[name = string("input_tensor_397_mode_0"), val = string("constant")];
            fp16 const_59_to_fp16 = const()[name = string("const_59_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 256, 511]> input_tensor_397_cast_fp16 = pad(constant_val = const_59_to_fp16, mode = input_tensor_397_mode_0, pad = input_tensor_397_pad_0, x = x_91_cast_fp16)[name = string("input_tensor_397_cast_fp16")];
            tensor<int32, [3]> var_1889 = const()[name = string("op_1889"), val = tensor<int32, [3]>([1, 4, 130816])];
            tensor<fp16, [1, 4, 130816]> input_101_cast_fp16 = reshape(shape = var_1889, x = input_tensor_397_cast_fp16)[name = string("input_101_cast_fp16")];
            tensor<int32, [6]> input_tensor_415_pad_0 = const()[name = string("input_tensor_415_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 256, 0])];
            string input_tensor_415_mode_0 = const()[name = string("input_tensor_415_mode_0"), val = string("constant")];
            fp16 const_60_to_fp16 = const()[name = string("const_60_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 131072]> input_tensor_415_cast_fp16 = pad(constant_val = const_60_to_fp16, mode = input_tensor_415_mode_0, pad = input_tensor_415_pad_0, x = input_101_cast_fp16)[name = string("input_tensor_415_cast_fp16")];
            tensor<int32, [4]> var_1919 = const()[name = string("op_1919"), val = tensor<int32, [4]>([1, 4, 256, 512])];
            tensor<fp16, [1, 4, 256, 512]> x_101_cast_fp16 = reshape(shape = var_1919, x = input_tensor_415_cast_fp16)[name = string("x_101_cast_fp16")];
            tensor<int32, [4]> x_109_begin_0 = const()[name = string("x_109_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 1])];
            tensor<int32, [4]> x_109_end_0 = const()[name = string("x_109_end_0"), val = tensor<int32, [4]>([1, 4, 256, 1])];
            tensor<bool, [4]> x_109_end_mask_0 = const()[name = string("x_109_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 256, 511]> x_109_cast_fp16 = slice_by_index(begin = x_109_begin_0, end = x_109_end_0, end_mask = x_109_end_mask_0, x = x_101_cast_fp16)[name = string("x_109_cast_fp16")];
            bool second_153_transpose_x_0 = const()[name = string("second_153_transpose_x_0"), val = bool(false)];
            bool second_153_transpose_y_0 = const()[name = string("second_153_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 511, 64]> y_21_to_fp16 = const()[name = string("y_21_to_fp16"), val = tensor<fp16, [1, 1, 511, 64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(19919360)))];
            tensor<fp16, [1, 4, 256, 64]> second_153_cast_fp16 = matmul(transpose_x = second_153_transpose_x_0, transpose_y = second_153_transpose_y_0, x = x_109_cast_fp16, y = y_21_to_fp16)[name = string("second_153_cast_fp16")];
            tensor<fp16, [1, 4, 256, 64]> input_tensor_433_cast_fp16 = add(x = first_155_cast_fp16, y = second_153_cast_fp16)[name = string("input_tensor_433_cast_fp16")];
            tensor<int32, [4]> var_1966 = const()[name = string("op_1966"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [3]> var_1985 = const()[name = string("op_1985"), val = tensor<int32, [3]>([1, 256, 256])];
            tensor<fp16, [1, 4, 64, 256]> input_tensor_437_cast_fp16 = transpose(perm = var_1966, x = input_tensor_433_cast_fp16)[name = string("transpose_27")];
            tensor<fp16, [1, 256, 256]> input_105_cast_fp16 = reshape(shape = var_1985, x = input_tensor_437_cast_fp16)[name = string("input_105_cast_fp16")];
            string second_155_pad_type_0 = const()[name = string("second_155_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_155_strides_0 = const()[name = string("second_155_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_155_pad_0 = const()[name = string("second_155_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_155_dilations_0 = const()[name = string("second_155_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_155_groups_0 = const()[name = string("second_155_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_1_conv_o_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_o_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12589376)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_1_conv_o_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_o_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12720512)))];
            tensor<fp16, [1, 256, 256]> second_155_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_1_conv_o_Conv_bias_to_fp16, dilations = second_155_dilations_0, groups = second_155_groups_0, pad = second_155_pad_0, pad_type = second_155_pad_type_0, strides = second_155_strides_0, weight = text_encoder_attn_encoder_attn_layers_1_conv_o_Conv_weight_to_fp16, x = input_105_cast_fp16)[name = string("second_155_cast_fp16")];
            tensor<fp16, [1, 256, 256]> input_tensor_439_cast_fp16 = add(x = input_89_cast_fp16, y = second_155_cast_fp16)[name = string("input_tensor_439_cast_fp16")];
            tensor<int32, [3]> var_2003 = const()[name = string("op_2003"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_441_axes_0 = const()[name = string("input_tensor_441_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_1_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_1_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12721088)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_1_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_1_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12721664)))];
            fp16 var_2006_to_fp16 = const()[name = string("op_2006_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 256, 256]> input_107_cast_fp16 = transpose(perm = var_2003, x = input_tensor_439_cast_fp16)[name = string("transpose_26")];
            tensor<fp16, [1, 256, 256]> input_tensor_441_cast_fp16 = layer_norm(axes = input_tensor_441_axes_0, beta = text_encoder_attn_encoder_norm_layers_1_1_norm_LayerNormalization_bias_to_fp16, epsilon = var_2006_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_1_1_norm_LayerNormalization_weight_to_fp16, x = input_107_cast_fp16)[name = string("input_tensor_441_cast_fp16")];
            tensor<int32, [3]> var_2015 = const()[name = string("op_2015"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 256, 256]> first_157_cast_fp16 = transpose(perm = var_2015, x = input_tensor_441_cast_fp16)[name = string("transpose_25")];
            tensor<fp16, [1, 256, 256]> input_109_cast_fp16 = mul(x = first_157_cast_fp16, y = text_mask)[name = string("input_109_cast_fp16")];
            string input_111_pad_type_0 = const()[name = string("input_111_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_111_strides_0 = const()[name = string("input_111_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_111_pad_0 = const()[name = string("input_111_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_111_dilations_0 = const()[name = string("input_111_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_111_groups_0 = const()[name = string("input_111_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_attn_encoder_ffn_layers_1_conv_1_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_1_conv_1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12722240)))];
            tensor<fp16, [1024]> text_encoder_attn_encoder_ffn_layers_1_conv_1_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_1_conv_1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13246592)))];
            tensor<fp16, [1, 1024, 256]> input_111_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_1_conv_1_Conv_bias_to_fp16, dilations = input_111_dilations_0, groups = input_111_groups_0, pad = input_111_pad_0, pad_type = input_111_pad_type_0, strides = input_111_strides_0, weight = text_encoder_attn_encoder_ffn_layers_1_conv_1_Conv_weight_to_fp16, x = input_109_cast_fp16)[name = string("input_111_cast_fp16")];
            tensor<fp16, [1, 1024, 256]> first_159_cast_fp16 = relu(x = input_111_cast_fp16)[name = string("first_159_cast_fp16")];
            tensor<fp16, [1, 1024, 256]> input_113_cast_fp16 = mul(x = first_159_cast_fp16, y = text_mask)[name = string("input_113_cast_fp16")];
            string first_161_pad_type_0 = const()[name = string("first_161_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_161_strides_0 = const()[name = string("first_161_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_161_pad_0 = const()[name = string("first_161_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_161_dilations_0 = const()[name = string("first_161_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_161_groups_0 = const()[name = string("first_161_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> text_encoder_attn_encoder_ffn_layers_1_conv_2_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_1_conv_2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13248704)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_ffn_layers_1_conv_2_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_1_conv_2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13773056)))];
            tensor<fp16, [1, 256, 256]> first_161_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_1_conv_2_Conv_bias_to_fp16, dilations = first_161_dilations_0, groups = first_161_groups_0, pad = first_161_pad_0, pad_type = first_161_pad_type_0, strides = first_161_strides_0, weight = text_encoder_attn_encoder_ffn_layers_1_conv_2_Conv_weight_to_fp16, x = input_113_cast_fp16)[name = string("first_161_cast_fp16")];
            tensor<fp16, [1, 256, 256]> second_157_cast_fp16 = mul(x = first_161_cast_fp16, y = text_mask)[name = string("second_157_cast_fp16")];
            tensor<fp16, [1, 256, 256]> input_tensor_443_cast_fp16 = add(x = first_157_cast_fp16, y = second_157_cast_fp16)[name = string("input_tensor_443_cast_fp16")];
            tensor<int32, [3]> var_2048 = const()[name = string("op_2048"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_445_axes_0 = const()[name = string("input_tensor_445_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_1_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_1_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13773632)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_1_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_1_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13774208)))];
            fp16 var_2051_to_fp16 = const()[name = string("op_2051_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 256, 256]> input_115_cast_fp16 = transpose(perm = var_2048, x = input_tensor_443_cast_fp16)[name = string("transpose_24")];
            tensor<fp16, [1, 256, 256]> input_tensor_445_cast_fp16 = layer_norm(axes = input_tensor_445_axes_0, beta = text_encoder_attn_encoder_norm_layers_2_1_norm_LayerNormalization_bias_to_fp16, epsilon = var_2051_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_2_1_norm_LayerNormalization_weight_to_fp16, x = input_115_cast_fp16)[name = string("input_tensor_445_cast_fp16")];
            tensor<int32, [3]> var_2060 = const()[name = string("op_2060"), val = tensor<int32, [3]>([0, 2, 1])];
            string input_tensor_455_pad_type_0 = const()[name = string("input_tensor_455_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_455_strides_0 = const()[name = string("input_tensor_455_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_455_pad_0 = const()[name = string("input_tensor_455_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_455_dilations_0 = const()[name = string("input_tensor_455_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_455_groups_0 = const()[name = string("input_tensor_455_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_2_conv_q_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_q_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13774784)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_2_conv_q_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_q_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13905920)))];
            tensor<fp16, [1, 256, 256]> input_117_cast_fp16 = transpose(perm = var_2060, x = input_tensor_445_cast_fp16)[name = string("transpose_23")];
            tensor<fp16, [1, 256, 256]> input_tensor_455_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_2_conv_q_Conv_bias_to_fp16, dilations = input_tensor_455_dilations_0, groups = input_tensor_455_groups_0, pad = input_tensor_455_pad_0, pad_type = input_tensor_455_pad_type_0, strides = input_tensor_455_strides_0, weight = text_encoder_attn_encoder_attn_layers_2_conv_q_Conv_weight_to_fp16, x = input_117_cast_fp16)[name = string("input_tensor_455_cast_fp16")];
            string input_tensor_447_pad_type_0 = const()[name = string("input_tensor_447_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_447_strides_0 = const()[name = string("input_tensor_447_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_447_pad_0 = const()[name = string("input_tensor_447_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_447_dilations_0 = const()[name = string("input_tensor_447_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_447_groups_0 = const()[name = string("input_tensor_447_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_2_conv_k_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_k_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13906496)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_2_conv_k_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_k_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14037632)))];
            tensor<fp16, [1, 256, 256]> input_tensor_447_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_2_conv_k_Conv_bias_to_fp16, dilations = input_tensor_447_dilations_0, groups = input_tensor_447_groups_0, pad = input_tensor_447_pad_0, pad_type = input_tensor_447_pad_type_0, strides = input_tensor_447_strides_0, weight = text_encoder_attn_encoder_attn_layers_2_conv_k_Conv_weight_to_fp16, x = input_117_cast_fp16)[name = string("input_tensor_447_cast_fp16")];
            string input_tensor_467_pad_type_0 = const()[name = string("input_tensor_467_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_467_strides_0 = const()[name = string("input_tensor_467_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_467_pad_0 = const()[name = string("input_tensor_467_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_467_dilations_0 = const()[name = string("input_tensor_467_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_467_groups_0 = const()[name = string("input_tensor_467_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_2_conv_v_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_v_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14038208)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_2_conv_v_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_v_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14169344)))];
            tensor<fp16, [1, 256, 256]> input_tensor_467_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_2_conv_v_Conv_bias_to_fp16, dilations = input_tensor_467_dilations_0, groups = input_tensor_467_groups_0, pad = input_tensor_467_pad_0, pad_type = input_tensor_467_pad_type_0, strides = input_tensor_467_strides_0, weight = text_encoder_attn_encoder_attn_layers_2_conv_v_Conv_weight_to_fp16, x = input_117_cast_fp16)[name = string("input_tensor_467_cast_fp16")];
            tensor<int32, [4]> var_2168 = const()[name = string("op_2168"), val = tensor<int32, [4]>([1, 4, 64, 256])];
            tensor<fp16, [1, 4, 64, 256]> input_tensor_463_cast_fp16 = reshape(shape = var_2168, x = input_tensor_455_cast_fp16)[name = string("input_tensor_463_cast_fp16")];
            tensor<int32, [4]> var_2174 = const()[name = string("op_2174"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [4]> var_2200 = const()[name = string("op_2200"), val = tensor<int32, [4]>([1, 4, 64, 256])];
            tensor<fp16, [1, 4, 64, 256]> y_23_cast_fp16 = reshape(shape = var_2200, x = input_tensor_447_cast_fp16)[name = string("y_23_cast_fp16")];
            tensor<int32, [4]> var_2212 = const()[name = string("op_2212"), val = tensor<int32, [4]>([1, 4, 64, 256])];
            tensor<fp16, [1, 4, 64, 256]> input_tensor_469_cast_fp16 = reshape(shape = var_2212, x = input_tensor_467_cast_fp16)[name = string("input_tensor_469_cast_fp16")];
            fp16 _inversed_x_111_y_0_to_fp16 = const()[name = string("_inversed_x_111_y_0_to_fp16"), val = fp16(0x1p-3)];
            tensor<fp16, [1, 4, 256, 64]> first_163_cast_fp16 = transpose(perm = var_2174, x = input_tensor_463_cast_fp16)[name = string("transpose_22")];
            tensor<fp16, [1, 4, 256, 64]> _inversed_x_111_cast_fp16 = mul(x = first_163_cast_fp16, y = _inversed_x_111_y_0_to_fp16)[name = string("_inversed_x_111_cast_fp16")];
            bool first_179_transpose_x_0 = const()[name = string("first_179_transpose_x_0"), val = bool(false)];
            bool first_179_transpose_y_0 = const()[name = string("first_179_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 4, 256, 256]> first_179_cast_fp16 = matmul(transpose_x = first_179_transpose_x_0, transpose_y = first_179_transpose_y_0, x = _inversed_x_111_cast_fp16, y = y_23_cast_fp16)[name = string("first_179_cast_fp16")];
            bool input_tensor_501_transpose_x_0 = const()[name = string("input_tensor_501_transpose_x_0"), val = bool(false)];
            bool input_tensor_501_transpose_y_0 = const()[name = string("input_tensor_501_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 64, 511]> y_25_to_fp16 = const()[name = string("y_25_to_fp16"), val = tensor<fp16, [1, 1, 64, 511]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(19984832)))];
            tensor<fp16, [1, 4, 256, 511]> input_tensor_501_cast_fp16 = matmul(transpose_x = input_tensor_501_transpose_x_0, transpose_y = input_tensor_501_transpose_y_0, x = _inversed_x_111_cast_fp16, y = y_25_to_fp16)[name = string("input_tensor_501_cast_fp16")];
            tensor<int32, [8]> input_tensor_523_pad_0 = const()[name = string("input_tensor_523_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 1])];
            string input_tensor_523_mode_0 = const()[name = string("input_tensor_523_mode_0"), val = string("constant")];
            fp16 const_79_to_fp16 = const()[name = string("const_79_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 256, 512]> input_tensor_523_cast_fp16 = pad(constant_val = const_79_to_fp16, mode = input_tensor_523_mode_0, pad = input_tensor_523_pad_0, x = input_tensor_501_cast_fp16)[name = string("input_tensor_523_cast_fp16")];
            tensor<int32, [3]> var_2335 = const()[name = string("op_2335"), val = tensor<int32, [3]>([1, 4, 131072])];
            tensor<fp16, [1, 4, 131072]> input_125_cast_fp16 = reshape(shape = var_2335, x = input_tensor_523_cast_fp16)[name = string("input_125_cast_fp16")];
            tensor<int32, [6]> input_tensor_545_pad_0 = const()[name = string("input_tensor_545_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 0, 255])];
            string input_tensor_545_mode_0 = const()[name = string("input_tensor_545_mode_0"), val = string("constant")];
            fp16 const_80_to_fp16 = const()[name = string("const_80_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 131327]> input_tensor_545_cast_fp16 = pad(constant_val = const_80_to_fp16, mode = input_tensor_545_mode_0, pad = input_tensor_545_pad_0, x = input_125_cast_fp16)[name = string("input_tensor_545_cast_fp16")];
            tensor<int32, [4]> var_2370 = const()[name = string("op_2370"), val = tensor<int32, [4]>([1, 4, 257, 511])];
            tensor<fp16, [1, 4, 257, 511]> x_127_cast_fp16 = reshape(shape = var_2370, x = input_tensor_545_cast_fp16)[name = string("x_127_cast_fp16")];
            tensor<int32, [4]> x_129_begin_0 = const()[name = string("x_129_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> x_129_end_0 = const()[name = string("x_129_end_0"), val = tensor<int32, [4]>([1, 4, 256, 511])];
            tensor<bool, [4]> x_129_end_mask_0 = const()[name = string("x_129_end_mask_0"), val = tensor<bool, [4]>([true, true, false, true])];
            tensor<fp16, [1, 4, 256, 511]> x_129_cast_fp16 = slice_by_index(begin = x_129_begin_0, end = x_129_end_0, end_mask = x_129_end_mask_0, x = x_127_cast_fp16)[name = string("x_129_cast_fp16")];
            tensor<int32, [4]> second_181_begin_0 = const()[name = string("second_181_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 255])];
            tensor<int32, [4]> second_181_end_0 = const()[name = string("second_181_end_0"), val = tensor<int32, [4]>([1, 4, 256, 1])];
            tensor<bool, [4]> second_181_end_mask_0 = const()[name = string("second_181_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 256, 256]> second_181_cast_fp16 = slice_by_index(begin = second_181_begin_0, end = second_181_end_0, end_mask = second_181_end_mask_0, x = x_129_cast_fp16)[name = string("second_181_cast_fp16")];
            tensor<fp16, [1, 4, 256, 256]> y_27_cast_fp16 = add(x = first_179_cast_fp16, y = second_181_cast_fp16)[name = string("y_27_cast_fp16")];
            tensor<fp16, [1, 4, 256, 256]> input_127_cast_fp16 = select(a = text_encoder_attn_encoder_attn_layers_0_Constant_88_value_after_broadcast_to_fp16, b = y_27_cast_fp16, cond = condition_1_after_broadcast)[name = string("input_127_cast_fp16")];
            int32 var_2412 = const()[name = string("op_2412"), val = int32(-1)];
            tensor<fp16, [1, 4, 256, 256]> x_133_cast_fp16 = softmax(axis = var_2412, x = input_127_cast_fp16)[name = string("x_133_cast_fp16")];
            bool first_191_transpose_x_1 = const()[name = string("first_191_transpose_x_1"), val = bool(false)];
            bool first_191_transpose_y_1 = const()[name = string("first_191_transpose_y_1"), val = bool(true)];
            tensor<fp16, [1, 4, 256, 64]> first_191_cast_fp16 = matmul(transpose_x = first_191_transpose_x_1, transpose_y = first_191_transpose_y_1, x = x_133_cast_fp16, y = input_tensor_469_cast_fp16)[name = string("first_191_cast_fp16")];
            tensor<int32, [8]> input_tensor_575_pad_0 = const()[name = string("input_tensor_575_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 255])];
            string input_tensor_575_mode_0 = const()[name = string("input_tensor_575_mode_0"), val = string("constant")];
            fp16 const_87_to_fp16 = const()[name = string("const_87_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 256, 511]> input_tensor_575_cast_fp16 = pad(constant_val = const_87_to_fp16, mode = input_tensor_575_mode_0, pad = input_tensor_575_pad_0, x = x_133_cast_fp16)[name = string("input_tensor_575_cast_fp16")];
            tensor<int32, [3]> var_2486 = const()[name = string("op_2486"), val = tensor<int32, [3]>([1, 4, 130816])];
            tensor<fp16, [1, 4, 130816]> input_129_cast_fp16 = reshape(shape = var_2486, x = input_tensor_575_cast_fp16)[name = string("input_129_cast_fp16")];
            tensor<int32, [6]> input_tensor_593_pad_0 = const()[name = string("input_tensor_593_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 256, 0])];
            string input_tensor_593_mode_0 = const()[name = string("input_tensor_593_mode_0"), val = string("constant")];
            fp16 const_88_to_fp16 = const()[name = string("const_88_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 131072]> input_tensor_593_cast_fp16 = pad(constant_val = const_88_to_fp16, mode = input_tensor_593_mode_0, pad = input_tensor_593_pad_0, x = input_129_cast_fp16)[name = string("input_tensor_593_cast_fp16")];
            tensor<int32, [4]> var_2516 = const()[name = string("op_2516"), val = tensor<int32, [4]>([1, 4, 256, 512])];
            tensor<fp16, [1, 4, 256, 512]> x_143_cast_fp16 = reshape(shape = var_2516, x = input_tensor_593_cast_fp16)[name = string("x_143_cast_fp16")];
            tensor<int32, [4]> x_151_begin_0 = const()[name = string("x_151_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 1])];
            tensor<int32, [4]> x_151_end_0 = const()[name = string("x_151_end_0"), val = tensor<int32, [4]>([1, 4, 256, 1])];
            tensor<bool, [4]> x_151_end_mask_0 = const()[name = string("x_151_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 256, 511]> x_151_cast_fp16 = slice_by_index(begin = x_151_begin_0, end = x_151_end_0, end_mask = x_151_end_mask_0, x = x_143_cast_fp16)[name = string("x_151_cast_fp16")];
            bool second_195_transpose_x_0 = const()[name = string("second_195_transpose_x_0"), val = bool(false)];
            bool second_195_transpose_y_0 = const()[name = string("second_195_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 511, 64]> y_31_to_fp16 = const()[name = string("y_31_to_fp16"), val = tensor<fp16, [1, 1, 511, 64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(20050304)))];
            tensor<fp16, [1, 4, 256, 64]> second_195_cast_fp16 = matmul(transpose_x = second_195_transpose_x_0, transpose_y = second_195_transpose_y_0, x = x_151_cast_fp16, y = y_31_to_fp16)[name = string("second_195_cast_fp16")];
            tensor<fp16, [1, 4, 256, 64]> input_tensor_611_cast_fp16 = add(x = first_191_cast_fp16, y = second_195_cast_fp16)[name = string("input_tensor_611_cast_fp16")];
            tensor<int32, [4]> var_2563 = const()[name = string("op_2563"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [3]> var_2582 = const()[name = string("op_2582"), val = tensor<int32, [3]>([1, 256, 256])];
            tensor<fp16, [1, 4, 64, 256]> input_tensor_615_cast_fp16 = transpose(perm = var_2563, x = input_tensor_611_cast_fp16)[name = string("transpose_21")];
            tensor<fp16, [1, 256, 256]> input_133_cast_fp16 = reshape(shape = var_2582, x = input_tensor_615_cast_fp16)[name = string("input_133_cast_fp16")];
            string second_197_pad_type_0 = const()[name = string("second_197_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_197_strides_0 = const()[name = string("second_197_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_197_pad_0 = const()[name = string("second_197_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_197_dilations_0 = const()[name = string("second_197_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_197_groups_0 = const()[name = string("second_197_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_2_conv_o_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_o_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14177984)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_2_conv_o_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_o_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14309120)))];
            tensor<fp16, [1, 256, 256]> second_197_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_2_conv_o_Conv_bias_to_fp16, dilations = second_197_dilations_0, groups = second_197_groups_0, pad = second_197_pad_0, pad_type = second_197_pad_type_0, strides = second_197_strides_0, weight = text_encoder_attn_encoder_attn_layers_2_conv_o_Conv_weight_to_fp16, x = input_133_cast_fp16)[name = string("second_197_cast_fp16")];
            tensor<fp16, [1, 256, 256]> input_tensor_617_cast_fp16 = add(x = input_117_cast_fp16, y = second_197_cast_fp16)[name = string("input_tensor_617_cast_fp16")];
            tensor<int32, [3]> var_2600 = const()[name = string("op_2600"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_619_axes_0 = const()[name = string("input_tensor_619_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_2_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_2_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14309696)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_2_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_2_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14310272)))];
            fp16 var_2603_to_fp16 = const()[name = string("op_2603_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 256, 256]> input_135_cast_fp16 = transpose(perm = var_2600, x = input_tensor_617_cast_fp16)[name = string("transpose_20")];
            tensor<fp16, [1, 256, 256]> input_tensor_619_cast_fp16 = layer_norm(axes = input_tensor_619_axes_0, beta = text_encoder_attn_encoder_norm_layers_1_2_norm_LayerNormalization_bias_to_fp16, epsilon = var_2603_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_1_2_norm_LayerNormalization_weight_to_fp16, x = input_135_cast_fp16)[name = string("input_tensor_619_cast_fp16")];
            tensor<int32, [3]> var_2612 = const()[name = string("op_2612"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 256, 256]> first_193_cast_fp16 = transpose(perm = var_2612, x = input_tensor_619_cast_fp16)[name = string("transpose_19")];
            tensor<fp16, [1, 256, 256]> input_137_cast_fp16 = mul(x = first_193_cast_fp16, y = text_mask)[name = string("input_137_cast_fp16")];
            string input_139_pad_type_0 = const()[name = string("input_139_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_139_strides_0 = const()[name = string("input_139_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_139_pad_0 = const()[name = string("input_139_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_139_dilations_0 = const()[name = string("input_139_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_139_groups_0 = const()[name = string("input_139_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_attn_encoder_ffn_layers_2_conv_1_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_2_conv_1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14310848)))];
            tensor<fp16, [1024]> text_encoder_attn_encoder_ffn_layers_2_conv_1_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_2_conv_1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14835200)))];
            tensor<fp16, [1, 1024, 256]> input_139_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_2_conv_1_Conv_bias_to_fp16, dilations = input_139_dilations_0, groups = input_139_groups_0, pad = input_139_pad_0, pad_type = input_139_pad_type_0, strides = input_139_strides_0, weight = text_encoder_attn_encoder_ffn_layers_2_conv_1_Conv_weight_to_fp16, x = input_137_cast_fp16)[name = string("input_139_cast_fp16")];
            tensor<fp16, [1, 1024, 256]> first_195_cast_fp16 = relu(x = input_139_cast_fp16)[name = string("first_195_cast_fp16")];
            tensor<fp16, [1, 1024, 256]> input_141_cast_fp16 = mul(x = first_195_cast_fp16, y = text_mask)[name = string("input_141_cast_fp16")];
            string first_197_pad_type_0 = const()[name = string("first_197_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_197_strides_0 = const()[name = string("first_197_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_197_pad_0 = const()[name = string("first_197_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_197_dilations_0 = const()[name = string("first_197_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_197_groups_0 = const()[name = string("first_197_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> text_encoder_attn_encoder_ffn_layers_2_conv_2_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_2_conv_2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14837312)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_ffn_layers_2_conv_2_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_2_conv_2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15361664)))];
            tensor<fp16, [1, 256, 256]> first_197_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_2_conv_2_Conv_bias_to_fp16, dilations = first_197_dilations_0, groups = first_197_groups_0, pad = first_197_pad_0, pad_type = first_197_pad_type_0, strides = first_197_strides_0, weight = text_encoder_attn_encoder_ffn_layers_2_conv_2_Conv_weight_to_fp16, x = input_141_cast_fp16)[name = string("first_197_cast_fp16")];
            tensor<fp16, [1, 256, 256]> second_199_cast_fp16 = mul(x = first_197_cast_fp16, y = text_mask)[name = string("second_199_cast_fp16")];
            tensor<fp16, [1, 256, 256]> input_tensor_621_cast_fp16 = add(x = first_193_cast_fp16, y = second_199_cast_fp16)[name = string("input_tensor_621_cast_fp16")];
            tensor<int32, [3]> var_2645 = const()[name = string("op_2645"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_623_axes_0 = const()[name = string("input_tensor_623_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_2_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_2_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15362240)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_2_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_2_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15362816)))];
            fp16 var_2648_to_fp16 = const()[name = string("op_2648_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 256, 256]> input_143_cast_fp16 = transpose(perm = var_2645, x = input_tensor_621_cast_fp16)[name = string("transpose_18")];
            tensor<fp16, [1, 256, 256]> input_tensor_623_cast_fp16 = layer_norm(axes = input_tensor_623_axes_0, beta = text_encoder_attn_encoder_norm_layers_2_2_norm_LayerNormalization_bias_to_fp16, epsilon = var_2648_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_2_2_norm_LayerNormalization_weight_to_fp16, x = input_143_cast_fp16)[name = string("input_tensor_623_cast_fp16")];
            tensor<int32, [3]> var_2657 = const()[name = string("op_2657"), val = tensor<int32, [3]>([0, 2, 1])];
            string input_tensor_633_pad_type_0 = const()[name = string("input_tensor_633_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_633_strides_0 = const()[name = string("input_tensor_633_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_633_pad_0 = const()[name = string("input_tensor_633_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_633_dilations_0 = const()[name = string("input_tensor_633_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_633_groups_0 = const()[name = string("input_tensor_633_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_3_conv_q_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_q_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15363392)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_3_conv_q_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_q_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15494528)))];
            tensor<fp16, [1, 256, 256]> input_145_cast_fp16 = transpose(perm = var_2657, x = input_tensor_623_cast_fp16)[name = string("transpose_17")];
            tensor<fp16, [1, 256, 256]> input_tensor_633_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_3_conv_q_Conv_bias_to_fp16, dilations = input_tensor_633_dilations_0, groups = input_tensor_633_groups_0, pad = input_tensor_633_pad_0, pad_type = input_tensor_633_pad_type_0, strides = input_tensor_633_strides_0, weight = text_encoder_attn_encoder_attn_layers_3_conv_q_Conv_weight_to_fp16, x = input_145_cast_fp16)[name = string("input_tensor_633_cast_fp16")];
            string input_tensor_625_pad_type_0 = const()[name = string("input_tensor_625_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_625_strides_0 = const()[name = string("input_tensor_625_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_625_pad_0 = const()[name = string("input_tensor_625_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_625_dilations_0 = const()[name = string("input_tensor_625_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_625_groups_0 = const()[name = string("input_tensor_625_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_3_conv_k_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_k_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15495104)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_3_conv_k_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_k_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15626240)))];
            tensor<fp16, [1, 256, 256]> input_tensor_625_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_3_conv_k_Conv_bias_to_fp16, dilations = input_tensor_625_dilations_0, groups = input_tensor_625_groups_0, pad = input_tensor_625_pad_0, pad_type = input_tensor_625_pad_type_0, strides = input_tensor_625_strides_0, weight = text_encoder_attn_encoder_attn_layers_3_conv_k_Conv_weight_to_fp16, x = input_145_cast_fp16)[name = string("input_tensor_625_cast_fp16")];
            string input_tensor_645_pad_type_0 = const()[name = string("input_tensor_645_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_645_strides_0 = const()[name = string("input_tensor_645_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_645_pad_0 = const()[name = string("input_tensor_645_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_645_dilations_0 = const()[name = string("input_tensor_645_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_645_groups_0 = const()[name = string("input_tensor_645_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_3_conv_v_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_v_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15626816)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_3_conv_v_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_v_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15757952)))];
            tensor<fp16, [1, 256, 256]> input_tensor_645_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_3_conv_v_Conv_bias_to_fp16, dilations = input_tensor_645_dilations_0, groups = input_tensor_645_groups_0, pad = input_tensor_645_pad_0, pad_type = input_tensor_645_pad_type_0, strides = input_tensor_645_strides_0, weight = text_encoder_attn_encoder_attn_layers_3_conv_v_Conv_weight_to_fp16, x = input_145_cast_fp16)[name = string("input_tensor_645_cast_fp16")];
            tensor<int32, [4]> var_2765 = const()[name = string("op_2765"), val = tensor<int32, [4]>([1, 4, 64, 256])];
            tensor<fp16, [1, 4, 64, 256]> input_tensor_641_cast_fp16 = reshape(shape = var_2765, x = input_tensor_633_cast_fp16)[name = string("input_tensor_641_cast_fp16")];
            tensor<int32, [4]> var_2771 = const()[name = string("op_2771"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [4]> var_2797 = const()[name = string("op_2797"), val = tensor<int32, [4]>([1, 4, 64, 256])];
            tensor<fp16, [1, 4, 64, 256]> y_33_cast_fp16 = reshape(shape = var_2797, x = input_tensor_625_cast_fp16)[name = string("y_33_cast_fp16")];
            tensor<int32, [4]> var_2809 = const()[name = string("op_2809"), val = tensor<int32, [4]>([1, 4, 64, 256])];
            tensor<fp16, [1, 4, 64, 256]> input_tensor_647_cast_fp16 = reshape(shape = var_2809, x = input_tensor_645_cast_fp16)[name = string("input_tensor_647_cast_fp16")];
            fp16 _inversed_x_153_y_0_to_fp16 = const()[name = string("_inversed_x_153_y_0_to_fp16"), val = fp16(0x1p-3)];
            tensor<fp16, [1, 4, 256, 64]> first_199_cast_fp16 = transpose(perm = var_2771, x = input_tensor_641_cast_fp16)[name = string("transpose_16")];
            tensor<fp16, [1, 4, 256, 64]> _inversed_x_153_cast_fp16 = mul(x = first_199_cast_fp16, y = _inversed_x_153_y_0_to_fp16)[name = string("_inversed_x_153_cast_fp16")];
            bool first_215_transpose_x_0 = const()[name = string("first_215_transpose_x_0"), val = bool(false)];
            bool first_215_transpose_y_0 = const()[name = string("first_215_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 4, 256, 256]> first_215_cast_fp16 = matmul(transpose_x = first_215_transpose_x_0, transpose_y = first_215_transpose_y_0, x = _inversed_x_153_cast_fp16, y = y_33_cast_fp16)[name = string("first_215_cast_fp16")];
            bool input_tensor_679_transpose_x_0 = const()[name = string("input_tensor_679_transpose_x_0"), val = bool(false)];
            bool input_tensor_679_transpose_y_0 = const()[name = string("input_tensor_679_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 64, 511]> y_35_to_fp16 = const()[name = string("y_35_to_fp16"), val = tensor<fp16, [1, 1, 64, 511]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(20115776)))];
            tensor<fp16, [1, 4, 256, 511]> input_tensor_679_cast_fp16 = matmul(transpose_x = input_tensor_679_transpose_x_0, transpose_y = input_tensor_679_transpose_y_0, x = _inversed_x_153_cast_fp16, y = y_35_to_fp16)[name = string("input_tensor_679_cast_fp16")];
            tensor<int32, [8]> input_tensor_701_pad_0 = const()[name = string("input_tensor_701_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 1])];
            string input_tensor_701_mode_0 = const()[name = string("input_tensor_701_mode_0"), val = string("constant")];
            fp16 const_107_to_fp16 = const()[name = string("const_107_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 256, 512]> input_tensor_701_cast_fp16 = pad(constant_val = const_107_to_fp16, mode = input_tensor_701_mode_0, pad = input_tensor_701_pad_0, x = input_tensor_679_cast_fp16)[name = string("input_tensor_701_cast_fp16")];
            tensor<int32, [3]> var_2932 = const()[name = string("op_2932"), val = tensor<int32, [3]>([1, 4, 131072])];
            tensor<fp16, [1, 4, 131072]> input_153_cast_fp16 = reshape(shape = var_2932, x = input_tensor_701_cast_fp16)[name = string("input_153_cast_fp16")];
            tensor<int32, [6]> input_tensor_723_pad_0 = const()[name = string("input_tensor_723_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 0, 255])];
            string input_tensor_723_mode_0 = const()[name = string("input_tensor_723_mode_0"), val = string("constant")];
            fp16 const_108_to_fp16 = const()[name = string("const_108_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 131327]> input_tensor_723_cast_fp16 = pad(constant_val = const_108_to_fp16, mode = input_tensor_723_mode_0, pad = input_tensor_723_pad_0, x = input_153_cast_fp16)[name = string("input_tensor_723_cast_fp16")];
            tensor<int32, [4]> var_2967 = const()[name = string("op_2967"), val = tensor<int32, [4]>([1, 4, 257, 511])];
            tensor<fp16, [1, 4, 257, 511]> x_169_cast_fp16 = reshape(shape = var_2967, x = input_tensor_723_cast_fp16)[name = string("x_169_cast_fp16")];
            tensor<int32, [4]> x_171_begin_0 = const()[name = string("x_171_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> x_171_end_0 = const()[name = string("x_171_end_0"), val = tensor<int32, [4]>([1, 4, 256, 511])];
            tensor<bool, [4]> x_171_end_mask_0 = const()[name = string("x_171_end_mask_0"), val = tensor<bool, [4]>([true, true, false, true])];
            tensor<fp16, [1, 4, 256, 511]> x_171_cast_fp16 = slice_by_index(begin = x_171_begin_0, end = x_171_end_0, end_mask = x_171_end_mask_0, x = x_169_cast_fp16)[name = string("x_171_cast_fp16")];
            tensor<int32, [4]> second_223_begin_0 = const()[name = string("second_223_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 255])];
            tensor<int32, [4]> second_223_end_0 = const()[name = string("second_223_end_0"), val = tensor<int32, [4]>([1, 4, 256, 1])];
            tensor<bool, [4]> second_223_end_mask_0 = const()[name = string("second_223_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 256, 256]> second_223_cast_fp16 = slice_by_index(begin = second_223_begin_0, end = second_223_end_0, end_mask = second_223_end_mask_0, x = x_171_cast_fp16)[name = string("second_223_cast_fp16")];
            tensor<fp16, [1, 4, 256, 256]> y_37_cast_fp16 = add(x = first_215_cast_fp16, y = second_223_cast_fp16)[name = string("y_37_cast_fp16")];
            tensor<fp16, [1, 4, 256, 256]> input_155_cast_fp16 = select(a = text_encoder_attn_encoder_attn_layers_0_Constant_88_value_after_broadcast_to_fp16, b = y_37_cast_fp16, cond = condition_1_after_broadcast)[name = string("input_155_cast_fp16")];
            int32 var_3009 = const()[name = string("op_3009"), val = int32(-1)];
            tensor<fp16, [1, 4, 256, 256]> x_175_cast_fp16 = softmax(axis = var_3009, x = input_155_cast_fp16)[name = string("x_175_cast_fp16")];
            bool first_227_transpose_x_1 = const()[name = string("first_227_transpose_x_1"), val = bool(false)];
            bool first_227_transpose_y_1 = const()[name = string("first_227_transpose_y_1"), val = bool(true)];
            tensor<fp16, [1, 4, 256, 64]> first_227_cast_fp16 = matmul(transpose_x = first_227_transpose_x_1, transpose_y = first_227_transpose_y_1, x = x_175_cast_fp16, y = input_tensor_647_cast_fp16)[name = string("first_227_cast_fp16")];
            tensor<int32, [8]> input_tensor_753_pad_0 = const()[name = string("input_tensor_753_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 255])];
            string input_tensor_753_mode_0 = const()[name = string("input_tensor_753_mode_0"), val = string("constant")];
            fp16 const_115_to_fp16 = const()[name = string("const_115_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 256, 511]> input_tensor_753_cast_fp16 = pad(constant_val = const_115_to_fp16, mode = input_tensor_753_mode_0, pad = input_tensor_753_pad_0, x = x_175_cast_fp16)[name = string("input_tensor_753_cast_fp16")];
            tensor<int32, [3]> var_3083 = const()[name = string("op_3083"), val = tensor<int32, [3]>([1, 4, 130816])];
            tensor<fp16, [1, 4, 130816]> input_157_cast_fp16 = reshape(shape = var_3083, x = input_tensor_753_cast_fp16)[name = string("input_157_cast_fp16")];
            tensor<int32, [6]> input_tensor_771_pad_0 = const()[name = string("input_tensor_771_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 256, 0])];
            string input_tensor_771_mode_0 = const()[name = string("input_tensor_771_mode_0"), val = string("constant")];
            fp16 const_116_to_fp16 = const()[name = string("const_116_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 131072]> input_tensor_771_cast_fp16 = pad(constant_val = const_116_to_fp16, mode = input_tensor_771_mode_0, pad = input_tensor_771_pad_0, x = input_157_cast_fp16)[name = string("input_tensor_771_cast_fp16")];
            tensor<int32, [4]> var_3113 = const()[name = string("op_3113"), val = tensor<int32, [4]>([1, 4, 256, 512])];
            tensor<fp16, [1, 4, 256, 512]> x_185_cast_fp16 = reshape(shape = var_3113, x = input_tensor_771_cast_fp16)[name = string("x_185_cast_fp16")];
            tensor<int32, [4]> x_193_begin_0 = const()[name = string("x_193_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 1])];
            tensor<int32, [4]> x_193_end_0 = const()[name = string("x_193_end_0"), val = tensor<int32, [4]>([1, 4, 256, 1])];
            tensor<bool, [4]> x_193_end_mask_0 = const()[name = string("x_193_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 256, 511]> x_193_cast_fp16 = slice_by_index(begin = x_193_begin_0, end = x_193_end_0, end_mask = x_193_end_mask_0, x = x_185_cast_fp16)[name = string("x_193_cast_fp16")];
            bool second_237_transpose_x_0 = const()[name = string("second_237_transpose_x_0"), val = bool(false)];
            bool second_237_transpose_y_0 = const()[name = string("second_237_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 511, 64]> y_41_to_fp16 = const()[name = string("y_41_to_fp16"), val = tensor<fp16, [1, 1, 511, 64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(20181248)))];
            tensor<fp16, [1, 4, 256, 64]> second_237_cast_fp16 = matmul(transpose_x = second_237_transpose_x_0, transpose_y = second_237_transpose_y_0, x = x_193_cast_fp16, y = y_41_to_fp16)[name = string("second_237_cast_fp16")];
            tensor<fp16, [1, 4, 256, 64]> input_tensor_789_cast_fp16 = add(x = first_227_cast_fp16, y = second_237_cast_fp16)[name = string("input_tensor_789_cast_fp16")];
            tensor<int32, [4]> var_3160 = const()[name = string("op_3160"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [3]> var_3179 = const()[name = string("op_3179"), val = tensor<int32, [3]>([1, 256, 256])];
            tensor<fp16, [1, 4, 64, 256]> input_tensor_793_cast_fp16 = transpose(perm = var_3160, x = input_tensor_789_cast_fp16)[name = string("transpose_15")];
            tensor<fp16, [1, 256, 256]> input_161_cast_fp16 = reshape(shape = var_3179, x = input_tensor_793_cast_fp16)[name = string("input_161_cast_fp16")];
            string second_239_pad_type_0 = const()[name = string("second_239_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_239_strides_0 = const()[name = string("second_239_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_239_pad_0 = const()[name = string("second_239_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_239_dilations_0 = const()[name = string("second_239_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_239_groups_0 = const()[name = string("second_239_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_3_conv_o_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_o_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15766592)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_3_conv_o_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_o_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15897728)))];
            tensor<fp16, [1, 256, 256]> second_239_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_3_conv_o_Conv_bias_to_fp16, dilations = second_239_dilations_0, groups = second_239_groups_0, pad = second_239_pad_0, pad_type = second_239_pad_type_0, strides = second_239_strides_0, weight = text_encoder_attn_encoder_attn_layers_3_conv_o_Conv_weight_to_fp16, x = input_161_cast_fp16)[name = string("second_239_cast_fp16")];
            tensor<fp16, [1, 256, 256]> input_tensor_795_cast_fp16 = add(x = input_145_cast_fp16, y = second_239_cast_fp16)[name = string("input_tensor_795_cast_fp16")];
            tensor<int32, [3]> var_3197 = const()[name = string("op_3197"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_797_axes_0 = const()[name = string("input_tensor_797_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_3_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_3_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15898304)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_3_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_3_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15898880)))];
            fp16 var_3200_to_fp16 = const()[name = string("op_3200_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 256, 256]> input_163_cast_fp16 = transpose(perm = var_3197, x = input_tensor_795_cast_fp16)[name = string("transpose_14")];
            tensor<fp16, [1, 256, 256]> input_tensor_797_cast_fp16 = layer_norm(axes = input_tensor_797_axes_0, beta = text_encoder_attn_encoder_norm_layers_1_3_norm_LayerNormalization_bias_to_fp16, epsilon = var_3200_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_1_3_norm_LayerNormalization_weight_to_fp16, x = input_163_cast_fp16)[name = string("input_tensor_797_cast_fp16")];
            tensor<int32, [3]> var_3209 = const()[name = string("op_3209"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 256, 256]> first_229_cast_fp16 = transpose(perm = var_3209, x = input_tensor_797_cast_fp16)[name = string("transpose_13")];
            tensor<fp16, [1, 256, 256]> input_165_cast_fp16 = mul(x = first_229_cast_fp16, y = text_mask)[name = string("input_165_cast_fp16")];
            string input_167_pad_type_0 = const()[name = string("input_167_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_167_strides_0 = const()[name = string("input_167_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_167_pad_0 = const()[name = string("input_167_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_167_dilations_0 = const()[name = string("input_167_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_167_groups_0 = const()[name = string("input_167_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_attn_encoder_ffn_layers_3_conv_1_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_3_conv_1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15899456)))];
            tensor<fp16, [1024]> text_encoder_attn_encoder_ffn_layers_3_conv_1_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_3_conv_1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16423808)))];
            tensor<fp16, [1, 1024, 256]> input_167_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_3_conv_1_Conv_bias_to_fp16, dilations = input_167_dilations_0, groups = input_167_groups_0, pad = input_167_pad_0, pad_type = input_167_pad_type_0, strides = input_167_strides_0, weight = text_encoder_attn_encoder_ffn_layers_3_conv_1_Conv_weight_to_fp16, x = input_165_cast_fp16)[name = string("input_167_cast_fp16")];
            tensor<fp16, [1, 1024, 256]> first_231_cast_fp16 = relu(x = input_167_cast_fp16)[name = string("first_231_cast_fp16")];
            tensor<fp16, [1, 1024, 256]> input_169_cast_fp16 = mul(x = first_231_cast_fp16, y = text_mask)[name = string("input_169_cast_fp16")];
            string first_233_pad_type_0 = const()[name = string("first_233_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_233_strides_0 = const()[name = string("first_233_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_233_pad_0 = const()[name = string("first_233_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_233_dilations_0 = const()[name = string("first_233_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_233_groups_0 = const()[name = string("first_233_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> text_encoder_attn_encoder_ffn_layers_3_conv_2_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_3_conv_2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16425920)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_ffn_layers_3_conv_2_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_3_conv_2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16950272)))];
            tensor<fp16, [1, 256, 256]> first_233_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_3_conv_2_Conv_bias_to_fp16, dilations = first_233_dilations_0, groups = first_233_groups_0, pad = first_233_pad_0, pad_type = first_233_pad_type_0, strides = first_233_strides_0, weight = text_encoder_attn_encoder_ffn_layers_3_conv_2_Conv_weight_to_fp16, x = input_169_cast_fp16)[name = string("first_233_cast_fp16")];
            tensor<fp16, [1, 256, 256]> second_241_cast_fp16 = mul(x = first_233_cast_fp16, y = text_mask)[name = string("second_241_cast_fp16")];
            tensor<fp16, [1, 256, 256]> input_tensor_799_cast_fp16 = add(x = first_229_cast_fp16, y = second_241_cast_fp16)[name = string("input_tensor_799_cast_fp16")];
            tensor<int32, [3]> var_3242 = const()[name = string("op_3242"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_801_axes_0 = const()[name = string("input_tensor_801_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_3_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_3_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16950848)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_3_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_3_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16951424)))];
            fp16 var_3245_to_fp16 = const()[name = string("op_3245_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 256, 256]> input_171_cast_fp16 = transpose(perm = var_3242, x = input_tensor_799_cast_fp16)[name = string("transpose_12")];
            tensor<fp16, [1, 256, 256]> input_tensor_801_cast_fp16 = layer_norm(axes = input_tensor_801_axes_0, beta = text_encoder_attn_encoder_norm_layers_2_3_norm_LayerNormalization_bias_to_fp16, epsilon = var_3245_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_2_3_norm_LayerNormalization_weight_to_fp16, x = input_171_cast_fp16)[name = string("input_tensor_801_cast_fp16")];
            tensor<int32, [3]> var_3254 = const()[name = string("op_3254"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 256, 256]> first_235_cast_fp16 = transpose(perm = var_3254, x = input_tensor_801_cast_fp16)[name = string("transpose_11")];
            tensor<fp16, [1, 256, 256]> first_237_cast_fp16 = mul(x = first_235_cast_fp16, y = text_mask)[name = string("first_237_cast_fp16")];
            tensor<fp16, [1, 256, 256]> first_239_cast_fp16 = add(x = first_237_cast_fp16, y = first_89_cast_fp16)[name = string("first_239_cast_fp16")];
            tensor<fp16, [1, 256, 256]> input_tensor_807_cast_fp16 = mul(x = first_239_cast_fp16, y = text_mask)[name = string("input_tensor_807_cast_fp16")];
            tensor<int32, [3]> var_3299 = const()[name = string("op_3299"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [3]> var_3304 = const()[name = string("op_3304"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [256, 256]> var_3308_weight_0_to_fp16 = const()[name = string("op_3308_weight_0_to_fp16"), val = tensor<fp16, [256, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16952000)))];
            tensor<fp16, [256]> var_3308_bias_0_to_fp16 = const()[name = string("op_3308_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17083136)))];
            tensor<fp16, [1, 256, 256]> x_195_cast_fp16 = transpose(perm = var_3299, x = input_tensor_807_cast_fp16)[name = string("transpose_10")];
            tensor<fp16, [1, 256, 256]> var_3308_cast_fp16 = linear(bias = var_3308_bias_0_to_fp16, weight = var_3308_weight_0_to_fp16, x = x_195_cast_fp16)[name = string("op_3308_cast_fp16")];
            tensor<fp16, [256, 256]> var_3314_weight_0_to_fp16 = const()[name = string("op_3314_weight_0_to_fp16"), val = tensor<fp16, [256, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17083712)))];
            tensor<fp16, [256]> var_3314_bias_0_to_fp16 = const()[name = string("op_3314_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17214848)))];
            tensor<fp16, [1, 50, 256]> var_3314_cast_fp16 = linear(bias = var_3314_bias_0_to_fp16, weight = var_3314_weight_0_to_fp16, x = style_ttl)[name = string("op_3314_cast_fp16")];
            tensor<int32, [2]> var_3317 = const()[name = string("op_3317"), val = tensor<int32, [2]>([128, 128])];
            int32 var_3318_axis_0 = const()[name = string("op_3318_axis_0"), val = int32(2)];
            tensor<fp16, [1, 256, 128]> var_3318_cast_fp16_0, tensor<fp16, [1, 256, 128]> var_3318_cast_fp16_1 = split(axis = var_3318_axis_0, split_sizes = var_3317, x = var_3308_cast_fp16)[name = string("op_3318_cast_fp16")];
            tensor<int32, [1]> var_3325_axes_0 = const()[name = string("op_3325_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 256, 128]> var_3325_cast_fp16 = expand_dims(axes = var_3325_axes_0, x = var_3318_cast_fp16_0)[name = string("op_3325_cast_fp16")];
            tensor<int32, [1]> var_3327_axes_0 = const()[name = string("op_3327_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 256, 128]> var_3327_cast_fp16 = expand_dims(axes = var_3327_axes_0, x = var_3318_cast_fp16_1)[name = string("op_3327_cast_fp16")];
            int32 var_3328 = const()[name = string("op_3328"), val = int32(0)];
            bool x_199_interleave_0 = const()[name = string("x_199_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 1, 256, 128]> x_199_cast_fp16 = concat(axis = var_3328, interleave = x_199_interleave_0, values = (var_3325_cast_fp16, var_3327_cast_fp16))[name = string("x_199_cast_fp16")];
            tensor<int32, [2]> var_3349 = const()[name = string("op_3349"), val = tensor<int32, [2]>([128, 128])];
            int32 var_3350_axis_0 = const()[name = string("op_3350_axis_0"), val = int32(2)];
            tensor<fp16, [1, 50, 128]> var_3350_cast_fp16_0, tensor<fp16, [1, 50, 128]> var_3350_cast_fp16_1 = split(axis = var_3350_axis_0, split_sizes = var_3349, x = var_3314_cast_fp16)[name = string("op_3350_cast_fp16")];
            tensor<int32, [1]> var_3357_axes_0 = const()[name = string("op_3357_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 50, 128]> var_3357_cast_fp16 = expand_dims(axes = var_3357_axes_0, x = var_3350_cast_fp16_0)[name = string("op_3357_cast_fp16")];
            tensor<int32, [1]> var_3359_axes_0 = const()[name = string("op_3359_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 50, 128]> var_3359_cast_fp16 = expand_dims(axes = var_3359_axes_0, x = var_3350_cast_fp16_1)[name = string("op_3359_cast_fp16")];
            int32 var_3360 = const()[name = string("op_3360"), val = int32(0)];
            bool y_55_interleave_0 = const()[name = string("y_55_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 1, 50, 128]> y_55_cast_fp16 = concat(axis = var_3360, interleave = y_55_interleave_0, values = (var_3357_cast_fp16, var_3359_cast_fp16))[name = string("y_55_cast_fp16")];
            bool first_247_transpose_x_0 = const()[name = string("first_247_transpose_x_0"), val = bool(false)];
            bool first_247_transpose_y_0 = const()[name = string("first_247_transpose_y_0"), val = bool(false)];
            tensor<fp16, [2, 1, 128, 50]> y_49_to_fp16 = const()[name = string("y_49_to_fp16"), val = tensor<fp16, [2, 1, 128, 50]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17215424)))];
            tensor<fp16, [2, 1, 256, 50]> first_247_cast_fp16 = matmul(transpose_x = first_247_transpose_x_0, transpose_y = first_247_transpose_y_0, x = x_199_cast_fp16, y = y_49_to_fp16)[name = string("first_247_cast_fp16")];
            fp16 _inversed_input_173_y_0_to_fp16 = const()[name = string("_inversed_input_173_y_0_to_fp16"), val = fp16(0x1p-4)];
            tensor<fp16, [2, 1, 256, 50]> _inversed_input_173_cast_fp16 = mul(x = first_247_cast_fp16, y = _inversed_input_173_y_0_to_fp16)[name = string("_inversed_input_173_cast_fp16")];
            int32 var_3373 = const()[name = string("op_3373"), val = int32(3)];
            tensor<fp16, [2, 1, 256, 50]> y_53_cast_fp16 = softmax(axis = var_3373, x = _inversed_input_173_cast_fp16)[name = string("y_53_cast_fp16")];
            tensor<int32, [1]> x_201_axes_0 = const()[name = string("x_201_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 256, 1]> input_tensor_825_cast_fp16 = transpose(perm = var_3304, x = text_mask)[name = string("transpose_9")];
            tensor<fp16, [1, 1, 256, 1]> x_201_cast_fp16 = expand_dims(axes = x_201_axes_0, x = input_tensor_825_cast_fp16)[name = string("x_201_cast_fp16")];
            fp16 speech_prompted_text_encoder_attention1_Constant_11_value_to_fp16 = const()[name = string("speech_prompted_text_encoder_attention1_Constant_11_value_to_fp16"), val = fp16(0x0p+0)];
            tensor<bool, [1, 1, 256, 1]> input_tensor_827_cast_fp16 = equal(x = x_201_cast_fp16, y = speech_prompted_text_encoder_attention1_Constant_11_value_to_fp16)[name = string("input_tensor_827_cast_fp16")];
            tensor<int32, [4]> condition_9_after_broadcast_reps_0 = const()[name = string("condition_9_after_broadcast_reps_0"), val = tensor<int32, [4]>([2, 1, 1, 50])];
            tensor<bool, [2, 1, 256, 50]> condition_9_after_broadcast = tile(reps = condition_9_after_broadcast_reps_0, x = input_tensor_827_cast_fp16)[name = string("condition_9_after_broadcast")];
            tensor<fp16, [2, 1, 256, 50]> speech_prompted_text_encoder_attention1_Constant_12_value_after_broadcast_to_fp16 = const()[name = string("speech_prompted_text_encoder_attention1_Constant_12_value_after_broadcast_to_fp16"), val = tensor<fp16, [2, 1, 256, 50]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(20246720)))];
            tensor<fp16, [2, 1, 256, 50]> x_205_cast_fp16 = select(a = speech_prompted_text_encoder_attention1_Constant_12_value_after_broadcast_to_fp16, b = y_53_cast_fp16, cond = condition_9_after_broadcast)[name = string("x_205_cast_fp16")];
            bool var_3383_transpose_x_0 = const()[name = string("op_3383_transpose_x_0"), val = bool(false)];
            bool var_3383_transpose_y_0 = const()[name = string("op_3383_transpose_y_0"), val = bool(false)];
            tensor<fp16, [2, 1, 256, 128]> var_3383_cast_fp16 = matmul(transpose_x = var_3383_transpose_x_0, transpose_y = var_3383_transpose_y_0, x = x_205_cast_fp16, y = y_55_cast_fp16)[name = string("op_3383_cast_fp16")];
            tensor<int32, [2]> var_3386 = const()[name = string("op_3386"), val = tensor<int32, [2]>([1, 1])];
            int32 var_3387_axis_0 = const()[name = string("op_3387_axis_0"), val = int32(0)];
            tensor<fp16, [1, 1, 256, 128]> var_3387_cast_fp16_0, tensor<fp16, [1, 1, 256, 128]> var_3387_cast_fp16_1 = split(axis = var_3387_axis_0, split_sizes = var_3386, x = var_3383_cast_fp16)[name = string("op_3387_cast_fp16")];
            int32 var_3393 = const()[name = string("op_3393"), val = int32(3)];
            bool result_1_interleave_0 = const()[name = string("result_1_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 1, 256, 256]> result_1_cast_fp16 = concat(axis = var_3393, interleave = result_1_interleave_0, values = (var_3387_cast_fp16_0, var_3387_cast_fp16_1))[name = string("result_1_cast_fp16")];
            tensor<int32, [1]> x_207_axes_0 = const()[name = string("x_207_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 256, 256]> x_207_cast_fp16 = squeeze(axes = x_207_axes_0, x = result_1_cast_fp16)[name = string("x_207_cast_fp16")];
            tensor<fp16, [256, 256]> first_251_weight_0_to_fp16 = const()[name = string("first_251_weight_0_to_fp16"), val = tensor<fp16, [256, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17244352)))];
            tensor<fp16, [256]> first_251_bias_0_to_fp16 = const()[name = string("first_251_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17375488)))];
            tensor<fp16, [1, 256, 256]> first_251_cast_fp16 = linear(bias = first_251_bias_0_to_fp16, weight = first_251_weight_0_to_fp16, x = x_207_cast_fp16)[name = string("first_251_cast_fp16")];
            tensor<fp16, [1, 256, 256]> first_253_cast_fp16 = mul(x = first_251_cast_fp16, y = input_tensor_825_cast_fp16)[name = string("first_253_cast_fp16")];
            tensor<fp16, [1, 256, 256]> x_209_cast_fp16 = add(x = first_253_cast_fp16, y = x_195_cast_fp16)[name = string("x_209_cast_fp16")];
            tensor<fp16, [256, 256]> var_3413_weight_0_to_fp16 = const()[name = string("op_3413_weight_0_to_fp16"), val = tensor<fp16, [256, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17376064)))];
            tensor<fp16, [256]> var_3413_bias_0_to_fp16 = const()[name = string("op_3413_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17507200)))];
            tensor<fp16, [1, 256, 256]> var_3413_cast_fp16 = linear(bias = var_3413_bias_0_to_fp16, weight = var_3413_weight_0_to_fp16, x = x_209_cast_fp16)[name = string("op_3413_cast_fp16")];
            tensor<fp16, [256, 256]> var_3419_weight_0_to_fp16 = const()[name = string("op_3419_weight_0_to_fp16"), val = tensor<fp16, [256, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17507776)))];
            tensor<fp16, [256]> var_3419_bias_0_to_fp16 = const()[name = string("op_3419_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17638912)))];
            tensor<fp16, [1, 50, 256]> var_3419_cast_fp16 = linear(bias = var_3419_bias_0_to_fp16, weight = var_3419_weight_0_to_fp16, x = style_ttl)[name = string("op_3419_cast_fp16")];
            tensor<int32, [2]> var_3422 = const()[name = string("op_3422"), val = tensor<int32, [2]>([128, 128])];
            int32 var_3423_axis_0 = const()[name = string("op_3423_axis_0"), val = int32(2)];
            tensor<fp16, [1, 256, 128]> var_3423_cast_fp16_0, tensor<fp16, [1, 256, 128]> var_3423_cast_fp16_1 = split(axis = var_3423_axis_0, split_sizes = var_3422, x = var_3413_cast_fp16)[name = string("op_3423_cast_fp16")];
            tensor<int32, [1]> var_3430_axes_0 = const()[name = string("op_3430_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 256, 128]> var_3430_cast_fp16 = expand_dims(axes = var_3430_axes_0, x = var_3423_cast_fp16_0)[name = string("op_3430_cast_fp16")];
            tensor<int32, [1]> var_3432_axes_0 = const()[name = string("op_3432_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 256, 128]> var_3432_cast_fp16 = expand_dims(axes = var_3432_axes_0, x = var_3423_cast_fp16_1)[name = string("op_3432_cast_fp16")];
            int32 var_3433 = const()[name = string("op_3433"), val = int32(0)];
            bool x_211_interleave_0 = const()[name = string("x_211_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 1, 256, 128]> x_211_cast_fp16 = concat(axis = var_3433, interleave = x_211_interleave_0, values = (var_3430_cast_fp16, var_3432_cast_fp16))[name = string("x_211_cast_fp16")];
            tensor<int32, [2]> var_3454 = const()[name = string("op_3454"), val = tensor<int32, [2]>([128, 128])];
            int32 var_3455_axis_0 = const()[name = string("op_3455_axis_0"), val = int32(2)];
            tensor<fp16, [1, 50, 128]> var_3455_cast_fp16_0, tensor<fp16, [1, 50, 128]> var_3455_cast_fp16_1 = split(axis = var_3455_axis_0, split_sizes = var_3454, x = var_3419_cast_fp16)[name = string("op_3455_cast_fp16")];
            tensor<int32, [1]> var_3462_axes_0 = const()[name = string("op_3462_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 50, 128]> var_3462_cast_fp16 = expand_dims(axes = var_3462_axes_0, x = var_3455_cast_fp16_0)[name = string("op_3462_cast_fp16")];
            tensor<int32, [1]> var_3464_axes_0 = const()[name = string("op_3464_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 50, 128]> var_3464_cast_fp16 = expand_dims(axes = var_3464_axes_0, x = var_3455_cast_fp16_1)[name = string("op_3464_cast_fp16")];
            int32 var_3465 = const()[name = string("op_3465"), val = int32(0)];
            bool y_69_interleave_0 = const()[name = string("y_69_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 1, 50, 128]> y_69_cast_fp16 = concat(axis = var_3465, interleave = y_69_interleave_0, values = (var_3462_cast_fp16, var_3464_cast_fp16))[name = string("y_69_cast_fp16")];
            bool first_261_transpose_x_0 = const()[name = string("first_261_transpose_x_0"), val = bool(false)];
            bool first_261_transpose_y_0 = const()[name = string("first_261_transpose_y_0"), val = bool(false)];
            tensor<fp16, [2, 1, 128, 50]> y_65_to_fp16 = const()[name = string("y_65_to_fp16"), val = tensor<fp16, [2, 1, 128, 50]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17639488)))];
            tensor<fp16, [2, 1, 256, 50]> first_261_cast_fp16 = matmul(transpose_x = first_261_transpose_x_0, transpose_y = first_261_transpose_y_0, x = x_211_cast_fp16, y = y_65_to_fp16)[name = string("first_261_cast_fp16")];
            fp16 _inversed_input_175_y_0_to_fp16 = const()[name = string("_inversed_input_175_y_0_to_fp16"), val = fp16(0x1p-4)];
            tensor<fp16, [2, 1, 256, 50]> _inversed_input_175_cast_fp16 = mul(x = first_261_cast_fp16, y = _inversed_input_175_y_0_to_fp16)[name = string("_inversed_input_175_cast_fp16")];
            int32 var_3478 = const()[name = string("op_3478"), val = int32(3)];
            tensor<fp16, [2, 1, 256, 50]> y_67_cast_fp16 = softmax(axis = var_3478, x = _inversed_input_175_cast_fp16)[name = string("y_67_cast_fp16")];
            tensor<fp16, [2, 1, 256, 50]> x_215_cast_fp16 = select(a = speech_prompted_text_encoder_attention1_Constant_12_value_after_broadcast_to_fp16, b = y_67_cast_fp16, cond = condition_9_after_broadcast)[name = string("x_215_cast_fp16")];
            bool var_3485_transpose_x_0 = const()[name = string("op_3485_transpose_x_0"), val = bool(false)];
            bool var_3485_transpose_y_0 = const()[name = string("op_3485_transpose_y_0"), val = bool(false)];
            tensor<fp16, [2, 1, 256, 128]> var_3485_cast_fp16 = matmul(transpose_x = var_3485_transpose_x_0, transpose_y = var_3485_transpose_y_0, x = x_215_cast_fp16, y = y_69_cast_fp16)[name = string("op_3485_cast_fp16")];
            tensor<int32, [2]> var_3488 = const()[name = string("op_3488"), val = tensor<int32, [2]>([1, 1])];
            int32 var_3489_axis_0 = const()[name = string("op_3489_axis_0"), val = int32(0)];
            tensor<fp16, [1, 1, 256, 128]> var_3489_cast_fp16_0, tensor<fp16, [1, 1, 256, 128]> var_3489_cast_fp16_1 = split(axis = var_3489_axis_0, split_sizes = var_3488, x = var_3485_cast_fp16)[name = string("op_3489_cast_fp16")];
            int32 var_3495 = const()[name = string("op_3495"), val = int32(3)];
            bool result_interleave_0 = const()[name = string("result_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 1, 256, 256]> result_cast_fp16 = concat(axis = var_3495, interleave = result_interleave_0, values = (var_3489_cast_fp16_0, var_3489_cast_fp16_1))[name = string("result_cast_fp16")];
            tensor<int32, [1]> x_axes_0 = const()[name = string("x_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 256, 256]> x_cast_fp16 = squeeze(axes = x_axes_0, x = result_cast_fp16)[name = string("x_cast_fp16")];
            tensor<fp16, [256, 256]> first_265_weight_0_to_fp16 = const()[name = string("first_265_weight_0_to_fp16"), val = tensor<fp16, [256, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17665152)))];
            tensor<fp16, [256]> first_265_bias_0_to_fp16 = const()[name = string("first_265_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17796288)))];
            tensor<fp16, [1, 256, 256]> first_265_cast_fp16 = linear(bias = first_265_bias_0_to_fp16, weight = first_265_weight_0_to_fp16, x = x_cast_fp16)[name = string("first_265_cast_fp16")];
            tensor<fp16, [1, 256, 256]> first_267_cast_fp16 = mul(x = first_265_cast_fp16, y = input_tensor_825_cast_fp16)[name = string("first_267_cast_fp16")];
            tensor<fp16, [1, 256, 256]> input_cast_fp16 = add(x = first_267_cast_fp16, y = x_195_cast_fp16)[name = string("input_cast_fp16")];
            tensor<int32, [1]> input_tensor_axes_0 = const()[name = string("input_tensor_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> speech_prompted_text_encoder_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("speech_prompted_text_encoder_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17796864)))];
            tensor<fp16, [256]> speech_prompted_text_encoder_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("speech_prompted_text_encoder_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17797440)))];
            fp16 var_3514_to_fp16 = const()[name = string("op_3514_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 256, 256]> input_tensor_cast_fp16 = layer_norm(axes = input_tensor_axes_0, beta = speech_prompted_text_encoder_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_3514_to_fp16, gamma = speech_prompted_text_encoder_norm_norm_LayerNormalization_weight_to_fp16, x = input_cast_fp16)[name = string("input_tensor_cast_fp16")];
            tensor<int32, [3]> var_3523 = const()[name = string("op_3523"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 256, 256]> first_cast_fp16 = transpose(perm = var_3523, x = input_tensor_cast_fp16)[name = string("transpose_8")];
            tensor<fp16, [1, 256, 256]> text_emb = mul(x = first_cast_fp16, y = text_mask)[name = string("op_3525_cast_fp16")];
        } -> (text_emb);
    func text_t32<ios18>(tensor<fp16, [1, 50, 256]> style_ttl, tensor<int32, [1, 32]> text_ids, tensor<fp16, [1, 1, 32]> text_mask) {
            int32 input_tensor_3_batch_dims_0 = const()[name = string("input_tensor_3_batch_dims_0"), val = int32(0)];
            bool input_tensor_3_validate_indices_0 = const()[name = string("input_tensor_3_validate_indices_0"), val = bool(false)];
            tensor<fp16, [8322, 256]> initializers_onnx_initializer_0_to_fp16 = const()[name = string("initializers_onnx_initializer_0_to_fp16"), val = tensor<fp16, [8322, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(64)))];
            string text_ids_to_int16_dtype_0 = const()[name = string("text_ids_to_int16_dtype_0"), val = string("int16")];
            string cast_59_dtype_0 = const()[name = string("cast_59_dtype_0"), val = string("int32")];
            int32 greater_equal_0_y_0 = const()[name = string("greater_equal_0_y_0"), val = int32(0)];
            tensor<int16, [1, 32]> text_ids_to_int16 = cast(dtype = text_ids_to_int16_dtype_0, x = text_ids)[name = string("cast_62")];
            tensor<int32, [1, 32]> cast_59 = cast(dtype = cast_59_dtype_0, x = text_ids_to_int16)[name = string("cast_61")];
            tensor<bool, [1, 32]> greater_equal_0 = greater_equal(x = cast_59, y = greater_equal_0_y_0)[name = string("greater_equal_0")];
            int32 slice_by_index_0 = const()[name = string("slice_by_index_0"), val = int32(8322)];
            tensor<int32, [1, 32]> add_0 = add(x = cast_59, y = slice_by_index_0)[name = string("add_0")];
            tensor<int32, [1, 32]> select_0 = select(a = cast_59, b = add_0, cond = greater_equal_0)[name = string("select_0")];
            int32 input_tensor_3_cast_fp16_cast_uint16_axis_0 = const()[name = string("input_tensor_3_cast_fp16_cast_uint16_axis_0"), val = int32(0)];
            string select_0_to_int16_dtype_0 = const()[name = string("select_0_to_int16_dtype_0"), val = string("int16")];
            tensor<int16, [1, 32]> select_0_to_int16 = cast(dtype = select_0_to_int16_dtype_0, x = select_0)[name = string("cast_60")];
            tensor<fp16, [1, 32, 256]> input_tensor_3_cast_fp16_cast_uint16_cast_uint16 = gather(axis = input_tensor_3_cast_fp16_cast_uint16_axis_0, batch_dims = input_tensor_3_batch_dims_0, indices = select_0_to_int16, validate_indices = input_tensor_3_validate_indices_0, x = initializers_onnx_initializer_0_to_fp16)[name = string("input_tensor_3_cast_fp16_cast_uint16_cast_uint16")];
            tensor<int32, [3]> var_446 = const()[name = string("op_446"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 256, 32]> first_1_cast_fp16 = transpose(perm = var_446, x = input_tensor_3_cast_fp16_cast_uint16_cast_uint16)[name = string("transpose_47")];
            tensor<fp16, [1, 256, 32]> first_3_cast_fp16 = mul(x = first_1_cast_fp16, y = text_mask)[name = string("first_3_cast_fp16")];
            tensor<fp16, [1, 256, 32]> input_1_cast_fp16 = mul(x = first_3_cast_fp16, y = text_mask)[name = string("input_1_cast_fp16")];
            tensor<int32, [6]> input_3_pad_0 = const()[name = string("input_3_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 2, 2])];
            string input_3_mode_0 = const()[name = string("input_3_mode_0"), val = string("replicate")];
            fp16 const_0_to_fp16 = const()[name = string("const_0_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 256, 36]> input_3_cast_fp16 = pad(constant_val = const_0_to_fp16, mode = input_3_mode_0, pad = input_3_pad_0, x = input_1_cast_fp16)[name = string("input_3_cast_fp16")];
            string first_5_pad_type_0 = const()[name = string("first_5_pad_type_0"), val = string("valid")];
            int32 first_5_groups_0 = const()[name = string("first_5_groups_0"), val = int32(256)];
            tensor<int32, [1]> first_5_strides_0 = const()[name = string("first_5_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_5_pad_0 = const()[name = string("first_5_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_5_dilations_0 = const()[name = string("first_5_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [256, 1, 5]> text_encoder_convnext_convnext_0_dwconv_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_0_dwconv_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4260992)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_0_dwconv_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_0_dwconv_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4263616)))];
            tensor<fp16, [1, 256, 32]> first_5_cast_fp16 = conv(bias = text_encoder_convnext_convnext_0_dwconv_Conv_bias_to_fp16, dilations = first_5_dilations_0, groups = first_5_groups_0, pad = first_5_pad_0, pad_type = first_5_pad_type_0, strides = first_5_strides_0, weight = text_encoder_convnext_convnext_0_dwconv_Conv_weight_to_fp16, x = input_3_cast_fp16)[name = string("first_5_cast_fp16")];
            tensor<fp16, [1, 256, 32]> input_tensor_13_cast_fp16 = mul(x = first_5_cast_fp16, y = text_mask)[name = string("input_tensor_13_cast_fp16")];
            tensor<int32, [3]> var_471 = const()[name = string("op_471"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_15_axes_0 = const()[name = string("input_tensor_15_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_convnext_convnext_0_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_0_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4264192)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_0_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_0_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4264768)))];
            fp16 var_474_to_fp16 = const()[name = string("op_474_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 32, 256]> input_5_cast_fp16 = transpose(perm = var_471, x = input_tensor_13_cast_fp16)[name = string("transpose_46")];
            tensor<fp16, [1, 32, 256]> input_tensor_15_cast_fp16 = layer_norm(axes = input_tensor_15_axes_0, beta = text_encoder_convnext_convnext_0_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_474_to_fp16, gamma = text_encoder_convnext_convnext_0_norm_norm_LayerNormalization_weight_to_fp16, x = input_5_cast_fp16)[name = string("input_tensor_15_cast_fp16")];
            tensor<int32, [3]> var_483 = const()[name = string("op_483"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_7_pad_type_0 = const()[name = string("first_7_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_7_strides_0 = const()[name = string("first_7_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_7_pad_0 = const()[name = string("first_7_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_7_dilations_0 = const()[name = string("first_7_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_7_groups_0 = const()[name = string("first_7_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_convnext_convnext_0_pwconv1_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_0_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4265344)))];
            tensor<fp16, [1024]> text_encoder_convnext_convnext_0_pwconv1_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_0_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4789696)))];
            tensor<fp16, [1, 256, 32]> input_7_cast_fp16 = transpose(perm = var_483, x = input_tensor_15_cast_fp16)[name = string("transpose_45")];
            tensor<fp16, [1, 1024, 32]> first_7_cast_fp16 = conv(bias = text_encoder_convnext_convnext_0_pwconv1_Conv_bias_to_fp16, dilations = first_7_dilations_0, groups = first_7_groups_0, pad = first_7_pad_0, pad_type = first_7_pad_type_0, strides = first_7_strides_0, weight = text_encoder_convnext_convnext_0_pwconv1_Conv_weight_to_fp16, x = input_7_cast_fp16)[name = string("first_7_cast_fp16")];
            string input_9_mode_0 = const()[name = string("input_9_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 1024, 32]> input_9_cast_fp16 = gelu(mode = input_9_mode_0, x = first_7_cast_fp16)[name = string("input_9_cast_fp16")];
            string second_9_pad_type_0 = const()[name = string("second_9_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_9_strides_0 = const()[name = string("second_9_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_9_pad_0 = const()[name = string("second_9_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_9_dilations_0 = const()[name = string("second_9_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_9_groups_0 = const()[name = string("second_9_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> second_11_weight_0_to_fp16 = const()[name = string("second_11_weight_0_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4791808)))];
            tensor<fp16, [256]> second_11_bias_0_to_fp16 = const()[name = string("second_11_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5316160)))];
            tensor<fp16, [1, 256, 32]> second_11_cast_fp16 = conv(bias = second_11_bias_0_to_fp16, dilations = second_9_dilations_0, groups = second_9_groups_0, pad = second_9_pad_0, pad_type = second_9_pad_type_0, strides = second_9_strides_0, weight = second_11_weight_0_to_fp16, x = input_9_cast_fp16)[name = string("second_11_cast_fp16")];
            tensor<fp16, [1, 256, 32]> first_15_cast_fp16 = add(x = input_1_cast_fp16, y = second_11_cast_fp16)[name = string("first_15_cast_fp16")];
            tensor<fp16, [1, 256, 32]> first_17_cast_fp16 = mul(x = first_15_cast_fp16, y = text_mask)[name = string("first_17_cast_fp16")];
            tensor<fp16, [1, 256, 32]> input_11_cast_fp16 = mul(x = first_17_cast_fp16, y = text_mask)[name = string("input_11_cast_fp16")];
            tensor<int32, [6]> input_13_pad_0 = const()[name = string("input_13_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 2, 2])];
            string input_13_mode_0 = const()[name = string("input_13_mode_0"), val = string("replicate")];
            fp16 const_1_to_fp16 = const()[name = string("const_1_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 256, 36]> input_13_cast_fp16 = pad(constant_val = const_1_to_fp16, mode = input_13_mode_0, pad = input_13_pad_0, x = input_11_cast_fp16)[name = string("input_13_cast_fp16")];
            string first_19_pad_type_0 = const()[name = string("first_19_pad_type_0"), val = string("valid")];
            int32 first_19_groups_0 = const()[name = string("first_19_groups_0"), val = int32(256)];
            tensor<int32, [1]> first_19_strides_0 = const()[name = string("first_19_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_19_pad_0 = const()[name = string("first_19_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_19_dilations_0 = const()[name = string("first_19_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [256, 1, 5]> text_encoder_convnext_convnext_1_dwconv_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_1_dwconv_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5316736)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_1_dwconv_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_1_dwconv_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5319360)))];
            tensor<fp16, [1, 256, 32]> first_19_cast_fp16 = conv(bias = text_encoder_convnext_convnext_1_dwconv_Conv_bias_to_fp16, dilations = first_19_dilations_0, groups = first_19_groups_0, pad = first_19_pad_0, pad_type = first_19_pad_type_0, strides = first_19_strides_0, weight = text_encoder_convnext_convnext_1_dwconv_Conv_weight_to_fp16, x = input_13_cast_fp16)[name = string("first_19_cast_fp16")];
            tensor<fp16, [1, 256, 32]> input_tensor_27_cast_fp16 = mul(x = first_19_cast_fp16, y = text_mask)[name = string("input_tensor_27_cast_fp16")];
            tensor<int32, [3]> var_539 = const()[name = string("op_539"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_29_axes_0 = const()[name = string("input_tensor_29_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_convnext_convnext_1_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_1_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5319936)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_1_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_1_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5320512)))];
            fp16 var_542_to_fp16 = const()[name = string("op_542_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 32, 256]> input_15_cast_fp16 = transpose(perm = var_539, x = input_tensor_27_cast_fp16)[name = string("transpose_44")];
            tensor<fp16, [1, 32, 256]> input_tensor_29_cast_fp16 = layer_norm(axes = input_tensor_29_axes_0, beta = text_encoder_convnext_convnext_1_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_542_to_fp16, gamma = text_encoder_convnext_convnext_1_norm_norm_LayerNormalization_weight_to_fp16, x = input_15_cast_fp16)[name = string("input_tensor_29_cast_fp16")];
            tensor<int32, [3]> var_551 = const()[name = string("op_551"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_21_pad_type_0 = const()[name = string("first_21_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_21_strides_0 = const()[name = string("first_21_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_21_pad_0 = const()[name = string("first_21_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_21_dilations_0 = const()[name = string("first_21_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_21_groups_0 = const()[name = string("first_21_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_convnext_convnext_1_pwconv1_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_1_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5321088)))];
            tensor<fp16, [1024]> text_encoder_convnext_convnext_1_pwconv1_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_1_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5845440)))];
            tensor<fp16, [1, 256, 32]> input_17_cast_fp16 = transpose(perm = var_551, x = input_tensor_29_cast_fp16)[name = string("transpose_43")];
            tensor<fp16, [1, 1024, 32]> first_21_cast_fp16 = conv(bias = text_encoder_convnext_convnext_1_pwconv1_Conv_bias_to_fp16, dilations = first_21_dilations_0, groups = first_21_groups_0, pad = first_21_pad_0, pad_type = first_21_pad_type_0, strides = first_21_strides_0, weight = text_encoder_convnext_convnext_1_pwconv1_Conv_weight_to_fp16, x = input_17_cast_fp16)[name = string("first_21_cast_fp16")];
            string input_19_mode_0 = const()[name = string("input_19_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 1024, 32]> input_19_cast_fp16 = gelu(mode = input_19_mode_0, x = first_21_cast_fp16)[name = string("input_19_cast_fp16")];
            string second_21_pad_type_0 = const()[name = string("second_21_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_21_strides_0 = const()[name = string("second_21_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_21_pad_0 = const()[name = string("second_21_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_21_dilations_0 = const()[name = string("second_21_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_21_groups_0 = const()[name = string("second_21_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> second_23_weight_0_to_fp16 = const()[name = string("second_23_weight_0_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5847552)))];
            tensor<fp16, [256]> second_23_bias_0_to_fp16 = const()[name = string("second_23_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6371904)))];
            tensor<fp16, [1, 256, 32]> second_23_cast_fp16 = conv(bias = second_23_bias_0_to_fp16, dilations = second_21_dilations_0, groups = second_21_groups_0, pad = second_21_pad_0, pad_type = second_21_pad_type_0, strides = second_21_strides_0, weight = second_23_weight_0_to_fp16, x = input_19_cast_fp16)[name = string("second_23_cast_fp16")];
            tensor<fp16, [1, 256, 32]> first_29_cast_fp16 = add(x = input_11_cast_fp16, y = second_23_cast_fp16)[name = string("first_29_cast_fp16")];
            tensor<fp16, [1, 256, 32]> first_31_cast_fp16 = mul(x = first_29_cast_fp16, y = text_mask)[name = string("first_31_cast_fp16")];
            tensor<fp16, [1, 256, 32]> input_21_cast_fp16 = mul(x = first_31_cast_fp16, y = text_mask)[name = string("input_21_cast_fp16")];
            tensor<int32, [6]> input_23_pad_0 = const()[name = string("input_23_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            string input_23_mode_0 = const()[name = string("input_23_mode_0"), val = string("replicate")];
            fp16 const_2_to_fp16 = const()[name = string("const_2_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 256, 40]> input_23_cast_fp16 = pad(constant_val = const_2_to_fp16, mode = input_23_mode_0, pad = input_23_pad_0, x = input_21_cast_fp16)[name = string("input_23_cast_fp16")];
            string first_33_pad_type_0 = const()[name = string("first_33_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_33_dilations_0 = const()[name = string("first_33_dilations_0"), val = tensor<int32, [1]>([2])];
            int32 first_33_groups_0 = const()[name = string("first_33_groups_0"), val = int32(256)];
            tensor<int32, [1]> first_33_strides_0 = const()[name = string("first_33_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_33_pad_0 = const()[name = string("first_33_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [256, 1, 5]> text_encoder_convnext_convnext_2_dwconv_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_2_dwconv_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6372480)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_2_dwconv_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_2_dwconv_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6375104)))];
            tensor<fp16, [1, 256, 32]> first_33_cast_fp16 = conv(bias = text_encoder_convnext_convnext_2_dwconv_Conv_bias_to_fp16, dilations = first_33_dilations_0, groups = first_33_groups_0, pad = first_33_pad_0, pad_type = first_33_pad_type_0, strides = first_33_strides_0, weight = text_encoder_convnext_convnext_2_dwconv_Conv_weight_to_fp16, x = input_23_cast_fp16)[name = string("first_33_cast_fp16")];
            tensor<fp16, [1, 256, 32]> input_tensor_41_cast_fp16 = mul(x = first_33_cast_fp16, y = text_mask)[name = string("input_tensor_41_cast_fp16")];
            tensor<int32, [3]> var_608 = const()[name = string("op_608"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_43_axes_0 = const()[name = string("input_tensor_43_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_convnext_convnext_2_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_2_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6375680)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_2_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_2_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6376256)))];
            fp16 var_611_to_fp16 = const()[name = string("op_611_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 32, 256]> input_25_cast_fp16 = transpose(perm = var_608, x = input_tensor_41_cast_fp16)[name = string("transpose_42")];
            tensor<fp16, [1, 32, 256]> input_tensor_43_cast_fp16 = layer_norm(axes = input_tensor_43_axes_0, beta = text_encoder_convnext_convnext_2_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_611_to_fp16, gamma = text_encoder_convnext_convnext_2_norm_norm_LayerNormalization_weight_to_fp16, x = input_25_cast_fp16)[name = string("input_tensor_43_cast_fp16")];
            tensor<int32, [3]> var_620 = const()[name = string("op_620"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_35_pad_type_0 = const()[name = string("first_35_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_35_strides_0 = const()[name = string("first_35_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_35_pad_0 = const()[name = string("first_35_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_35_dilations_0 = const()[name = string("first_35_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_35_groups_0 = const()[name = string("first_35_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_convnext_convnext_2_pwconv1_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_2_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6376832)))];
            tensor<fp16, [1024]> text_encoder_convnext_convnext_2_pwconv1_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_2_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6901184)))];
            tensor<fp16, [1, 256, 32]> input_27_cast_fp16 = transpose(perm = var_620, x = input_tensor_43_cast_fp16)[name = string("transpose_41")];
            tensor<fp16, [1, 1024, 32]> first_35_cast_fp16 = conv(bias = text_encoder_convnext_convnext_2_pwconv1_Conv_bias_to_fp16, dilations = first_35_dilations_0, groups = first_35_groups_0, pad = first_35_pad_0, pad_type = first_35_pad_type_0, strides = first_35_strides_0, weight = text_encoder_convnext_convnext_2_pwconv1_Conv_weight_to_fp16, x = input_27_cast_fp16)[name = string("first_35_cast_fp16")];
            string input_29_mode_0 = const()[name = string("input_29_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 1024, 32]> input_29_cast_fp16 = gelu(mode = input_29_mode_0, x = first_35_cast_fp16)[name = string("input_29_cast_fp16")];
            string second_33_pad_type_0 = const()[name = string("second_33_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_33_strides_0 = const()[name = string("second_33_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_33_pad_0 = const()[name = string("second_33_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_33_dilations_0 = const()[name = string("second_33_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_33_groups_0 = const()[name = string("second_33_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> second_35_weight_0_to_fp16 = const()[name = string("second_35_weight_0_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6903296)))];
            tensor<fp16, [256]> second_35_bias_0_to_fp16 = const()[name = string("second_35_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7427648)))];
            tensor<fp16, [1, 256, 32]> second_35_cast_fp16 = conv(bias = second_35_bias_0_to_fp16, dilations = second_33_dilations_0, groups = second_33_groups_0, pad = second_33_pad_0, pad_type = second_33_pad_type_0, strides = second_33_strides_0, weight = second_35_weight_0_to_fp16, x = input_29_cast_fp16)[name = string("second_35_cast_fp16")];
            tensor<fp16, [1, 256, 32]> first_43_cast_fp16 = add(x = input_21_cast_fp16, y = second_35_cast_fp16)[name = string("first_43_cast_fp16")];
            tensor<fp16, [1, 256, 32]> first_45_cast_fp16 = mul(x = first_43_cast_fp16, y = text_mask)[name = string("first_45_cast_fp16")];
            tensor<fp16, [1, 256, 32]> input_31_cast_fp16 = mul(x = first_45_cast_fp16, y = text_mask)[name = string("input_31_cast_fp16")];
            tensor<int32, [6]> input_33_pad_0 = const()[name = string("input_33_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            string input_33_mode_0 = const()[name = string("input_33_mode_0"), val = string("replicate")];
            fp16 const_3_to_fp16 = const()[name = string("const_3_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 256, 40]> input_33_cast_fp16 = pad(constant_val = const_3_to_fp16, mode = input_33_mode_0, pad = input_33_pad_0, x = input_31_cast_fp16)[name = string("input_33_cast_fp16")];
            string first_47_pad_type_0 = const()[name = string("first_47_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_47_dilations_0 = const()[name = string("first_47_dilations_0"), val = tensor<int32, [1]>([2])];
            int32 first_47_groups_0 = const()[name = string("first_47_groups_0"), val = int32(256)];
            tensor<int32, [1]> first_47_strides_0 = const()[name = string("first_47_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_47_pad_0 = const()[name = string("first_47_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [256, 1, 5]> text_encoder_convnext_convnext_3_dwconv_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_3_dwconv_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7428224)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_3_dwconv_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_3_dwconv_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7430848)))];
            tensor<fp16, [1, 256, 32]> first_47_cast_fp16 = conv(bias = text_encoder_convnext_convnext_3_dwconv_Conv_bias_to_fp16, dilations = first_47_dilations_0, groups = first_47_groups_0, pad = first_47_pad_0, pad_type = first_47_pad_type_0, strides = first_47_strides_0, weight = text_encoder_convnext_convnext_3_dwconv_Conv_weight_to_fp16, x = input_33_cast_fp16)[name = string("first_47_cast_fp16")];
            tensor<fp16, [1, 256, 32]> input_tensor_55_cast_fp16 = mul(x = first_47_cast_fp16, y = text_mask)[name = string("input_tensor_55_cast_fp16")];
            tensor<int32, [3]> var_677 = const()[name = string("op_677"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_57_axes_0 = const()[name = string("input_tensor_57_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_convnext_convnext_3_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_3_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7431424)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_3_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_3_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7432000)))];
            fp16 var_680_to_fp16 = const()[name = string("op_680_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 32, 256]> input_35_cast_fp16 = transpose(perm = var_677, x = input_tensor_55_cast_fp16)[name = string("transpose_40")];
            tensor<fp16, [1, 32, 256]> input_tensor_57_cast_fp16 = layer_norm(axes = input_tensor_57_axes_0, beta = text_encoder_convnext_convnext_3_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_680_to_fp16, gamma = text_encoder_convnext_convnext_3_norm_norm_LayerNormalization_weight_to_fp16, x = input_35_cast_fp16)[name = string("input_tensor_57_cast_fp16")];
            tensor<int32, [3]> var_689 = const()[name = string("op_689"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_49_pad_type_0 = const()[name = string("first_49_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_49_strides_0 = const()[name = string("first_49_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_49_pad_0 = const()[name = string("first_49_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_49_dilations_0 = const()[name = string("first_49_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_49_groups_0 = const()[name = string("first_49_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_convnext_convnext_3_pwconv1_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_3_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7432576)))];
            tensor<fp16, [1024]> text_encoder_convnext_convnext_3_pwconv1_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_3_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7956928)))];
            tensor<fp16, [1, 256, 32]> input_37_cast_fp16 = transpose(perm = var_689, x = input_tensor_57_cast_fp16)[name = string("transpose_39")];
            tensor<fp16, [1, 1024, 32]> first_49_cast_fp16 = conv(bias = text_encoder_convnext_convnext_3_pwconv1_Conv_bias_to_fp16, dilations = first_49_dilations_0, groups = first_49_groups_0, pad = first_49_pad_0, pad_type = first_49_pad_type_0, strides = first_49_strides_0, weight = text_encoder_convnext_convnext_3_pwconv1_Conv_weight_to_fp16, x = input_37_cast_fp16)[name = string("first_49_cast_fp16")];
            string input_39_mode_0 = const()[name = string("input_39_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 1024, 32]> input_39_cast_fp16 = gelu(mode = input_39_mode_0, x = first_49_cast_fp16)[name = string("input_39_cast_fp16")];
            string second_45_pad_type_0 = const()[name = string("second_45_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_45_strides_0 = const()[name = string("second_45_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_45_pad_0 = const()[name = string("second_45_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_45_dilations_0 = const()[name = string("second_45_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_45_groups_0 = const()[name = string("second_45_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> second_47_weight_0_to_fp16 = const()[name = string("second_47_weight_0_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7959040)))];
            tensor<fp16, [256]> second_47_bias_0_to_fp16 = const()[name = string("second_47_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8483392)))];
            tensor<fp16, [1, 256, 32]> second_47_cast_fp16 = conv(bias = second_47_bias_0_to_fp16, dilations = second_45_dilations_0, groups = second_45_groups_0, pad = second_45_pad_0, pad_type = second_45_pad_type_0, strides = second_45_strides_0, weight = second_47_weight_0_to_fp16, x = input_39_cast_fp16)[name = string("second_47_cast_fp16")];
            tensor<fp16, [1, 256, 32]> first_57_cast_fp16 = add(x = input_31_cast_fp16, y = second_47_cast_fp16)[name = string("first_57_cast_fp16")];
            tensor<fp16, [1, 256, 32]> first_59_cast_fp16 = mul(x = first_57_cast_fp16, y = text_mask)[name = string("first_59_cast_fp16")];
            tensor<fp16, [1, 256, 32]> input_41_cast_fp16 = mul(x = first_59_cast_fp16, y = text_mask)[name = string("input_41_cast_fp16")];
            tensor<int32, [6]> input_43_pad_0 = const()[name = string("input_43_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 8, 8])];
            string input_43_mode_0 = const()[name = string("input_43_mode_0"), val = string("replicate")];
            fp16 const_4_to_fp16 = const()[name = string("const_4_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 256, 48]> input_43_cast_fp16 = pad(constant_val = const_4_to_fp16, mode = input_43_mode_0, pad = input_43_pad_0, x = input_41_cast_fp16)[name = string("input_43_cast_fp16")];
            string first_61_pad_type_0 = const()[name = string("first_61_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_61_dilations_0 = const()[name = string("first_61_dilations_0"), val = tensor<int32, [1]>([4])];
            int32 first_61_groups_0 = const()[name = string("first_61_groups_0"), val = int32(256)];
            tensor<int32, [1]> first_61_strides_0 = const()[name = string("first_61_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_61_pad_0 = const()[name = string("first_61_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [256, 1, 5]> text_encoder_convnext_convnext_4_dwconv_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_4_dwconv_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8483968)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_4_dwconv_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_4_dwconv_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8486592)))];
            tensor<fp16, [1, 256, 32]> first_61_cast_fp16 = conv(bias = text_encoder_convnext_convnext_4_dwconv_Conv_bias_to_fp16, dilations = first_61_dilations_0, groups = first_61_groups_0, pad = first_61_pad_0, pad_type = first_61_pad_type_0, strides = first_61_strides_0, weight = text_encoder_convnext_convnext_4_dwconv_Conv_weight_to_fp16, x = input_43_cast_fp16)[name = string("first_61_cast_fp16")];
            tensor<fp16, [1, 256, 32]> input_tensor_69_cast_fp16 = mul(x = first_61_cast_fp16, y = text_mask)[name = string("input_tensor_69_cast_fp16")];
            tensor<int32, [3]> var_746 = const()[name = string("op_746"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_71_axes_0 = const()[name = string("input_tensor_71_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_convnext_convnext_4_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_4_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8487168)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_4_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_4_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8487744)))];
            fp16 var_749_to_fp16 = const()[name = string("op_749_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 32, 256]> input_45_cast_fp16 = transpose(perm = var_746, x = input_tensor_69_cast_fp16)[name = string("transpose_38")];
            tensor<fp16, [1, 32, 256]> input_tensor_71_cast_fp16 = layer_norm(axes = input_tensor_71_axes_0, beta = text_encoder_convnext_convnext_4_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_749_to_fp16, gamma = text_encoder_convnext_convnext_4_norm_norm_LayerNormalization_weight_to_fp16, x = input_45_cast_fp16)[name = string("input_tensor_71_cast_fp16")];
            tensor<int32, [3]> var_758 = const()[name = string("op_758"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_63_pad_type_0 = const()[name = string("first_63_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_63_strides_0 = const()[name = string("first_63_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_63_pad_0 = const()[name = string("first_63_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_63_dilations_0 = const()[name = string("first_63_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_63_groups_0 = const()[name = string("first_63_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_convnext_convnext_4_pwconv1_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_4_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8488320)))];
            tensor<fp16, [1024]> text_encoder_convnext_convnext_4_pwconv1_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_4_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9012672)))];
            tensor<fp16, [1, 256, 32]> input_47_cast_fp16 = transpose(perm = var_758, x = input_tensor_71_cast_fp16)[name = string("transpose_37")];
            tensor<fp16, [1, 1024, 32]> first_63_cast_fp16 = conv(bias = text_encoder_convnext_convnext_4_pwconv1_Conv_bias_to_fp16, dilations = first_63_dilations_0, groups = first_63_groups_0, pad = first_63_pad_0, pad_type = first_63_pad_type_0, strides = first_63_strides_0, weight = text_encoder_convnext_convnext_4_pwconv1_Conv_weight_to_fp16, x = input_47_cast_fp16)[name = string("first_63_cast_fp16")];
            string input_49_mode_0 = const()[name = string("input_49_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 1024, 32]> input_49_cast_fp16 = gelu(mode = input_49_mode_0, x = first_63_cast_fp16)[name = string("input_49_cast_fp16")];
            string second_57_pad_type_0 = const()[name = string("second_57_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_57_strides_0 = const()[name = string("second_57_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_57_pad_0 = const()[name = string("second_57_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_57_dilations_0 = const()[name = string("second_57_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_57_groups_0 = const()[name = string("second_57_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> second_59_weight_0_to_fp16 = const()[name = string("second_59_weight_0_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9014784)))];
            tensor<fp16, [256]> second_59_bias_0_to_fp16 = const()[name = string("second_59_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9539136)))];
            tensor<fp16, [1, 256, 32]> second_59_cast_fp16 = conv(bias = second_59_bias_0_to_fp16, dilations = second_57_dilations_0, groups = second_57_groups_0, pad = second_57_pad_0, pad_type = second_57_pad_type_0, strides = second_57_strides_0, weight = second_59_weight_0_to_fp16, x = input_49_cast_fp16)[name = string("second_59_cast_fp16")];
            tensor<fp16, [1, 256, 32]> first_71_cast_fp16 = add(x = input_41_cast_fp16, y = second_59_cast_fp16)[name = string("first_71_cast_fp16")];
            tensor<fp16, [1, 256, 32]> first_73_cast_fp16 = mul(x = first_71_cast_fp16, y = text_mask)[name = string("first_73_cast_fp16")];
            tensor<fp16, [1, 256, 32]> input_51_cast_fp16 = mul(x = first_73_cast_fp16, y = text_mask)[name = string("input_51_cast_fp16")];
            tensor<int32, [6]> input_53_pad_0 = const()[name = string("input_53_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 8, 8])];
            string input_53_mode_0 = const()[name = string("input_53_mode_0"), val = string("replicate")];
            fp16 const_5_to_fp16 = const()[name = string("const_5_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 256, 48]> input_53_cast_fp16 = pad(constant_val = const_5_to_fp16, mode = input_53_mode_0, pad = input_53_pad_0, x = input_51_cast_fp16)[name = string("input_53_cast_fp16")];
            string first_75_pad_type_0 = const()[name = string("first_75_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_75_dilations_0 = const()[name = string("first_75_dilations_0"), val = tensor<int32, [1]>([4])];
            int32 first_75_groups_0 = const()[name = string("first_75_groups_0"), val = int32(256)];
            tensor<int32, [1]> first_75_strides_0 = const()[name = string("first_75_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_75_pad_0 = const()[name = string("first_75_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [256, 1, 5]> text_encoder_convnext_convnext_5_dwconv_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_5_dwconv_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9539712)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_5_dwconv_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_5_dwconv_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9542336)))];
            tensor<fp16, [1, 256, 32]> first_75_cast_fp16 = conv(bias = text_encoder_convnext_convnext_5_dwconv_Conv_bias_to_fp16, dilations = first_75_dilations_0, groups = first_75_groups_0, pad = first_75_pad_0, pad_type = first_75_pad_type_0, strides = first_75_strides_0, weight = text_encoder_convnext_convnext_5_dwconv_Conv_weight_to_fp16, x = input_53_cast_fp16)[name = string("first_75_cast_fp16")];
            tensor<fp16, [1, 256, 32]> input_tensor_83_cast_fp16 = mul(x = first_75_cast_fp16, y = text_mask)[name = string("input_tensor_83_cast_fp16")];
            tensor<int32, [3]> var_815 = const()[name = string("op_815"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_85_axes_0 = const()[name = string("input_tensor_85_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_convnext_convnext_5_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_5_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9542912)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_5_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_5_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9543488)))];
            fp16 var_818_to_fp16 = const()[name = string("op_818_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 32, 256]> input_55_cast_fp16 = transpose(perm = var_815, x = input_tensor_83_cast_fp16)[name = string("transpose_36")];
            tensor<fp16, [1, 32, 256]> input_tensor_85_cast_fp16 = layer_norm(axes = input_tensor_85_axes_0, beta = text_encoder_convnext_convnext_5_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_818_to_fp16, gamma = text_encoder_convnext_convnext_5_norm_norm_LayerNormalization_weight_to_fp16, x = input_55_cast_fp16)[name = string("input_tensor_85_cast_fp16")];
            tensor<int32, [3]> var_827 = const()[name = string("op_827"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_77_pad_type_0 = const()[name = string("first_77_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_77_strides_0 = const()[name = string("first_77_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_77_pad_0 = const()[name = string("first_77_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_77_dilations_0 = const()[name = string("first_77_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_77_groups_0 = const()[name = string("first_77_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_convnext_convnext_5_pwconv1_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_5_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9544064)))];
            tensor<fp16, [1024]> text_encoder_convnext_convnext_5_pwconv1_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_5_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10068416)))];
            tensor<fp16, [1, 256, 32]> input_57_cast_fp16 = transpose(perm = var_827, x = input_tensor_85_cast_fp16)[name = string("transpose_35")];
            tensor<fp16, [1, 1024, 32]> first_77_cast_fp16 = conv(bias = text_encoder_convnext_convnext_5_pwconv1_Conv_bias_to_fp16, dilations = first_77_dilations_0, groups = first_77_groups_0, pad = first_77_pad_0, pad_type = first_77_pad_type_0, strides = first_77_strides_0, weight = text_encoder_convnext_convnext_5_pwconv1_Conv_weight_to_fp16, x = input_57_cast_fp16)[name = string("first_77_cast_fp16")];
            string input_59_mode_0 = const()[name = string("input_59_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 1024, 32]> input_59_cast_fp16 = gelu(mode = input_59_mode_0, x = first_77_cast_fp16)[name = string("input_59_cast_fp16")];
            string second_69_pad_type_0 = const()[name = string("second_69_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_69_strides_0 = const()[name = string("second_69_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_69_pad_0 = const()[name = string("second_69_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_69_dilations_0 = const()[name = string("second_69_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_69_groups_0 = const()[name = string("second_69_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> second_71_weight_0_to_fp16 = const()[name = string("second_71_weight_0_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10070528)))];
            tensor<fp16, [256]> second_71_bias_0_to_fp16 = const()[name = string("second_71_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10594880)))];
            tensor<fp16, [1, 256, 32]> second_71_cast_fp16 = conv(bias = second_71_bias_0_to_fp16, dilations = second_69_dilations_0, groups = second_69_groups_0, pad = second_69_pad_0, pad_type = second_69_pad_type_0, strides = second_69_strides_0, weight = second_71_weight_0_to_fp16, x = input_59_cast_fp16)[name = string("second_71_cast_fp16")];
            tensor<fp16, [1, 256, 32]> first_85_cast_fp16 = add(x = input_51_cast_fp16, y = second_71_cast_fp16)[name = string("first_85_cast_fp16")];
            tensor<fp16, [1, 256, 32]> first_89_cast_fp16 = mul(x = first_85_cast_fp16, y = text_mask)[name = string("first_89_cast_fp16")];
            tensor<int32, [1]> first_87_axes_0 = const()[name = string("first_87_axes_0"), val = tensor<int32, [1]>([2])];
            tensor<fp16, [1, 1, 1, 32]> first_87_cast_fp16 = expand_dims(axes = first_87_axes_0, x = text_mask)[name = string("first_87_cast_fp16")];
            tensor<int32, [1]> second_73_axes_0 = const()[name = string("second_73_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 1, 32, 1]> second_73_cast_fp16 = expand_dims(axes = second_73_axes_0, x = text_mask)[name = string("second_73_cast_fp16")];
            tensor<fp16, [1, 1, 32, 32]> x_45_cast_fp16 = mul(x = first_87_cast_fp16, y = second_73_cast_fp16)[name = string("x_45_cast_fp16")];
            tensor<fp16, [1, 256, 32]> input_61_cast_fp16 = mul(x = first_89_cast_fp16, y = text_mask)[name = string("input_61_cast_fp16")];
            string input_tensor_97_pad_type_0 = const()[name = string("input_tensor_97_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_97_strides_0 = const()[name = string("input_tensor_97_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_97_pad_0 = const()[name = string("input_tensor_97_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_97_dilations_0 = const()[name = string("input_tensor_97_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_97_groups_0 = const()[name = string("input_tensor_97_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_0_conv_q_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_q_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10595456)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_0_conv_q_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_q_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10726592)))];
            tensor<fp16, [1, 256, 32]> input_tensor_97_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_0_conv_q_Conv_bias_to_fp16, dilations = input_tensor_97_dilations_0, groups = input_tensor_97_groups_0, pad = input_tensor_97_pad_0, pad_type = input_tensor_97_pad_type_0, strides = input_tensor_97_strides_0, weight = text_encoder_attn_encoder_attn_layers_0_conv_q_Conv_weight_to_fp16, x = input_61_cast_fp16)[name = string("input_tensor_97_cast_fp16")];
            string input_tensor_89_pad_type_0 = const()[name = string("input_tensor_89_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_89_strides_0 = const()[name = string("input_tensor_89_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_89_pad_0 = const()[name = string("input_tensor_89_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_89_dilations_0 = const()[name = string("input_tensor_89_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_89_groups_0 = const()[name = string("input_tensor_89_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_0_conv_k_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_k_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10727168)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_0_conv_k_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_k_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10858304)))];
            tensor<fp16, [1, 256, 32]> input_tensor_89_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_0_conv_k_Conv_bias_to_fp16, dilations = input_tensor_89_dilations_0, groups = input_tensor_89_groups_0, pad = input_tensor_89_pad_0, pad_type = input_tensor_89_pad_type_0, strides = input_tensor_89_strides_0, weight = text_encoder_attn_encoder_attn_layers_0_conv_k_Conv_weight_to_fp16, x = input_61_cast_fp16)[name = string("input_tensor_89_cast_fp16")];
            string input_tensor_109_pad_type_0 = const()[name = string("input_tensor_109_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_109_strides_0 = const()[name = string("input_tensor_109_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_109_pad_0 = const()[name = string("input_tensor_109_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_109_dilations_0 = const()[name = string("input_tensor_109_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_109_groups_0 = const()[name = string("input_tensor_109_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_0_conv_v_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_v_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10858880)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_0_conv_v_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_v_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10990016)))];
            tensor<fp16, [1, 256, 32]> input_tensor_109_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_0_conv_v_Conv_bias_to_fp16, dilations = input_tensor_109_dilations_0, groups = input_tensor_109_groups_0, pad = input_tensor_109_pad_0, pad_type = input_tensor_109_pad_type_0, strides = input_tensor_109_strides_0, weight = text_encoder_attn_encoder_attn_layers_0_conv_v_Conv_weight_to_fp16, x = input_61_cast_fp16)[name = string("input_tensor_109_cast_fp16")];
            tensor<int32, [4]> var_973 = const()[name = string("op_973"), val = tensor<int32, [4]>([1, 4, 64, 32])];
            tensor<fp16, [1, 4, 64, 32]> input_tensor_105_cast_fp16 = reshape(shape = var_973, x = input_tensor_97_cast_fp16)[name = string("input_tensor_105_cast_fp16")];
            tensor<int32, [4]> var_979 = const()[name = string("op_979"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [4]> var_1005 = const()[name = string("op_1005"), val = tensor<int32, [4]>([1, 4, 64, 32])];
            tensor<fp16, [1, 4, 64, 32]> y_1_cast_fp16 = reshape(shape = var_1005, x = input_tensor_89_cast_fp16)[name = string("y_1_cast_fp16")];
            tensor<int32, [4]> var_1017 = const()[name = string("op_1017"), val = tensor<int32, [4]>([1, 4, 64, 32])];
            tensor<fp16, [1, 4, 64, 32]> input_tensor_111_cast_fp16 = reshape(shape = var_1017, x = input_tensor_109_cast_fp16)[name = string("input_tensor_111_cast_fp16")];
            fp16 _inversed_x_25_y_0_to_fp16 = const()[name = string("_inversed_x_25_y_0_to_fp16"), val = fp16(0x1p-3)];
            tensor<fp16, [1, 4, 32, 64]> first_91_cast_fp16 = transpose(perm = var_979, x = input_tensor_105_cast_fp16)[name = string("transpose_34")];
            tensor<fp16, [1, 4, 32, 64]> _inversed_x_25_cast_fp16 = mul(x = first_91_cast_fp16, y = _inversed_x_25_y_0_to_fp16)[name = string("_inversed_x_25_cast_fp16")];
            bool first_107_transpose_x_0 = const()[name = string("first_107_transpose_x_0"), val = bool(false)];
            bool first_107_transpose_y_0 = const()[name = string("first_107_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 4, 32, 32]> first_107_cast_fp16 = matmul(transpose_x = first_107_transpose_x_0, transpose_y = first_107_transpose_y_0, x = _inversed_x_25_cast_fp16, y = y_1_cast_fp16)[name = string("first_107_cast_fp16")];
            bool input_tensor_143_transpose_x_0 = const()[name = string("input_tensor_143_transpose_x_0"), val = bool(false)];
            bool input_tensor_143_transpose_y_0 = const()[name = string("input_tensor_143_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 64, 63]> y_3_to_fp16 = const()[name = string("y_3_to_fp16"), val = tensor<fp16, [1, 1, 64, 63]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17798016)))];
            tensor<fp16, [1, 4, 32, 63]> input_tensor_143_cast_fp16 = matmul(transpose_x = input_tensor_143_transpose_x_0, transpose_y = input_tensor_143_transpose_y_0, x = _inversed_x_25_cast_fp16, y = y_3_to_fp16)[name = string("input_tensor_143_cast_fp16")];
            tensor<int32, [8]> input_tensor_165_pad_0 = const()[name = string("input_tensor_165_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 1])];
            string input_tensor_165_mode_0 = const()[name = string("input_tensor_165_mode_0"), val = string("constant")];
            fp16 const_23_to_fp16 = const()[name = string("const_23_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 32, 64]> input_tensor_165_cast_fp16 = pad(constant_val = const_23_to_fp16, mode = input_tensor_165_mode_0, pad = input_tensor_165_pad_0, x = input_tensor_143_cast_fp16)[name = string("input_tensor_165_cast_fp16")];
            tensor<int32, [3]> var_1140 = const()[name = string("op_1140"), val = tensor<int32, [3]>([1, 4, 2048])];
            tensor<fp16, [1, 4, 2048]> input_69_cast_fp16 = reshape(shape = var_1140, x = input_tensor_165_cast_fp16)[name = string("input_69_cast_fp16")];
            tensor<int32, [6]> input_tensor_187_pad_0 = const()[name = string("input_tensor_187_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 0, 31])];
            string input_tensor_187_mode_0 = const()[name = string("input_tensor_187_mode_0"), val = string("constant")];
            fp16 const_24_to_fp16 = const()[name = string("const_24_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 2079]> input_tensor_187_cast_fp16 = pad(constant_val = const_24_to_fp16, mode = input_tensor_187_mode_0, pad = input_tensor_187_pad_0, x = input_69_cast_fp16)[name = string("input_tensor_187_cast_fp16")];
            tensor<int32, [4]> var_1175 = const()[name = string("op_1175"), val = tensor<int32, [4]>([1, 4, 33, 63])];
            tensor<fp16, [1, 4, 33, 63]> x_41_cast_fp16 = reshape(shape = var_1175, x = input_tensor_187_cast_fp16)[name = string("x_41_cast_fp16")];
            tensor<int32, [4]> x_43_begin_0 = const()[name = string("x_43_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> x_43_end_0 = const()[name = string("x_43_end_0"), val = tensor<int32, [4]>([1, 4, 32, 63])];
            tensor<bool, [4]> x_43_end_mask_0 = const()[name = string("x_43_end_mask_0"), val = tensor<bool, [4]>([true, true, false, true])];
            tensor<fp16, [1, 4, 32, 63]> x_43_cast_fp16 = slice_by_index(begin = x_43_begin_0, end = x_43_end_0, end_mask = x_43_end_mask_0, x = x_41_cast_fp16)[name = string("x_43_cast_fp16")];
            tensor<int32, [4]> second_97_begin_0 = const()[name = string("second_97_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 31])];
            tensor<int32, [4]> second_97_end_0 = const()[name = string("second_97_end_0"), val = tensor<int32, [4]>([1, 4, 32, 1])];
            tensor<bool, [4]> second_97_end_mask_0 = const()[name = string("second_97_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 32, 32]> second_97_cast_fp16 = slice_by_index(begin = second_97_begin_0, end = second_97_end_0, end_mask = second_97_end_mask_0, x = x_43_cast_fp16)[name = string("second_97_cast_fp16")];
            tensor<fp16, [1, 4, 32, 32]> y_7_cast_fp16 = add(x = first_107_cast_fp16, y = second_97_cast_fp16)[name = string("y_7_cast_fp16")];
            fp16 text_encoder_attn_encoder_attn_layers_0_Constant_87_value_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_Constant_87_value_to_fp16"), val = fp16(0x0p+0)];
            tensor<bool, [1, 1, 32, 32]> input_tensor_189_cast_fp16 = equal(x = x_45_cast_fp16, y = text_encoder_attn_encoder_attn_layers_0_Constant_87_value_to_fp16)[name = string("input_tensor_189_cast_fp16")];
            tensor<int32, [4]> condition_1_after_broadcast_reps_0 = const()[name = string("condition_1_after_broadcast_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<bool, [1, 4, 32, 32]> condition_1_after_broadcast = tile(reps = condition_1_after_broadcast_reps_0, x = input_tensor_189_cast_fp16)[name = string("condition_1_after_broadcast")];
            tensor<fp16, [1, 4, 32, 32]> text_encoder_attn_encoder_attn_layers_0_Constant_88_value_after_broadcast_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_Constant_88_value_after_broadcast_to_fp16"), val = tensor<fp16, [1, 4, 32, 32]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17806144)))];
            tensor<fp16, [1, 4, 32, 32]> input_71_cast_fp16 = select(a = text_encoder_attn_encoder_attn_layers_0_Constant_88_value_after_broadcast_to_fp16, b = y_7_cast_fp16, cond = condition_1_after_broadcast)[name = string("input_71_cast_fp16")];
            int32 var_1218 = const()[name = string("op_1218"), val = int32(-1)];
            tensor<fp16, [1, 4, 32, 32]> x_49_cast_fp16 = softmax(axis = var_1218, x = input_71_cast_fp16)[name = string("x_49_cast_fp16")];
            bool first_119_transpose_x_1 = const()[name = string("first_119_transpose_x_1"), val = bool(false)];
            bool first_119_transpose_y_1 = const()[name = string("first_119_transpose_y_1"), val = bool(true)];
            tensor<fp16, [1, 4, 32, 64]> first_119_cast_fp16 = matmul(transpose_x = first_119_transpose_x_1, transpose_y = first_119_transpose_y_1, x = x_49_cast_fp16, y = input_tensor_111_cast_fp16)[name = string("first_119_cast_fp16")];
            tensor<int32, [8]> input_tensor_219_pad_0 = const()[name = string("input_tensor_219_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 31])];
            string input_tensor_219_mode_0 = const()[name = string("input_tensor_219_mode_0"), val = string("constant")];
            fp16 const_31_to_fp16 = const()[name = string("const_31_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 32, 63]> input_tensor_219_cast_fp16 = pad(constant_val = const_31_to_fp16, mode = input_tensor_219_mode_0, pad = input_tensor_219_pad_0, x = x_49_cast_fp16)[name = string("input_tensor_219_cast_fp16")];
            tensor<int32, [3]> var_1292 = const()[name = string("op_1292"), val = tensor<int32, [3]>([1, 4, 2016])];
            tensor<fp16, [1, 4, 2016]> input_73_cast_fp16 = reshape(shape = var_1292, x = input_tensor_219_cast_fp16)[name = string("input_73_cast_fp16")];
            tensor<int32, [6]> input_tensor_237_pad_0 = const()[name = string("input_tensor_237_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 32, 0])];
            string input_tensor_237_mode_0 = const()[name = string("input_tensor_237_mode_0"), val = string("constant")];
            fp16 const_32_to_fp16 = const()[name = string("const_32_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 2048]> input_tensor_237_cast_fp16 = pad(constant_val = const_32_to_fp16, mode = input_tensor_237_mode_0, pad = input_tensor_237_pad_0, x = input_73_cast_fp16)[name = string("input_tensor_237_cast_fp16")];
            tensor<int32, [4]> var_1322 = const()[name = string("op_1322"), val = tensor<int32, [4]>([1, 4, 32, 64])];
            tensor<fp16, [1, 4, 32, 64]> x_59_cast_fp16 = reshape(shape = var_1322, x = input_tensor_237_cast_fp16)[name = string("x_59_cast_fp16")];
            tensor<int32, [4]> x_67_begin_0 = const()[name = string("x_67_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 1])];
            tensor<int32, [4]> x_67_end_0 = const()[name = string("x_67_end_0"), val = tensor<int32, [4]>([1, 4, 32, 1])];
            tensor<bool, [4]> x_67_end_mask_0 = const()[name = string("x_67_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 32, 63]> x_67_cast_fp16 = slice_by_index(begin = x_67_begin_0, end = x_67_end_0, end_mask = x_67_end_mask_0, x = x_59_cast_fp16)[name = string("x_67_cast_fp16")];
            bool second_111_transpose_x_0 = const()[name = string("second_111_transpose_x_0"), val = bool(false)];
            bool second_111_transpose_y_0 = const()[name = string("second_111_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 63, 64]> y_11_to_fp16 = const()[name = string("y_11_to_fp16"), val = tensor<fp16, [1, 1, 63, 64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17814400)))];
            tensor<fp16, [1, 4, 32, 64]> second_111_cast_fp16 = matmul(transpose_x = second_111_transpose_x_0, transpose_y = second_111_transpose_y_0, x = x_67_cast_fp16, y = y_11_to_fp16)[name = string("second_111_cast_fp16")];
            tensor<fp16, [1, 4, 32, 64]> input_tensor_255_cast_fp16 = add(x = first_119_cast_fp16, y = second_111_cast_fp16)[name = string("input_tensor_255_cast_fp16")];
            tensor<int32, [4]> var_1369 = const()[name = string("op_1369"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [3]> var_1388 = const()[name = string("op_1388"), val = tensor<int32, [3]>([1, 256, 32])];
            tensor<fp16, [1, 4, 64, 32]> input_tensor_259_cast_fp16 = transpose(perm = var_1369, x = input_tensor_255_cast_fp16)[name = string("transpose_33")];
            tensor<fp16, [1, 256, 32]> input_77_cast_fp16 = reshape(shape = var_1388, x = input_tensor_259_cast_fp16)[name = string("input_77_cast_fp16")];
            string second_113_pad_type_0 = const()[name = string("second_113_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_113_strides_0 = const()[name = string("second_113_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_113_pad_0 = const()[name = string("second_113_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_113_dilations_0 = const()[name = string("second_113_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_113_groups_0 = const()[name = string("second_113_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_0_conv_o_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_o_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11000768)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_0_conv_o_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_o_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11131904)))];
            tensor<fp16, [1, 256, 32]> second_113_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_0_conv_o_Conv_bias_to_fp16, dilations = second_113_dilations_0, groups = second_113_groups_0, pad = second_113_pad_0, pad_type = second_113_pad_type_0, strides = second_113_strides_0, weight = text_encoder_attn_encoder_attn_layers_0_conv_o_Conv_weight_to_fp16, x = input_77_cast_fp16)[name = string("second_113_cast_fp16")];
            tensor<fp16, [1, 256, 32]> input_tensor_261_cast_fp16 = add(x = input_61_cast_fp16, y = second_113_cast_fp16)[name = string("input_tensor_261_cast_fp16")];
            tensor<int32, [3]> var_1406 = const()[name = string("op_1406"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_263_axes_0 = const()[name = string("input_tensor_263_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_0_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_0_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11132480)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_0_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_0_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11133056)))];
            fp16 var_1409_to_fp16 = const()[name = string("op_1409_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 32, 256]> input_79_cast_fp16 = transpose(perm = var_1406, x = input_tensor_261_cast_fp16)[name = string("transpose_32")];
            tensor<fp16, [1, 32, 256]> input_tensor_263_cast_fp16 = layer_norm(axes = input_tensor_263_axes_0, beta = text_encoder_attn_encoder_norm_layers_1_0_norm_LayerNormalization_bias_to_fp16, epsilon = var_1409_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_1_0_norm_LayerNormalization_weight_to_fp16, x = input_79_cast_fp16)[name = string("input_tensor_263_cast_fp16")];
            tensor<int32, [3]> var_1418 = const()[name = string("op_1418"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 256, 32]> first_121_cast_fp16 = transpose(perm = var_1418, x = input_tensor_263_cast_fp16)[name = string("transpose_31")];
            tensor<fp16, [1, 256, 32]> input_81_cast_fp16 = mul(x = first_121_cast_fp16, y = text_mask)[name = string("input_81_cast_fp16")];
            string input_83_pad_type_0 = const()[name = string("input_83_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_83_strides_0 = const()[name = string("input_83_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_83_pad_0 = const()[name = string("input_83_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_83_dilations_0 = const()[name = string("input_83_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_83_groups_0 = const()[name = string("input_83_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_attn_encoder_ffn_layers_0_conv_1_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_0_conv_1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11133632)))];
            tensor<fp16, [1024]> text_encoder_attn_encoder_ffn_layers_0_conv_1_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_0_conv_1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11657984)))];
            tensor<fp16, [1, 1024, 32]> input_83_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_0_conv_1_Conv_bias_to_fp16, dilations = input_83_dilations_0, groups = input_83_groups_0, pad = input_83_pad_0, pad_type = input_83_pad_type_0, strides = input_83_strides_0, weight = text_encoder_attn_encoder_ffn_layers_0_conv_1_Conv_weight_to_fp16, x = input_81_cast_fp16)[name = string("input_83_cast_fp16")];
            tensor<fp16, [1, 1024, 32]> first_123_cast_fp16 = relu(x = input_83_cast_fp16)[name = string("first_123_cast_fp16")];
            tensor<fp16, [1, 1024, 32]> input_85_cast_fp16 = mul(x = first_123_cast_fp16, y = text_mask)[name = string("input_85_cast_fp16")];
            string first_125_pad_type_0 = const()[name = string("first_125_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_125_strides_0 = const()[name = string("first_125_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_125_pad_0 = const()[name = string("first_125_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_125_dilations_0 = const()[name = string("first_125_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_125_groups_0 = const()[name = string("first_125_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> text_encoder_attn_encoder_ffn_layers_0_conv_2_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_0_conv_2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11660096)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_ffn_layers_0_conv_2_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_0_conv_2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12184448)))];
            tensor<fp16, [1, 256, 32]> first_125_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_0_conv_2_Conv_bias_to_fp16, dilations = first_125_dilations_0, groups = first_125_groups_0, pad = first_125_pad_0, pad_type = first_125_pad_type_0, strides = first_125_strides_0, weight = text_encoder_attn_encoder_ffn_layers_0_conv_2_Conv_weight_to_fp16, x = input_85_cast_fp16)[name = string("first_125_cast_fp16")];
            tensor<fp16, [1, 256, 32]> second_115_cast_fp16 = mul(x = first_125_cast_fp16, y = text_mask)[name = string("second_115_cast_fp16")];
            tensor<fp16, [1, 256, 32]> input_tensor_265_cast_fp16 = add(x = first_121_cast_fp16, y = second_115_cast_fp16)[name = string("input_tensor_265_cast_fp16")];
            tensor<int32, [3]> var_1451 = const()[name = string("op_1451"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_267_axes_0 = const()[name = string("input_tensor_267_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_0_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_0_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12185024)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_0_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_0_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12185600)))];
            fp16 var_1454_to_fp16 = const()[name = string("op_1454_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 32, 256]> input_87_cast_fp16 = transpose(perm = var_1451, x = input_tensor_265_cast_fp16)[name = string("transpose_30")];
            tensor<fp16, [1, 32, 256]> input_tensor_267_cast_fp16 = layer_norm(axes = input_tensor_267_axes_0, beta = text_encoder_attn_encoder_norm_layers_2_0_norm_LayerNormalization_bias_to_fp16, epsilon = var_1454_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_2_0_norm_LayerNormalization_weight_to_fp16, x = input_87_cast_fp16)[name = string("input_tensor_267_cast_fp16")];
            tensor<int32, [3]> var_1463 = const()[name = string("op_1463"), val = tensor<int32, [3]>([0, 2, 1])];
            string input_tensor_277_pad_type_0 = const()[name = string("input_tensor_277_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_277_strides_0 = const()[name = string("input_tensor_277_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_277_pad_0 = const()[name = string("input_tensor_277_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_277_dilations_0 = const()[name = string("input_tensor_277_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_277_groups_0 = const()[name = string("input_tensor_277_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_1_conv_q_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_q_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12186176)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_1_conv_q_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_q_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12317312)))];
            tensor<fp16, [1, 256, 32]> input_89_cast_fp16 = transpose(perm = var_1463, x = input_tensor_267_cast_fp16)[name = string("transpose_29")];
            tensor<fp16, [1, 256, 32]> input_tensor_277_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_1_conv_q_Conv_bias_to_fp16, dilations = input_tensor_277_dilations_0, groups = input_tensor_277_groups_0, pad = input_tensor_277_pad_0, pad_type = input_tensor_277_pad_type_0, strides = input_tensor_277_strides_0, weight = text_encoder_attn_encoder_attn_layers_1_conv_q_Conv_weight_to_fp16, x = input_89_cast_fp16)[name = string("input_tensor_277_cast_fp16")];
            string input_tensor_269_pad_type_0 = const()[name = string("input_tensor_269_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_269_strides_0 = const()[name = string("input_tensor_269_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_269_pad_0 = const()[name = string("input_tensor_269_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_269_dilations_0 = const()[name = string("input_tensor_269_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_269_groups_0 = const()[name = string("input_tensor_269_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_1_conv_k_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_k_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12317888)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_1_conv_k_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_k_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12449024)))];
            tensor<fp16, [1, 256, 32]> input_tensor_269_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_1_conv_k_Conv_bias_to_fp16, dilations = input_tensor_269_dilations_0, groups = input_tensor_269_groups_0, pad = input_tensor_269_pad_0, pad_type = input_tensor_269_pad_type_0, strides = input_tensor_269_strides_0, weight = text_encoder_attn_encoder_attn_layers_1_conv_k_Conv_weight_to_fp16, x = input_89_cast_fp16)[name = string("input_tensor_269_cast_fp16")];
            string input_tensor_289_pad_type_0 = const()[name = string("input_tensor_289_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_289_strides_0 = const()[name = string("input_tensor_289_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_289_pad_0 = const()[name = string("input_tensor_289_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_289_dilations_0 = const()[name = string("input_tensor_289_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_289_groups_0 = const()[name = string("input_tensor_289_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_1_conv_v_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_v_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12449600)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_1_conv_v_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_v_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12580736)))];
            tensor<fp16, [1, 256, 32]> input_tensor_289_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_1_conv_v_Conv_bias_to_fp16, dilations = input_tensor_289_dilations_0, groups = input_tensor_289_groups_0, pad = input_tensor_289_pad_0, pad_type = input_tensor_289_pad_type_0, strides = input_tensor_289_strides_0, weight = text_encoder_attn_encoder_attn_layers_1_conv_v_Conv_weight_to_fp16, x = input_89_cast_fp16)[name = string("input_tensor_289_cast_fp16")];
            tensor<int32, [4]> var_1571 = const()[name = string("op_1571"), val = tensor<int32, [4]>([1, 4, 64, 32])];
            tensor<fp16, [1, 4, 64, 32]> input_tensor_285_cast_fp16 = reshape(shape = var_1571, x = input_tensor_277_cast_fp16)[name = string("input_tensor_285_cast_fp16")];
            tensor<int32, [4]> var_1577 = const()[name = string("op_1577"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [4]> var_1603 = const()[name = string("op_1603"), val = tensor<int32, [4]>([1, 4, 64, 32])];
            tensor<fp16, [1, 4, 64, 32]> y_13_cast_fp16 = reshape(shape = var_1603, x = input_tensor_269_cast_fp16)[name = string("y_13_cast_fp16")];
            tensor<int32, [4]> var_1615 = const()[name = string("op_1615"), val = tensor<int32, [4]>([1, 4, 64, 32])];
            tensor<fp16, [1, 4, 64, 32]> input_tensor_291_cast_fp16 = reshape(shape = var_1615, x = input_tensor_289_cast_fp16)[name = string("input_tensor_291_cast_fp16")];
            fp16 _inversed_x_69_y_0_to_fp16 = const()[name = string("_inversed_x_69_y_0_to_fp16"), val = fp16(0x1p-3)];
            tensor<fp16, [1, 4, 32, 64]> first_127_cast_fp16 = transpose(perm = var_1577, x = input_tensor_285_cast_fp16)[name = string("transpose_28")];
            tensor<fp16, [1, 4, 32, 64]> _inversed_x_69_cast_fp16 = mul(x = first_127_cast_fp16, y = _inversed_x_69_y_0_to_fp16)[name = string("_inversed_x_69_cast_fp16")];
            bool first_143_transpose_x_0 = const()[name = string("first_143_transpose_x_0"), val = bool(false)];
            bool first_143_transpose_y_0 = const()[name = string("first_143_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 4, 32, 32]> first_143_cast_fp16 = matmul(transpose_x = first_143_transpose_x_0, transpose_y = first_143_transpose_y_0, x = _inversed_x_69_cast_fp16, y = y_13_cast_fp16)[name = string("first_143_cast_fp16")];
            bool input_tensor_323_transpose_x_0 = const()[name = string("input_tensor_323_transpose_x_0"), val = bool(false)];
            bool input_tensor_323_transpose_y_0 = const()[name = string("input_tensor_323_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 64, 63]> y_15_to_fp16 = const()[name = string("y_15_to_fp16"), val = tensor<fp16, [1, 1, 64, 63]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17822528)))];
            tensor<fp16, [1, 4, 32, 63]> input_tensor_323_cast_fp16 = matmul(transpose_x = input_tensor_323_transpose_x_0, transpose_y = input_tensor_323_transpose_y_0, x = _inversed_x_69_cast_fp16, y = y_15_to_fp16)[name = string("input_tensor_323_cast_fp16")];
            tensor<int32, [8]> input_tensor_345_pad_0 = const()[name = string("input_tensor_345_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 1])];
            string input_tensor_345_mode_0 = const()[name = string("input_tensor_345_mode_0"), val = string("constant")];
            fp16 const_51_to_fp16 = const()[name = string("const_51_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 32, 64]> input_tensor_345_cast_fp16 = pad(constant_val = const_51_to_fp16, mode = input_tensor_345_mode_0, pad = input_tensor_345_pad_0, x = input_tensor_323_cast_fp16)[name = string("input_tensor_345_cast_fp16")];
            tensor<int32, [3]> var_1738 = const()[name = string("op_1738"), val = tensor<int32, [3]>([1, 4, 2048])];
            tensor<fp16, [1, 4, 2048]> input_97_cast_fp16 = reshape(shape = var_1738, x = input_tensor_345_cast_fp16)[name = string("input_97_cast_fp16")];
            tensor<int32, [6]> input_tensor_367_pad_0 = const()[name = string("input_tensor_367_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 0, 31])];
            string input_tensor_367_mode_0 = const()[name = string("input_tensor_367_mode_0"), val = string("constant")];
            fp16 const_52_to_fp16 = const()[name = string("const_52_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 2079]> input_tensor_367_cast_fp16 = pad(constant_val = const_52_to_fp16, mode = input_tensor_367_mode_0, pad = input_tensor_367_pad_0, x = input_97_cast_fp16)[name = string("input_tensor_367_cast_fp16")];
            tensor<int32, [4]> var_1773 = const()[name = string("op_1773"), val = tensor<int32, [4]>([1, 4, 33, 63])];
            tensor<fp16, [1, 4, 33, 63]> x_85_cast_fp16 = reshape(shape = var_1773, x = input_tensor_367_cast_fp16)[name = string("x_85_cast_fp16")];
            tensor<int32, [4]> x_87_begin_0 = const()[name = string("x_87_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> x_87_end_0 = const()[name = string("x_87_end_0"), val = tensor<int32, [4]>([1, 4, 32, 63])];
            tensor<bool, [4]> x_87_end_mask_0 = const()[name = string("x_87_end_mask_0"), val = tensor<bool, [4]>([true, true, false, true])];
            tensor<fp16, [1, 4, 32, 63]> x_87_cast_fp16 = slice_by_index(begin = x_87_begin_0, end = x_87_end_0, end_mask = x_87_end_mask_0, x = x_85_cast_fp16)[name = string("x_87_cast_fp16")];
            tensor<int32, [4]> second_139_begin_0 = const()[name = string("second_139_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 31])];
            tensor<int32, [4]> second_139_end_0 = const()[name = string("second_139_end_0"), val = tensor<int32, [4]>([1, 4, 32, 1])];
            tensor<bool, [4]> second_139_end_mask_0 = const()[name = string("second_139_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 32, 32]> second_139_cast_fp16 = slice_by_index(begin = second_139_begin_0, end = second_139_end_0, end_mask = second_139_end_mask_0, x = x_87_cast_fp16)[name = string("second_139_cast_fp16")];
            tensor<fp16, [1, 4, 32, 32]> y_17_cast_fp16 = add(x = first_143_cast_fp16, y = second_139_cast_fp16)[name = string("y_17_cast_fp16")];
            tensor<fp16, [1, 4, 32, 32]> input_99_cast_fp16 = select(a = text_encoder_attn_encoder_attn_layers_0_Constant_88_value_after_broadcast_to_fp16, b = y_17_cast_fp16, cond = condition_1_after_broadcast)[name = string("input_99_cast_fp16")];
            int32 var_1815 = const()[name = string("op_1815"), val = int32(-1)];
            tensor<fp16, [1, 4, 32, 32]> x_91_cast_fp16 = softmax(axis = var_1815, x = input_99_cast_fp16)[name = string("x_91_cast_fp16")];
            bool first_155_transpose_x_1 = const()[name = string("first_155_transpose_x_1"), val = bool(false)];
            bool first_155_transpose_y_1 = const()[name = string("first_155_transpose_y_1"), val = bool(true)];
            tensor<fp16, [1, 4, 32, 64]> first_155_cast_fp16 = matmul(transpose_x = first_155_transpose_x_1, transpose_y = first_155_transpose_y_1, x = x_91_cast_fp16, y = input_tensor_291_cast_fp16)[name = string("first_155_cast_fp16")];
            tensor<int32, [8]> input_tensor_397_pad_0 = const()[name = string("input_tensor_397_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 31])];
            string input_tensor_397_mode_0 = const()[name = string("input_tensor_397_mode_0"), val = string("constant")];
            fp16 const_59_to_fp16 = const()[name = string("const_59_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 32, 63]> input_tensor_397_cast_fp16 = pad(constant_val = const_59_to_fp16, mode = input_tensor_397_mode_0, pad = input_tensor_397_pad_0, x = x_91_cast_fp16)[name = string("input_tensor_397_cast_fp16")];
            tensor<int32, [3]> var_1889 = const()[name = string("op_1889"), val = tensor<int32, [3]>([1, 4, 2016])];
            tensor<fp16, [1, 4, 2016]> input_101_cast_fp16 = reshape(shape = var_1889, x = input_tensor_397_cast_fp16)[name = string("input_101_cast_fp16")];
            tensor<int32, [6]> input_tensor_415_pad_0 = const()[name = string("input_tensor_415_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 32, 0])];
            string input_tensor_415_mode_0 = const()[name = string("input_tensor_415_mode_0"), val = string("constant")];
            fp16 const_60_to_fp16 = const()[name = string("const_60_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 2048]> input_tensor_415_cast_fp16 = pad(constant_val = const_60_to_fp16, mode = input_tensor_415_mode_0, pad = input_tensor_415_pad_0, x = input_101_cast_fp16)[name = string("input_tensor_415_cast_fp16")];
            tensor<int32, [4]> var_1919 = const()[name = string("op_1919"), val = tensor<int32, [4]>([1, 4, 32, 64])];
            tensor<fp16, [1, 4, 32, 64]> x_101_cast_fp16 = reshape(shape = var_1919, x = input_tensor_415_cast_fp16)[name = string("x_101_cast_fp16")];
            tensor<int32, [4]> x_109_begin_0 = const()[name = string("x_109_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 1])];
            tensor<int32, [4]> x_109_end_0 = const()[name = string("x_109_end_0"), val = tensor<int32, [4]>([1, 4, 32, 1])];
            tensor<bool, [4]> x_109_end_mask_0 = const()[name = string("x_109_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 32, 63]> x_109_cast_fp16 = slice_by_index(begin = x_109_begin_0, end = x_109_end_0, end_mask = x_109_end_mask_0, x = x_101_cast_fp16)[name = string("x_109_cast_fp16")];
            bool second_153_transpose_x_0 = const()[name = string("second_153_transpose_x_0"), val = bool(false)];
            bool second_153_transpose_y_0 = const()[name = string("second_153_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 63, 64]> y_21_to_fp16 = const()[name = string("y_21_to_fp16"), val = tensor<fp16, [1, 1, 63, 64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17830656)))];
            tensor<fp16, [1, 4, 32, 64]> second_153_cast_fp16 = matmul(transpose_x = second_153_transpose_x_0, transpose_y = second_153_transpose_y_0, x = x_109_cast_fp16, y = y_21_to_fp16)[name = string("second_153_cast_fp16")];
            tensor<fp16, [1, 4, 32, 64]> input_tensor_433_cast_fp16 = add(x = first_155_cast_fp16, y = second_153_cast_fp16)[name = string("input_tensor_433_cast_fp16")];
            tensor<int32, [4]> var_1966 = const()[name = string("op_1966"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [3]> var_1985 = const()[name = string("op_1985"), val = tensor<int32, [3]>([1, 256, 32])];
            tensor<fp16, [1, 4, 64, 32]> input_tensor_437_cast_fp16 = transpose(perm = var_1966, x = input_tensor_433_cast_fp16)[name = string("transpose_27")];
            tensor<fp16, [1, 256, 32]> input_105_cast_fp16 = reshape(shape = var_1985, x = input_tensor_437_cast_fp16)[name = string("input_105_cast_fp16")];
            string second_155_pad_type_0 = const()[name = string("second_155_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_155_strides_0 = const()[name = string("second_155_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_155_pad_0 = const()[name = string("second_155_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_155_dilations_0 = const()[name = string("second_155_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_155_groups_0 = const()[name = string("second_155_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_1_conv_o_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_o_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12589376)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_1_conv_o_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_o_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12720512)))];
            tensor<fp16, [1, 256, 32]> second_155_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_1_conv_o_Conv_bias_to_fp16, dilations = second_155_dilations_0, groups = second_155_groups_0, pad = second_155_pad_0, pad_type = second_155_pad_type_0, strides = second_155_strides_0, weight = text_encoder_attn_encoder_attn_layers_1_conv_o_Conv_weight_to_fp16, x = input_105_cast_fp16)[name = string("second_155_cast_fp16")];
            tensor<fp16, [1, 256, 32]> input_tensor_439_cast_fp16 = add(x = input_89_cast_fp16, y = second_155_cast_fp16)[name = string("input_tensor_439_cast_fp16")];
            tensor<int32, [3]> var_2003 = const()[name = string("op_2003"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_441_axes_0 = const()[name = string("input_tensor_441_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_1_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_1_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12721088)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_1_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_1_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12721664)))];
            fp16 var_2006_to_fp16 = const()[name = string("op_2006_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 32, 256]> input_107_cast_fp16 = transpose(perm = var_2003, x = input_tensor_439_cast_fp16)[name = string("transpose_26")];
            tensor<fp16, [1, 32, 256]> input_tensor_441_cast_fp16 = layer_norm(axes = input_tensor_441_axes_0, beta = text_encoder_attn_encoder_norm_layers_1_1_norm_LayerNormalization_bias_to_fp16, epsilon = var_2006_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_1_1_norm_LayerNormalization_weight_to_fp16, x = input_107_cast_fp16)[name = string("input_tensor_441_cast_fp16")];
            tensor<int32, [3]> var_2015 = const()[name = string("op_2015"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 256, 32]> first_157_cast_fp16 = transpose(perm = var_2015, x = input_tensor_441_cast_fp16)[name = string("transpose_25")];
            tensor<fp16, [1, 256, 32]> input_109_cast_fp16 = mul(x = first_157_cast_fp16, y = text_mask)[name = string("input_109_cast_fp16")];
            string input_111_pad_type_0 = const()[name = string("input_111_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_111_strides_0 = const()[name = string("input_111_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_111_pad_0 = const()[name = string("input_111_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_111_dilations_0 = const()[name = string("input_111_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_111_groups_0 = const()[name = string("input_111_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_attn_encoder_ffn_layers_1_conv_1_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_1_conv_1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12722240)))];
            tensor<fp16, [1024]> text_encoder_attn_encoder_ffn_layers_1_conv_1_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_1_conv_1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13246592)))];
            tensor<fp16, [1, 1024, 32]> input_111_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_1_conv_1_Conv_bias_to_fp16, dilations = input_111_dilations_0, groups = input_111_groups_0, pad = input_111_pad_0, pad_type = input_111_pad_type_0, strides = input_111_strides_0, weight = text_encoder_attn_encoder_ffn_layers_1_conv_1_Conv_weight_to_fp16, x = input_109_cast_fp16)[name = string("input_111_cast_fp16")];
            tensor<fp16, [1, 1024, 32]> first_159_cast_fp16 = relu(x = input_111_cast_fp16)[name = string("first_159_cast_fp16")];
            tensor<fp16, [1, 1024, 32]> input_113_cast_fp16 = mul(x = first_159_cast_fp16, y = text_mask)[name = string("input_113_cast_fp16")];
            string first_161_pad_type_0 = const()[name = string("first_161_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_161_strides_0 = const()[name = string("first_161_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_161_pad_0 = const()[name = string("first_161_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_161_dilations_0 = const()[name = string("first_161_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_161_groups_0 = const()[name = string("first_161_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> text_encoder_attn_encoder_ffn_layers_1_conv_2_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_1_conv_2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13248704)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_ffn_layers_1_conv_2_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_1_conv_2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13773056)))];
            tensor<fp16, [1, 256, 32]> first_161_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_1_conv_2_Conv_bias_to_fp16, dilations = first_161_dilations_0, groups = first_161_groups_0, pad = first_161_pad_0, pad_type = first_161_pad_type_0, strides = first_161_strides_0, weight = text_encoder_attn_encoder_ffn_layers_1_conv_2_Conv_weight_to_fp16, x = input_113_cast_fp16)[name = string("first_161_cast_fp16")];
            tensor<fp16, [1, 256, 32]> second_157_cast_fp16 = mul(x = first_161_cast_fp16, y = text_mask)[name = string("second_157_cast_fp16")];
            tensor<fp16, [1, 256, 32]> input_tensor_443_cast_fp16 = add(x = first_157_cast_fp16, y = second_157_cast_fp16)[name = string("input_tensor_443_cast_fp16")];
            tensor<int32, [3]> var_2048 = const()[name = string("op_2048"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_445_axes_0 = const()[name = string("input_tensor_445_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_1_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_1_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13773632)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_1_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_1_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13774208)))];
            fp16 var_2051_to_fp16 = const()[name = string("op_2051_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 32, 256]> input_115_cast_fp16 = transpose(perm = var_2048, x = input_tensor_443_cast_fp16)[name = string("transpose_24")];
            tensor<fp16, [1, 32, 256]> input_tensor_445_cast_fp16 = layer_norm(axes = input_tensor_445_axes_0, beta = text_encoder_attn_encoder_norm_layers_2_1_norm_LayerNormalization_bias_to_fp16, epsilon = var_2051_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_2_1_norm_LayerNormalization_weight_to_fp16, x = input_115_cast_fp16)[name = string("input_tensor_445_cast_fp16")];
            tensor<int32, [3]> var_2060 = const()[name = string("op_2060"), val = tensor<int32, [3]>([0, 2, 1])];
            string input_tensor_455_pad_type_0 = const()[name = string("input_tensor_455_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_455_strides_0 = const()[name = string("input_tensor_455_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_455_pad_0 = const()[name = string("input_tensor_455_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_455_dilations_0 = const()[name = string("input_tensor_455_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_455_groups_0 = const()[name = string("input_tensor_455_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_2_conv_q_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_q_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13774784)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_2_conv_q_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_q_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13905920)))];
            tensor<fp16, [1, 256, 32]> input_117_cast_fp16 = transpose(perm = var_2060, x = input_tensor_445_cast_fp16)[name = string("transpose_23")];
            tensor<fp16, [1, 256, 32]> input_tensor_455_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_2_conv_q_Conv_bias_to_fp16, dilations = input_tensor_455_dilations_0, groups = input_tensor_455_groups_0, pad = input_tensor_455_pad_0, pad_type = input_tensor_455_pad_type_0, strides = input_tensor_455_strides_0, weight = text_encoder_attn_encoder_attn_layers_2_conv_q_Conv_weight_to_fp16, x = input_117_cast_fp16)[name = string("input_tensor_455_cast_fp16")];
            string input_tensor_447_pad_type_0 = const()[name = string("input_tensor_447_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_447_strides_0 = const()[name = string("input_tensor_447_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_447_pad_0 = const()[name = string("input_tensor_447_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_447_dilations_0 = const()[name = string("input_tensor_447_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_447_groups_0 = const()[name = string("input_tensor_447_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_2_conv_k_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_k_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13906496)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_2_conv_k_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_k_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14037632)))];
            tensor<fp16, [1, 256, 32]> input_tensor_447_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_2_conv_k_Conv_bias_to_fp16, dilations = input_tensor_447_dilations_0, groups = input_tensor_447_groups_0, pad = input_tensor_447_pad_0, pad_type = input_tensor_447_pad_type_0, strides = input_tensor_447_strides_0, weight = text_encoder_attn_encoder_attn_layers_2_conv_k_Conv_weight_to_fp16, x = input_117_cast_fp16)[name = string("input_tensor_447_cast_fp16")];
            string input_tensor_467_pad_type_0 = const()[name = string("input_tensor_467_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_467_strides_0 = const()[name = string("input_tensor_467_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_467_pad_0 = const()[name = string("input_tensor_467_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_467_dilations_0 = const()[name = string("input_tensor_467_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_467_groups_0 = const()[name = string("input_tensor_467_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_2_conv_v_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_v_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14038208)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_2_conv_v_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_v_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14169344)))];
            tensor<fp16, [1, 256, 32]> input_tensor_467_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_2_conv_v_Conv_bias_to_fp16, dilations = input_tensor_467_dilations_0, groups = input_tensor_467_groups_0, pad = input_tensor_467_pad_0, pad_type = input_tensor_467_pad_type_0, strides = input_tensor_467_strides_0, weight = text_encoder_attn_encoder_attn_layers_2_conv_v_Conv_weight_to_fp16, x = input_117_cast_fp16)[name = string("input_tensor_467_cast_fp16")];
            tensor<int32, [4]> var_2168 = const()[name = string("op_2168"), val = tensor<int32, [4]>([1, 4, 64, 32])];
            tensor<fp16, [1, 4, 64, 32]> input_tensor_463_cast_fp16 = reshape(shape = var_2168, x = input_tensor_455_cast_fp16)[name = string("input_tensor_463_cast_fp16")];
            tensor<int32, [4]> var_2174 = const()[name = string("op_2174"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [4]> var_2200 = const()[name = string("op_2200"), val = tensor<int32, [4]>([1, 4, 64, 32])];
            tensor<fp16, [1, 4, 64, 32]> y_23_cast_fp16 = reshape(shape = var_2200, x = input_tensor_447_cast_fp16)[name = string("y_23_cast_fp16")];
            tensor<int32, [4]> var_2212 = const()[name = string("op_2212"), val = tensor<int32, [4]>([1, 4, 64, 32])];
            tensor<fp16, [1, 4, 64, 32]> input_tensor_469_cast_fp16 = reshape(shape = var_2212, x = input_tensor_467_cast_fp16)[name = string("input_tensor_469_cast_fp16")];
            fp16 _inversed_x_111_y_0_to_fp16 = const()[name = string("_inversed_x_111_y_0_to_fp16"), val = fp16(0x1p-3)];
            tensor<fp16, [1, 4, 32, 64]> first_163_cast_fp16 = transpose(perm = var_2174, x = input_tensor_463_cast_fp16)[name = string("transpose_22")];
            tensor<fp16, [1, 4, 32, 64]> _inversed_x_111_cast_fp16 = mul(x = first_163_cast_fp16, y = _inversed_x_111_y_0_to_fp16)[name = string("_inversed_x_111_cast_fp16")];
            bool first_179_transpose_x_0 = const()[name = string("first_179_transpose_x_0"), val = bool(false)];
            bool first_179_transpose_y_0 = const()[name = string("first_179_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 4, 32, 32]> first_179_cast_fp16 = matmul(transpose_x = first_179_transpose_x_0, transpose_y = first_179_transpose_y_0, x = _inversed_x_111_cast_fp16, y = y_23_cast_fp16)[name = string("first_179_cast_fp16")];
            bool input_tensor_501_transpose_x_0 = const()[name = string("input_tensor_501_transpose_x_0"), val = bool(false)];
            bool input_tensor_501_transpose_y_0 = const()[name = string("input_tensor_501_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 64, 63]> y_25_to_fp16 = const()[name = string("y_25_to_fp16"), val = tensor<fp16, [1, 1, 64, 63]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17838784)))];
            tensor<fp16, [1, 4, 32, 63]> input_tensor_501_cast_fp16 = matmul(transpose_x = input_tensor_501_transpose_x_0, transpose_y = input_tensor_501_transpose_y_0, x = _inversed_x_111_cast_fp16, y = y_25_to_fp16)[name = string("input_tensor_501_cast_fp16")];
            tensor<int32, [8]> input_tensor_523_pad_0 = const()[name = string("input_tensor_523_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 1])];
            string input_tensor_523_mode_0 = const()[name = string("input_tensor_523_mode_0"), val = string("constant")];
            fp16 const_79_to_fp16 = const()[name = string("const_79_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 32, 64]> input_tensor_523_cast_fp16 = pad(constant_val = const_79_to_fp16, mode = input_tensor_523_mode_0, pad = input_tensor_523_pad_0, x = input_tensor_501_cast_fp16)[name = string("input_tensor_523_cast_fp16")];
            tensor<int32, [3]> var_2335 = const()[name = string("op_2335"), val = tensor<int32, [3]>([1, 4, 2048])];
            tensor<fp16, [1, 4, 2048]> input_125_cast_fp16 = reshape(shape = var_2335, x = input_tensor_523_cast_fp16)[name = string("input_125_cast_fp16")];
            tensor<int32, [6]> input_tensor_545_pad_0 = const()[name = string("input_tensor_545_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 0, 31])];
            string input_tensor_545_mode_0 = const()[name = string("input_tensor_545_mode_0"), val = string("constant")];
            fp16 const_80_to_fp16 = const()[name = string("const_80_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 2079]> input_tensor_545_cast_fp16 = pad(constant_val = const_80_to_fp16, mode = input_tensor_545_mode_0, pad = input_tensor_545_pad_0, x = input_125_cast_fp16)[name = string("input_tensor_545_cast_fp16")];
            tensor<int32, [4]> var_2370 = const()[name = string("op_2370"), val = tensor<int32, [4]>([1, 4, 33, 63])];
            tensor<fp16, [1, 4, 33, 63]> x_127_cast_fp16 = reshape(shape = var_2370, x = input_tensor_545_cast_fp16)[name = string("x_127_cast_fp16")];
            tensor<int32, [4]> x_129_begin_0 = const()[name = string("x_129_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> x_129_end_0 = const()[name = string("x_129_end_0"), val = tensor<int32, [4]>([1, 4, 32, 63])];
            tensor<bool, [4]> x_129_end_mask_0 = const()[name = string("x_129_end_mask_0"), val = tensor<bool, [4]>([true, true, false, true])];
            tensor<fp16, [1, 4, 32, 63]> x_129_cast_fp16 = slice_by_index(begin = x_129_begin_0, end = x_129_end_0, end_mask = x_129_end_mask_0, x = x_127_cast_fp16)[name = string("x_129_cast_fp16")];
            tensor<int32, [4]> second_181_begin_0 = const()[name = string("second_181_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 31])];
            tensor<int32, [4]> second_181_end_0 = const()[name = string("second_181_end_0"), val = tensor<int32, [4]>([1, 4, 32, 1])];
            tensor<bool, [4]> second_181_end_mask_0 = const()[name = string("second_181_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 32, 32]> second_181_cast_fp16 = slice_by_index(begin = second_181_begin_0, end = second_181_end_0, end_mask = second_181_end_mask_0, x = x_129_cast_fp16)[name = string("second_181_cast_fp16")];
            tensor<fp16, [1, 4, 32, 32]> y_27_cast_fp16 = add(x = first_179_cast_fp16, y = second_181_cast_fp16)[name = string("y_27_cast_fp16")];
            tensor<fp16, [1, 4, 32, 32]> input_127_cast_fp16 = select(a = text_encoder_attn_encoder_attn_layers_0_Constant_88_value_after_broadcast_to_fp16, b = y_27_cast_fp16, cond = condition_1_after_broadcast)[name = string("input_127_cast_fp16")];
            int32 var_2412 = const()[name = string("op_2412"), val = int32(-1)];
            tensor<fp16, [1, 4, 32, 32]> x_133_cast_fp16 = softmax(axis = var_2412, x = input_127_cast_fp16)[name = string("x_133_cast_fp16")];
            bool first_191_transpose_x_1 = const()[name = string("first_191_transpose_x_1"), val = bool(false)];
            bool first_191_transpose_y_1 = const()[name = string("first_191_transpose_y_1"), val = bool(true)];
            tensor<fp16, [1, 4, 32, 64]> first_191_cast_fp16 = matmul(transpose_x = first_191_transpose_x_1, transpose_y = first_191_transpose_y_1, x = x_133_cast_fp16, y = input_tensor_469_cast_fp16)[name = string("first_191_cast_fp16")];
            tensor<int32, [8]> input_tensor_575_pad_0 = const()[name = string("input_tensor_575_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 31])];
            string input_tensor_575_mode_0 = const()[name = string("input_tensor_575_mode_0"), val = string("constant")];
            fp16 const_87_to_fp16 = const()[name = string("const_87_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 32, 63]> input_tensor_575_cast_fp16 = pad(constant_val = const_87_to_fp16, mode = input_tensor_575_mode_0, pad = input_tensor_575_pad_0, x = x_133_cast_fp16)[name = string("input_tensor_575_cast_fp16")];
            tensor<int32, [3]> var_2486 = const()[name = string("op_2486"), val = tensor<int32, [3]>([1, 4, 2016])];
            tensor<fp16, [1, 4, 2016]> input_129_cast_fp16 = reshape(shape = var_2486, x = input_tensor_575_cast_fp16)[name = string("input_129_cast_fp16")];
            tensor<int32, [6]> input_tensor_593_pad_0 = const()[name = string("input_tensor_593_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 32, 0])];
            string input_tensor_593_mode_0 = const()[name = string("input_tensor_593_mode_0"), val = string("constant")];
            fp16 const_88_to_fp16 = const()[name = string("const_88_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 2048]> input_tensor_593_cast_fp16 = pad(constant_val = const_88_to_fp16, mode = input_tensor_593_mode_0, pad = input_tensor_593_pad_0, x = input_129_cast_fp16)[name = string("input_tensor_593_cast_fp16")];
            tensor<int32, [4]> var_2516 = const()[name = string("op_2516"), val = tensor<int32, [4]>([1, 4, 32, 64])];
            tensor<fp16, [1, 4, 32, 64]> x_143_cast_fp16 = reshape(shape = var_2516, x = input_tensor_593_cast_fp16)[name = string("x_143_cast_fp16")];
            tensor<int32, [4]> x_151_begin_0 = const()[name = string("x_151_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 1])];
            tensor<int32, [4]> x_151_end_0 = const()[name = string("x_151_end_0"), val = tensor<int32, [4]>([1, 4, 32, 1])];
            tensor<bool, [4]> x_151_end_mask_0 = const()[name = string("x_151_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 32, 63]> x_151_cast_fp16 = slice_by_index(begin = x_151_begin_0, end = x_151_end_0, end_mask = x_151_end_mask_0, x = x_143_cast_fp16)[name = string("x_151_cast_fp16")];
            bool second_195_transpose_x_0 = const()[name = string("second_195_transpose_x_0"), val = bool(false)];
            bool second_195_transpose_y_0 = const()[name = string("second_195_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 63, 64]> y_31_to_fp16 = const()[name = string("y_31_to_fp16"), val = tensor<fp16, [1, 1, 63, 64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17846912)))];
            tensor<fp16, [1, 4, 32, 64]> second_195_cast_fp16 = matmul(transpose_x = second_195_transpose_x_0, transpose_y = second_195_transpose_y_0, x = x_151_cast_fp16, y = y_31_to_fp16)[name = string("second_195_cast_fp16")];
            tensor<fp16, [1, 4, 32, 64]> input_tensor_611_cast_fp16 = add(x = first_191_cast_fp16, y = second_195_cast_fp16)[name = string("input_tensor_611_cast_fp16")];
            tensor<int32, [4]> var_2563 = const()[name = string("op_2563"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [3]> var_2582 = const()[name = string("op_2582"), val = tensor<int32, [3]>([1, 256, 32])];
            tensor<fp16, [1, 4, 64, 32]> input_tensor_615_cast_fp16 = transpose(perm = var_2563, x = input_tensor_611_cast_fp16)[name = string("transpose_21")];
            tensor<fp16, [1, 256, 32]> input_133_cast_fp16 = reshape(shape = var_2582, x = input_tensor_615_cast_fp16)[name = string("input_133_cast_fp16")];
            string second_197_pad_type_0 = const()[name = string("second_197_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_197_strides_0 = const()[name = string("second_197_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_197_pad_0 = const()[name = string("second_197_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_197_dilations_0 = const()[name = string("second_197_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_197_groups_0 = const()[name = string("second_197_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_2_conv_o_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_o_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14177984)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_2_conv_o_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_o_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14309120)))];
            tensor<fp16, [1, 256, 32]> second_197_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_2_conv_o_Conv_bias_to_fp16, dilations = second_197_dilations_0, groups = second_197_groups_0, pad = second_197_pad_0, pad_type = second_197_pad_type_0, strides = second_197_strides_0, weight = text_encoder_attn_encoder_attn_layers_2_conv_o_Conv_weight_to_fp16, x = input_133_cast_fp16)[name = string("second_197_cast_fp16")];
            tensor<fp16, [1, 256, 32]> input_tensor_617_cast_fp16 = add(x = input_117_cast_fp16, y = second_197_cast_fp16)[name = string("input_tensor_617_cast_fp16")];
            tensor<int32, [3]> var_2600 = const()[name = string("op_2600"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_619_axes_0 = const()[name = string("input_tensor_619_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_2_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_2_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14309696)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_2_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_2_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14310272)))];
            fp16 var_2603_to_fp16 = const()[name = string("op_2603_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 32, 256]> input_135_cast_fp16 = transpose(perm = var_2600, x = input_tensor_617_cast_fp16)[name = string("transpose_20")];
            tensor<fp16, [1, 32, 256]> input_tensor_619_cast_fp16 = layer_norm(axes = input_tensor_619_axes_0, beta = text_encoder_attn_encoder_norm_layers_1_2_norm_LayerNormalization_bias_to_fp16, epsilon = var_2603_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_1_2_norm_LayerNormalization_weight_to_fp16, x = input_135_cast_fp16)[name = string("input_tensor_619_cast_fp16")];
            tensor<int32, [3]> var_2612 = const()[name = string("op_2612"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 256, 32]> first_193_cast_fp16 = transpose(perm = var_2612, x = input_tensor_619_cast_fp16)[name = string("transpose_19")];
            tensor<fp16, [1, 256, 32]> input_137_cast_fp16 = mul(x = first_193_cast_fp16, y = text_mask)[name = string("input_137_cast_fp16")];
            string input_139_pad_type_0 = const()[name = string("input_139_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_139_strides_0 = const()[name = string("input_139_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_139_pad_0 = const()[name = string("input_139_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_139_dilations_0 = const()[name = string("input_139_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_139_groups_0 = const()[name = string("input_139_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_attn_encoder_ffn_layers_2_conv_1_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_2_conv_1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14310848)))];
            tensor<fp16, [1024]> text_encoder_attn_encoder_ffn_layers_2_conv_1_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_2_conv_1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14835200)))];
            tensor<fp16, [1, 1024, 32]> input_139_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_2_conv_1_Conv_bias_to_fp16, dilations = input_139_dilations_0, groups = input_139_groups_0, pad = input_139_pad_0, pad_type = input_139_pad_type_0, strides = input_139_strides_0, weight = text_encoder_attn_encoder_ffn_layers_2_conv_1_Conv_weight_to_fp16, x = input_137_cast_fp16)[name = string("input_139_cast_fp16")];
            tensor<fp16, [1, 1024, 32]> first_195_cast_fp16 = relu(x = input_139_cast_fp16)[name = string("first_195_cast_fp16")];
            tensor<fp16, [1, 1024, 32]> input_141_cast_fp16 = mul(x = first_195_cast_fp16, y = text_mask)[name = string("input_141_cast_fp16")];
            string first_197_pad_type_0 = const()[name = string("first_197_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_197_strides_0 = const()[name = string("first_197_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_197_pad_0 = const()[name = string("first_197_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_197_dilations_0 = const()[name = string("first_197_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_197_groups_0 = const()[name = string("first_197_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> text_encoder_attn_encoder_ffn_layers_2_conv_2_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_2_conv_2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14837312)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_ffn_layers_2_conv_2_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_2_conv_2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15361664)))];
            tensor<fp16, [1, 256, 32]> first_197_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_2_conv_2_Conv_bias_to_fp16, dilations = first_197_dilations_0, groups = first_197_groups_0, pad = first_197_pad_0, pad_type = first_197_pad_type_0, strides = first_197_strides_0, weight = text_encoder_attn_encoder_ffn_layers_2_conv_2_Conv_weight_to_fp16, x = input_141_cast_fp16)[name = string("first_197_cast_fp16")];
            tensor<fp16, [1, 256, 32]> second_199_cast_fp16 = mul(x = first_197_cast_fp16, y = text_mask)[name = string("second_199_cast_fp16")];
            tensor<fp16, [1, 256, 32]> input_tensor_621_cast_fp16 = add(x = first_193_cast_fp16, y = second_199_cast_fp16)[name = string("input_tensor_621_cast_fp16")];
            tensor<int32, [3]> var_2645 = const()[name = string("op_2645"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_623_axes_0 = const()[name = string("input_tensor_623_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_2_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_2_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15362240)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_2_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_2_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15362816)))];
            fp16 var_2648_to_fp16 = const()[name = string("op_2648_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 32, 256]> input_143_cast_fp16 = transpose(perm = var_2645, x = input_tensor_621_cast_fp16)[name = string("transpose_18")];
            tensor<fp16, [1, 32, 256]> input_tensor_623_cast_fp16 = layer_norm(axes = input_tensor_623_axes_0, beta = text_encoder_attn_encoder_norm_layers_2_2_norm_LayerNormalization_bias_to_fp16, epsilon = var_2648_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_2_2_norm_LayerNormalization_weight_to_fp16, x = input_143_cast_fp16)[name = string("input_tensor_623_cast_fp16")];
            tensor<int32, [3]> var_2657 = const()[name = string("op_2657"), val = tensor<int32, [3]>([0, 2, 1])];
            string input_tensor_633_pad_type_0 = const()[name = string("input_tensor_633_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_633_strides_0 = const()[name = string("input_tensor_633_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_633_pad_0 = const()[name = string("input_tensor_633_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_633_dilations_0 = const()[name = string("input_tensor_633_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_633_groups_0 = const()[name = string("input_tensor_633_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_3_conv_q_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_q_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15363392)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_3_conv_q_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_q_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15494528)))];
            tensor<fp16, [1, 256, 32]> input_145_cast_fp16 = transpose(perm = var_2657, x = input_tensor_623_cast_fp16)[name = string("transpose_17")];
            tensor<fp16, [1, 256, 32]> input_tensor_633_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_3_conv_q_Conv_bias_to_fp16, dilations = input_tensor_633_dilations_0, groups = input_tensor_633_groups_0, pad = input_tensor_633_pad_0, pad_type = input_tensor_633_pad_type_0, strides = input_tensor_633_strides_0, weight = text_encoder_attn_encoder_attn_layers_3_conv_q_Conv_weight_to_fp16, x = input_145_cast_fp16)[name = string("input_tensor_633_cast_fp16")];
            string input_tensor_625_pad_type_0 = const()[name = string("input_tensor_625_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_625_strides_0 = const()[name = string("input_tensor_625_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_625_pad_0 = const()[name = string("input_tensor_625_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_625_dilations_0 = const()[name = string("input_tensor_625_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_625_groups_0 = const()[name = string("input_tensor_625_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_3_conv_k_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_k_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15495104)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_3_conv_k_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_k_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15626240)))];
            tensor<fp16, [1, 256, 32]> input_tensor_625_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_3_conv_k_Conv_bias_to_fp16, dilations = input_tensor_625_dilations_0, groups = input_tensor_625_groups_0, pad = input_tensor_625_pad_0, pad_type = input_tensor_625_pad_type_0, strides = input_tensor_625_strides_0, weight = text_encoder_attn_encoder_attn_layers_3_conv_k_Conv_weight_to_fp16, x = input_145_cast_fp16)[name = string("input_tensor_625_cast_fp16")];
            string input_tensor_645_pad_type_0 = const()[name = string("input_tensor_645_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_645_strides_0 = const()[name = string("input_tensor_645_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_645_pad_0 = const()[name = string("input_tensor_645_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_645_dilations_0 = const()[name = string("input_tensor_645_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_645_groups_0 = const()[name = string("input_tensor_645_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_3_conv_v_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_v_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15626816)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_3_conv_v_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_v_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15757952)))];
            tensor<fp16, [1, 256, 32]> input_tensor_645_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_3_conv_v_Conv_bias_to_fp16, dilations = input_tensor_645_dilations_0, groups = input_tensor_645_groups_0, pad = input_tensor_645_pad_0, pad_type = input_tensor_645_pad_type_0, strides = input_tensor_645_strides_0, weight = text_encoder_attn_encoder_attn_layers_3_conv_v_Conv_weight_to_fp16, x = input_145_cast_fp16)[name = string("input_tensor_645_cast_fp16")];
            tensor<int32, [4]> var_2765 = const()[name = string("op_2765"), val = tensor<int32, [4]>([1, 4, 64, 32])];
            tensor<fp16, [1, 4, 64, 32]> input_tensor_641_cast_fp16 = reshape(shape = var_2765, x = input_tensor_633_cast_fp16)[name = string("input_tensor_641_cast_fp16")];
            tensor<int32, [4]> var_2771 = const()[name = string("op_2771"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [4]> var_2797 = const()[name = string("op_2797"), val = tensor<int32, [4]>([1, 4, 64, 32])];
            tensor<fp16, [1, 4, 64, 32]> y_33_cast_fp16 = reshape(shape = var_2797, x = input_tensor_625_cast_fp16)[name = string("y_33_cast_fp16")];
            tensor<int32, [4]> var_2809 = const()[name = string("op_2809"), val = tensor<int32, [4]>([1, 4, 64, 32])];
            tensor<fp16, [1, 4, 64, 32]> input_tensor_647_cast_fp16 = reshape(shape = var_2809, x = input_tensor_645_cast_fp16)[name = string("input_tensor_647_cast_fp16")];
            fp16 _inversed_x_153_y_0_to_fp16 = const()[name = string("_inversed_x_153_y_0_to_fp16"), val = fp16(0x1p-3)];
            tensor<fp16, [1, 4, 32, 64]> first_199_cast_fp16 = transpose(perm = var_2771, x = input_tensor_641_cast_fp16)[name = string("transpose_16")];
            tensor<fp16, [1, 4, 32, 64]> _inversed_x_153_cast_fp16 = mul(x = first_199_cast_fp16, y = _inversed_x_153_y_0_to_fp16)[name = string("_inversed_x_153_cast_fp16")];
            bool first_215_transpose_x_0 = const()[name = string("first_215_transpose_x_0"), val = bool(false)];
            bool first_215_transpose_y_0 = const()[name = string("first_215_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 4, 32, 32]> first_215_cast_fp16 = matmul(transpose_x = first_215_transpose_x_0, transpose_y = first_215_transpose_y_0, x = _inversed_x_153_cast_fp16, y = y_33_cast_fp16)[name = string("first_215_cast_fp16")];
            bool input_tensor_679_transpose_x_0 = const()[name = string("input_tensor_679_transpose_x_0"), val = bool(false)];
            bool input_tensor_679_transpose_y_0 = const()[name = string("input_tensor_679_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 64, 63]> y_35_to_fp16 = const()[name = string("y_35_to_fp16"), val = tensor<fp16, [1, 1, 64, 63]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17855040)))];
            tensor<fp16, [1, 4, 32, 63]> input_tensor_679_cast_fp16 = matmul(transpose_x = input_tensor_679_transpose_x_0, transpose_y = input_tensor_679_transpose_y_0, x = _inversed_x_153_cast_fp16, y = y_35_to_fp16)[name = string("input_tensor_679_cast_fp16")];
            tensor<int32, [8]> input_tensor_701_pad_0 = const()[name = string("input_tensor_701_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 1])];
            string input_tensor_701_mode_0 = const()[name = string("input_tensor_701_mode_0"), val = string("constant")];
            fp16 const_107_to_fp16 = const()[name = string("const_107_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 32, 64]> input_tensor_701_cast_fp16 = pad(constant_val = const_107_to_fp16, mode = input_tensor_701_mode_0, pad = input_tensor_701_pad_0, x = input_tensor_679_cast_fp16)[name = string("input_tensor_701_cast_fp16")];
            tensor<int32, [3]> var_2932 = const()[name = string("op_2932"), val = tensor<int32, [3]>([1, 4, 2048])];
            tensor<fp16, [1, 4, 2048]> input_153_cast_fp16 = reshape(shape = var_2932, x = input_tensor_701_cast_fp16)[name = string("input_153_cast_fp16")];
            tensor<int32, [6]> input_tensor_723_pad_0 = const()[name = string("input_tensor_723_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 0, 31])];
            string input_tensor_723_mode_0 = const()[name = string("input_tensor_723_mode_0"), val = string("constant")];
            fp16 const_108_to_fp16 = const()[name = string("const_108_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 2079]> input_tensor_723_cast_fp16 = pad(constant_val = const_108_to_fp16, mode = input_tensor_723_mode_0, pad = input_tensor_723_pad_0, x = input_153_cast_fp16)[name = string("input_tensor_723_cast_fp16")];
            tensor<int32, [4]> var_2967 = const()[name = string("op_2967"), val = tensor<int32, [4]>([1, 4, 33, 63])];
            tensor<fp16, [1, 4, 33, 63]> x_169_cast_fp16 = reshape(shape = var_2967, x = input_tensor_723_cast_fp16)[name = string("x_169_cast_fp16")];
            tensor<int32, [4]> x_171_begin_0 = const()[name = string("x_171_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> x_171_end_0 = const()[name = string("x_171_end_0"), val = tensor<int32, [4]>([1, 4, 32, 63])];
            tensor<bool, [4]> x_171_end_mask_0 = const()[name = string("x_171_end_mask_0"), val = tensor<bool, [4]>([true, true, false, true])];
            tensor<fp16, [1, 4, 32, 63]> x_171_cast_fp16 = slice_by_index(begin = x_171_begin_0, end = x_171_end_0, end_mask = x_171_end_mask_0, x = x_169_cast_fp16)[name = string("x_171_cast_fp16")];
            tensor<int32, [4]> second_223_begin_0 = const()[name = string("second_223_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 31])];
            tensor<int32, [4]> second_223_end_0 = const()[name = string("second_223_end_0"), val = tensor<int32, [4]>([1, 4, 32, 1])];
            tensor<bool, [4]> second_223_end_mask_0 = const()[name = string("second_223_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 32, 32]> second_223_cast_fp16 = slice_by_index(begin = second_223_begin_0, end = second_223_end_0, end_mask = second_223_end_mask_0, x = x_171_cast_fp16)[name = string("second_223_cast_fp16")];
            tensor<fp16, [1, 4, 32, 32]> y_37_cast_fp16 = add(x = first_215_cast_fp16, y = second_223_cast_fp16)[name = string("y_37_cast_fp16")];
            tensor<fp16, [1, 4, 32, 32]> input_155_cast_fp16 = select(a = text_encoder_attn_encoder_attn_layers_0_Constant_88_value_after_broadcast_to_fp16, b = y_37_cast_fp16, cond = condition_1_after_broadcast)[name = string("input_155_cast_fp16")];
            int32 var_3009 = const()[name = string("op_3009"), val = int32(-1)];
            tensor<fp16, [1, 4, 32, 32]> x_175_cast_fp16 = softmax(axis = var_3009, x = input_155_cast_fp16)[name = string("x_175_cast_fp16")];
            bool first_227_transpose_x_1 = const()[name = string("first_227_transpose_x_1"), val = bool(false)];
            bool first_227_transpose_y_1 = const()[name = string("first_227_transpose_y_1"), val = bool(true)];
            tensor<fp16, [1, 4, 32, 64]> first_227_cast_fp16 = matmul(transpose_x = first_227_transpose_x_1, transpose_y = first_227_transpose_y_1, x = x_175_cast_fp16, y = input_tensor_647_cast_fp16)[name = string("first_227_cast_fp16")];
            tensor<int32, [8]> input_tensor_753_pad_0 = const()[name = string("input_tensor_753_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 31])];
            string input_tensor_753_mode_0 = const()[name = string("input_tensor_753_mode_0"), val = string("constant")];
            fp16 const_115_to_fp16 = const()[name = string("const_115_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 32, 63]> input_tensor_753_cast_fp16 = pad(constant_val = const_115_to_fp16, mode = input_tensor_753_mode_0, pad = input_tensor_753_pad_0, x = x_175_cast_fp16)[name = string("input_tensor_753_cast_fp16")];
            tensor<int32, [3]> var_3083 = const()[name = string("op_3083"), val = tensor<int32, [3]>([1, 4, 2016])];
            tensor<fp16, [1, 4, 2016]> input_157_cast_fp16 = reshape(shape = var_3083, x = input_tensor_753_cast_fp16)[name = string("input_157_cast_fp16")];
            tensor<int32, [6]> input_tensor_771_pad_0 = const()[name = string("input_tensor_771_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 32, 0])];
            string input_tensor_771_mode_0 = const()[name = string("input_tensor_771_mode_0"), val = string("constant")];
            fp16 const_116_to_fp16 = const()[name = string("const_116_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 2048]> input_tensor_771_cast_fp16 = pad(constant_val = const_116_to_fp16, mode = input_tensor_771_mode_0, pad = input_tensor_771_pad_0, x = input_157_cast_fp16)[name = string("input_tensor_771_cast_fp16")];
            tensor<int32, [4]> var_3113 = const()[name = string("op_3113"), val = tensor<int32, [4]>([1, 4, 32, 64])];
            tensor<fp16, [1, 4, 32, 64]> x_185_cast_fp16 = reshape(shape = var_3113, x = input_tensor_771_cast_fp16)[name = string("x_185_cast_fp16")];
            tensor<int32, [4]> x_193_begin_0 = const()[name = string("x_193_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 1])];
            tensor<int32, [4]> x_193_end_0 = const()[name = string("x_193_end_0"), val = tensor<int32, [4]>([1, 4, 32, 1])];
            tensor<bool, [4]> x_193_end_mask_0 = const()[name = string("x_193_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 32, 63]> x_193_cast_fp16 = slice_by_index(begin = x_193_begin_0, end = x_193_end_0, end_mask = x_193_end_mask_0, x = x_185_cast_fp16)[name = string("x_193_cast_fp16")];
            bool second_237_transpose_x_0 = const()[name = string("second_237_transpose_x_0"), val = bool(false)];
            bool second_237_transpose_y_0 = const()[name = string("second_237_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 63, 64]> y_41_to_fp16 = const()[name = string("y_41_to_fp16"), val = tensor<fp16, [1, 1, 63, 64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17863168)))];
            tensor<fp16, [1, 4, 32, 64]> second_237_cast_fp16 = matmul(transpose_x = second_237_transpose_x_0, transpose_y = second_237_transpose_y_0, x = x_193_cast_fp16, y = y_41_to_fp16)[name = string("second_237_cast_fp16")];
            tensor<fp16, [1, 4, 32, 64]> input_tensor_789_cast_fp16 = add(x = first_227_cast_fp16, y = second_237_cast_fp16)[name = string("input_tensor_789_cast_fp16")];
            tensor<int32, [4]> var_3160 = const()[name = string("op_3160"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [3]> var_3179 = const()[name = string("op_3179"), val = tensor<int32, [3]>([1, 256, 32])];
            tensor<fp16, [1, 4, 64, 32]> input_tensor_793_cast_fp16 = transpose(perm = var_3160, x = input_tensor_789_cast_fp16)[name = string("transpose_15")];
            tensor<fp16, [1, 256, 32]> input_161_cast_fp16 = reshape(shape = var_3179, x = input_tensor_793_cast_fp16)[name = string("input_161_cast_fp16")];
            string second_239_pad_type_0 = const()[name = string("second_239_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_239_strides_0 = const()[name = string("second_239_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_239_pad_0 = const()[name = string("second_239_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_239_dilations_0 = const()[name = string("second_239_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_239_groups_0 = const()[name = string("second_239_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_3_conv_o_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_o_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15766592)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_3_conv_o_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_o_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15897728)))];
            tensor<fp16, [1, 256, 32]> second_239_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_3_conv_o_Conv_bias_to_fp16, dilations = second_239_dilations_0, groups = second_239_groups_0, pad = second_239_pad_0, pad_type = second_239_pad_type_0, strides = second_239_strides_0, weight = text_encoder_attn_encoder_attn_layers_3_conv_o_Conv_weight_to_fp16, x = input_161_cast_fp16)[name = string("second_239_cast_fp16")];
            tensor<fp16, [1, 256, 32]> input_tensor_795_cast_fp16 = add(x = input_145_cast_fp16, y = second_239_cast_fp16)[name = string("input_tensor_795_cast_fp16")];
            tensor<int32, [3]> var_3197 = const()[name = string("op_3197"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_797_axes_0 = const()[name = string("input_tensor_797_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_3_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_3_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15898304)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_3_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_3_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15898880)))];
            fp16 var_3200_to_fp16 = const()[name = string("op_3200_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 32, 256]> input_163_cast_fp16 = transpose(perm = var_3197, x = input_tensor_795_cast_fp16)[name = string("transpose_14")];
            tensor<fp16, [1, 32, 256]> input_tensor_797_cast_fp16 = layer_norm(axes = input_tensor_797_axes_0, beta = text_encoder_attn_encoder_norm_layers_1_3_norm_LayerNormalization_bias_to_fp16, epsilon = var_3200_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_1_3_norm_LayerNormalization_weight_to_fp16, x = input_163_cast_fp16)[name = string("input_tensor_797_cast_fp16")];
            tensor<int32, [3]> var_3209 = const()[name = string("op_3209"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 256, 32]> first_229_cast_fp16 = transpose(perm = var_3209, x = input_tensor_797_cast_fp16)[name = string("transpose_13")];
            tensor<fp16, [1, 256, 32]> input_165_cast_fp16 = mul(x = first_229_cast_fp16, y = text_mask)[name = string("input_165_cast_fp16")];
            string input_167_pad_type_0 = const()[name = string("input_167_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_167_strides_0 = const()[name = string("input_167_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_167_pad_0 = const()[name = string("input_167_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_167_dilations_0 = const()[name = string("input_167_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_167_groups_0 = const()[name = string("input_167_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_attn_encoder_ffn_layers_3_conv_1_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_3_conv_1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15899456)))];
            tensor<fp16, [1024]> text_encoder_attn_encoder_ffn_layers_3_conv_1_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_3_conv_1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16423808)))];
            tensor<fp16, [1, 1024, 32]> input_167_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_3_conv_1_Conv_bias_to_fp16, dilations = input_167_dilations_0, groups = input_167_groups_0, pad = input_167_pad_0, pad_type = input_167_pad_type_0, strides = input_167_strides_0, weight = text_encoder_attn_encoder_ffn_layers_3_conv_1_Conv_weight_to_fp16, x = input_165_cast_fp16)[name = string("input_167_cast_fp16")];
            tensor<fp16, [1, 1024, 32]> first_231_cast_fp16 = relu(x = input_167_cast_fp16)[name = string("first_231_cast_fp16")];
            tensor<fp16, [1, 1024, 32]> input_169_cast_fp16 = mul(x = first_231_cast_fp16, y = text_mask)[name = string("input_169_cast_fp16")];
            string first_233_pad_type_0 = const()[name = string("first_233_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_233_strides_0 = const()[name = string("first_233_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_233_pad_0 = const()[name = string("first_233_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_233_dilations_0 = const()[name = string("first_233_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_233_groups_0 = const()[name = string("first_233_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> text_encoder_attn_encoder_ffn_layers_3_conv_2_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_3_conv_2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16425920)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_ffn_layers_3_conv_2_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_3_conv_2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16950272)))];
            tensor<fp16, [1, 256, 32]> first_233_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_3_conv_2_Conv_bias_to_fp16, dilations = first_233_dilations_0, groups = first_233_groups_0, pad = first_233_pad_0, pad_type = first_233_pad_type_0, strides = first_233_strides_0, weight = text_encoder_attn_encoder_ffn_layers_3_conv_2_Conv_weight_to_fp16, x = input_169_cast_fp16)[name = string("first_233_cast_fp16")];
            tensor<fp16, [1, 256, 32]> second_241_cast_fp16 = mul(x = first_233_cast_fp16, y = text_mask)[name = string("second_241_cast_fp16")];
            tensor<fp16, [1, 256, 32]> input_tensor_799_cast_fp16 = add(x = first_229_cast_fp16, y = second_241_cast_fp16)[name = string("input_tensor_799_cast_fp16")];
            tensor<int32, [3]> var_3242 = const()[name = string("op_3242"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_801_axes_0 = const()[name = string("input_tensor_801_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_3_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_3_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16950848)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_3_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_3_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16951424)))];
            fp16 var_3245_to_fp16 = const()[name = string("op_3245_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 32, 256]> input_171_cast_fp16 = transpose(perm = var_3242, x = input_tensor_799_cast_fp16)[name = string("transpose_12")];
            tensor<fp16, [1, 32, 256]> input_tensor_801_cast_fp16 = layer_norm(axes = input_tensor_801_axes_0, beta = text_encoder_attn_encoder_norm_layers_2_3_norm_LayerNormalization_bias_to_fp16, epsilon = var_3245_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_2_3_norm_LayerNormalization_weight_to_fp16, x = input_171_cast_fp16)[name = string("input_tensor_801_cast_fp16")];
            tensor<int32, [3]> var_3254 = const()[name = string("op_3254"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 256, 32]> first_235_cast_fp16 = transpose(perm = var_3254, x = input_tensor_801_cast_fp16)[name = string("transpose_11")];
            tensor<fp16, [1, 256, 32]> first_237_cast_fp16 = mul(x = first_235_cast_fp16, y = text_mask)[name = string("first_237_cast_fp16")];
            tensor<fp16, [1, 256, 32]> first_239_cast_fp16 = add(x = first_237_cast_fp16, y = first_89_cast_fp16)[name = string("first_239_cast_fp16")];
            tensor<fp16, [1, 256, 32]> input_tensor_807_cast_fp16 = mul(x = first_239_cast_fp16, y = text_mask)[name = string("input_tensor_807_cast_fp16")];
            tensor<int32, [3]> var_3299 = const()[name = string("op_3299"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [3]> var_3304 = const()[name = string("op_3304"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [256, 256]> var_3308_weight_0_to_fp16 = const()[name = string("op_3308_weight_0_to_fp16"), val = tensor<fp16, [256, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16952000)))];
            tensor<fp16, [256]> var_3308_bias_0_to_fp16 = const()[name = string("op_3308_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17083136)))];
            tensor<fp16, [1, 32, 256]> x_195_cast_fp16 = transpose(perm = var_3299, x = input_tensor_807_cast_fp16)[name = string("transpose_10")];
            tensor<fp16, [1, 32, 256]> var_3308_cast_fp16 = linear(bias = var_3308_bias_0_to_fp16, weight = var_3308_weight_0_to_fp16, x = x_195_cast_fp16)[name = string("op_3308_cast_fp16")];
            tensor<fp16, [256, 256]> var_3314_weight_0_to_fp16 = const()[name = string("op_3314_weight_0_to_fp16"), val = tensor<fp16, [256, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17083712)))];
            tensor<fp16, [256]> var_3314_bias_0_to_fp16 = const()[name = string("op_3314_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17214848)))];
            tensor<fp16, [1, 50, 256]> var_3314_cast_fp16 = linear(bias = var_3314_bias_0_to_fp16, weight = var_3314_weight_0_to_fp16, x = style_ttl)[name = string("op_3314_cast_fp16")];
            tensor<int32, [2]> var_3317 = const()[name = string("op_3317"), val = tensor<int32, [2]>([128, 128])];
            int32 var_3318_axis_0 = const()[name = string("op_3318_axis_0"), val = int32(2)];
            tensor<fp16, [1, 32, 128]> var_3318_cast_fp16_0, tensor<fp16, [1, 32, 128]> var_3318_cast_fp16_1 = split(axis = var_3318_axis_0, split_sizes = var_3317, x = var_3308_cast_fp16)[name = string("op_3318_cast_fp16")];
            tensor<int32, [1]> var_3325_axes_0 = const()[name = string("op_3325_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 32, 128]> var_3325_cast_fp16 = expand_dims(axes = var_3325_axes_0, x = var_3318_cast_fp16_0)[name = string("op_3325_cast_fp16")];
            tensor<int32, [1]> var_3327_axes_0 = const()[name = string("op_3327_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 32, 128]> var_3327_cast_fp16 = expand_dims(axes = var_3327_axes_0, x = var_3318_cast_fp16_1)[name = string("op_3327_cast_fp16")];
            int32 var_3328 = const()[name = string("op_3328"), val = int32(0)];
            bool x_199_interleave_0 = const()[name = string("x_199_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 1, 32, 128]> x_199_cast_fp16 = concat(axis = var_3328, interleave = x_199_interleave_0, values = (var_3325_cast_fp16, var_3327_cast_fp16))[name = string("x_199_cast_fp16")];
            tensor<int32, [2]> var_3349 = const()[name = string("op_3349"), val = tensor<int32, [2]>([128, 128])];
            int32 var_3350_axis_0 = const()[name = string("op_3350_axis_0"), val = int32(2)];
            tensor<fp16, [1, 50, 128]> var_3350_cast_fp16_0, tensor<fp16, [1, 50, 128]> var_3350_cast_fp16_1 = split(axis = var_3350_axis_0, split_sizes = var_3349, x = var_3314_cast_fp16)[name = string("op_3350_cast_fp16")];
            tensor<int32, [1]> var_3357_axes_0 = const()[name = string("op_3357_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 50, 128]> var_3357_cast_fp16 = expand_dims(axes = var_3357_axes_0, x = var_3350_cast_fp16_0)[name = string("op_3357_cast_fp16")];
            tensor<int32, [1]> var_3359_axes_0 = const()[name = string("op_3359_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 50, 128]> var_3359_cast_fp16 = expand_dims(axes = var_3359_axes_0, x = var_3350_cast_fp16_1)[name = string("op_3359_cast_fp16")];
            int32 var_3360 = const()[name = string("op_3360"), val = int32(0)];
            bool y_55_interleave_0 = const()[name = string("y_55_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 1, 50, 128]> y_55_cast_fp16 = concat(axis = var_3360, interleave = y_55_interleave_0, values = (var_3357_cast_fp16, var_3359_cast_fp16))[name = string("y_55_cast_fp16")];
            bool first_247_transpose_x_0 = const()[name = string("first_247_transpose_x_0"), val = bool(false)];
            bool first_247_transpose_y_0 = const()[name = string("first_247_transpose_y_0"), val = bool(false)];
            tensor<fp16, [2, 1, 128, 50]> y_49_to_fp16 = const()[name = string("y_49_to_fp16"), val = tensor<fp16, [2, 1, 128, 50]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17215424)))];
            tensor<fp16, [2, 1, 32, 50]> first_247_cast_fp16 = matmul(transpose_x = first_247_transpose_x_0, transpose_y = first_247_transpose_y_0, x = x_199_cast_fp16, y = y_49_to_fp16)[name = string("first_247_cast_fp16")];
            fp16 _inversed_input_173_y_0_to_fp16 = const()[name = string("_inversed_input_173_y_0_to_fp16"), val = fp16(0x1p-4)];
            tensor<fp16, [2, 1, 32, 50]> _inversed_input_173_cast_fp16 = mul(x = first_247_cast_fp16, y = _inversed_input_173_y_0_to_fp16)[name = string("_inversed_input_173_cast_fp16")];
            int32 var_3373 = const()[name = string("op_3373"), val = int32(3)];
            tensor<fp16, [2, 1, 32, 50]> y_53_cast_fp16 = softmax(axis = var_3373, x = _inversed_input_173_cast_fp16)[name = string("y_53_cast_fp16")];
            tensor<int32, [1]> x_201_axes_0 = const()[name = string("x_201_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 32, 1]> input_tensor_825_cast_fp16 = transpose(perm = var_3304, x = text_mask)[name = string("transpose_9")];
            tensor<fp16, [1, 1, 32, 1]> x_201_cast_fp16 = expand_dims(axes = x_201_axes_0, x = input_tensor_825_cast_fp16)[name = string("x_201_cast_fp16")];
            fp16 speech_prompted_text_encoder_attention1_Constant_11_value_to_fp16 = const()[name = string("speech_prompted_text_encoder_attention1_Constant_11_value_to_fp16"), val = fp16(0x0p+0)];
            tensor<bool, [1, 1, 32, 1]> input_tensor_827_cast_fp16 = equal(x = x_201_cast_fp16, y = speech_prompted_text_encoder_attention1_Constant_11_value_to_fp16)[name = string("input_tensor_827_cast_fp16")];
            tensor<int32, [4]> condition_9_after_broadcast_reps_0 = const()[name = string("condition_9_after_broadcast_reps_0"), val = tensor<int32, [4]>([2, 1, 1, 50])];
            tensor<bool, [2, 1, 32, 50]> condition_9_after_broadcast = tile(reps = condition_9_after_broadcast_reps_0, x = input_tensor_827_cast_fp16)[name = string("condition_9_after_broadcast")];
            tensor<fp16, [2, 1, 32, 50]> speech_prompted_text_encoder_attention1_Constant_12_value_after_broadcast_to_fp16 = const()[name = string("speech_prompted_text_encoder_attention1_Constant_12_value_after_broadcast_to_fp16"), val = tensor<fp16, [2, 1, 32, 50]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17871296)))];
            tensor<fp16, [2, 1, 32, 50]> x_205_cast_fp16 = select(a = speech_prompted_text_encoder_attention1_Constant_12_value_after_broadcast_to_fp16, b = y_53_cast_fp16, cond = condition_9_after_broadcast)[name = string("x_205_cast_fp16")];
            bool var_3383_transpose_x_0 = const()[name = string("op_3383_transpose_x_0"), val = bool(false)];
            bool var_3383_transpose_y_0 = const()[name = string("op_3383_transpose_y_0"), val = bool(false)];
            tensor<fp16, [2, 1, 32, 128]> var_3383_cast_fp16 = matmul(transpose_x = var_3383_transpose_x_0, transpose_y = var_3383_transpose_y_0, x = x_205_cast_fp16, y = y_55_cast_fp16)[name = string("op_3383_cast_fp16")];
            tensor<int32, [2]> var_3386 = const()[name = string("op_3386"), val = tensor<int32, [2]>([1, 1])];
            int32 var_3387_axis_0 = const()[name = string("op_3387_axis_0"), val = int32(0)];
            tensor<fp16, [1, 1, 32, 128]> var_3387_cast_fp16_0, tensor<fp16, [1, 1, 32, 128]> var_3387_cast_fp16_1 = split(axis = var_3387_axis_0, split_sizes = var_3386, x = var_3383_cast_fp16)[name = string("op_3387_cast_fp16")];
            int32 var_3393 = const()[name = string("op_3393"), val = int32(3)];
            bool result_1_interleave_0 = const()[name = string("result_1_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 1, 32, 256]> result_1_cast_fp16 = concat(axis = var_3393, interleave = result_1_interleave_0, values = (var_3387_cast_fp16_0, var_3387_cast_fp16_1))[name = string("result_1_cast_fp16")];
            tensor<int32, [1]> x_207_axes_0 = const()[name = string("x_207_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 32, 256]> x_207_cast_fp16 = squeeze(axes = x_207_axes_0, x = result_1_cast_fp16)[name = string("x_207_cast_fp16")];
            tensor<fp16, [256, 256]> first_251_weight_0_to_fp16 = const()[name = string("first_251_weight_0_to_fp16"), val = tensor<fp16, [256, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17244352)))];
            tensor<fp16, [256]> first_251_bias_0_to_fp16 = const()[name = string("first_251_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17375488)))];
            tensor<fp16, [1, 32, 256]> first_251_cast_fp16 = linear(bias = first_251_bias_0_to_fp16, weight = first_251_weight_0_to_fp16, x = x_207_cast_fp16)[name = string("first_251_cast_fp16")];
            tensor<fp16, [1, 32, 256]> first_253_cast_fp16 = mul(x = first_251_cast_fp16, y = input_tensor_825_cast_fp16)[name = string("first_253_cast_fp16")];
            tensor<fp16, [1, 32, 256]> x_209_cast_fp16 = add(x = first_253_cast_fp16, y = x_195_cast_fp16)[name = string("x_209_cast_fp16")];
            tensor<fp16, [256, 256]> var_3413_weight_0_to_fp16 = const()[name = string("op_3413_weight_0_to_fp16"), val = tensor<fp16, [256, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17376064)))];
            tensor<fp16, [256]> var_3413_bias_0_to_fp16 = const()[name = string("op_3413_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17507200)))];
            tensor<fp16, [1, 32, 256]> var_3413_cast_fp16 = linear(bias = var_3413_bias_0_to_fp16, weight = var_3413_weight_0_to_fp16, x = x_209_cast_fp16)[name = string("op_3413_cast_fp16")];
            tensor<fp16, [256, 256]> var_3419_weight_0_to_fp16 = const()[name = string("op_3419_weight_0_to_fp16"), val = tensor<fp16, [256, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17507776)))];
            tensor<fp16, [256]> var_3419_bias_0_to_fp16 = const()[name = string("op_3419_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17638912)))];
            tensor<fp16, [1, 50, 256]> var_3419_cast_fp16 = linear(bias = var_3419_bias_0_to_fp16, weight = var_3419_weight_0_to_fp16, x = style_ttl)[name = string("op_3419_cast_fp16")];
            tensor<int32, [2]> var_3422 = const()[name = string("op_3422"), val = tensor<int32, [2]>([128, 128])];
            int32 var_3423_axis_0 = const()[name = string("op_3423_axis_0"), val = int32(2)];
            tensor<fp16, [1, 32, 128]> var_3423_cast_fp16_0, tensor<fp16, [1, 32, 128]> var_3423_cast_fp16_1 = split(axis = var_3423_axis_0, split_sizes = var_3422, x = var_3413_cast_fp16)[name = string("op_3423_cast_fp16")];
            tensor<int32, [1]> var_3430_axes_0 = const()[name = string("op_3430_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 32, 128]> var_3430_cast_fp16 = expand_dims(axes = var_3430_axes_0, x = var_3423_cast_fp16_0)[name = string("op_3430_cast_fp16")];
            tensor<int32, [1]> var_3432_axes_0 = const()[name = string("op_3432_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 32, 128]> var_3432_cast_fp16 = expand_dims(axes = var_3432_axes_0, x = var_3423_cast_fp16_1)[name = string("op_3432_cast_fp16")];
            int32 var_3433 = const()[name = string("op_3433"), val = int32(0)];
            bool x_211_interleave_0 = const()[name = string("x_211_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 1, 32, 128]> x_211_cast_fp16 = concat(axis = var_3433, interleave = x_211_interleave_0, values = (var_3430_cast_fp16, var_3432_cast_fp16))[name = string("x_211_cast_fp16")];
            tensor<int32, [2]> var_3454 = const()[name = string("op_3454"), val = tensor<int32, [2]>([128, 128])];
            int32 var_3455_axis_0 = const()[name = string("op_3455_axis_0"), val = int32(2)];
            tensor<fp16, [1, 50, 128]> var_3455_cast_fp16_0, tensor<fp16, [1, 50, 128]> var_3455_cast_fp16_1 = split(axis = var_3455_axis_0, split_sizes = var_3454, x = var_3419_cast_fp16)[name = string("op_3455_cast_fp16")];
            tensor<int32, [1]> var_3462_axes_0 = const()[name = string("op_3462_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 50, 128]> var_3462_cast_fp16 = expand_dims(axes = var_3462_axes_0, x = var_3455_cast_fp16_0)[name = string("op_3462_cast_fp16")];
            tensor<int32, [1]> var_3464_axes_0 = const()[name = string("op_3464_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 50, 128]> var_3464_cast_fp16 = expand_dims(axes = var_3464_axes_0, x = var_3455_cast_fp16_1)[name = string("op_3464_cast_fp16")];
            int32 var_3465 = const()[name = string("op_3465"), val = int32(0)];
            bool y_69_interleave_0 = const()[name = string("y_69_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 1, 50, 128]> y_69_cast_fp16 = concat(axis = var_3465, interleave = y_69_interleave_0, values = (var_3462_cast_fp16, var_3464_cast_fp16))[name = string("y_69_cast_fp16")];
            bool first_261_transpose_x_0 = const()[name = string("first_261_transpose_x_0"), val = bool(false)];
            bool first_261_transpose_y_0 = const()[name = string("first_261_transpose_y_0"), val = bool(false)];
            tensor<fp16, [2, 1, 128, 50]> y_65_to_fp16 = const()[name = string("y_65_to_fp16"), val = tensor<fp16, [2, 1, 128, 50]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17639488)))];
            tensor<fp16, [2, 1, 32, 50]> first_261_cast_fp16 = matmul(transpose_x = first_261_transpose_x_0, transpose_y = first_261_transpose_y_0, x = x_211_cast_fp16, y = y_65_to_fp16)[name = string("first_261_cast_fp16")];
            fp16 _inversed_input_175_y_0_to_fp16 = const()[name = string("_inversed_input_175_y_0_to_fp16"), val = fp16(0x1p-4)];
            tensor<fp16, [2, 1, 32, 50]> _inversed_input_175_cast_fp16 = mul(x = first_261_cast_fp16, y = _inversed_input_175_y_0_to_fp16)[name = string("_inversed_input_175_cast_fp16")];
            int32 var_3478 = const()[name = string("op_3478"), val = int32(3)];
            tensor<fp16, [2, 1, 32, 50]> y_67_cast_fp16 = softmax(axis = var_3478, x = _inversed_input_175_cast_fp16)[name = string("y_67_cast_fp16")];
            tensor<fp16, [2, 1, 32, 50]> x_215_cast_fp16 = select(a = speech_prompted_text_encoder_attention1_Constant_12_value_after_broadcast_to_fp16, b = y_67_cast_fp16, cond = condition_9_after_broadcast)[name = string("x_215_cast_fp16")];
            bool var_3485_transpose_x_0 = const()[name = string("op_3485_transpose_x_0"), val = bool(false)];
            bool var_3485_transpose_y_0 = const()[name = string("op_3485_transpose_y_0"), val = bool(false)];
            tensor<fp16, [2, 1, 32, 128]> var_3485_cast_fp16 = matmul(transpose_x = var_3485_transpose_x_0, transpose_y = var_3485_transpose_y_0, x = x_215_cast_fp16, y = y_69_cast_fp16)[name = string("op_3485_cast_fp16")];
            tensor<int32, [2]> var_3488 = const()[name = string("op_3488"), val = tensor<int32, [2]>([1, 1])];
            int32 var_3489_axis_0 = const()[name = string("op_3489_axis_0"), val = int32(0)];
            tensor<fp16, [1, 1, 32, 128]> var_3489_cast_fp16_0, tensor<fp16, [1, 1, 32, 128]> var_3489_cast_fp16_1 = split(axis = var_3489_axis_0, split_sizes = var_3488, x = var_3485_cast_fp16)[name = string("op_3489_cast_fp16")];
            int32 var_3495 = const()[name = string("op_3495"), val = int32(3)];
            bool result_interleave_0 = const()[name = string("result_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 1, 32, 256]> result_cast_fp16 = concat(axis = var_3495, interleave = result_interleave_0, values = (var_3489_cast_fp16_0, var_3489_cast_fp16_1))[name = string("result_cast_fp16")];
            tensor<int32, [1]> x_axes_0 = const()[name = string("x_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 32, 256]> x_cast_fp16 = squeeze(axes = x_axes_0, x = result_cast_fp16)[name = string("x_cast_fp16")];
            tensor<fp16, [256, 256]> first_265_weight_0_to_fp16 = const()[name = string("first_265_weight_0_to_fp16"), val = tensor<fp16, [256, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17665152)))];
            tensor<fp16, [256]> first_265_bias_0_to_fp16 = const()[name = string("first_265_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17796288)))];
            tensor<fp16, [1, 32, 256]> first_265_cast_fp16 = linear(bias = first_265_bias_0_to_fp16, weight = first_265_weight_0_to_fp16, x = x_cast_fp16)[name = string("first_265_cast_fp16")];
            tensor<fp16, [1, 32, 256]> first_267_cast_fp16 = mul(x = first_265_cast_fp16, y = input_tensor_825_cast_fp16)[name = string("first_267_cast_fp16")];
            tensor<fp16, [1, 32, 256]> input_cast_fp16 = add(x = first_267_cast_fp16, y = x_195_cast_fp16)[name = string("input_cast_fp16")];
            tensor<int32, [1]> input_tensor_axes_0 = const()[name = string("input_tensor_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> speech_prompted_text_encoder_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("speech_prompted_text_encoder_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17796864)))];
            tensor<fp16, [256]> speech_prompted_text_encoder_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("speech_prompted_text_encoder_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17797440)))];
            fp16 var_3514_to_fp16 = const()[name = string("op_3514_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 32, 256]> input_tensor_cast_fp16 = layer_norm(axes = input_tensor_axes_0, beta = speech_prompted_text_encoder_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_3514_to_fp16, gamma = speech_prompted_text_encoder_norm_norm_LayerNormalization_weight_to_fp16, x = input_cast_fp16)[name = string("input_tensor_cast_fp16")];
            tensor<int32, [3]> var_3523 = const()[name = string("op_3523"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 256, 32]> first_cast_fp16 = transpose(perm = var_3523, x = input_tensor_cast_fp16)[name = string("transpose_8")];
            tensor<fp16, [1, 256, 32]> text_emb = mul(x = first_cast_fp16, y = text_mask)[name = string("op_3525_cast_fp16")];
        } -> (text_emb);
    func text_t320<ios18>(tensor<fp16, [1, 50, 256]> style_ttl, tensor<int32, [1, 320]> text_ids, tensor<fp16, [1, 1, 320]> text_mask) {
            int32 input_tensor_3_batch_dims_0 = const()[name = string("input_tensor_3_batch_dims_0"), val = int32(0)];
            bool input_tensor_3_validate_indices_0 = const()[name = string("input_tensor_3_validate_indices_0"), val = bool(false)];
            tensor<fp16, [8322, 256]> initializers_onnx_initializer_0_to_fp16 = const()[name = string("initializers_onnx_initializer_0_to_fp16"), val = tensor<fp16, [8322, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(64)))];
            string text_ids_to_int16_dtype_0 = const()[name = string("text_ids_to_int16_dtype_0"), val = string("int16")];
            string cast_59_dtype_0 = const()[name = string("cast_59_dtype_0"), val = string("int32")];
            int32 greater_equal_0_y_0 = const()[name = string("greater_equal_0_y_0"), val = int32(0)];
            tensor<int16, [1, 320]> text_ids_to_int16 = cast(dtype = text_ids_to_int16_dtype_0, x = text_ids)[name = string("cast_62")];
            tensor<int32, [1, 320]> cast_59 = cast(dtype = cast_59_dtype_0, x = text_ids_to_int16)[name = string("cast_61")];
            tensor<bool, [1, 320]> greater_equal_0 = greater_equal(x = cast_59, y = greater_equal_0_y_0)[name = string("greater_equal_0")];
            int32 slice_by_index_0 = const()[name = string("slice_by_index_0"), val = int32(8322)];
            tensor<int32, [1, 320]> add_0 = add(x = cast_59, y = slice_by_index_0)[name = string("add_0")];
            tensor<int32, [1, 320]> select_0 = select(a = cast_59, b = add_0, cond = greater_equal_0)[name = string("select_0")];
            int32 input_tensor_3_cast_fp16_cast_uint16_axis_0 = const()[name = string("input_tensor_3_cast_fp16_cast_uint16_axis_0"), val = int32(0)];
            string select_0_to_int16_dtype_0 = const()[name = string("select_0_to_int16_dtype_0"), val = string("int16")];
            tensor<int16, [1, 320]> select_0_to_int16 = cast(dtype = select_0_to_int16_dtype_0, x = select_0)[name = string("cast_60")];
            tensor<fp16, [1, 320, 256]> input_tensor_3_cast_fp16_cast_uint16_cast_uint16 = gather(axis = input_tensor_3_cast_fp16_cast_uint16_axis_0, batch_dims = input_tensor_3_batch_dims_0, indices = select_0_to_int16, validate_indices = input_tensor_3_validate_indices_0, x = initializers_onnx_initializer_0_to_fp16)[name = string("input_tensor_3_cast_fp16_cast_uint16_cast_uint16")];
            tensor<int32, [3]> var_446 = const()[name = string("op_446"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 256, 320]> first_1_cast_fp16 = transpose(perm = var_446, x = input_tensor_3_cast_fp16_cast_uint16_cast_uint16)[name = string("transpose_47")];
            tensor<fp16, [1, 256, 320]> first_3_cast_fp16 = mul(x = first_1_cast_fp16, y = text_mask)[name = string("first_3_cast_fp16")];
            tensor<fp16, [1, 256, 320]> input_1_cast_fp16 = mul(x = first_3_cast_fp16, y = text_mask)[name = string("input_1_cast_fp16")];
            tensor<int32, [6]> input_3_pad_0 = const()[name = string("input_3_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 2, 2])];
            string input_3_mode_0 = const()[name = string("input_3_mode_0"), val = string("replicate")];
            fp16 const_0_to_fp16 = const()[name = string("const_0_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 256, 324]> input_3_cast_fp16 = pad(constant_val = const_0_to_fp16, mode = input_3_mode_0, pad = input_3_pad_0, x = input_1_cast_fp16)[name = string("input_3_cast_fp16")];
            string first_5_pad_type_0 = const()[name = string("first_5_pad_type_0"), val = string("valid")];
            int32 first_5_groups_0 = const()[name = string("first_5_groups_0"), val = int32(256)];
            tensor<int32, [1]> first_5_strides_0 = const()[name = string("first_5_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_5_pad_0 = const()[name = string("first_5_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_5_dilations_0 = const()[name = string("first_5_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [256, 1, 5]> text_encoder_convnext_convnext_0_dwconv_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_0_dwconv_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4260992)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_0_dwconv_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_0_dwconv_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4263616)))];
            tensor<fp16, [1, 256, 320]> first_5_cast_fp16 = conv(bias = text_encoder_convnext_convnext_0_dwconv_Conv_bias_to_fp16, dilations = first_5_dilations_0, groups = first_5_groups_0, pad = first_5_pad_0, pad_type = first_5_pad_type_0, strides = first_5_strides_0, weight = text_encoder_convnext_convnext_0_dwconv_Conv_weight_to_fp16, x = input_3_cast_fp16)[name = string("first_5_cast_fp16")];
            tensor<fp16, [1, 256, 320]> input_tensor_13_cast_fp16 = mul(x = first_5_cast_fp16, y = text_mask)[name = string("input_tensor_13_cast_fp16")];
            tensor<int32, [3]> var_471 = const()[name = string("op_471"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_15_axes_0 = const()[name = string("input_tensor_15_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_convnext_convnext_0_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_0_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4264192)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_0_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_0_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4264768)))];
            fp16 var_474_to_fp16 = const()[name = string("op_474_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 320, 256]> input_5_cast_fp16 = transpose(perm = var_471, x = input_tensor_13_cast_fp16)[name = string("transpose_46")];
            tensor<fp16, [1, 320, 256]> input_tensor_15_cast_fp16 = layer_norm(axes = input_tensor_15_axes_0, beta = text_encoder_convnext_convnext_0_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_474_to_fp16, gamma = text_encoder_convnext_convnext_0_norm_norm_LayerNormalization_weight_to_fp16, x = input_5_cast_fp16)[name = string("input_tensor_15_cast_fp16")];
            tensor<int32, [3]> var_483 = const()[name = string("op_483"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_7_pad_type_0 = const()[name = string("first_7_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_7_strides_0 = const()[name = string("first_7_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_7_pad_0 = const()[name = string("first_7_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_7_dilations_0 = const()[name = string("first_7_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_7_groups_0 = const()[name = string("first_7_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_convnext_convnext_0_pwconv1_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_0_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4265344)))];
            tensor<fp16, [1024]> text_encoder_convnext_convnext_0_pwconv1_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_0_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4789696)))];
            tensor<fp16, [1, 256, 320]> input_7_cast_fp16 = transpose(perm = var_483, x = input_tensor_15_cast_fp16)[name = string("transpose_45")];
            tensor<fp16, [1, 1024, 320]> first_7_cast_fp16 = conv(bias = text_encoder_convnext_convnext_0_pwconv1_Conv_bias_to_fp16, dilations = first_7_dilations_0, groups = first_7_groups_0, pad = first_7_pad_0, pad_type = first_7_pad_type_0, strides = first_7_strides_0, weight = text_encoder_convnext_convnext_0_pwconv1_Conv_weight_to_fp16, x = input_7_cast_fp16)[name = string("first_7_cast_fp16")];
            string input_9_mode_0 = const()[name = string("input_9_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 1024, 320]> input_9_cast_fp16 = gelu(mode = input_9_mode_0, x = first_7_cast_fp16)[name = string("input_9_cast_fp16")];
            string second_9_pad_type_0 = const()[name = string("second_9_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_9_strides_0 = const()[name = string("second_9_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_9_pad_0 = const()[name = string("second_9_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_9_dilations_0 = const()[name = string("second_9_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_9_groups_0 = const()[name = string("second_9_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> second_11_weight_0_to_fp16 = const()[name = string("second_11_weight_0_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4791808)))];
            tensor<fp16, [256]> second_11_bias_0_to_fp16 = const()[name = string("second_11_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5316160)))];
            tensor<fp16, [1, 256, 320]> second_11_cast_fp16 = conv(bias = second_11_bias_0_to_fp16, dilations = second_9_dilations_0, groups = second_9_groups_0, pad = second_9_pad_0, pad_type = second_9_pad_type_0, strides = second_9_strides_0, weight = second_11_weight_0_to_fp16, x = input_9_cast_fp16)[name = string("second_11_cast_fp16")];
            tensor<fp16, [1, 256, 320]> first_15_cast_fp16 = add(x = input_1_cast_fp16, y = second_11_cast_fp16)[name = string("first_15_cast_fp16")];
            tensor<fp16, [1, 256, 320]> first_17_cast_fp16 = mul(x = first_15_cast_fp16, y = text_mask)[name = string("first_17_cast_fp16")];
            tensor<fp16, [1, 256, 320]> input_11_cast_fp16 = mul(x = first_17_cast_fp16, y = text_mask)[name = string("input_11_cast_fp16")];
            tensor<int32, [6]> input_13_pad_0 = const()[name = string("input_13_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 2, 2])];
            string input_13_mode_0 = const()[name = string("input_13_mode_0"), val = string("replicate")];
            fp16 const_1_to_fp16 = const()[name = string("const_1_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 256, 324]> input_13_cast_fp16 = pad(constant_val = const_1_to_fp16, mode = input_13_mode_0, pad = input_13_pad_0, x = input_11_cast_fp16)[name = string("input_13_cast_fp16")];
            string first_19_pad_type_0 = const()[name = string("first_19_pad_type_0"), val = string("valid")];
            int32 first_19_groups_0 = const()[name = string("first_19_groups_0"), val = int32(256)];
            tensor<int32, [1]> first_19_strides_0 = const()[name = string("first_19_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_19_pad_0 = const()[name = string("first_19_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_19_dilations_0 = const()[name = string("first_19_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [256, 1, 5]> text_encoder_convnext_convnext_1_dwconv_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_1_dwconv_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5316736)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_1_dwconv_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_1_dwconv_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5319360)))];
            tensor<fp16, [1, 256, 320]> first_19_cast_fp16 = conv(bias = text_encoder_convnext_convnext_1_dwconv_Conv_bias_to_fp16, dilations = first_19_dilations_0, groups = first_19_groups_0, pad = first_19_pad_0, pad_type = first_19_pad_type_0, strides = first_19_strides_0, weight = text_encoder_convnext_convnext_1_dwconv_Conv_weight_to_fp16, x = input_13_cast_fp16)[name = string("first_19_cast_fp16")];
            tensor<fp16, [1, 256, 320]> input_tensor_27_cast_fp16 = mul(x = first_19_cast_fp16, y = text_mask)[name = string("input_tensor_27_cast_fp16")];
            tensor<int32, [3]> var_539 = const()[name = string("op_539"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_29_axes_0 = const()[name = string("input_tensor_29_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_convnext_convnext_1_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_1_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5319936)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_1_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_1_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5320512)))];
            fp16 var_542_to_fp16 = const()[name = string("op_542_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 320, 256]> input_15_cast_fp16 = transpose(perm = var_539, x = input_tensor_27_cast_fp16)[name = string("transpose_44")];
            tensor<fp16, [1, 320, 256]> input_tensor_29_cast_fp16 = layer_norm(axes = input_tensor_29_axes_0, beta = text_encoder_convnext_convnext_1_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_542_to_fp16, gamma = text_encoder_convnext_convnext_1_norm_norm_LayerNormalization_weight_to_fp16, x = input_15_cast_fp16)[name = string("input_tensor_29_cast_fp16")];
            tensor<int32, [3]> var_551 = const()[name = string("op_551"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_21_pad_type_0 = const()[name = string("first_21_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_21_strides_0 = const()[name = string("first_21_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_21_pad_0 = const()[name = string("first_21_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_21_dilations_0 = const()[name = string("first_21_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_21_groups_0 = const()[name = string("first_21_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_convnext_convnext_1_pwconv1_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_1_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5321088)))];
            tensor<fp16, [1024]> text_encoder_convnext_convnext_1_pwconv1_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_1_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5845440)))];
            tensor<fp16, [1, 256, 320]> input_17_cast_fp16 = transpose(perm = var_551, x = input_tensor_29_cast_fp16)[name = string("transpose_43")];
            tensor<fp16, [1, 1024, 320]> first_21_cast_fp16 = conv(bias = text_encoder_convnext_convnext_1_pwconv1_Conv_bias_to_fp16, dilations = first_21_dilations_0, groups = first_21_groups_0, pad = first_21_pad_0, pad_type = first_21_pad_type_0, strides = first_21_strides_0, weight = text_encoder_convnext_convnext_1_pwconv1_Conv_weight_to_fp16, x = input_17_cast_fp16)[name = string("first_21_cast_fp16")];
            string input_19_mode_0 = const()[name = string("input_19_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 1024, 320]> input_19_cast_fp16 = gelu(mode = input_19_mode_0, x = first_21_cast_fp16)[name = string("input_19_cast_fp16")];
            string second_21_pad_type_0 = const()[name = string("second_21_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_21_strides_0 = const()[name = string("second_21_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_21_pad_0 = const()[name = string("second_21_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_21_dilations_0 = const()[name = string("second_21_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_21_groups_0 = const()[name = string("second_21_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> second_23_weight_0_to_fp16 = const()[name = string("second_23_weight_0_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5847552)))];
            tensor<fp16, [256]> second_23_bias_0_to_fp16 = const()[name = string("second_23_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6371904)))];
            tensor<fp16, [1, 256, 320]> second_23_cast_fp16 = conv(bias = second_23_bias_0_to_fp16, dilations = second_21_dilations_0, groups = second_21_groups_0, pad = second_21_pad_0, pad_type = second_21_pad_type_0, strides = second_21_strides_0, weight = second_23_weight_0_to_fp16, x = input_19_cast_fp16)[name = string("second_23_cast_fp16")];
            tensor<fp16, [1, 256, 320]> first_29_cast_fp16 = add(x = input_11_cast_fp16, y = second_23_cast_fp16)[name = string("first_29_cast_fp16")];
            tensor<fp16, [1, 256, 320]> first_31_cast_fp16 = mul(x = first_29_cast_fp16, y = text_mask)[name = string("first_31_cast_fp16")];
            tensor<fp16, [1, 256, 320]> input_21_cast_fp16 = mul(x = first_31_cast_fp16, y = text_mask)[name = string("input_21_cast_fp16")];
            tensor<int32, [6]> input_23_pad_0 = const()[name = string("input_23_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            string input_23_mode_0 = const()[name = string("input_23_mode_0"), val = string("replicate")];
            fp16 const_2_to_fp16 = const()[name = string("const_2_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 256, 328]> input_23_cast_fp16 = pad(constant_val = const_2_to_fp16, mode = input_23_mode_0, pad = input_23_pad_0, x = input_21_cast_fp16)[name = string("input_23_cast_fp16")];
            string first_33_pad_type_0 = const()[name = string("first_33_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_33_dilations_0 = const()[name = string("first_33_dilations_0"), val = tensor<int32, [1]>([2])];
            int32 first_33_groups_0 = const()[name = string("first_33_groups_0"), val = int32(256)];
            tensor<int32, [1]> first_33_strides_0 = const()[name = string("first_33_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_33_pad_0 = const()[name = string("first_33_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [256, 1, 5]> text_encoder_convnext_convnext_2_dwconv_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_2_dwconv_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6372480)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_2_dwconv_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_2_dwconv_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6375104)))];
            tensor<fp16, [1, 256, 320]> first_33_cast_fp16 = conv(bias = text_encoder_convnext_convnext_2_dwconv_Conv_bias_to_fp16, dilations = first_33_dilations_0, groups = first_33_groups_0, pad = first_33_pad_0, pad_type = first_33_pad_type_0, strides = first_33_strides_0, weight = text_encoder_convnext_convnext_2_dwconv_Conv_weight_to_fp16, x = input_23_cast_fp16)[name = string("first_33_cast_fp16")];
            tensor<fp16, [1, 256, 320]> input_tensor_41_cast_fp16 = mul(x = first_33_cast_fp16, y = text_mask)[name = string("input_tensor_41_cast_fp16")];
            tensor<int32, [3]> var_608 = const()[name = string("op_608"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_43_axes_0 = const()[name = string("input_tensor_43_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_convnext_convnext_2_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_2_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6375680)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_2_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_2_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6376256)))];
            fp16 var_611_to_fp16 = const()[name = string("op_611_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 320, 256]> input_25_cast_fp16 = transpose(perm = var_608, x = input_tensor_41_cast_fp16)[name = string("transpose_42")];
            tensor<fp16, [1, 320, 256]> input_tensor_43_cast_fp16 = layer_norm(axes = input_tensor_43_axes_0, beta = text_encoder_convnext_convnext_2_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_611_to_fp16, gamma = text_encoder_convnext_convnext_2_norm_norm_LayerNormalization_weight_to_fp16, x = input_25_cast_fp16)[name = string("input_tensor_43_cast_fp16")];
            tensor<int32, [3]> var_620 = const()[name = string("op_620"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_35_pad_type_0 = const()[name = string("first_35_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_35_strides_0 = const()[name = string("first_35_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_35_pad_0 = const()[name = string("first_35_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_35_dilations_0 = const()[name = string("first_35_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_35_groups_0 = const()[name = string("first_35_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_convnext_convnext_2_pwconv1_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_2_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6376832)))];
            tensor<fp16, [1024]> text_encoder_convnext_convnext_2_pwconv1_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_2_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6901184)))];
            tensor<fp16, [1, 256, 320]> input_27_cast_fp16 = transpose(perm = var_620, x = input_tensor_43_cast_fp16)[name = string("transpose_41")];
            tensor<fp16, [1, 1024, 320]> first_35_cast_fp16 = conv(bias = text_encoder_convnext_convnext_2_pwconv1_Conv_bias_to_fp16, dilations = first_35_dilations_0, groups = first_35_groups_0, pad = first_35_pad_0, pad_type = first_35_pad_type_0, strides = first_35_strides_0, weight = text_encoder_convnext_convnext_2_pwconv1_Conv_weight_to_fp16, x = input_27_cast_fp16)[name = string("first_35_cast_fp16")];
            string input_29_mode_0 = const()[name = string("input_29_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 1024, 320]> input_29_cast_fp16 = gelu(mode = input_29_mode_0, x = first_35_cast_fp16)[name = string("input_29_cast_fp16")];
            string second_33_pad_type_0 = const()[name = string("second_33_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_33_strides_0 = const()[name = string("second_33_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_33_pad_0 = const()[name = string("second_33_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_33_dilations_0 = const()[name = string("second_33_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_33_groups_0 = const()[name = string("second_33_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> second_35_weight_0_to_fp16 = const()[name = string("second_35_weight_0_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6903296)))];
            tensor<fp16, [256]> second_35_bias_0_to_fp16 = const()[name = string("second_35_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7427648)))];
            tensor<fp16, [1, 256, 320]> second_35_cast_fp16 = conv(bias = second_35_bias_0_to_fp16, dilations = second_33_dilations_0, groups = second_33_groups_0, pad = second_33_pad_0, pad_type = second_33_pad_type_0, strides = second_33_strides_0, weight = second_35_weight_0_to_fp16, x = input_29_cast_fp16)[name = string("second_35_cast_fp16")];
            tensor<fp16, [1, 256, 320]> first_43_cast_fp16 = add(x = input_21_cast_fp16, y = second_35_cast_fp16)[name = string("first_43_cast_fp16")];
            tensor<fp16, [1, 256, 320]> first_45_cast_fp16 = mul(x = first_43_cast_fp16, y = text_mask)[name = string("first_45_cast_fp16")];
            tensor<fp16, [1, 256, 320]> input_31_cast_fp16 = mul(x = first_45_cast_fp16, y = text_mask)[name = string("input_31_cast_fp16")];
            tensor<int32, [6]> input_33_pad_0 = const()[name = string("input_33_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            string input_33_mode_0 = const()[name = string("input_33_mode_0"), val = string("replicate")];
            fp16 const_3_to_fp16 = const()[name = string("const_3_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 256, 328]> input_33_cast_fp16 = pad(constant_val = const_3_to_fp16, mode = input_33_mode_0, pad = input_33_pad_0, x = input_31_cast_fp16)[name = string("input_33_cast_fp16")];
            string first_47_pad_type_0 = const()[name = string("first_47_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_47_dilations_0 = const()[name = string("first_47_dilations_0"), val = tensor<int32, [1]>([2])];
            int32 first_47_groups_0 = const()[name = string("first_47_groups_0"), val = int32(256)];
            tensor<int32, [1]> first_47_strides_0 = const()[name = string("first_47_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_47_pad_0 = const()[name = string("first_47_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [256, 1, 5]> text_encoder_convnext_convnext_3_dwconv_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_3_dwconv_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7428224)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_3_dwconv_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_3_dwconv_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7430848)))];
            tensor<fp16, [1, 256, 320]> first_47_cast_fp16 = conv(bias = text_encoder_convnext_convnext_3_dwconv_Conv_bias_to_fp16, dilations = first_47_dilations_0, groups = first_47_groups_0, pad = first_47_pad_0, pad_type = first_47_pad_type_0, strides = first_47_strides_0, weight = text_encoder_convnext_convnext_3_dwconv_Conv_weight_to_fp16, x = input_33_cast_fp16)[name = string("first_47_cast_fp16")];
            tensor<fp16, [1, 256, 320]> input_tensor_55_cast_fp16 = mul(x = first_47_cast_fp16, y = text_mask)[name = string("input_tensor_55_cast_fp16")];
            tensor<int32, [3]> var_677 = const()[name = string("op_677"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_57_axes_0 = const()[name = string("input_tensor_57_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_convnext_convnext_3_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_3_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7431424)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_3_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_3_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7432000)))];
            fp16 var_680_to_fp16 = const()[name = string("op_680_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 320, 256]> input_35_cast_fp16 = transpose(perm = var_677, x = input_tensor_55_cast_fp16)[name = string("transpose_40")];
            tensor<fp16, [1, 320, 256]> input_tensor_57_cast_fp16 = layer_norm(axes = input_tensor_57_axes_0, beta = text_encoder_convnext_convnext_3_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_680_to_fp16, gamma = text_encoder_convnext_convnext_3_norm_norm_LayerNormalization_weight_to_fp16, x = input_35_cast_fp16)[name = string("input_tensor_57_cast_fp16")];
            tensor<int32, [3]> var_689 = const()[name = string("op_689"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_49_pad_type_0 = const()[name = string("first_49_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_49_strides_0 = const()[name = string("first_49_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_49_pad_0 = const()[name = string("first_49_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_49_dilations_0 = const()[name = string("first_49_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_49_groups_0 = const()[name = string("first_49_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_convnext_convnext_3_pwconv1_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_3_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7432576)))];
            tensor<fp16, [1024]> text_encoder_convnext_convnext_3_pwconv1_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_3_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7956928)))];
            tensor<fp16, [1, 256, 320]> input_37_cast_fp16 = transpose(perm = var_689, x = input_tensor_57_cast_fp16)[name = string("transpose_39")];
            tensor<fp16, [1, 1024, 320]> first_49_cast_fp16 = conv(bias = text_encoder_convnext_convnext_3_pwconv1_Conv_bias_to_fp16, dilations = first_49_dilations_0, groups = first_49_groups_0, pad = first_49_pad_0, pad_type = first_49_pad_type_0, strides = first_49_strides_0, weight = text_encoder_convnext_convnext_3_pwconv1_Conv_weight_to_fp16, x = input_37_cast_fp16)[name = string("first_49_cast_fp16")];
            string input_39_mode_0 = const()[name = string("input_39_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 1024, 320]> input_39_cast_fp16 = gelu(mode = input_39_mode_0, x = first_49_cast_fp16)[name = string("input_39_cast_fp16")];
            string second_45_pad_type_0 = const()[name = string("second_45_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_45_strides_0 = const()[name = string("second_45_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_45_pad_0 = const()[name = string("second_45_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_45_dilations_0 = const()[name = string("second_45_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_45_groups_0 = const()[name = string("second_45_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> second_47_weight_0_to_fp16 = const()[name = string("second_47_weight_0_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7959040)))];
            tensor<fp16, [256]> second_47_bias_0_to_fp16 = const()[name = string("second_47_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8483392)))];
            tensor<fp16, [1, 256, 320]> second_47_cast_fp16 = conv(bias = second_47_bias_0_to_fp16, dilations = second_45_dilations_0, groups = second_45_groups_0, pad = second_45_pad_0, pad_type = second_45_pad_type_0, strides = second_45_strides_0, weight = second_47_weight_0_to_fp16, x = input_39_cast_fp16)[name = string("second_47_cast_fp16")];
            tensor<fp16, [1, 256, 320]> first_57_cast_fp16 = add(x = input_31_cast_fp16, y = second_47_cast_fp16)[name = string("first_57_cast_fp16")];
            tensor<fp16, [1, 256, 320]> first_59_cast_fp16 = mul(x = first_57_cast_fp16, y = text_mask)[name = string("first_59_cast_fp16")];
            tensor<fp16, [1, 256, 320]> input_41_cast_fp16 = mul(x = first_59_cast_fp16, y = text_mask)[name = string("input_41_cast_fp16")];
            tensor<int32, [6]> input_43_pad_0 = const()[name = string("input_43_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 8, 8])];
            string input_43_mode_0 = const()[name = string("input_43_mode_0"), val = string("replicate")];
            fp16 const_4_to_fp16 = const()[name = string("const_4_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 256, 336]> input_43_cast_fp16 = pad(constant_val = const_4_to_fp16, mode = input_43_mode_0, pad = input_43_pad_0, x = input_41_cast_fp16)[name = string("input_43_cast_fp16")];
            string first_61_pad_type_0 = const()[name = string("first_61_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_61_dilations_0 = const()[name = string("first_61_dilations_0"), val = tensor<int32, [1]>([4])];
            int32 first_61_groups_0 = const()[name = string("first_61_groups_0"), val = int32(256)];
            tensor<int32, [1]> first_61_strides_0 = const()[name = string("first_61_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_61_pad_0 = const()[name = string("first_61_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [256, 1, 5]> text_encoder_convnext_convnext_4_dwconv_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_4_dwconv_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8483968)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_4_dwconv_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_4_dwconv_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8486592)))];
            tensor<fp16, [1, 256, 320]> first_61_cast_fp16 = conv(bias = text_encoder_convnext_convnext_4_dwconv_Conv_bias_to_fp16, dilations = first_61_dilations_0, groups = first_61_groups_0, pad = first_61_pad_0, pad_type = first_61_pad_type_0, strides = first_61_strides_0, weight = text_encoder_convnext_convnext_4_dwconv_Conv_weight_to_fp16, x = input_43_cast_fp16)[name = string("first_61_cast_fp16")];
            tensor<fp16, [1, 256, 320]> input_tensor_69_cast_fp16 = mul(x = first_61_cast_fp16, y = text_mask)[name = string("input_tensor_69_cast_fp16")];
            tensor<int32, [3]> var_746 = const()[name = string("op_746"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_71_axes_0 = const()[name = string("input_tensor_71_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_convnext_convnext_4_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_4_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8487168)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_4_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_4_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8487744)))];
            fp16 var_749_to_fp16 = const()[name = string("op_749_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 320, 256]> input_45_cast_fp16 = transpose(perm = var_746, x = input_tensor_69_cast_fp16)[name = string("transpose_38")];
            tensor<fp16, [1, 320, 256]> input_tensor_71_cast_fp16 = layer_norm(axes = input_tensor_71_axes_0, beta = text_encoder_convnext_convnext_4_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_749_to_fp16, gamma = text_encoder_convnext_convnext_4_norm_norm_LayerNormalization_weight_to_fp16, x = input_45_cast_fp16)[name = string("input_tensor_71_cast_fp16")];
            tensor<int32, [3]> var_758 = const()[name = string("op_758"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_63_pad_type_0 = const()[name = string("first_63_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_63_strides_0 = const()[name = string("first_63_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_63_pad_0 = const()[name = string("first_63_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_63_dilations_0 = const()[name = string("first_63_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_63_groups_0 = const()[name = string("first_63_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_convnext_convnext_4_pwconv1_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_4_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8488320)))];
            tensor<fp16, [1024]> text_encoder_convnext_convnext_4_pwconv1_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_4_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9012672)))];
            tensor<fp16, [1, 256, 320]> input_47_cast_fp16 = transpose(perm = var_758, x = input_tensor_71_cast_fp16)[name = string("transpose_37")];
            tensor<fp16, [1, 1024, 320]> first_63_cast_fp16 = conv(bias = text_encoder_convnext_convnext_4_pwconv1_Conv_bias_to_fp16, dilations = first_63_dilations_0, groups = first_63_groups_0, pad = first_63_pad_0, pad_type = first_63_pad_type_0, strides = first_63_strides_0, weight = text_encoder_convnext_convnext_4_pwconv1_Conv_weight_to_fp16, x = input_47_cast_fp16)[name = string("first_63_cast_fp16")];
            string input_49_mode_0 = const()[name = string("input_49_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 1024, 320]> input_49_cast_fp16 = gelu(mode = input_49_mode_0, x = first_63_cast_fp16)[name = string("input_49_cast_fp16")];
            string second_57_pad_type_0 = const()[name = string("second_57_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_57_strides_0 = const()[name = string("second_57_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_57_pad_0 = const()[name = string("second_57_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_57_dilations_0 = const()[name = string("second_57_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_57_groups_0 = const()[name = string("second_57_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> second_59_weight_0_to_fp16 = const()[name = string("second_59_weight_0_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9014784)))];
            tensor<fp16, [256]> second_59_bias_0_to_fp16 = const()[name = string("second_59_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9539136)))];
            tensor<fp16, [1, 256, 320]> second_59_cast_fp16 = conv(bias = second_59_bias_0_to_fp16, dilations = second_57_dilations_0, groups = second_57_groups_0, pad = second_57_pad_0, pad_type = second_57_pad_type_0, strides = second_57_strides_0, weight = second_59_weight_0_to_fp16, x = input_49_cast_fp16)[name = string("second_59_cast_fp16")];
            tensor<fp16, [1, 256, 320]> first_71_cast_fp16 = add(x = input_41_cast_fp16, y = second_59_cast_fp16)[name = string("first_71_cast_fp16")];
            tensor<fp16, [1, 256, 320]> first_73_cast_fp16 = mul(x = first_71_cast_fp16, y = text_mask)[name = string("first_73_cast_fp16")];
            tensor<fp16, [1, 256, 320]> input_51_cast_fp16 = mul(x = first_73_cast_fp16, y = text_mask)[name = string("input_51_cast_fp16")];
            tensor<int32, [6]> input_53_pad_0 = const()[name = string("input_53_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 8, 8])];
            string input_53_mode_0 = const()[name = string("input_53_mode_0"), val = string("replicate")];
            fp16 const_5_to_fp16 = const()[name = string("const_5_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 256, 336]> input_53_cast_fp16 = pad(constant_val = const_5_to_fp16, mode = input_53_mode_0, pad = input_53_pad_0, x = input_51_cast_fp16)[name = string("input_53_cast_fp16")];
            string first_75_pad_type_0 = const()[name = string("first_75_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_75_dilations_0 = const()[name = string("first_75_dilations_0"), val = tensor<int32, [1]>([4])];
            int32 first_75_groups_0 = const()[name = string("first_75_groups_0"), val = int32(256)];
            tensor<int32, [1]> first_75_strides_0 = const()[name = string("first_75_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_75_pad_0 = const()[name = string("first_75_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [256, 1, 5]> text_encoder_convnext_convnext_5_dwconv_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_5_dwconv_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9539712)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_5_dwconv_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_5_dwconv_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9542336)))];
            tensor<fp16, [1, 256, 320]> first_75_cast_fp16 = conv(bias = text_encoder_convnext_convnext_5_dwconv_Conv_bias_to_fp16, dilations = first_75_dilations_0, groups = first_75_groups_0, pad = first_75_pad_0, pad_type = first_75_pad_type_0, strides = first_75_strides_0, weight = text_encoder_convnext_convnext_5_dwconv_Conv_weight_to_fp16, x = input_53_cast_fp16)[name = string("first_75_cast_fp16")];
            tensor<fp16, [1, 256, 320]> input_tensor_83_cast_fp16 = mul(x = first_75_cast_fp16, y = text_mask)[name = string("input_tensor_83_cast_fp16")];
            tensor<int32, [3]> var_815 = const()[name = string("op_815"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_85_axes_0 = const()[name = string("input_tensor_85_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_convnext_convnext_5_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_5_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9542912)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_5_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_5_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9543488)))];
            fp16 var_818_to_fp16 = const()[name = string("op_818_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 320, 256]> input_55_cast_fp16 = transpose(perm = var_815, x = input_tensor_83_cast_fp16)[name = string("transpose_36")];
            tensor<fp16, [1, 320, 256]> input_tensor_85_cast_fp16 = layer_norm(axes = input_tensor_85_axes_0, beta = text_encoder_convnext_convnext_5_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_818_to_fp16, gamma = text_encoder_convnext_convnext_5_norm_norm_LayerNormalization_weight_to_fp16, x = input_55_cast_fp16)[name = string("input_tensor_85_cast_fp16")];
            tensor<int32, [3]> var_827 = const()[name = string("op_827"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_77_pad_type_0 = const()[name = string("first_77_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_77_strides_0 = const()[name = string("first_77_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_77_pad_0 = const()[name = string("first_77_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_77_dilations_0 = const()[name = string("first_77_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_77_groups_0 = const()[name = string("first_77_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_convnext_convnext_5_pwconv1_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_5_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9544064)))];
            tensor<fp16, [1024]> text_encoder_convnext_convnext_5_pwconv1_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_5_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10068416)))];
            tensor<fp16, [1, 256, 320]> input_57_cast_fp16 = transpose(perm = var_827, x = input_tensor_85_cast_fp16)[name = string("transpose_35")];
            tensor<fp16, [1, 1024, 320]> first_77_cast_fp16 = conv(bias = text_encoder_convnext_convnext_5_pwconv1_Conv_bias_to_fp16, dilations = first_77_dilations_0, groups = first_77_groups_0, pad = first_77_pad_0, pad_type = first_77_pad_type_0, strides = first_77_strides_0, weight = text_encoder_convnext_convnext_5_pwconv1_Conv_weight_to_fp16, x = input_57_cast_fp16)[name = string("first_77_cast_fp16")];
            string input_59_mode_0 = const()[name = string("input_59_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 1024, 320]> input_59_cast_fp16 = gelu(mode = input_59_mode_0, x = first_77_cast_fp16)[name = string("input_59_cast_fp16")];
            string second_69_pad_type_0 = const()[name = string("second_69_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_69_strides_0 = const()[name = string("second_69_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_69_pad_0 = const()[name = string("second_69_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_69_dilations_0 = const()[name = string("second_69_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_69_groups_0 = const()[name = string("second_69_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> second_71_weight_0_to_fp16 = const()[name = string("second_71_weight_0_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10070528)))];
            tensor<fp16, [256]> second_71_bias_0_to_fp16 = const()[name = string("second_71_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10594880)))];
            tensor<fp16, [1, 256, 320]> second_71_cast_fp16 = conv(bias = second_71_bias_0_to_fp16, dilations = second_69_dilations_0, groups = second_69_groups_0, pad = second_69_pad_0, pad_type = second_69_pad_type_0, strides = second_69_strides_0, weight = second_71_weight_0_to_fp16, x = input_59_cast_fp16)[name = string("second_71_cast_fp16")];
            tensor<fp16, [1, 256, 320]> first_85_cast_fp16 = add(x = input_51_cast_fp16, y = second_71_cast_fp16)[name = string("first_85_cast_fp16")];
            tensor<fp16, [1, 256, 320]> first_89_cast_fp16 = mul(x = first_85_cast_fp16, y = text_mask)[name = string("first_89_cast_fp16")];
            tensor<int32, [1]> first_87_axes_0 = const()[name = string("first_87_axes_0"), val = tensor<int32, [1]>([2])];
            tensor<fp16, [1, 1, 1, 320]> first_87_cast_fp16 = expand_dims(axes = first_87_axes_0, x = text_mask)[name = string("first_87_cast_fp16")];
            tensor<int32, [1]> second_73_axes_0 = const()[name = string("second_73_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 1, 320, 1]> second_73_cast_fp16 = expand_dims(axes = second_73_axes_0, x = text_mask)[name = string("second_73_cast_fp16")];
            tensor<fp16, [1, 1, 320, 320]> x_45_cast_fp16 = mul(x = first_87_cast_fp16, y = second_73_cast_fp16)[name = string("x_45_cast_fp16")];
            tensor<fp16, [1, 256, 320]> input_61_cast_fp16 = mul(x = first_89_cast_fp16, y = text_mask)[name = string("input_61_cast_fp16")];
            string input_tensor_97_pad_type_0 = const()[name = string("input_tensor_97_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_97_strides_0 = const()[name = string("input_tensor_97_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_97_pad_0 = const()[name = string("input_tensor_97_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_97_dilations_0 = const()[name = string("input_tensor_97_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_97_groups_0 = const()[name = string("input_tensor_97_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_0_conv_q_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_q_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10595456)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_0_conv_q_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_q_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10726592)))];
            tensor<fp16, [1, 256, 320]> input_tensor_97_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_0_conv_q_Conv_bias_to_fp16, dilations = input_tensor_97_dilations_0, groups = input_tensor_97_groups_0, pad = input_tensor_97_pad_0, pad_type = input_tensor_97_pad_type_0, strides = input_tensor_97_strides_0, weight = text_encoder_attn_encoder_attn_layers_0_conv_q_Conv_weight_to_fp16, x = input_61_cast_fp16)[name = string("input_tensor_97_cast_fp16")];
            string input_tensor_89_pad_type_0 = const()[name = string("input_tensor_89_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_89_strides_0 = const()[name = string("input_tensor_89_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_89_pad_0 = const()[name = string("input_tensor_89_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_89_dilations_0 = const()[name = string("input_tensor_89_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_89_groups_0 = const()[name = string("input_tensor_89_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_0_conv_k_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_k_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10727168)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_0_conv_k_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_k_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10858304)))];
            tensor<fp16, [1, 256, 320]> input_tensor_89_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_0_conv_k_Conv_bias_to_fp16, dilations = input_tensor_89_dilations_0, groups = input_tensor_89_groups_0, pad = input_tensor_89_pad_0, pad_type = input_tensor_89_pad_type_0, strides = input_tensor_89_strides_0, weight = text_encoder_attn_encoder_attn_layers_0_conv_k_Conv_weight_to_fp16, x = input_61_cast_fp16)[name = string("input_tensor_89_cast_fp16")];
            string input_tensor_109_pad_type_0 = const()[name = string("input_tensor_109_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_109_strides_0 = const()[name = string("input_tensor_109_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_109_pad_0 = const()[name = string("input_tensor_109_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_109_dilations_0 = const()[name = string("input_tensor_109_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_109_groups_0 = const()[name = string("input_tensor_109_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_0_conv_v_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_v_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10858880)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_0_conv_v_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_v_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10990016)))];
            tensor<fp16, [1, 256, 320]> input_tensor_109_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_0_conv_v_Conv_bias_to_fp16, dilations = input_tensor_109_dilations_0, groups = input_tensor_109_groups_0, pad = input_tensor_109_pad_0, pad_type = input_tensor_109_pad_type_0, strides = input_tensor_109_strides_0, weight = text_encoder_attn_encoder_attn_layers_0_conv_v_Conv_weight_to_fp16, x = input_61_cast_fp16)[name = string("input_tensor_109_cast_fp16")];
            tensor<int32, [4]> var_973 = const()[name = string("op_973"), val = tensor<int32, [4]>([1, 4, 64, 320])];
            tensor<fp16, [1, 4, 64, 320]> input_tensor_105_cast_fp16 = reshape(shape = var_973, x = input_tensor_97_cast_fp16)[name = string("input_tensor_105_cast_fp16")];
            tensor<int32, [4]> var_979 = const()[name = string("op_979"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [4]> var_1005 = const()[name = string("op_1005"), val = tensor<int32, [4]>([1, 4, 64, 320])];
            tensor<fp16, [1, 4, 64, 320]> y_1_cast_fp16 = reshape(shape = var_1005, x = input_tensor_89_cast_fp16)[name = string("y_1_cast_fp16")];
            tensor<int32, [4]> var_1017 = const()[name = string("op_1017"), val = tensor<int32, [4]>([1, 4, 64, 320])];
            tensor<fp16, [1, 4, 64, 320]> input_tensor_111_cast_fp16 = reshape(shape = var_1017, x = input_tensor_109_cast_fp16)[name = string("input_tensor_111_cast_fp16")];
            fp16 _inversed_x_25_y_0_to_fp16 = const()[name = string("_inversed_x_25_y_0_to_fp16"), val = fp16(0x1p-3)];
            tensor<fp16, [1, 4, 320, 64]> first_91_cast_fp16 = transpose(perm = var_979, x = input_tensor_105_cast_fp16)[name = string("transpose_34")];
            tensor<fp16, [1, 4, 320, 64]> _inversed_x_25_cast_fp16 = mul(x = first_91_cast_fp16, y = _inversed_x_25_y_0_to_fp16)[name = string("_inversed_x_25_cast_fp16")];
            bool first_107_transpose_x_0 = const()[name = string("first_107_transpose_x_0"), val = bool(false)];
            bool first_107_transpose_y_0 = const()[name = string("first_107_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 4, 320, 320]> first_107_cast_fp16 = matmul(transpose_x = first_107_transpose_x_0, transpose_y = first_107_transpose_y_0, x = _inversed_x_25_cast_fp16, y = y_1_cast_fp16)[name = string("first_107_cast_fp16")];
            bool input_tensor_143_transpose_x_0 = const()[name = string("input_tensor_143_transpose_x_0"), val = bool(false)];
            bool input_tensor_143_transpose_y_0 = const()[name = string("input_tensor_143_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 64, 639]> y_3_to_fp16 = const()[name = string("y_3_to_fp16"), val = tensor<fp16, [1, 1, 64, 639]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(20297984)))];
            tensor<fp16, [1, 4, 320, 639]> input_tensor_143_cast_fp16 = matmul(transpose_x = input_tensor_143_transpose_x_0, transpose_y = input_tensor_143_transpose_y_0, x = _inversed_x_25_cast_fp16, y = y_3_to_fp16)[name = string("input_tensor_143_cast_fp16")];
            tensor<int32, [8]> input_tensor_165_pad_0 = const()[name = string("input_tensor_165_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 1])];
            string input_tensor_165_mode_0 = const()[name = string("input_tensor_165_mode_0"), val = string("constant")];
            fp16 const_23_to_fp16 = const()[name = string("const_23_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 320, 640]> input_tensor_165_cast_fp16 = pad(constant_val = const_23_to_fp16, mode = input_tensor_165_mode_0, pad = input_tensor_165_pad_0, x = input_tensor_143_cast_fp16)[name = string("input_tensor_165_cast_fp16")];
            tensor<int32, [3]> var_1140 = const()[name = string("op_1140"), val = tensor<int32, [3]>([1, 4, 204800])];
            tensor<fp16, [1, 4, 204800]> input_69_cast_fp16 = reshape(shape = var_1140, x = input_tensor_165_cast_fp16)[name = string("input_69_cast_fp16")];
            tensor<int32, [6]> input_tensor_187_pad_0 = const()[name = string("input_tensor_187_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 0, 319])];
            string input_tensor_187_mode_0 = const()[name = string("input_tensor_187_mode_0"), val = string("constant")];
            fp16 const_24_to_fp16 = const()[name = string("const_24_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 205119]> input_tensor_187_cast_fp16 = pad(constant_val = const_24_to_fp16, mode = input_tensor_187_mode_0, pad = input_tensor_187_pad_0, x = input_69_cast_fp16)[name = string("input_tensor_187_cast_fp16")];
            tensor<int32, [4]> var_1175 = const()[name = string("op_1175"), val = tensor<int32, [4]>([1, 4, 321, 639])];
            tensor<fp16, [1, 4, 321, 639]> x_41_cast_fp16 = reshape(shape = var_1175, x = input_tensor_187_cast_fp16)[name = string("x_41_cast_fp16")];
            tensor<int32, [4]> x_43_begin_0 = const()[name = string("x_43_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> x_43_end_0 = const()[name = string("x_43_end_0"), val = tensor<int32, [4]>([1, 4, 320, 639])];
            tensor<bool, [4]> x_43_end_mask_0 = const()[name = string("x_43_end_mask_0"), val = tensor<bool, [4]>([true, true, false, true])];
            tensor<fp16, [1, 4, 320, 639]> x_43_cast_fp16 = slice_by_index(begin = x_43_begin_0, end = x_43_end_0, end_mask = x_43_end_mask_0, x = x_41_cast_fp16)[name = string("x_43_cast_fp16")];
            tensor<int32, [4]> second_97_begin_0 = const()[name = string("second_97_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 319])];
            tensor<int32, [4]> second_97_end_0 = const()[name = string("second_97_end_0"), val = tensor<int32, [4]>([1, 4, 320, 1])];
            tensor<bool, [4]> second_97_end_mask_0 = const()[name = string("second_97_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 320, 320]> second_97_cast_fp16 = slice_by_index(begin = second_97_begin_0, end = second_97_end_0, end_mask = second_97_end_mask_0, x = x_43_cast_fp16)[name = string("second_97_cast_fp16")];
            tensor<fp16, [1, 4, 320, 320]> y_7_cast_fp16 = add(x = first_107_cast_fp16, y = second_97_cast_fp16)[name = string("y_7_cast_fp16")];
            fp16 text_encoder_attn_encoder_attn_layers_0_Constant_87_value_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_Constant_87_value_to_fp16"), val = fp16(0x0p+0)];
            tensor<bool, [1, 1, 320, 320]> input_tensor_189_cast_fp16 = equal(x = x_45_cast_fp16, y = text_encoder_attn_encoder_attn_layers_0_Constant_87_value_to_fp16)[name = string("input_tensor_189_cast_fp16")];
            tensor<int32, [4]> condition_1_after_broadcast_reps_0 = const()[name = string("condition_1_after_broadcast_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<bool, [1, 4, 320, 320]> condition_1_after_broadcast = tile(reps = condition_1_after_broadcast_reps_0, x = input_tensor_189_cast_fp16)[name = string("condition_1_after_broadcast")];
            tensor<fp16, [1, 4, 320, 320]> text_encoder_attn_encoder_attn_layers_0_Constant_88_value_after_broadcast_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_Constant_88_value_after_broadcast_to_fp16"), val = tensor<fp16, [1, 4, 320, 320]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(20379840)))];
            tensor<fp16, [1, 4, 320, 320]> input_71_cast_fp16 = select(a = text_encoder_attn_encoder_attn_layers_0_Constant_88_value_after_broadcast_to_fp16, b = y_7_cast_fp16, cond = condition_1_after_broadcast)[name = string("input_71_cast_fp16")];
            int32 var_1218 = const()[name = string("op_1218"), val = int32(-1)];
            tensor<fp16, [1, 4, 320, 320]> x_49_cast_fp16 = softmax(axis = var_1218, x = input_71_cast_fp16)[name = string("x_49_cast_fp16")];
            bool first_119_transpose_x_1 = const()[name = string("first_119_transpose_x_1"), val = bool(false)];
            bool first_119_transpose_y_1 = const()[name = string("first_119_transpose_y_1"), val = bool(true)];
            tensor<fp16, [1, 4, 320, 64]> first_119_cast_fp16 = matmul(transpose_x = first_119_transpose_x_1, transpose_y = first_119_transpose_y_1, x = x_49_cast_fp16, y = input_tensor_111_cast_fp16)[name = string("first_119_cast_fp16")];
            tensor<int32, [8]> input_tensor_219_pad_0 = const()[name = string("input_tensor_219_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 319])];
            string input_tensor_219_mode_0 = const()[name = string("input_tensor_219_mode_0"), val = string("constant")];
            fp16 const_31_to_fp16 = const()[name = string("const_31_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 320, 639]> input_tensor_219_cast_fp16 = pad(constant_val = const_31_to_fp16, mode = input_tensor_219_mode_0, pad = input_tensor_219_pad_0, x = x_49_cast_fp16)[name = string("input_tensor_219_cast_fp16")];
            tensor<int32, [3]> var_1292 = const()[name = string("op_1292"), val = tensor<int32, [3]>([1, 4, 204480])];
            tensor<fp16, [1, 4, 204480]> input_73_cast_fp16 = reshape(shape = var_1292, x = input_tensor_219_cast_fp16)[name = string("input_73_cast_fp16")];
            tensor<int32, [6]> input_tensor_237_pad_0 = const()[name = string("input_tensor_237_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 320, 0])];
            string input_tensor_237_mode_0 = const()[name = string("input_tensor_237_mode_0"), val = string("constant")];
            fp16 const_32_to_fp16 = const()[name = string("const_32_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 204800]> input_tensor_237_cast_fp16 = pad(constant_val = const_32_to_fp16, mode = input_tensor_237_mode_0, pad = input_tensor_237_pad_0, x = input_73_cast_fp16)[name = string("input_tensor_237_cast_fp16")];
            tensor<int32, [4]> var_1322 = const()[name = string("op_1322"), val = tensor<int32, [4]>([1, 4, 320, 640])];
            tensor<fp16, [1, 4, 320, 640]> x_59_cast_fp16 = reshape(shape = var_1322, x = input_tensor_237_cast_fp16)[name = string("x_59_cast_fp16")];
            tensor<int32, [4]> x_67_begin_0 = const()[name = string("x_67_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 1])];
            tensor<int32, [4]> x_67_end_0 = const()[name = string("x_67_end_0"), val = tensor<int32, [4]>([1, 4, 320, 1])];
            tensor<bool, [4]> x_67_end_mask_0 = const()[name = string("x_67_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 320, 639]> x_67_cast_fp16 = slice_by_index(begin = x_67_begin_0, end = x_67_end_0, end_mask = x_67_end_mask_0, x = x_59_cast_fp16)[name = string("x_67_cast_fp16")];
            bool second_111_transpose_x_0 = const()[name = string("second_111_transpose_x_0"), val = bool(false)];
            bool second_111_transpose_y_0 = const()[name = string("second_111_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 639, 64]> y_11_to_fp16 = const()[name = string("y_11_to_fp16"), val = tensor<fp16, [1, 1, 639, 64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21199104)))];
            tensor<fp16, [1, 4, 320, 64]> second_111_cast_fp16 = matmul(transpose_x = second_111_transpose_x_0, transpose_y = second_111_transpose_y_0, x = x_67_cast_fp16, y = y_11_to_fp16)[name = string("second_111_cast_fp16")];
            tensor<fp16, [1, 4, 320, 64]> input_tensor_255_cast_fp16 = add(x = first_119_cast_fp16, y = second_111_cast_fp16)[name = string("input_tensor_255_cast_fp16")];
            tensor<int32, [4]> var_1369 = const()[name = string("op_1369"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [3]> var_1388 = const()[name = string("op_1388"), val = tensor<int32, [3]>([1, 256, 320])];
            tensor<fp16, [1, 4, 64, 320]> input_tensor_259_cast_fp16 = transpose(perm = var_1369, x = input_tensor_255_cast_fp16)[name = string("transpose_33")];
            tensor<fp16, [1, 256, 320]> input_77_cast_fp16 = reshape(shape = var_1388, x = input_tensor_259_cast_fp16)[name = string("input_77_cast_fp16")];
            string second_113_pad_type_0 = const()[name = string("second_113_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_113_strides_0 = const()[name = string("second_113_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_113_pad_0 = const()[name = string("second_113_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_113_dilations_0 = const()[name = string("second_113_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_113_groups_0 = const()[name = string("second_113_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_0_conv_o_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_o_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11000768)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_0_conv_o_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_o_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11131904)))];
            tensor<fp16, [1, 256, 320]> second_113_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_0_conv_o_Conv_bias_to_fp16, dilations = second_113_dilations_0, groups = second_113_groups_0, pad = second_113_pad_0, pad_type = second_113_pad_type_0, strides = second_113_strides_0, weight = text_encoder_attn_encoder_attn_layers_0_conv_o_Conv_weight_to_fp16, x = input_77_cast_fp16)[name = string("second_113_cast_fp16")];
            tensor<fp16, [1, 256, 320]> input_tensor_261_cast_fp16 = add(x = input_61_cast_fp16, y = second_113_cast_fp16)[name = string("input_tensor_261_cast_fp16")];
            tensor<int32, [3]> var_1406 = const()[name = string("op_1406"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_263_axes_0 = const()[name = string("input_tensor_263_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_0_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_0_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11132480)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_0_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_0_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11133056)))];
            fp16 var_1409_to_fp16 = const()[name = string("op_1409_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 320, 256]> input_79_cast_fp16 = transpose(perm = var_1406, x = input_tensor_261_cast_fp16)[name = string("transpose_32")];
            tensor<fp16, [1, 320, 256]> input_tensor_263_cast_fp16 = layer_norm(axes = input_tensor_263_axes_0, beta = text_encoder_attn_encoder_norm_layers_1_0_norm_LayerNormalization_bias_to_fp16, epsilon = var_1409_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_1_0_norm_LayerNormalization_weight_to_fp16, x = input_79_cast_fp16)[name = string("input_tensor_263_cast_fp16")];
            tensor<int32, [3]> var_1418 = const()[name = string("op_1418"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 256, 320]> first_121_cast_fp16 = transpose(perm = var_1418, x = input_tensor_263_cast_fp16)[name = string("transpose_31")];
            tensor<fp16, [1, 256, 320]> input_81_cast_fp16 = mul(x = first_121_cast_fp16, y = text_mask)[name = string("input_81_cast_fp16")];
            string input_83_pad_type_0 = const()[name = string("input_83_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_83_strides_0 = const()[name = string("input_83_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_83_pad_0 = const()[name = string("input_83_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_83_dilations_0 = const()[name = string("input_83_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_83_groups_0 = const()[name = string("input_83_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_attn_encoder_ffn_layers_0_conv_1_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_0_conv_1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11133632)))];
            tensor<fp16, [1024]> text_encoder_attn_encoder_ffn_layers_0_conv_1_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_0_conv_1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11657984)))];
            tensor<fp16, [1, 1024, 320]> input_83_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_0_conv_1_Conv_bias_to_fp16, dilations = input_83_dilations_0, groups = input_83_groups_0, pad = input_83_pad_0, pad_type = input_83_pad_type_0, strides = input_83_strides_0, weight = text_encoder_attn_encoder_ffn_layers_0_conv_1_Conv_weight_to_fp16, x = input_81_cast_fp16)[name = string("input_83_cast_fp16")];
            tensor<fp16, [1, 1024, 320]> first_123_cast_fp16 = relu(x = input_83_cast_fp16)[name = string("first_123_cast_fp16")];
            tensor<fp16, [1, 1024, 320]> input_85_cast_fp16 = mul(x = first_123_cast_fp16, y = text_mask)[name = string("input_85_cast_fp16")];
            string first_125_pad_type_0 = const()[name = string("first_125_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_125_strides_0 = const()[name = string("first_125_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_125_pad_0 = const()[name = string("first_125_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_125_dilations_0 = const()[name = string("first_125_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_125_groups_0 = const()[name = string("first_125_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> text_encoder_attn_encoder_ffn_layers_0_conv_2_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_0_conv_2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11660096)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_ffn_layers_0_conv_2_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_0_conv_2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12184448)))];
            tensor<fp16, [1, 256, 320]> first_125_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_0_conv_2_Conv_bias_to_fp16, dilations = first_125_dilations_0, groups = first_125_groups_0, pad = first_125_pad_0, pad_type = first_125_pad_type_0, strides = first_125_strides_0, weight = text_encoder_attn_encoder_ffn_layers_0_conv_2_Conv_weight_to_fp16, x = input_85_cast_fp16)[name = string("first_125_cast_fp16")];
            tensor<fp16, [1, 256, 320]> second_115_cast_fp16 = mul(x = first_125_cast_fp16, y = text_mask)[name = string("second_115_cast_fp16")];
            tensor<fp16, [1, 256, 320]> input_tensor_265_cast_fp16 = add(x = first_121_cast_fp16, y = second_115_cast_fp16)[name = string("input_tensor_265_cast_fp16")];
            tensor<int32, [3]> var_1451 = const()[name = string("op_1451"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_267_axes_0 = const()[name = string("input_tensor_267_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_0_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_0_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12185024)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_0_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_0_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12185600)))];
            fp16 var_1454_to_fp16 = const()[name = string("op_1454_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 320, 256]> input_87_cast_fp16 = transpose(perm = var_1451, x = input_tensor_265_cast_fp16)[name = string("transpose_30")];
            tensor<fp16, [1, 320, 256]> input_tensor_267_cast_fp16 = layer_norm(axes = input_tensor_267_axes_0, beta = text_encoder_attn_encoder_norm_layers_2_0_norm_LayerNormalization_bias_to_fp16, epsilon = var_1454_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_2_0_norm_LayerNormalization_weight_to_fp16, x = input_87_cast_fp16)[name = string("input_tensor_267_cast_fp16")];
            tensor<int32, [3]> var_1463 = const()[name = string("op_1463"), val = tensor<int32, [3]>([0, 2, 1])];
            string input_tensor_277_pad_type_0 = const()[name = string("input_tensor_277_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_277_strides_0 = const()[name = string("input_tensor_277_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_277_pad_0 = const()[name = string("input_tensor_277_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_277_dilations_0 = const()[name = string("input_tensor_277_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_277_groups_0 = const()[name = string("input_tensor_277_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_1_conv_q_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_q_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12186176)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_1_conv_q_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_q_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12317312)))];
            tensor<fp16, [1, 256, 320]> input_89_cast_fp16 = transpose(perm = var_1463, x = input_tensor_267_cast_fp16)[name = string("transpose_29")];
            tensor<fp16, [1, 256, 320]> input_tensor_277_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_1_conv_q_Conv_bias_to_fp16, dilations = input_tensor_277_dilations_0, groups = input_tensor_277_groups_0, pad = input_tensor_277_pad_0, pad_type = input_tensor_277_pad_type_0, strides = input_tensor_277_strides_0, weight = text_encoder_attn_encoder_attn_layers_1_conv_q_Conv_weight_to_fp16, x = input_89_cast_fp16)[name = string("input_tensor_277_cast_fp16")];
            string input_tensor_269_pad_type_0 = const()[name = string("input_tensor_269_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_269_strides_0 = const()[name = string("input_tensor_269_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_269_pad_0 = const()[name = string("input_tensor_269_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_269_dilations_0 = const()[name = string("input_tensor_269_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_269_groups_0 = const()[name = string("input_tensor_269_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_1_conv_k_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_k_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12317888)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_1_conv_k_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_k_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12449024)))];
            tensor<fp16, [1, 256, 320]> input_tensor_269_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_1_conv_k_Conv_bias_to_fp16, dilations = input_tensor_269_dilations_0, groups = input_tensor_269_groups_0, pad = input_tensor_269_pad_0, pad_type = input_tensor_269_pad_type_0, strides = input_tensor_269_strides_0, weight = text_encoder_attn_encoder_attn_layers_1_conv_k_Conv_weight_to_fp16, x = input_89_cast_fp16)[name = string("input_tensor_269_cast_fp16")];
            string input_tensor_289_pad_type_0 = const()[name = string("input_tensor_289_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_289_strides_0 = const()[name = string("input_tensor_289_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_289_pad_0 = const()[name = string("input_tensor_289_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_289_dilations_0 = const()[name = string("input_tensor_289_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_289_groups_0 = const()[name = string("input_tensor_289_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_1_conv_v_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_v_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12449600)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_1_conv_v_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_v_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12580736)))];
            tensor<fp16, [1, 256, 320]> input_tensor_289_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_1_conv_v_Conv_bias_to_fp16, dilations = input_tensor_289_dilations_0, groups = input_tensor_289_groups_0, pad = input_tensor_289_pad_0, pad_type = input_tensor_289_pad_type_0, strides = input_tensor_289_strides_0, weight = text_encoder_attn_encoder_attn_layers_1_conv_v_Conv_weight_to_fp16, x = input_89_cast_fp16)[name = string("input_tensor_289_cast_fp16")];
            tensor<int32, [4]> var_1571 = const()[name = string("op_1571"), val = tensor<int32, [4]>([1, 4, 64, 320])];
            tensor<fp16, [1, 4, 64, 320]> input_tensor_285_cast_fp16 = reshape(shape = var_1571, x = input_tensor_277_cast_fp16)[name = string("input_tensor_285_cast_fp16")];
            tensor<int32, [4]> var_1577 = const()[name = string("op_1577"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [4]> var_1603 = const()[name = string("op_1603"), val = tensor<int32, [4]>([1, 4, 64, 320])];
            tensor<fp16, [1, 4, 64, 320]> y_13_cast_fp16 = reshape(shape = var_1603, x = input_tensor_269_cast_fp16)[name = string("y_13_cast_fp16")];
            tensor<int32, [4]> var_1615 = const()[name = string("op_1615"), val = tensor<int32, [4]>([1, 4, 64, 320])];
            tensor<fp16, [1, 4, 64, 320]> input_tensor_291_cast_fp16 = reshape(shape = var_1615, x = input_tensor_289_cast_fp16)[name = string("input_tensor_291_cast_fp16")];
            fp16 _inversed_x_69_y_0_to_fp16 = const()[name = string("_inversed_x_69_y_0_to_fp16"), val = fp16(0x1p-3)];
            tensor<fp16, [1, 4, 320, 64]> first_127_cast_fp16 = transpose(perm = var_1577, x = input_tensor_285_cast_fp16)[name = string("transpose_28")];
            tensor<fp16, [1, 4, 320, 64]> _inversed_x_69_cast_fp16 = mul(x = first_127_cast_fp16, y = _inversed_x_69_y_0_to_fp16)[name = string("_inversed_x_69_cast_fp16")];
            bool first_143_transpose_x_0 = const()[name = string("first_143_transpose_x_0"), val = bool(false)];
            bool first_143_transpose_y_0 = const()[name = string("first_143_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 4, 320, 320]> first_143_cast_fp16 = matmul(transpose_x = first_143_transpose_x_0, transpose_y = first_143_transpose_y_0, x = _inversed_x_69_cast_fp16, y = y_13_cast_fp16)[name = string("first_143_cast_fp16")];
            bool input_tensor_323_transpose_x_0 = const()[name = string("input_tensor_323_transpose_x_0"), val = bool(false)];
            bool input_tensor_323_transpose_y_0 = const()[name = string("input_tensor_323_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 64, 639]> y_15_to_fp16 = const()[name = string("y_15_to_fp16"), val = tensor<fp16, [1, 1, 64, 639]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21280960)))];
            tensor<fp16, [1, 4, 320, 639]> input_tensor_323_cast_fp16 = matmul(transpose_x = input_tensor_323_transpose_x_0, transpose_y = input_tensor_323_transpose_y_0, x = _inversed_x_69_cast_fp16, y = y_15_to_fp16)[name = string("input_tensor_323_cast_fp16")];
            tensor<int32, [8]> input_tensor_345_pad_0 = const()[name = string("input_tensor_345_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 1])];
            string input_tensor_345_mode_0 = const()[name = string("input_tensor_345_mode_0"), val = string("constant")];
            fp16 const_51_to_fp16 = const()[name = string("const_51_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 320, 640]> input_tensor_345_cast_fp16 = pad(constant_val = const_51_to_fp16, mode = input_tensor_345_mode_0, pad = input_tensor_345_pad_0, x = input_tensor_323_cast_fp16)[name = string("input_tensor_345_cast_fp16")];
            tensor<int32, [3]> var_1738 = const()[name = string("op_1738"), val = tensor<int32, [3]>([1, 4, 204800])];
            tensor<fp16, [1, 4, 204800]> input_97_cast_fp16 = reshape(shape = var_1738, x = input_tensor_345_cast_fp16)[name = string("input_97_cast_fp16")];
            tensor<int32, [6]> input_tensor_367_pad_0 = const()[name = string("input_tensor_367_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 0, 319])];
            string input_tensor_367_mode_0 = const()[name = string("input_tensor_367_mode_0"), val = string("constant")];
            fp16 const_52_to_fp16 = const()[name = string("const_52_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 205119]> input_tensor_367_cast_fp16 = pad(constant_val = const_52_to_fp16, mode = input_tensor_367_mode_0, pad = input_tensor_367_pad_0, x = input_97_cast_fp16)[name = string("input_tensor_367_cast_fp16")];
            tensor<int32, [4]> var_1773 = const()[name = string("op_1773"), val = tensor<int32, [4]>([1, 4, 321, 639])];
            tensor<fp16, [1, 4, 321, 639]> x_85_cast_fp16 = reshape(shape = var_1773, x = input_tensor_367_cast_fp16)[name = string("x_85_cast_fp16")];
            tensor<int32, [4]> x_87_begin_0 = const()[name = string("x_87_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> x_87_end_0 = const()[name = string("x_87_end_0"), val = tensor<int32, [4]>([1, 4, 320, 639])];
            tensor<bool, [4]> x_87_end_mask_0 = const()[name = string("x_87_end_mask_0"), val = tensor<bool, [4]>([true, true, false, true])];
            tensor<fp16, [1, 4, 320, 639]> x_87_cast_fp16 = slice_by_index(begin = x_87_begin_0, end = x_87_end_0, end_mask = x_87_end_mask_0, x = x_85_cast_fp16)[name = string("x_87_cast_fp16")];
            tensor<int32, [4]> second_139_begin_0 = const()[name = string("second_139_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 319])];
            tensor<int32, [4]> second_139_end_0 = const()[name = string("second_139_end_0"), val = tensor<int32, [4]>([1, 4, 320, 1])];
            tensor<bool, [4]> second_139_end_mask_0 = const()[name = string("second_139_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 320, 320]> second_139_cast_fp16 = slice_by_index(begin = second_139_begin_0, end = second_139_end_0, end_mask = second_139_end_mask_0, x = x_87_cast_fp16)[name = string("second_139_cast_fp16")];
            tensor<fp16, [1, 4, 320, 320]> y_17_cast_fp16 = add(x = first_143_cast_fp16, y = second_139_cast_fp16)[name = string("y_17_cast_fp16")];
            tensor<fp16, [1, 4, 320, 320]> input_99_cast_fp16 = select(a = text_encoder_attn_encoder_attn_layers_0_Constant_88_value_after_broadcast_to_fp16, b = y_17_cast_fp16, cond = condition_1_after_broadcast)[name = string("input_99_cast_fp16")];
            int32 var_1815 = const()[name = string("op_1815"), val = int32(-1)];
            tensor<fp16, [1, 4, 320, 320]> x_91_cast_fp16 = softmax(axis = var_1815, x = input_99_cast_fp16)[name = string("x_91_cast_fp16")];
            bool first_155_transpose_x_1 = const()[name = string("first_155_transpose_x_1"), val = bool(false)];
            bool first_155_transpose_y_1 = const()[name = string("first_155_transpose_y_1"), val = bool(true)];
            tensor<fp16, [1, 4, 320, 64]> first_155_cast_fp16 = matmul(transpose_x = first_155_transpose_x_1, transpose_y = first_155_transpose_y_1, x = x_91_cast_fp16, y = input_tensor_291_cast_fp16)[name = string("first_155_cast_fp16")];
            tensor<int32, [8]> input_tensor_397_pad_0 = const()[name = string("input_tensor_397_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 319])];
            string input_tensor_397_mode_0 = const()[name = string("input_tensor_397_mode_0"), val = string("constant")];
            fp16 const_59_to_fp16 = const()[name = string("const_59_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 320, 639]> input_tensor_397_cast_fp16 = pad(constant_val = const_59_to_fp16, mode = input_tensor_397_mode_0, pad = input_tensor_397_pad_0, x = x_91_cast_fp16)[name = string("input_tensor_397_cast_fp16")];
            tensor<int32, [3]> var_1889 = const()[name = string("op_1889"), val = tensor<int32, [3]>([1, 4, 204480])];
            tensor<fp16, [1, 4, 204480]> input_101_cast_fp16 = reshape(shape = var_1889, x = input_tensor_397_cast_fp16)[name = string("input_101_cast_fp16")];
            tensor<int32, [6]> input_tensor_415_pad_0 = const()[name = string("input_tensor_415_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 320, 0])];
            string input_tensor_415_mode_0 = const()[name = string("input_tensor_415_mode_0"), val = string("constant")];
            fp16 const_60_to_fp16 = const()[name = string("const_60_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 204800]> input_tensor_415_cast_fp16 = pad(constant_val = const_60_to_fp16, mode = input_tensor_415_mode_0, pad = input_tensor_415_pad_0, x = input_101_cast_fp16)[name = string("input_tensor_415_cast_fp16")];
            tensor<int32, [4]> var_1919 = const()[name = string("op_1919"), val = tensor<int32, [4]>([1, 4, 320, 640])];
            tensor<fp16, [1, 4, 320, 640]> x_101_cast_fp16 = reshape(shape = var_1919, x = input_tensor_415_cast_fp16)[name = string("x_101_cast_fp16")];
            tensor<int32, [4]> x_109_begin_0 = const()[name = string("x_109_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 1])];
            tensor<int32, [4]> x_109_end_0 = const()[name = string("x_109_end_0"), val = tensor<int32, [4]>([1, 4, 320, 1])];
            tensor<bool, [4]> x_109_end_mask_0 = const()[name = string("x_109_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 320, 639]> x_109_cast_fp16 = slice_by_index(begin = x_109_begin_0, end = x_109_end_0, end_mask = x_109_end_mask_0, x = x_101_cast_fp16)[name = string("x_109_cast_fp16")];
            bool second_153_transpose_x_0 = const()[name = string("second_153_transpose_x_0"), val = bool(false)];
            bool second_153_transpose_y_0 = const()[name = string("second_153_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 639, 64]> y_21_to_fp16 = const()[name = string("y_21_to_fp16"), val = tensor<fp16, [1, 1, 639, 64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21362816)))];
            tensor<fp16, [1, 4, 320, 64]> second_153_cast_fp16 = matmul(transpose_x = second_153_transpose_x_0, transpose_y = second_153_transpose_y_0, x = x_109_cast_fp16, y = y_21_to_fp16)[name = string("second_153_cast_fp16")];
            tensor<fp16, [1, 4, 320, 64]> input_tensor_433_cast_fp16 = add(x = first_155_cast_fp16, y = second_153_cast_fp16)[name = string("input_tensor_433_cast_fp16")];
            tensor<int32, [4]> var_1966 = const()[name = string("op_1966"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [3]> var_1985 = const()[name = string("op_1985"), val = tensor<int32, [3]>([1, 256, 320])];
            tensor<fp16, [1, 4, 64, 320]> input_tensor_437_cast_fp16 = transpose(perm = var_1966, x = input_tensor_433_cast_fp16)[name = string("transpose_27")];
            tensor<fp16, [1, 256, 320]> input_105_cast_fp16 = reshape(shape = var_1985, x = input_tensor_437_cast_fp16)[name = string("input_105_cast_fp16")];
            string second_155_pad_type_0 = const()[name = string("second_155_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_155_strides_0 = const()[name = string("second_155_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_155_pad_0 = const()[name = string("second_155_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_155_dilations_0 = const()[name = string("second_155_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_155_groups_0 = const()[name = string("second_155_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_1_conv_o_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_o_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12589376)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_1_conv_o_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_o_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12720512)))];
            tensor<fp16, [1, 256, 320]> second_155_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_1_conv_o_Conv_bias_to_fp16, dilations = second_155_dilations_0, groups = second_155_groups_0, pad = second_155_pad_0, pad_type = second_155_pad_type_0, strides = second_155_strides_0, weight = text_encoder_attn_encoder_attn_layers_1_conv_o_Conv_weight_to_fp16, x = input_105_cast_fp16)[name = string("second_155_cast_fp16")];
            tensor<fp16, [1, 256, 320]> input_tensor_439_cast_fp16 = add(x = input_89_cast_fp16, y = second_155_cast_fp16)[name = string("input_tensor_439_cast_fp16")];
            tensor<int32, [3]> var_2003 = const()[name = string("op_2003"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_441_axes_0 = const()[name = string("input_tensor_441_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_1_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_1_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12721088)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_1_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_1_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12721664)))];
            fp16 var_2006_to_fp16 = const()[name = string("op_2006_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 320, 256]> input_107_cast_fp16 = transpose(perm = var_2003, x = input_tensor_439_cast_fp16)[name = string("transpose_26")];
            tensor<fp16, [1, 320, 256]> input_tensor_441_cast_fp16 = layer_norm(axes = input_tensor_441_axes_0, beta = text_encoder_attn_encoder_norm_layers_1_1_norm_LayerNormalization_bias_to_fp16, epsilon = var_2006_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_1_1_norm_LayerNormalization_weight_to_fp16, x = input_107_cast_fp16)[name = string("input_tensor_441_cast_fp16")];
            tensor<int32, [3]> var_2015 = const()[name = string("op_2015"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 256, 320]> first_157_cast_fp16 = transpose(perm = var_2015, x = input_tensor_441_cast_fp16)[name = string("transpose_25")];
            tensor<fp16, [1, 256, 320]> input_109_cast_fp16 = mul(x = first_157_cast_fp16, y = text_mask)[name = string("input_109_cast_fp16")];
            string input_111_pad_type_0 = const()[name = string("input_111_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_111_strides_0 = const()[name = string("input_111_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_111_pad_0 = const()[name = string("input_111_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_111_dilations_0 = const()[name = string("input_111_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_111_groups_0 = const()[name = string("input_111_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_attn_encoder_ffn_layers_1_conv_1_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_1_conv_1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12722240)))];
            tensor<fp16, [1024]> text_encoder_attn_encoder_ffn_layers_1_conv_1_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_1_conv_1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13246592)))];
            tensor<fp16, [1, 1024, 320]> input_111_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_1_conv_1_Conv_bias_to_fp16, dilations = input_111_dilations_0, groups = input_111_groups_0, pad = input_111_pad_0, pad_type = input_111_pad_type_0, strides = input_111_strides_0, weight = text_encoder_attn_encoder_ffn_layers_1_conv_1_Conv_weight_to_fp16, x = input_109_cast_fp16)[name = string("input_111_cast_fp16")];
            tensor<fp16, [1, 1024, 320]> first_159_cast_fp16 = relu(x = input_111_cast_fp16)[name = string("first_159_cast_fp16")];
            tensor<fp16, [1, 1024, 320]> input_113_cast_fp16 = mul(x = first_159_cast_fp16, y = text_mask)[name = string("input_113_cast_fp16")];
            string first_161_pad_type_0 = const()[name = string("first_161_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_161_strides_0 = const()[name = string("first_161_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_161_pad_0 = const()[name = string("first_161_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_161_dilations_0 = const()[name = string("first_161_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_161_groups_0 = const()[name = string("first_161_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> text_encoder_attn_encoder_ffn_layers_1_conv_2_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_1_conv_2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13248704)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_ffn_layers_1_conv_2_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_1_conv_2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13773056)))];
            tensor<fp16, [1, 256, 320]> first_161_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_1_conv_2_Conv_bias_to_fp16, dilations = first_161_dilations_0, groups = first_161_groups_0, pad = first_161_pad_0, pad_type = first_161_pad_type_0, strides = first_161_strides_0, weight = text_encoder_attn_encoder_ffn_layers_1_conv_2_Conv_weight_to_fp16, x = input_113_cast_fp16)[name = string("first_161_cast_fp16")];
            tensor<fp16, [1, 256, 320]> second_157_cast_fp16 = mul(x = first_161_cast_fp16, y = text_mask)[name = string("second_157_cast_fp16")];
            tensor<fp16, [1, 256, 320]> input_tensor_443_cast_fp16 = add(x = first_157_cast_fp16, y = second_157_cast_fp16)[name = string("input_tensor_443_cast_fp16")];
            tensor<int32, [3]> var_2048 = const()[name = string("op_2048"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_445_axes_0 = const()[name = string("input_tensor_445_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_1_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_1_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13773632)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_1_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_1_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13774208)))];
            fp16 var_2051_to_fp16 = const()[name = string("op_2051_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 320, 256]> input_115_cast_fp16 = transpose(perm = var_2048, x = input_tensor_443_cast_fp16)[name = string("transpose_24")];
            tensor<fp16, [1, 320, 256]> input_tensor_445_cast_fp16 = layer_norm(axes = input_tensor_445_axes_0, beta = text_encoder_attn_encoder_norm_layers_2_1_norm_LayerNormalization_bias_to_fp16, epsilon = var_2051_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_2_1_norm_LayerNormalization_weight_to_fp16, x = input_115_cast_fp16)[name = string("input_tensor_445_cast_fp16")];
            tensor<int32, [3]> var_2060 = const()[name = string("op_2060"), val = tensor<int32, [3]>([0, 2, 1])];
            string input_tensor_455_pad_type_0 = const()[name = string("input_tensor_455_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_455_strides_0 = const()[name = string("input_tensor_455_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_455_pad_0 = const()[name = string("input_tensor_455_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_455_dilations_0 = const()[name = string("input_tensor_455_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_455_groups_0 = const()[name = string("input_tensor_455_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_2_conv_q_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_q_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13774784)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_2_conv_q_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_q_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13905920)))];
            tensor<fp16, [1, 256, 320]> input_117_cast_fp16 = transpose(perm = var_2060, x = input_tensor_445_cast_fp16)[name = string("transpose_23")];
            tensor<fp16, [1, 256, 320]> input_tensor_455_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_2_conv_q_Conv_bias_to_fp16, dilations = input_tensor_455_dilations_0, groups = input_tensor_455_groups_0, pad = input_tensor_455_pad_0, pad_type = input_tensor_455_pad_type_0, strides = input_tensor_455_strides_0, weight = text_encoder_attn_encoder_attn_layers_2_conv_q_Conv_weight_to_fp16, x = input_117_cast_fp16)[name = string("input_tensor_455_cast_fp16")];
            string input_tensor_447_pad_type_0 = const()[name = string("input_tensor_447_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_447_strides_0 = const()[name = string("input_tensor_447_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_447_pad_0 = const()[name = string("input_tensor_447_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_447_dilations_0 = const()[name = string("input_tensor_447_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_447_groups_0 = const()[name = string("input_tensor_447_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_2_conv_k_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_k_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13906496)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_2_conv_k_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_k_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14037632)))];
            tensor<fp16, [1, 256, 320]> input_tensor_447_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_2_conv_k_Conv_bias_to_fp16, dilations = input_tensor_447_dilations_0, groups = input_tensor_447_groups_0, pad = input_tensor_447_pad_0, pad_type = input_tensor_447_pad_type_0, strides = input_tensor_447_strides_0, weight = text_encoder_attn_encoder_attn_layers_2_conv_k_Conv_weight_to_fp16, x = input_117_cast_fp16)[name = string("input_tensor_447_cast_fp16")];
            string input_tensor_467_pad_type_0 = const()[name = string("input_tensor_467_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_467_strides_0 = const()[name = string("input_tensor_467_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_467_pad_0 = const()[name = string("input_tensor_467_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_467_dilations_0 = const()[name = string("input_tensor_467_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_467_groups_0 = const()[name = string("input_tensor_467_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_2_conv_v_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_v_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14038208)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_2_conv_v_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_v_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14169344)))];
            tensor<fp16, [1, 256, 320]> input_tensor_467_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_2_conv_v_Conv_bias_to_fp16, dilations = input_tensor_467_dilations_0, groups = input_tensor_467_groups_0, pad = input_tensor_467_pad_0, pad_type = input_tensor_467_pad_type_0, strides = input_tensor_467_strides_0, weight = text_encoder_attn_encoder_attn_layers_2_conv_v_Conv_weight_to_fp16, x = input_117_cast_fp16)[name = string("input_tensor_467_cast_fp16")];
            tensor<int32, [4]> var_2168 = const()[name = string("op_2168"), val = tensor<int32, [4]>([1, 4, 64, 320])];
            tensor<fp16, [1, 4, 64, 320]> input_tensor_463_cast_fp16 = reshape(shape = var_2168, x = input_tensor_455_cast_fp16)[name = string("input_tensor_463_cast_fp16")];
            tensor<int32, [4]> var_2174 = const()[name = string("op_2174"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [4]> var_2200 = const()[name = string("op_2200"), val = tensor<int32, [4]>([1, 4, 64, 320])];
            tensor<fp16, [1, 4, 64, 320]> y_23_cast_fp16 = reshape(shape = var_2200, x = input_tensor_447_cast_fp16)[name = string("y_23_cast_fp16")];
            tensor<int32, [4]> var_2212 = const()[name = string("op_2212"), val = tensor<int32, [4]>([1, 4, 64, 320])];
            tensor<fp16, [1, 4, 64, 320]> input_tensor_469_cast_fp16 = reshape(shape = var_2212, x = input_tensor_467_cast_fp16)[name = string("input_tensor_469_cast_fp16")];
            fp16 _inversed_x_111_y_0_to_fp16 = const()[name = string("_inversed_x_111_y_0_to_fp16"), val = fp16(0x1p-3)];
            tensor<fp16, [1, 4, 320, 64]> first_163_cast_fp16 = transpose(perm = var_2174, x = input_tensor_463_cast_fp16)[name = string("transpose_22")];
            tensor<fp16, [1, 4, 320, 64]> _inversed_x_111_cast_fp16 = mul(x = first_163_cast_fp16, y = _inversed_x_111_y_0_to_fp16)[name = string("_inversed_x_111_cast_fp16")];
            bool first_179_transpose_x_0 = const()[name = string("first_179_transpose_x_0"), val = bool(false)];
            bool first_179_transpose_y_0 = const()[name = string("first_179_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 4, 320, 320]> first_179_cast_fp16 = matmul(transpose_x = first_179_transpose_x_0, transpose_y = first_179_transpose_y_0, x = _inversed_x_111_cast_fp16, y = y_23_cast_fp16)[name = string("first_179_cast_fp16")];
            bool input_tensor_501_transpose_x_0 = const()[name = string("input_tensor_501_transpose_x_0"), val = bool(false)];
            bool input_tensor_501_transpose_y_0 = const()[name = string("input_tensor_501_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 64, 639]> y_25_to_fp16 = const()[name = string("y_25_to_fp16"), val = tensor<fp16, [1, 1, 64, 639]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21444672)))];
            tensor<fp16, [1, 4, 320, 639]> input_tensor_501_cast_fp16 = matmul(transpose_x = input_tensor_501_transpose_x_0, transpose_y = input_tensor_501_transpose_y_0, x = _inversed_x_111_cast_fp16, y = y_25_to_fp16)[name = string("input_tensor_501_cast_fp16")];
            tensor<int32, [8]> input_tensor_523_pad_0 = const()[name = string("input_tensor_523_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 1])];
            string input_tensor_523_mode_0 = const()[name = string("input_tensor_523_mode_0"), val = string("constant")];
            fp16 const_79_to_fp16 = const()[name = string("const_79_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 320, 640]> input_tensor_523_cast_fp16 = pad(constant_val = const_79_to_fp16, mode = input_tensor_523_mode_0, pad = input_tensor_523_pad_0, x = input_tensor_501_cast_fp16)[name = string("input_tensor_523_cast_fp16")];
            tensor<int32, [3]> var_2335 = const()[name = string("op_2335"), val = tensor<int32, [3]>([1, 4, 204800])];
            tensor<fp16, [1, 4, 204800]> input_125_cast_fp16 = reshape(shape = var_2335, x = input_tensor_523_cast_fp16)[name = string("input_125_cast_fp16")];
            tensor<int32, [6]> input_tensor_545_pad_0 = const()[name = string("input_tensor_545_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 0, 319])];
            string input_tensor_545_mode_0 = const()[name = string("input_tensor_545_mode_0"), val = string("constant")];
            fp16 const_80_to_fp16 = const()[name = string("const_80_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 205119]> input_tensor_545_cast_fp16 = pad(constant_val = const_80_to_fp16, mode = input_tensor_545_mode_0, pad = input_tensor_545_pad_0, x = input_125_cast_fp16)[name = string("input_tensor_545_cast_fp16")];
            tensor<int32, [4]> var_2370 = const()[name = string("op_2370"), val = tensor<int32, [4]>([1, 4, 321, 639])];
            tensor<fp16, [1, 4, 321, 639]> x_127_cast_fp16 = reshape(shape = var_2370, x = input_tensor_545_cast_fp16)[name = string("x_127_cast_fp16")];
            tensor<int32, [4]> x_129_begin_0 = const()[name = string("x_129_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> x_129_end_0 = const()[name = string("x_129_end_0"), val = tensor<int32, [4]>([1, 4, 320, 639])];
            tensor<bool, [4]> x_129_end_mask_0 = const()[name = string("x_129_end_mask_0"), val = tensor<bool, [4]>([true, true, false, true])];
            tensor<fp16, [1, 4, 320, 639]> x_129_cast_fp16 = slice_by_index(begin = x_129_begin_0, end = x_129_end_0, end_mask = x_129_end_mask_0, x = x_127_cast_fp16)[name = string("x_129_cast_fp16")];
            tensor<int32, [4]> second_181_begin_0 = const()[name = string("second_181_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 319])];
            tensor<int32, [4]> second_181_end_0 = const()[name = string("second_181_end_0"), val = tensor<int32, [4]>([1, 4, 320, 1])];
            tensor<bool, [4]> second_181_end_mask_0 = const()[name = string("second_181_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 320, 320]> second_181_cast_fp16 = slice_by_index(begin = second_181_begin_0, end = second_181_end_0, end_mask = second_181_end_mask_0, x = x_129_cast_fp16)[name = string("second_181_cast_fp16")];
            tensor<fp16, [1, 4, 320, 320]> y_27_cast_fp16 = add(x = first_179_cast_fp16, y = second_181_cast_fp16)[name = string("y_27_cast_fp16")];
            tensor<fp16, [1, 4, 320, 320]> input_127_cast_fp16 = select(a = text_encoder_attn_encoder_attn_layers_0_Constant_88_value_after_broadcast_to_fp16, b = y_27_cast_fp16, cond = condition_1_after_broadcast)[name = string("input_127_cast_fp16")];
            int32 var_2412 = const()[name = string("op_2412"), val = int32(-1)];
            tensor<fp16, [1, 4, 320, 320]> x_133_cast_fp16 = softmax(axis = var_2412, x = input_127_cast_fp16)[name = string("x_133_cast_fp16")];
            bool first_191_transpose_x_1 = const()[name = string("first_191_transpose_x_1"), val = bool(false)];
            bool first_191_transpose_y_1 = const()[name = string("first_191_transpose_y_1"), val = bool(true)];
            tensor<fp16, [1, 4, 320, 64]> first_191_cast_fp16 = matmul(transpose_x = first_191_transpose_x_1, transpose_y = first_191_transpose_y_1, x = x_133_cast_fp16, y = input_tensor_469_cast_fp16)[name = string("first_191_cast_fp16")];
            tensor<int32, [8]> input_tensor_575_pad_0 = const()[name = string("input_tensor_575_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 319])];
            string input_tensor_575_mode_0 = const()[name = string("input_tensor_575_mode_0"), val = string("constant")];
            fp16 const_87_to_fp16 = const()[name = string("const_87_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 320, 639]> input_tensor_575_cast_fp16 = pad(constant_val = const_87_to_fp16, mode = input_tensor_575_mode_0, pad = input_tensor_575_pad_0, x = x_133_cast_fp16)[name = string("input_tensor_575_cast_fp16")];
            tensor<int32, [3]> var_2486 = const()[name = string("op_2486"), val = tensor<int32, [3]>([1, 4, 204480])];
            tensor<fp16, [1, 4, 204480]> input_129_cast_fp16 = reshape(shape = var_2486, x = input_tensor_575_cast_fp16)[name = string("input_129_cast_fp16")];
            tensor<int32, [6]> input_tensor_593_pad_0 = const()[name = string("input_tensor_593_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 320, 0])];
            string input_tensor_593_mode_0 = const()[name = string("input_tensor_593_mode_0"), val = string("constant")];
            fp16 const_88_to_fp16 = const()[name = string("const_88_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 204800]> input_tensor_593_cast_fp16 = pad(constant_val = const_88_to_fp16, mode = input_tensor_593_mode_0, pad = input_tensor_593_pad_0, x = input_129_cast_fp16)[name = string("input_tensor_593_cast_fp16")];
            tensor<int32, [4]> var_2516 = const()[name = string("op_2516"), val = tensor<int32, [4]>([1, 4, 320, 640])];
            tensor<fp16, [1, 4, 320, 640]> x_143_cast_fp16 = reshape(shape = var_2516, x = input_tensor_593_cast_fp16)[name = string("x_143_cast_fp16")];
            tensor<int32, [4]> x_151_begin_0 = const()[name = string("x_151_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 1])];
            tensor<int32, [4]> x_151_end_0 = const()[name = string("x_151_end_0"), val = tensor<int32, [4]>([1, 4, 320, 1])];
            tensor<bool, [4]> x_151_end_mask_0 = const()[name = string("x_151_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 320, 639]> x_151_cast_fp16 = slice_by_index(begin = x_151_begin_0, end = x_151_end_0, end_mask = x_151_end_mask_0, x = x_143_cast_fp16)[name = string("x_151_cast_fp16")];
            bool second_195_transpose_x_0 = const()[name = string("second_195_transpose_x_0"), val = bool(false)];
            bool second_195_transpose_y_0 = const()[name = string("second_195_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 639, 64]> y_31_to_fp16 = const()[name = string("y_31_to_fp16"), val = tensor<fp16, [1, 1, 639, 64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21526528)))];
            tensor<fp16, [1, 4, 320, 64]> second_195_cast_fp16 = matmul(transpose_x = second_195_transpose_x_0, transpose_y = second_195_transpose_y_0, x = x_151_cast_fp16, y = y_31_to_fp16)[name = string("second_195_cast_fp16")];
            tensor<fp16, [1, 4, 320, 64]> input_tensor_611_cast_fp16 = add(x = first_191_cast_fp16, y = second_195_cast_fp16)[name = string("input_tensor_611_cast_fp16")];
            tensor<int32, [4]> var_2563 = const()[name = string("op_2563"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [3]> var_2582 = const()[name = string("op_2582"), val = tensor<int32, [3]>([1, 256, 320])];
            tensor<fp16, [1, 4, 64, 320]> input_tensor_615_cast_fp16 = transpose(perm = var_2563, x = input_tensor_611_cast_fp16)[name = string("transpose_21")];
            tensor<fp16, [1, 256, 320]> input_133_cast_fp16 = reshape(shape = var_2582, x = input_tensor_615_cast_fp16)[name = string("input_133_cast_fp16")];
            string second_197_pad_type_0 = const()[name = string("second_197_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_197_strides_0 = const()[name = string("second_197_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_197_pad_0 = const()[name = string("second_197_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_197_dilations_0 = const()[name = string("second_197_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_197_groups_0 = const()[name = string("second_197_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_2_conv_o_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_o_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14177984)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_2_conv_o_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_o_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14309120)))];
            tensor<fp16, [1, 256, 320]> second_197_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_2_conv_o_Conv_bias_to_fp16, dilations = second_197_dilations_0, groups = second_197_groups_0, pad = second_197_pad_0, pad_type = second_197_pad_type_0, strides = second_197_strides_0, weight = text_encoder_attn_encoder_attn_layers_2_conv_o_Conv_weight_to_fp16, x = input_133_cast_fp16)[name = string("second_197_cast_fp16")];
            tensor<fp16, [1, 256, 320]> input_tensor_617_cast_fp16 = add(x = input_117_cast_fp16, y = second_197_cast_fp16)[name = string("input_tensor_617_cast_fp16")];
            tensor<int32, [3]> var_2600 = const()[name = string("op_2600"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_619_axes_0 = const()[name = string("input_tensor_619_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_2_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_2_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14309696)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_2_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_2_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14310272)))];
            fp16 var_2603_to_fp16 = const()[name = string("op_2603_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 320, 256]> input_135_cast_fp16 = transpose(perm = var_2600, x = input_tensor_617_cast_fp16)[name = string("transpose_20")];
            tensor<fp16, [1, 320, 256]> input_tensor_619_cast_fp16 = layer_norm(axes = input_tensor_619_axes_0, beta = text_encoder_attn_encoder_norm_layers_1_2_norm_LayerNormalization_bias_to_fp16, epsilon = var_2603_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_1_2_norm_LayerNormalization_weight_to_fp16, x = input_135_cast_fp16)[name = string("input_tensor_619_cast_fp16")];
            tensor<int32, [3]> var_2612 = const()[name = string("op_2612"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 256, 320]> first_193_cast_fp16 = transpose(perm = var_2612, x = input_tensor_619_cast_fp16)[name = string("transpose_19")];
            tensor<fp16, [1, 256, 320]> input_137_cast_fp16 = mul(x = first_193_cast_fp16, y = text_mask)[name = string("input_137_cast_fp16")];
            string input_139_pad_type_0 = const()[name = string("input_139_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_139_strides_0 = const()[name = string("input_139_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_139_pad_0 = const()[name = string("input_139_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_139_dilations_0 = const()[name = string("input_139_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_139_groups_0 = const()[name = string("input_139_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_attn_encoder_ffn_layers_2_conv_1_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_2_conv_1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14310848)))];
            tensor<fp16, [1024]> text_encoder_attn_encoder_ffn_layers_2_conv_1_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_2_conv_1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14835200)))];
            tensor<fp16, [1, 1024, 320]> input_139_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_2_conv_1_Conv_bias_to_fp16, dilations = input_139_dilations_0, groups = input_139_groups_0, pad = input_139_pad_0, pad_type = input_139_pad_type_0, strides = input_139_strides_0, weight = text_encoder_attn_encoder_ffn_layers_2_conv_1_Conv_weight_to_fp16, x = input_137_cast_fp16)[name = string("input_139_cast_fp16")];
            tensor<fp16, [1, 1024, 320]> first_195_cast_fp16 = relu(x = input_139_cast_fp16)[name = string("first_195_cast_fp16")];
            tensor<fp16, [1, 1024, 320]> input_141_cast_fp16 = mul(x = first_195_cast_fp16, y = text_mask)[name = string("input_141_cast_fp16")];
            string first_197_pad_type_0 = const()[name = string("first_197_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_197_strides_0 = const()[name = string("first_197_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_197_pad_0 = const()[name = string("first_197_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_197_dilations_0 = const()[name = string("first_197_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_197_groups_0 = const()[name = string("first_197_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> text_encoder_attn_encoder_ffn_layers_2_conv_2_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_2_conv_2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14837312)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_ffn_layers_2_conv_2_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_2_conv_2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15361664)))];
            tensor<fp16, [1, 256, 320]> first_197_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_2_conv_2_Conv_bias_to_fp16, dilations = first_197_dilations_0, groups = first_197_groups_0, pad = first_197_pad_0, pad_type = first_197_pad_type_0, strides = first_197_strides_0, weight = text_encoder_attn_encoder_ffn_layers_2_conv_2_Conv_weight_to_fp16, x = input_141_cast_fp16)[name = string("first_197_cast_fp16")];
            tensor<fp16, [1, 256, 320]> second_199_cast_fp16 = mul(x = first_197_cast_fp16, y = text_mask)[name = string("second_199_cast_fp16")];
            tensor<fp16, [1, 256, 320]> input_tensor_621_cast_fp16 = add(x = first_193_cast_fp16, y = second_199_cast_fp16)[name = string("input_tensor_621_cast_fp16")];
            tensor<int32, [3]> var_2645 = const()[name = string("op_2645"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_623_axes_0 = const()[name = string("input_tensor_623_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_2_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_2_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15362240)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_2_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_2_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15362816)))];
            fp16 var_2648_to_fp16 = const()[name = string("op_2648_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 320, 256]> input_143_cast_fp16 = transpose(perm = var_2645, x = input_tensor_621_cast_fp16)[name = string("transpose_18")];
            tensor<fp16, [1, 320, 256]> input_tensor_623_cast_fp16 = layer_norm(axes = input_tensor_623_axes_0, beta = text_encoder_attn_encoder_norm_layers_2_2_norm_LayerNormalization_bias_to_fp16, epsilon = var_2648_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_2_2_norm_LayerNormalization_weight_to_fp16, x = input_143_cast_fp16)[name = string("input_tensor_623_cast_fp16")];
            tensor<int32, [3]> var_2657 = const()[name = string("op_2657"), val = tensor<int32, [3]>([0, 2, 1])];
            string input_tensor_633_pad_type_0 = const()[name = string("input_tensor_633_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_633_strides_0 = const()[name = string("input_tensor_633_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_633_pad_0 = const()[name = string("input_tensor_633_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_633_dilations_0 = const()[name = string("input_tensor_633_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_633_groups_0 = const()[name = string("input_tensor_633_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_3_conv_q_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_q_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15363392)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_3_conv_q_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_q_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15494528)))];
            tensor<fp16, [1, 256, 320]> input_145_cast_fp16 = transpose(perm = var_2657, x = input_tensor_623_cast_fp16)[name = string("transpose_17")];
            tensor<fp16, [1, 256, 320]> input_tensor_633_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_3_conv_q_Conv_bias_to_fp16, dilations = input_tensor_633_dilations_0, groups = input_tensor_633_groups_0, pad = input_tensor_633_pad_0, pad_type = input_tensor_633_pad_type_0, strides = input_tensor_633_strides_0, weight = text_encoder_attn_encoder_attn_layers_3_conv_q_Conv_weight_to_fp16, x = input_145_cast_fp16)[name = string("input_tensor_633_cast_fp16")];
            string input_tensor_625_pad_type_0 = const()[name = string("input_tensor_625_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_625_strides_0 = const()[name = string("input_tensor_625_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_625_pad_0 = const()[name = string("input_tensor_625_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_625_dilations_0 = const()[name = string("input_tensor_625_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_625_groups_0 = const()[name = string("input_tensor_625_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_3_conv_k_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_k_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15495104)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_3_conv_k_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_k_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15626240)))];
            tensor<fp16, [1, 256, 320]> input_tensor_625_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_3_conv_k_Conv_bias_to_fp16, dilations = input_tensor_625_dilations_0, groups = input_tensor_625_groups_0, pad = input_tensor_625_pad_0, pad_type = input_tensor_625_pad_type_0, strides = input_tensor_625_strides_0, weight = text_encoder_attn_encoder_attn_layers_3_conv_k_Conv_weight_to_fp16, x = input_145_cast_fp16)[name = string("input_tensor_625_cast_fp16")];
            string input_tensor_645_pad_type_0 = const()[name = string("input_tensor_645_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_645_strides_0 = const()[name = string("input_tensor_645_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_645_pad_0 = const()[name = string("input_tensor_645_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_645_dilations_0 = const()[name = string("input_tensor_645_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_645_groups_0 = const()[name = string("input_tensor_645_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_3_conv_v_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_v_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15626816)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_3_conv_v_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_v_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15757952)))];
            tensor<fp16, [1, 256, 320]> input_tensor_645_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_3_conv_v_Conv_bias_to_fp16, dilations = input_tensor_645_dilations_0, groups = input_tensor_645_groups_0, pad = input_tensor_645_pad_0, pad_type = input_tensor_645_pad_type_0, strides = input_tensor_645_strides_0, weight = text_encoder_attn_encoder_attn_layers_3_conv_v_Conv_weight_to_fp16, x = input_145_cast_fp16)[name = string("input_tensor_645_cast_fp16")];
            tensor<int32, [4]> var_2765 = const()[name = string("op_2765"), val = tensor<int32, [4]>([1, 4, 64, 320])];
            tensor<fp16, [1, 4, 64, 320]> input_tensor_641_cast_fp16 = reshape(shape = var_2765, x = input_tensor_633_cast_fp16)[name = string("input_tensor_641_cast_fp16")];
            tensor<int32, [4]> var_2771 = const()[name = string("op_2771"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [4]> var_2797 = const()[name = string("op_2797"), val = tensor<int32, [4]>([1, 4, 64, 320])];
            tensor<fp16, [1, 4, 64, 320]> y_33_cast_fp16 = reshape(shape = var_2797, x = input_tensor_625_cast_fp16)[name = string("y_33_cast_fp16")];
            tensor<int32, [4]> var_2809 = const()[name = string("op_2809"), val = tensor<int32, [4]>([1, 4, 64, 320])];
            tensor<fp16, [1, 4, 64, 320]> input_tensor_647_cast_fp16 = reshape(shape = var_2809, x = input_tensor_645_cast_fp16)[name = string("input_tensor_647_cast_fp16")];
            fp16 _inversed_x_153_y_0_to_fp16 = const()[name = string("_inversed_x_153_y_0_to_fp16"), val = fp16(0x1p-3)];
            tensor<fp16, [1, 4, 320, 64]> first_199_cast_fp16 = transpose(perm = var_2771, x = input_tensor_641_cast_fp16)[name = string("transpose_16")];
            tensor<fp16, [1, 4, 320, 64]> _inversed_x_153_cast_fp16 = mul(x = first_199_cast_fp16, y = _inversed_x_153_y_0_to_fp16)[name = string("_inversed_x_153_cast_fp16")];
            bool first_215_transpose_x_0 = const()[name = string("first_215_transpose_x_0"), val = bool(false)];
            bool first_215_transpose_y_0 = const()[name = string("first_215_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 4, 320, 320]> first_215_cast_fp16 = matmul(transpose_x = first_215_transpose_x_0, transpose_y = first_215_transpose_y_0, x = _inversed_x_153_cast_fp16, y = y_33_cast_fp16)[name = string("first_215_cast_fp16")];
            bool input_tensor_679_transpose_x_0 = const()[name = string("input_tensor_679_transpose_x_0"), val = bool(false)];
            bool input_tensor_679_transpose_y_0 = const()[name = string("input_tensor_679_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 64, 639]> y_35_to_fp16 = const()[name = string("y_35_to_fp16"), val = tensor<fp16, [1, 1, 64, 639]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21608384)))];
            tensor<fp16, [1, 4, 320, 639]> input_tensor_679_cast_fp16 = matmul(transpose_x = input_tensor_679_transpose_x_0, transpose_y = input_tensor_679_transpose_y_0, x = _inversed_x_153_cast_fp16, y = y_35_to_fp16)[name = string("input_tensor_679_cast_fp16")];
            tensor<int32, [8]> input_tensor_701_pad_0 = const()[name = string("input_tensor_701_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 1])];
            string input_tensor_701_mode_0 = const()[name = string("input_tensor_701_mode_0"), val = string("constant")];
            fp16 const_107_to_fp16 = const()[name = string("const_107_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 320, 640]> input_tensor_701_cast_fp16 = pad(constant_val = const_107_to_fp16, mode = input_tensor_701_mode_0, pad = input_tensor_701_pad_0, x = input_tensor_679_cast_fp16)[name = string("input_tensor_701_cast_fp16")];
            tensor<int32, [3]> var_2932 = const()[name = string("op_2932"), val = tensor<int32, [3]>([1, 4, 204800])];
            tensor<fp16, [1, 4, 204800]> input_153_cast_fp16 = reshape(shape = var_2932, x = input_tensor_701_cast_fp16)[name = string("input_153_cast_fp16")];
            tensor<int32, [6]> input_tensor_723_pad_0 = const()[name = string("input_tensor_723_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 0, 319])];
            string input_tensor_723_mode_0 = const()[name = string("input_tensor_723_mode_0"), val = string("constant")];
            fp16 const_108_to_fp16 = const()[name = string("const_108_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 205119]> input_tensor_723_cast_fp16 = pad(constant_val = const_108_to_fp16, mode = input_tensor_723_mode_0, pad = input_tensor_723_pad_0, x = input_153_cast_fp16)[name = string("input_tensor_723_cast_fp16")];
            tensor<int32, [4]> var_2967 = const()[name = string("op_2967"), val = tensor<int32, [4]>([1, 4, 321, 639])];
            tensor<fp16, [1, 4, 321, 639]> x_169_cast_fp16 = reshape(shape = var_2967, x = input_tensor_723_cast_fp16)[name = string("x_169_cast_fp16")];
            tensor<int32, [4]> x_171_begin_0 = const()[name = string("x_171_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> x_171_end_0 = const()[name = string("x_171_end_0"), val = tensor<int32, [4]>([1, 4, 320, 639])];
            tensor<bool, [4]> x_171_end_mask_0 = const()[name = string("x_171_end_mask_0"), val = tensor<bool, [4]>([true, true, false, true])];
            tensor<fp16, [1, 4, 320, 639]> x_171_cast_fp16 = slice_by_index(begin = x_171_begin_0, end = x_171_end_0, end_mask = x_171_end_mask_0, x = x_169_cast_fp16)[name = string("x_171_cast_fp16")];
            tensor<int32, [4]> second_223_begin_0 = const()[name = string("second_223_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 319])];
            tensor<int32, [4]> second_223_end_0 = const()[name = string("second_223_end_0"), val = tensor<int32, [4]>([1, 4, 320, 1])];
            tensor<bool, [4]> second_223_end_mask_0 = const()[name = string("second_223_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 320, 320]> second_223_cast_fp16 = slice_by_index(begin = second_223_begin_0, end = second_223_end_0, end_mask = second_223_end_mask_0, x = x_171_cast_fp16)[name = string("second_223_cast_fp16")];
            tensor<fp16, [1, 4, 320, 320]> y_37_cast_fp16 = add(x = first_215_cast_fp16, y = second_223_cast_fp16)[name = string("y_37_cast_fp16")];
            tensor<fp16, [1, 4, 320, 320]> input_155_cast_fp16 = select(a = text_encoder_attn_encoder_attn_layers_0_Constant_88_value_after_broadcast_to_fp16, b = y_37_cast_fp16, cond = condition_1_after_broadcast)[name = string("input_155_cast_fp16")];
            int32 var_3009 = const()[name = string("op_3009"), val = int32(-1)];
            tensor<fp16, [1, 4, 320, 320]> x_175_cast_fp16 = softmax(axis = var_3009, x = input_155_cast_fp16)[name = string("x_175_cast_fp16")];
            bool first_227_transpose_x_1 = const()[name = string("first_227_transpose_x_1"), val = bool(false)];
            bool first_227_transpose_y_1 = const()[name = string("first_227_transpose_y_1"), val = bool(true)];
            tensor<fp16, [1, 4, 320, 64]> first_227_cast_fp16 = matmul(transpose_x = first_227_transpose_x_1, transpose_y = first_227_transpose_y_1, x = x_175_cast_fp16, y = input_tensor_647_cast_fp16)[name = string("first_227_cast_fp16")];
            tensor<int32, [8]> input_tensor_753_pad_0 = const()[name = string("input_tensor_753_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 319])];
            string input_tensor_753_mode_0 = const()[name = string("input_tensor_753_mode_0"), val = string("constant")];
            fp16 const_115_to_fp16 = const()[name = string("const_115_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 320, 639]> input_tensor_753_cast_fp16 = pad(constant_val = const_115_to_fp16, mode = input_tensor_753_mode_0, pad = input_tensor_753_pad_0, x = x_175_cast_fp16)[name = string("input_tensor_753_cast_fp16")];
            tensor<int32, [3]> var_3083 = const()[name = string("op_3083"), val = tensor<int32, [3]>([1, 4, 204480])];
            tensor<fp16, [1, 4, 204480]> input_157_cast_fp16 = reshape(shape = var_3083, x = input_tensor_753_cast_fp16)[name = string("input_157_cast_fp16")];
            tensor<int32, [6]> input_tensor_771_pad_0 = const()[name = string("input_tensor_771_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 320, 0])];
            string input_tensor_771_mode_0 = const()[name = string("input_tensor_771_mode_0"), val = string("constant")];
            fp16 const_116_to_fp16 = const()[name = string("const_116_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 204800]> input_tensor_771_cast_fp16 = pad(constant_val = const_116_to_fp16, mode = input_tensor_771_mode_0, pad = input_tensor_771_pad_0, x = input_157_cast_fp16)[name = string("input_tensor_771_cast_fp16")];
            tensor<int32, [4]> var_3113 = const()[name = string("op_3113"), val = tensor<int32, [4]>([1, 4, 320, 640])];
            tensor<fp16, [1, 4, 320, 640]> x_185_cast_fp16 = reshape(shape = var_3113, x = input_tensor_771_cast_fp16)[name = string("x_185_cast_fp16")];
            tensor<int32, [4]> x_193_begin_0 = const()[name = string("x_193_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 1])];
            tensor<int32, [4]> x_193_end_0 = const()[name = string("x_193_end_0"), val = tensor<int32, [4]>([1, 4, 320, 1])];
            tensor<bool, [4]> x_193_end_mask_0 = const()[name = string("x_193_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 320, 639]> x_193_cast_fp16 = slice_by_index(begin = x_193_begin_0, end = x_193_end_0, end_mask = x_193_end_mask_0, x = x_185_cast_fp16)[name = string("x_193_cast_fp16")];
            bool second_237_transpose_x_0 = const()[name = string("second_237_transpose_x_0"), val = bool(false)];
            bool second_237_transpose_y_0 = const()[name = string("second_237_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 639, 64]> y_41_to_fp16 = const()[name = string("y_41_to_fp16"), val = tensor<fp16, [1, 1, 639, 64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21690240)))];
            tensor<fp16, [1, 4, 320, 64]> second_237_cast_fp16 = matmul(transpose_x = second_237_transpose_x_0, transpose_y = second_237_transpose_y_0, x = x_193_cast_fp16, y = y_41_to_fp16)[name = string("second_237_cast_fp16")];
            tensor<fp16, [1, 4, 320, 64]> input_tensor_789_cast_fp16 = add(x = first_227_cast_fp16, y = second_237_cast_fp16)[name = string("input_tensor_789_cast_fp16")];
            tensor<int32, [4]> var_3160 = const()[name = string("op_3160"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [3]> var_3179 = const()[name = string("op_3179"), val = tensor<int32, [3]>([1, 256, 320])];
            tensor<fp16, [1, 4, 64, 320]> input_tensor_793_cast_fp16 = transpose(perm = var_3160, x = input_tensor_789_cast_fp16)[name = string("transpose_15")];
            tensor<fp16, [1, 256, 320]> input_161_cast_fp16 = reshape(shape = var_3179, x = input_tensor_793_cast_fp16)[name = string("input_161_cast_fp16")];
            string second_239_pad_type_0 = const()[name = string("second_239_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_239_strides_0 = const()[name = string("second_239_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_239_pad_0 = const()[name = string("second_239_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_239_dilations_0 = const()[name = string("second_239_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_239_groups_0 = const()[name = string("second_239_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_3_conv_o_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_o_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15766592)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_3_conv_o_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_o_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15897728)))];
            tensor<fp16, [1, 256, 320]> second_239_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_3_conv_o_Conv_bias_to_fp16, dilations = second_239_dilations_0, groups = second_239_groups_0, pad = second_239_pad_0, pad_type = second_239_pad_type_0, strides = second_239_strides_0, weight = text_encoder_attn_encoder_attn_layers_3_conv_o_Conv_weight_to_fp16, x = input_161_cast_fp16)[name = string("second_239_cast_fp16")];
            tensor<fp16, [1, 256, 320]> input_tensor_795_cast_fp16 = add(x = input_145_cast_fp16, y = second_239_cast_fp16)[name = string("input_tensor_795_cast_fp16")];
            tensor<int32, [3]> var_3197 = const()[name = string("op_3197"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_797_axes_0 = const()[name = string("input_tensor_797_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_3_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_3_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15898304)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_3_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_3_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15898880)))];
            fp16 var_3200_to_fp16 = const()[name = string("op_3200_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 320, 256]> input_163_cast_fp16 = transpose(perm = var_3197, x = input_tensor_795_cast_fp16)[name = string("transpose_14")];
            tensor<fp16, [1, 320, 256]> input_tensor_797_cast_fp16 = layer_norm(axes = input_tensor_797_axes_0, beta = text_encoder_attn_encoder_norm_layers_1_3_norm_LayerNormalization_bias_to_fp16, epsilon = var_3200_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_1_3_norm_LayerNormalization_weight_to_fp16, x = input_163_cast_fp16)[name = string("input_tensor_797_cast_fp16")];
            tensor<int32, [3]> var_3209 = const()[name = string("op_3209"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 256, 320]> first_229_cast_fp16 = transpose(perm = var_3209, x = input_tensor_797_cast_fp16)[name = string("transpose_13")];
            tensor<fp16, [1, 256, 320]> input_165_cast_fp16 = mul(x = first_229_cast_fp16, y = text_mask)[name = string("input_165_cast_fp16")];
            string input_167_pad_type_0 = const()[name = string("input_167_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_167_strides_0 = const()[name = string("input_167_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_167_pad_0 = const()[name = string("input_167_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_167_dilations_0 = const()[name = string("input_167_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_167_groups_0 = const()[name = string("input_167_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_attn_encoder_ffn_layers_3_conv_1_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_3_conv_1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15899456)))];
            tensor<fp16, [1024]> text_encoder_attn_encoder_ffn_layers_3_conv_1_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_3_conv_1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16423808)))];
            tensor<fp16, [1, 1024, 320]> input_167_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_3_conv_1_Conv_bias_to_fp16, dilations = input_167_dilations_0, groups = input_167_groups_0, pad = input_167_pad_0, pad_type = input_167_pad_type_0, strides = input_167_strides_0, weight = text_encoder_attn_encoder_ffn_layers_3_conv_1_Conv_weight_to_fp16, x = input_165_cast_fp16)[name = string("input_167_cast_fp16")];
            tensor<fp16, [1, 1024, 320]> first_231_cast_fp16 = relu(x = input_167_cast_fp16)[name = string("first_231_cast_fp16")];
            tensor<fp16, [1, 1024, 320]> input_169_cast_fp16 = mul(x = first_231_cast_fp16, y = text_mask)[name = string("input_169_cast_fp16")];
            string first_233_pad_type_0 = const()[name = string("first_233_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_233_strides_0 = const()[name = string("first_233_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_233_pad_0 = const()[name = string("first_233_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_233_dilations_0 = const()[name = string("first_233_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_233_groups_0 = const()[name = string("first_233_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> text_encoder_attn_encoder_ffn_layers_3_conv_2_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_3_conv_2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16425920)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_ffn_layers_3_conv_2_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_3_conv_2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16950272)))];
            tensor<fp16, [1, 256, 320]> first_233_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_3_conv_2_Conv_bias_to_fp16, dilations = first_233_dilations_0, groups = first_233_groups_0, pad = first_233_pad_0, pad_type = first_233_pad_type_0, strides = first_233_strides_0, weight = text_encoder_attn_encoder_ffn_layers_3_conv_2_Conv_weight_to_fp16, x = input_169_cast_fp16)[name = string("first_233_cast_fp16")];
            tensor<fp16, [1, 256, 320]> second_241_cast_fp16 = mul(x = first_233_cast_fp16, y = text_mask)[name = string("second_241_cast_fp16")];
            tensor<fp16, [1, 256, 320]> input_tensor_799_cast_fp16 = add(x = first_229_cast_fp16, y = second_241_cast_fp16)[name = string("input_tensor_799_cast_fp16")];
            tensor<int32, [3]> var_3242 = const()[name = string("op_3242"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_801_axes_0 = const()[name = string("input_tensor_801_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_3_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_3_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16950848)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_3_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_3_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16951424)))];
            fp16 var_3245_to_fp16 = const()[name = string("op_3245_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 320, 256]> input_171_cast_fp16 = transpose(perm = var_3242, x = input_tensor_799_cast_fp16)[name = string("transpose_12")];
            tensor<fp16, [1, 320, 256]> input_tensor_801_cast_fp16 = layer_norm(axes = input_tensor_801_axes_0, beta = text_encoder_attn_encoder_norm_layers_2_3_norm_LayerNormalization_bias_to_fp16, epsilon = var_3245_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_2_3_norm_LayerNormalization_weight_to_fp16, x = input_171_cast_fp16)[name = string("input_tensor_801_cast_fp16")];
            tensor<int32, [3]> var_3254 = const()[name = string("op_3254"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 256, 320]> first_235_cast_fp16 = transpose(perm = var_3254, x = input_tensor_801_cast_fp16)[name = string("transpose_11")];
            tensor<fp16, [1, 256, 320]> first_237_cast_fp16 = mul(x = first_235_cast_fp16, y = text_mask)[name = string("first_237_cast_fp16")];
            tensor<fp16, [1, 256, 320]> first_239_cast_fp16 = add(x = first_237_cast_fp16, y = first_89_cast_fp16)[name = string("first_239_cast_fp16")];
            tensor<fp16, [1, 256, 320]> input_tensor_807_cast_fp16 = mul(x = first_239_cast_fp16, y = text_mask)[name = string("input_tensor_807_cast_fp16")];
            tensor<int32, [3]> var_3299 = const()[name = string("op_3299"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [3]> var_3304 = const()[name = string("op_3304"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [256, 256]> var_3308_weight_0_to_fp16 = const()[name = string("op_3308_weight_0_to_fp16"), val = tensor<fp16, [256, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16952000)))];
            tensor<fp16, [256]> var_3308_bias_0_to_fp16 = const()[name = string("op_3308_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17083136)))];
            tensor<fp16, [1, 320, 256]> x_195_cast_fp16 = transpose(perm = var_3299, x = input_tensor_807_cast_fp16)[name = string("transpose_10")];
            tensor<fp16, [1, 320, 256]> var_3308_cast_fp16 = linear(bias = var_3308_bias_0_to_fp16, weight = var_3308_weight_0_to_fp16, x = x_195_cast_fp16)[name = string("op_3308_cast_fp16")];
            tensor<fp16, [256, 256]> var_3314_weight_0_to_fp16 = const()[name = string("op_3314_weight_0_to_fp16"), val = tensor<fp16, [256, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17083712)))];
            tensor<fp16, [256]> var_3314_bias_0_to_fp16 = const()[name = string("op_3314_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17214848)))];
            tensor<fp16, [1, 50, 256]> var_3314_cast_fp16 = linear(bias = var_3314_bias_0_to_fp16, weight = var_3314_weight_0_to_fp16, x = style_ttl)[name = string("op_3314_cast_fp16")];
            tensor<int32, [2]> var_3317 = const()[name = string("op_3317"), val = tensor<int32, [2]>([128, 128])];
            int32 var_3318_axis_0 = const()[name = string("op_3318_axis_0"), val = int32(2)];
            tensor<fp16, [1, 320, 128]> var_3318_cast_fp16_0, tensor<fp16, [1, 320, 128]> var_3318_cast_fp16_1 = split(axis = var_3318_axis_0, split_sizes = var_3317, x = var_3308_cast_fp16)[name = string("op_3318_cast_fp16")];
            tensor<int32, [1]> var_3325_axes_0 = const()[name = string("op_3325_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 320, 128]> var_3325_cast_fp16 = expand_dims(axes = var_3325_axes_0, x = var_3318_cast_fp16_0)[name = string("op_3325_cast_fp16")];
            tensor<int32, [1]> var_3327_axes_0 = const()[name = string("op_3327_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 320, 128]> var_3327_cast_fp16 = expand_dims(axes = var_3327_axes_0, x = var_3318_cast_fp16_1)[name = string("op_3327_cast_fp16")];
            int32 var_3328 = const()[name = string("op_3328"), val = int32(0)];
            bool x_199_interleave_0 = const()[name = string("x_199_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 1, 320, 128]> x_199_cast_fp16 = concat(axis = var_3328, interleave = x_199_interleave_0, values = (var_3325_cast_fp16, var_3327_cast_fp16))[name = string("x_199_cast_fp16")];
            tensor<int32, [2]> var_3349 = const()[name = string("op_3349"), val = tensor<int32, [2]>([128, 128])];
            int32 var_3350_axis_0 = const()[name = string("op_3350_axis_0"), val = int32(2)];
            tensor<fp16, [1, 50, 128]> var_3350_cast_fp16_0, tensor<fp16, [1, 50, 128]> var_3350_cast_fp16_1 = split(axis = var_3350_axis_0, split_sizes = var_3349, x = var_3314_cast_fp16)[name = string("op_3350_cast_fp16")];
            tensor<int32, [1]> var_3357_axes_0 = const()[name = string("op_3357_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 50, 128]> var_3357_cast_fp16 = expand_dims(axes = var_3357_axes_0, x = var_3350_cast_fp16_0)[name = string("op_3357_cast_fp16")];
            tensor<int32, [1]> var_3359_axes_0 = const()[name = string("op_3359_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 50, 128]> var_3359_cast_fp16 = expand_dims(axes = var_3359_axes_0, x = var_3350_cast_fp16_1)[name = string("op_3359_cast_fp16")];
            int32 var_3360 = const()[name = string("op_3360"), val = int32(0)];
            bool y_55_interleave_0 = const()[name = string("y_55_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 1, 50, 128]> y_55_cast_fp16 = concat(axis = var_3360, interleave = y_55_interleave_0, values = (var_3357_cast_fp16, var_3359_cast_fp16))[name = string("y_55_cast_fp16")];
            bool first_247_transpose_x_0 = const()[name = string("first_247_transpose_x_0"), val = bool(false)];
            bool first_247_transpose_y_0 = const()[name = string("first_247_transpose_y_0"), val = bool(false)];
            tensor<fp16, [2, 1, 128, 50]> y_49_to_fp16 = const()[name = string("y_49_to_fp16"), val = tensor<fp16, [2, 1, 128, 50]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17215424)))];
            tensor<fp16, [2, 1, 320, 50]> first_247_cast_fp16 = matmul(transpose_x = first_247_transpose_x_0, transpose_y = first_247_transpose_y_0, x = x_199_cast_fp16, y = y_49_to_fp16)[name = string("first_247_cast_fp16")];
            fp16 _inversed_input_173_y_0_to_fp16 = const()[name = string("_inversed_input_173_y_0_to_fp16"), val = fp16(0x1p-4)];
            tensor<fp16, [2, 1, 320, 50]> _inversed_input_173_cast_fp16 = mul(x = first_247_cast_fp16, y = _inversed_input_173_y_0_to_fp16)[name = string("_inversed_input_173_cast_fp16")];
            int32 var_3373 = const()[name = string("op_3373"), val = int32(3)];
            tensor<fp16, [2, 1, 320, 50]> y_53_cast_fp16 = softmax(axis = var_3373, x = _inversed_input_173_cast_fp16)[name = string("y_53_cast_fp16")];
            tensor<int32, [1]> x_201_axes_0 = const()[name = string("x_201_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 320, 1]> input_tensor_825_cast_fp16 = transpose(perm = var_3304, x = text_mask)[name = string("transpose_9")];
            tensor<fp16, [1, 1, 320, 1]> x_201_cast_fp16 = expand_dims(axes = x_201_axes_0, x = input_tensor_825_cast_fp16)[name = string("x_201_cast_fp16")];
            fp16 speech_prompted_text_encoder_attention1_Constant_11_value_to_fp16 = const()[name = string("speech_prompted_text_encoder_attention1_Constant_11_value_to_fp16"), val = fp16(0x0p+0)];
            tensor<bool, [1, 1, 320, 1]> input_tensor_827_cast_fp16 = equal(x = x_201_cast_fp16, y = speech_prompted_text_encoder_attention1_Constant_11_value_to_fp16)[name = string("input_tensor_827_cast_fp16")];
            tensor<int32, [4]> condition_9_after_broadcast_reps_0 = const()[name = string("condition_9_after_broadcast_reps_0"), val = tensor<int32, [4]>([2, 1, 1, 50])];
            tensor<bool, [2, 1, 320, 50]> condition_9_after_broadcast = tile(reps = condition_9_after_broadcast_reps_0, x = input_tensor_827_cast_fp16)[name = string("condition_9_after_broadcast")];
            tensor<fp16, [2, 1, 320, 50]> speech_prompted_text_encoder_attention1_Constant_12_value_after_broadcast_to_fp16 = const()[name = string("speech_prompted_text_encoder_attention1_Constant_12_value_after_broadcast_to_fp16"), val = tensor<fp16, [2, 1, 320, 50]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(21772096)))];
            tensor<fp16, [2, 1, 320, 50]> x_205_cast_fp16 = select(a = speech_prompted_text_encoder_attention1_Constant_12_value_after_broadcast_to_fp16, b = y_53_cast_fp16, cond = condition_9_after_broadcast)[name = string("x_205_cast_fp16")];
            bool var_3383_transpose_x_0 = const()[name = string("op_3383_transpose_x_0"), val = bool(false)];
            bool var_3383_transpose_y_0 = const()[name = string("op_3383_transpose_y_0"), val = bool(false)];
            tensor<fp16, [2, 1, 320, 128]> var_3383_cast_fp16 = matmul(transpose_x = var_3383_transpose_x_0, transpose_y = var_3383_transpose_y_0, x = x_205_cast_fp16, y = y_55_cast_fp16)[name = string("op_3383_cast_fp16")];
            tensor<int32, [2]> var_3386 = const()[name = string("op_3386"), val = tensor<int32, [2]>([1, 1])];
            int32 var_3387_axis_0 = const()[name = string("op_3387_axis_0"), val = int32(0)];
            tensor<fp16, [1, 1, 320, 128]> var_3387_cast_fp16_0, tensor<fp16, [1, 1, 320, 128]> var_3387_cast_fp16_1 = split(axis = var_3387_axis_0, split_sizes = var_3386, x = var_3383_cast_fp16)[name = string("op_3387_cast_fp16")];
            int32 var_3393 = const()[name = string("op_3393"), val = int32(3)];
            bool result_1_interleave_0 = const()[name = string("result_1_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 1, 320, 256]> result_1_cast_fp16 = concat(axis = var_3393, interleave = result_1_interleave_0, values = (var_3387_cast_fp16_0, var_3387_cast_fp16_1))[name = string("result_1_cast_fp16")];
            tensor<int32, [1]> x_207_axes_0 = const()[name = string("x_207_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 320, 256]> x_207_cast_fp16 = squeeze(axes = x_207_axes_0, x = result_1_cast_fp16)[name = string("x_207_cast_fp16")];
            tensor<fp16, [256, 256]> first_251_weight_0_to_fp16 = const()[name = string("first_251_weight_0_to_fp16"), val = tensor<fp16, [256, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17244352)))];
            tensor<fp16, [256]> first_251_bias_0_to_fp16 = const()[name = string("first_251_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17375488)))];
            tensor<fp16, [1, 320, 256]> first_251_cast_fp16 = linear(bias = first_251_bias_0_to_fp16, weight = first_251_weight_0_to_fp16, x = x_207_cast_fp16)[name = string("first_251_cast_fp16")];
            tensor<fp16, [1, 320, 256]> first_253_cast_fp16 = mul(x = first_251_cast_fp16, y = input_tensor_825_cast_fp16)[name = string("first_253_cast_fp16")];
            tensor<fp16, [1, 320, 256]> x_209_cast_fp16 = add(x = first_253_cast_fp16, y = x_195_cast_fp16)[name = string("x_209_cast_fp16")];
            tensor<fp16, [256, 256]> var_3413_weight_0_to_fp16 = const()[name = string("op_3413_weight_0_to_fp16"), val = tensor<fp16, [256, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17376064)))];
            tensor<fp16, [256]> var_3413_bias_0_to_fp16 = const()[name = string("op_3413_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17507200)))];
            tensor<fp16, [1, 320, 256]> var_3413_cast_fp16 = linear(bias = var_3413_bias_0_to_fp16, weight = var_3413_weight_0_to_fp16, x = x_209_cast_fp16)[name = string("op_3413_cast_fp16")];
            tensor<fp16, [256, 256]> var_3419_weight_0_to_fp16 = const()[name = string("op_3419_weight_0_to_fp16"), val = tensor<fp16, [256, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17507776)))];
            tensor<fp16, [256]> var_3419_bias_0_to_fp16 = const()[name = string("op_3419_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17638912)))];
            tensor<fp16, [1, 50, 256]> var_3419_cast_fp16 = linear(bias = var_3419_bias_0_to_fp16, weight = var_3419_weight_0_to_fp16, x = style_ttl)[name = string("op_3419_cast_fp16")];
            tensor<int32, [2]> var_3422 = const()[name = string("op_3422"), val = tensor<int32, [2]>([128, 128])];
            int32 var_3423_axis_0 = const()[name = string("op_3423_axis_0"), val = int32(2)];
            tensor<fp16, [1, 320, 128]> var_3423_cast_fp16_0, tensor<fp16, [1, 320, 128]> var_3423_cast_fp16_1 = split(axis = var_3423_axis_0, split_sizes = var_3422, x = var_3413_cast_fp16)[name = string("op_3423_cast_fp16")];
            tensor<int32, [1]> var_3430_axes_0 = const()[name = string("op_3430_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 320, 128]> var_3430_cast_fp16 = expand_dims(axes = var_3430_axes_0, x = var_3423_cast_fp16_0)[name = string("op_3430_cast_fp16")];
            tensor<int32, [1]> var_3432_axes_0 = const()[name = string("op_3432_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 320, 128]> var_3432_cast_fp16 = expand_dims(axes = var_3432_axes_0, x = var_3423_cast_fp16_1)[name = string("op_3432_cast_fp16")];
            int32 var_3433 = const()[name = string("op_3433"), val = int32(0)];
            bool x_211_interleave_0 = const()[name = string("x_211_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 1, 320, 128]> x_211_cast_fp16 = concat(axis = var_3433, interleave = x_211_interleave_0, values = (var_3430_cast_fp16, var_3432_cast_fp16))[name = string("x_211_cast_fp16")];
            tensor<int32, [2]> var_3454 = const()[name = string("op_3454"), val = tensor<int32, [2]>([128, 128])];
            int32 var_3455_axis_0 = const()[name = string("op_3455_axis_0"), val = int32(2)];
            tensor<fp16, [1, 50, 128]> var_3455_cast_fp16_0, tensor<fp16, [1, 50, 128]> var_3455_cast_fp16_1 = split(axis = var_3455_axis_0, split_sizes = var_3454, x = var_3419_cast_fp16)[name = string("op_3455_cast_fp16")];
            tensor<int32, [1]> var_3462_axes_0 = const()[name = string("op_3462_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 50, 128]> var_3462_cast_fp16 = expand_dims(axes = var_3462_axes_0, x = var_3455_cast_fp16_0)[name = string("op_3462_cast_fp16")];
            tensor<int32, [1]> var_3464_axes_0 = const()[name = string("op_3464_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 50, 128]> var_3464_cast_fp16 = expand_dims(axes = var_3464_axes_0, x = var_3455_cast_fp16_1)[name = string("op_3464_cast_fp16")];
            int32 var_3465 = const()[name = string("op_3465"), val = int32(0)];
            bool y_69_interleave_0 = const()[name = string("y_69_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 1, 50, 128]> y_69_cast_fp16 = concat(axis = var_3465, interleave = y_69_interleave_0, values = (var_3462_cast_fp16, var_3464_cast_fp16))[name = string("y_69_cast_fp16")];
            bool first_261_transpose_x_0 = const()[name = string("first_261_transpose_x_0"), val = bool(false)];
            bool first_261_transpose_y_0 = const()[name = string("first_261_transpose_y_0"), val = bool(false)];
            tensor<fp16, [2, 1, 128, 50]> y_65_to_fp16 = const()[name = string("y_65_to_fp16"), val = tensor<fp16, [2, 1, 128, 50]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17639488)))];
            tensor<fp16, [2, 1, 320, 50]> first_261_cast_fp16 = matmul(transpose_x = first_261_transpose_x_0, transpose_y = first_261_transpose_y_0, x = x_211_cast_fp16, y = y_65_to_fp16)[name = string("first_261_cast_fp16")];
            fp16 _inversed_input_175_y_0_to_fp16 = const()[name = string("_inversed_input_175_y_0_to_fp16"), val = fp16(0x1p-4)];
            tensor<fp16, [2, 1, 320, 50]> _inversed_input_175_cast_fp16 = mul(x = first_261_cast_fp16, y = _inversed_input_175_y_0_to_fp16)[name = string("_inversed_input_175_cast_fp16")];
            int32 var_3478 = const()[name = string("op_3478"), val = int32(3)];
            tensor<fp16, [2, 1, 320, 50]> y_67_cast_fp16 = softmax(axis = var_3478, x = _inversed_input_175_cast_fp16)[name = string("y_67_cast_fp16")];
            tensor<fp16, [2, 1, 320, 50]> x_215_cast_fp16 = select(a = speech_prompted_text_encoder_attention1_Constant_12_value_after_broadcast_to_fp16, b = y_67_cast_fp16, cond = condition_9_after_broadcast)[name = string("x_215_cast_fp16")];
            bool var_3485_transpose_x_0 = const()[name = string("op_3485_transpose_x_0"), val = bool(false)];
            bool var_3485_transpose_y_0 = const()[name = string("op_3485_transpose_y_0"), val = bool(false)];
            tensor<fp16, [2, 1, 320, 128]> var_3485_cast_fp16 = matmul(transpose_x = var_3485_transpose_x_0, transpose_y = var_3485_transpose_y_0, x = x_215_cast_fp16, y = y_69_cast_fp16)[name = string("op_3485_cast_fp16")];
            tensor<int32, [2]> var_3488 = const()[name = string("op_3488"), val = tensor<int32, [2]>([1, 1])];
            int32 var_3489_axis_0 = const()[name = string("op_3489_axis_0"), val = int32(0)];
            tensor<fp16, [1, 1, 320, 128]> var_3489_cast_fp16_0, tensor<fp16, [1, 1, 320, 128]> var_3489_cast_fp16_1 = split(axis = var_3489_axis_0, split_sizes = var_3488, x = var_3485_cast_fp16)[name = string("op_3489_cast_fp16")];
            int32 var_3495 = const()[name = string("op_3495"), val = int32(3)];
            bool result_interleave_0 = const()[name = string("result_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 1, 320, 256]> result_cast_fp16 = concat(axis = var_3495, interleave = result_interleave_0, values = (var_3489_cast_fp16_0, var_3489_cast_fp16_1))[name = string("result_cast_fp16")];
            tensor<int32, [1]> x_axes_0 = const()[name = string("x_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 320, 256]> x_cast_fp16 = squeeze(axes = x_axes_0, x = result_cast_fp16)[name = string("x_cast_fp16")];
            tensor<fp16, [256, 256]> first_265_weight_0_to_fp16 = const()[name = string("first_265_weight_0_to_fp16"), val = tensor<fp16, [256, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17665152)))];
            tensor<fp16, [256]> first_265_bias_0_to_fp16 = const()[name = string("first_265_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17796288)))];
            tensor<fp16, [1, 320, 256]> first_265_cast_fp16 = linear(bias = first_265_bias_0_to_fp16, weight = first_265_weight_0_to_fp16, x = x_cast_fp16)[name = string("first_265_cast_fp16")];
            tensor<fp16, [1, 320, 256]> first_267_cast_fp16 = mul(x = first_265_cast_fp16, y = input_tensor_825_cast_fp16)[name = string("first_267_cast_fp16")];
            tensor<fp16, [1, 320, 256]> input_cast_fp16 = add(x = first_267_cast_fp16, y = x_195_cast_fp16)[name = string("input_cast_fp16")];
            tensor<int32, [1]> input_tensor_axes_0 = const()[name = string("input_tensor_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> speech_prompted_text_encoder_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("speech_prompted_text_encoder_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17796864)))];
            tensor<fp16, [256]> speech_prompted_text_encoder_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("speech_prompted_text_encoder_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17797440)))];
            fp16 var_3514_to_fp16 = const()[name = string("op_3514_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 320, 256]> input_tensor_cast_fp16 = layer_norm(axes = input_tensor_axes_0, beta = speech_prompted_text_encoder_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_3514_to_fp16, gamma = speech_prompted_text_encoder_norm_norm_LayerNormalization_weight_to_fp16, x = input_cast_fp16)[name = string("input_tensor_cast_fp16")];
            tensor<int32, [3]> var_3523 = const()[name = string("op_3523"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 256, 320]> first_cast_fp16 = transpose(perm = var_3523, x = input_tensor_cast_fp16)[name = string("transpose_8")];
            tensor<fp16, [1, 256, 320]> text_emb = mul(x = first_cast_fp16, y = text_mask)[name = string("op_3525_cast_fp16")];
        } -> (text_emb);
    func text_t64<ios18>(tensor<fp16, [1, 50, 256]> style_ttl, tensor<int32, [1, 64]> text_ids, tensor<fp16, [1, 1, 64]> text_mask) {
            int32 input_tensor_3_batch_dims_0 = const()[name = string("input_tensor_3_batch_dims_0"), val = int32(0)];
            bool input_tensor_3_validate_indices_0 = const()[name = string("input_tensor_3_validate_indices_0"), val = bool(false)];
            tensor<fp16, [8322, 256]> initializers_onnx_initializer_0_to_fp16 = const()[name = string("initializers_onnx_initializer_0_to_fp16"), val = tensor<fp16, [8322, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(64)))];
            string text_ids_to_int16_dtype_0 = const()[name = string("text_ids_to_int16_dtype_0"), val = string("int16")];
            string cast_59_dtype_0 = const()[name = string("cast_59_dtype_0"), val = string("int32")];
            int32 greater_equal_0_y_0 = const()[name = string("greater_equal_0_y_0"), val = int32(0)];
            tensor<int16, [1, 64]> text_ids_to_int16 = cast(dtype = text_ids_to_int16_dtype_0, x = text_ids)[name = string("cast_62")];
            tensor<int32, [1, 64]> cast_59 = cast(dtype = cast_59_dtype_0, x = text_ids_to_int16)[name = string("cast_61")];
            tensor<bool, [1, 64]> greater_equal_0 = greater_equal(x = cast_59, y = greater_equal_0_y_0)[name = string("greater_equal_0")];
            int32 slice_by_index_0 = const()[name = string("slice_by_index_0"), val = int32(8322)];
            tensor<int32, [1, 64]> add_0 = add(x = cast_59, y = slice_by_index_0)[name = string("add_0")];
            tensor<int32, [1, 64]> select_0 = select(a = cast_59, b = add_0, cond = greater_equal_0)[name = string("select_0")];
            int32 input_tensor_3_cast_fp16_cast_uint16_axis_0 = const()[name = string("input_tensor_3_cast_fp16_cast_uint16_axis_0"), val = int32(0)];
            string select_0_to_int16_dtype_0 = const()[name = string("select_0_to_int16_dtype_0"), val = string("int16")];
            tensor<int16, [1, 64]> select_0_to_int16 = cast(dtype = select_0_to_int16_dtype_0, x = select_0)[name = string("cast_60")];
            tensor<fp16, [1, 64, 256]> input_tensor_3_cast_fp16_cast_uint16_cast_uint16 = gather(axis = input_tensor_3_cast_fp16_cast_uint16_axis_0, batch_dims = input_tensor_3_batch_dims_0, indices = select_0_to_int16, validate_indices = input_tensor_3_validate_indices_0, x = initializers_onnx_initializer_0_to_fp16)[name = string("input_tensor_3_cast_fp16_cast_uint16_cast_uint16")];
            tensor<int32, [3]> var_446 = const()[name = string("op_446"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 256, 64]> first_1_cast_fp16 = transpose(perm = var_446, x = input_tensor_3_cast_fp16_cast_uint16_cast_uint16)[name = string("transpose_47")];
            tensor<fp16, [1, 256, 64]> first_3_cast_fp16 = mul(x = first_1_cast_fp16, y = text_mask)[name = string("first_3_cast_fp16")];
            tensor<fp16, [1, 256, 64]> input_1_cast_fp16 = mul(x = first_3_cast_fp16, y = text_mask)[name = string("input_1_cast_fp16")];
            tensor<int32, [6]> input_3_pad_0 = const()[name = string("input_3_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 2, 2])];
            string input_3_mode_0 = const()[name = string("input_3_mode_0"), val = string("replicate")];
            fp16 const_0_to_fp16 = const()[name = string("const_0_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 256, 68]> input_3_cast_fp16 = pad(constant_val = const_0_to_fp16, mode = input_3_mode_0, pad = input_3_pad_0, x = input_1_cast_fp16)[name = string("input_3_cast_fp16")];
            string first_5_pad_type_0 = const()[name = string("first_5_pad_type_0"), val = string("valid")];
            int32 first_5_groups_0 = const()[name = string("first_5_groups_0"), val = int32(256)];
            tensor<int32, [1]> first_5_strides_0 = const()[name = string("first_5_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_5_pad_0 = const()[name = string("first_5_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_5_dilations_0 = const()[name = string("first_5_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [256, 1, 5]> text_encoder_convnext_convnext_0_dwconv_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_0_dwconv_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4260992)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_0_dwconv_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_0_dwconv_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4263616)))];
            tensor<fp16, [1, 256, 64]> first_5_cast_fp16 = conv(bias = text_encoder_convnext_convnext_0_dwconv_Conv_bias_to_fp16, dilations = first_5_dilations_0, groups = first_5_groups_0, pad = first_5_pad_0, pad_type = first_5_pad_type_0, strides = first_5_strides_0, weight = text_encoder_convnext_convnext_0_dwconv_Conv_weight_to_fp16, x = input_3_cast_fp16)[name = string("first_5_cast_fp16")];
            tensor<fp16, [1, 256, 64]> input_tensor_13_cast_fp16 = mul(x = first_5_cast_fp16, y = text_mask)[name = string("input_tensor_13_cast_fp16")];
            tensor<int32, [3]> var_471 = const()[name = string("op_471"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_15_axes_0 = const()[name = string("input_tensor_15_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_convnext_convnext_0_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_0_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4264192)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_0_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_0_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4264768)))];
            fp16 var_474_to_fp16 = const()[name = string("op_474_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 64, 256]> input_5_cast_fp16 = transpose(perm = var_471, x = input_tensor_13_cast_fp16)[name = string("transpose_46")];
            tensor<fp16, [1, 64, 256]> input_tensor_15_cast_fp16 = layer_norm(axes = input_tensor_15_axes_0, beta = text_encoder_convnext_convnext_0_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_474_to_fp16, gamma = text_encoder_convnext_convnext_0_norm_norm_LayerNormalization_weight_to_fp16, x = input_5_cast_fp16)[name = string("input_tensor_15_cast_fp16")];
            tensor<int32, [3]> var_483 = const()[name = string("op_483"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_7_pad_type_0 = const()[name = string("first_7_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_7_strides_0 = const()[name = string("first_7_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_7_pad_0 = const()[name = string("first_7_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_7_dilations_0 = const()[name = string("first_7_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_7_groups_0 = const()[name = string("first_7_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_convnext_convnext_0_pwconv1_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_0_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4265344)))];
            tensor<fp16, [1024]> text_encoder_convnext_convnext_0_pwconv1_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_0_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4789696)))];
            tensor<fp16, [1, 256, 64]> input_7_cast_fp16 = transpose(perm = var_483, x = input_tensor_15_cast_fp16)[name = string("transpose_45")];
            tensor<fp16, [1, 1024, 64]> first_7_cast_fp16 = conv(bias = text_encoder_convnext_convnext_0_pwconv1_Conv_bias_to_fp16, dilations = first_7_dilations_0, groups = first_7_groups_0, pad = first_7_pad_0, pad_type = first_7_pad_type_0, strides = first_7_strides_0, weight = text_encoder_convnext_convnext_0_pwconv1_Conv_weight_to_fp16, x = input_7_cast_fp16)[name = string("first_7_cast_fp16")];
            string input_9_mode_0 = const()[name = string("input_9_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 1024, 64]> input_9_cast_fp16 = gelu(mode = input_9_mode_0, x = first_7_cast_fp16)[name = string("input_9_cast_fp16")];
            string second_9_pad_type_0 = const()[name = string("second_9_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_9_strides_0 = const()[name = string("second_9_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_9_pad_0 = const()[name = string("second_9_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_9_dilations_0 = const()[name = string("second_9_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_9_groups_0 = const()[name = string("second_9_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> second_11_weight_0_to_fp16 = const()[name = string("second_11_weight_0_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(4791808)))];
            tensor<fp16, [256]> second_11_bias_0_to_fp16 = const()[name = string("second_11_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5316160)))];
            tensor<fp16, [1, 256, 64]> second_11_cast_fp16 = conv(bias = second_11_bias_0_to_fp16, dilations = second_9_dilations_0, groups = second_9_groups_0, pad = second_9_pad_0, pad_type = second_9_pad_type_0, strides = second_9_strides_0, weight = second_11_weight_0_to_fp16, x = input_9_cast_fp16)[name = string("second_11_cast_fp16")];
            tensor<fp16, [1, 256, 64]> first_15_cast_fp16 = add(x = input_1_cast_fp16, y = second_11_cast_fp16)[name = string("first_15_cast_fp16")];
            tensor<fp16, [1, 256, 64]> first_17_cast_fp16 = mul(x = first_15_cast_fp16, y = text_mask)[name = string("first_17_cast_fp16")];
            tensor<fp16, [1, 256, 64]> input_11_cast_fp16 = mul(x = first_17_cast_fp16, y = text_mask)[name = string("input_11_cast_fp16")];
            tensor<int32, [6]> input_13_pad_0 = const()[name = string("input_13_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 2, 2])];
            string input_13_mode_0 = const()[name = string("input_13_mode_0"), val = string("replicate")];
            fp16 const_1_to_fp16 = const()[name = string("const_1_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 256, 68]> input_13_cast_fp16 = pad(constant_val = const_1_to_fp16, mode = input_13_mode_0, pad = input_13_pad_0, x = input_11_cast_fp16)[name = string("input_13_cast_fp16")];
            string first_19_pad_type_0 = const()[name = string("first_19_pad_type_0"), val = string("valid")];
            int32 first_19_groups_0 = const()[name = string("first_19_groups_0"), val = int32(256)];
            tensor<int32, [1]> first_19_strides_0 = const()[name = string("first_19_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_19_pad_0 = const()[name = string("first_19_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_19_dilations_0 = const()[name = string("first_19_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [256, 1, 5]> text_encoder_convnext_convnext_1_dwconv_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_1_dwconv_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5316736)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_1_dwconv_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_1_dwconv_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5319360)))];
            tensor<fp16, [1, 256, 64]> first_19_cast_fp16 = conv(bias = text_encoder_convnext_convnext_1_dwconv_Conv_bias_to_fp16, dilations = first_19_dilations_0, groups = first_19_groups_0, pad = first_19_pad_0, pad_type = first_19_pad_type_0, strides = first_19_strides_0, weight = text_encoder_convnext_convnext_1_dwconv_Conv_weight_to_fp16, x = input_13_cast_fp16)[name = string("first_19_cast_fp16")];
            tensor<fp16, [1, 256, 64]> input_tensor_27_cast_fp16 = mul(x = first_19_cast_fp16, y = text_mask)[name = string("input_tensor_27_cast_fp16")];
            tensor<int32, [3]> var_539 = const()[name = string("op_539"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_29_axes_0 = const()[name = string("input_tensor_29_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_convnext_convnext_1_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_1_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5319936)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_1_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_1_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5320512)))];
            fp16 var_542_to_fp16 = const()[name = string("op_542_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 64, 256]> input_15_cast_fp16 = transpose(perm = var_539, x = input_tensor_27_cast_fp16)[name = string("transpose_44")];
            tensor<fp16, [1, 64, 256]> input_tensor_29_cast_fp16 = layer_norm(axes = input_tensor_29_axes_0, beta = text_encoder_convnext_convnext_1_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_542_to_fp16, gamma = text_encoder_convnext_convnext_1_norm_norm_LayerNormalization_weight_to_fp16, x = input_15_cast_fp16)[name = string("input_tensor_29_cast_fp16")];
            tensor<int32, [3]> var_551 = const()[name = string("op_551"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_21_pad_type_0 = const()[name = string("first_21_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_21_strides_0 = const()[name = string("first_21_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_21_pad_0 = const()[name = string("first_21_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_21_dilations_0 = const()[name = string("first_21_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_21_groups_0 = const()[name = string("first_21_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_convnext_convnext_1_pwconv1_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_1_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5321088)))];
            tensor<fp16, [1024]> text_encoder_convnext_convnext_1_pwconv1_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_1_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5845440)))];
            tensor<fp16, [1, 256, 64]> input_17_cast_fp16 = transpose(perm = var_551, x = input_tensor_29_cast_fp16)[name = string("transpose_43")];
            tensor<fp16, [1, 1024, 64]> first_21_cast_fp16 = conv(bias = text_encoder_convnext_convnext_1_pwconv1_Conv_bias_to_fp16, dilations = first_21_dilations_0, groups = first_21_groups_0, pad = first_21_pad_0, pad_type = first_21_pad_type_0, strides = first_21_strides_0, weight = text_encoder_convnext_convnext_1_pwconv1_Conv_weight_to_fp16, x = input_17_cast_fp16)[name = string("first_21_cast_fp16")];
            string input_19_mode_0 = const()[name = string("input_19_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 1024, 64]> input_19_cast_fp16 = gelu(mode = input_19_mode_0, x = first_21_cast_fp16)[name = string("input_19_cast_fp16")];
            string second_21_pad_type_0 = const()[name = string("second_21_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_21_strides_0 = const()[name = string("second_21_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_21_pad_0 = const()[name = string("second_21_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_21_dilations_0 = const()[name = string("second_21_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_21_groups_0 = const()[name = string("second_21_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> second_23_weight_0_to_fp16 = const()[name = string("second_23_weight_0_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(5847552)))];
            tensor<fp16, [256]> second_23_bias_0_to_fp16 = const()[name = string("second_23_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6371904)))];
            tensor<fp16, [1, 256, 64]> second_23_cast_fp16 = conv(bias = second_23_bias_0_to_fp16, dilations = second_21_dilations_0, groups = second_21_groups_0, pad = second_21_pad_0, pad_type = second_21_pad_type_0, strides = second_21_strides_0, weight = second_23_weight_0_to_fp16, x = input_19_cast_fp16)[name = string("second_23_cast_fp16")];
            tensor<fp16, [1, 256, 64]> first_29_cast_fp16 = add(x = input_11_cast_fp16, y = second_23_cast_fp16)[name = string("first_29_cast_fp16")];
            tensor<fp16, [1, 256, 64]> first_31_cast_fp16 = mul(x = first_29_cast_fp16, y = text_mask)[name = string("first_31_cast_fp16")];
            tensor<fp16, [1, 256, 64]> input_21_cast_fp16 = mul(x = first_31_cast_fp16, y = text_mask)[name = string("input_21_cast_fp16")];
            tensor<int32, [6]> input_23_pad_0 = const()[name = string("input_23_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            string input_23_mode_0 = const()[name = string("input_23_mode_0"), val = string("replicate")];
            fp16 const_2_to_fp16 = const()[name = string("const_2_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 256, 72]> input_23_cast_fp16 = pad(constant_val = const_2_to_fp16, mode = input_23_mode_0, pad = input_23_pad_0, x = input_21_cast_fp16)[name = string("input_23_cast_fp16")];
            string first_33_pad_type_0 = const()[name = string("first_33_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_33_dilations_0 = const()[name = string("first_33_dilations_0"), val = tensor<int32, [1]>([2])];
            int32 first_33_groups_0 = const()[name = string("first_33_groups_0"), val = int32(256)];
            tensor<int32, [1]> first_33_strides_0 = const()[name = string("first_33_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_33_pad_0 = const()[name = string("first_33_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [256, 1, 5]> text_encoder_convnext_convnext_2_dwconv_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_2_dwconv_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6372480)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_2_dwconv_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_2_dwconv_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6375104)))];
            tensor<fp16, [1, 256, 64]> first_33_cast_fp16 = conv(bias = text_encoder_convnext_convnext_2_dwconv_Conv_bias_to_fp16, dilations = first_33_dilations_0, groups = first_33_groups_0, pad = first_33_pad_0, pad_type = first_33_pad_type_0, strides = first_33_strides_0, weight = text_encoder_convnext_convnext_2_dwconv_Conv_weight_to_fp16, x = input_23_cast_fp16)[name = string("first_33_cast_fp16")];
            tensor<fp16, [1, 256, 64]> input_tensor_41_cast_fp16 = mul(x = first_33_cast_fp16, y = text_mask)[name = string("input_tensor_41_cast_fp16")];
            tensor<int32, [3]> var_608 = const()[name = string("op_608"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_43_axes_0 = const()[name = string("input_tensor_43_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_convnext_convnext_2_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_2_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6375680)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_2_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_2_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6376256)))];
            fp16 var_611_to_fp16 = const()[name = string("op_611_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 64, 256]> input_25_cast_fp16 = transpose(perm = var_608, x = input_tensor_41_cast_fp16)[name = string("transpose_42")];
            tensor<fp16, [1, 64, 256]> input_tensor_43_cast_fp16 = layer_norm(axes = input_tensor_43_axes_0, beta = text_encoder_convnext_convnext_2_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_611_to_fp16, gamma = text_encoder_convnext_convnext_2_norm_norm_LayerNormalization_weight_to_fp16, x = input_25_cast_fp16)[name = string("input_tensor_43_cast_fp16")];
            tensor<int32, [3]> var_620 = const()[name = string("op_620"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_35_pad_type_0 = const()[name = string("first_35_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_35_strides_0 = const()[name = string("first_35_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_35_pad_0 = const()[name = string("first_35_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_35_dilations_0 = const()[name = string("first_35_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_35_groups_0 = const()[name = string("first_35_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_convnext_convnext_2_pwconv1_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_2_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6376832)))];
            tensor<fp16, [1024]> text_encoder_convnext_convnext_2_pwconv1_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_2_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6901184)))];
            tensor<fp16, [1, 256, 64]> input_27_cast_fp16 = transpose(perm = var_620, x = input_tensor_43_cast_fp16)[name = string("transpose_41")];
            tensor<fp16, [1, 1024, 64]> first_35_cast_fp16 = conv(bias = text_encoder_convnext_convnext_2_pwconv1_Conv_bias_to_fp16, dilations = first_35_dilations_0, groups = first_35_groups_0, pad = first_35_pad_0, pad_type = first_35_pad_type_0, strides = first_35_strides_0, weight = text_encoder_convnext_convnext_2_pwconv1_Conv_weight_to_fp16, x = input_27_cast_fp16)[name = string("first_35_cast_fp16")];
            string input_29_mode_0 = const()[name = string("input_29_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 1024, 64]> input_29_cast_fp16 = gelu(mode = input_29_mode_0, x = first_35_cast_fp16)[name = string("input_29_cast_fp16")];
            string second_33_pad_type_0 = const()[name = string("second_33_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_33_strides_0 = const()[name = string("second_33_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_33_pad_0 = const()[name = string("second_33_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_33_dilations_0 = const()[name = string("second_33_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_33_groups_0 = const()[name = string("second_33_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> second_35_weight_0_to_fp16 = const()[name = string("second_35_weight_0_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(6903296)))];
            tensor<fp16, [256]> second_35_bias_0_to_fp16 = const()[name = string("second_35_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7427648)))];
            tensor<fp16, [1, 256, 64]> second_35_cast_fp16 = conv(bias = second_35_bias_0_to_fp16, dilations = second_33_dilations_0, groups = second_33_groups_0, pad = second_33_pad_0, pad_type = second_33_pad_type_0, strides = second_33_strides_0, weight = second_35_weight_0_to_fp16, x = input_29_cast_fp16)[name = string("second_35_cast_fp16")];
            tensor<fp16, [1, 256, 64]> first_43_cast_fp16 = add(x = input_21_cast_fp16, y = second_35_cast_fp16)[name = string("first_43_cast_fp16")];
            tensor<fp16, [1, 256, 64]> first_45_cast_fp16 = mul(x = first_43_cast_fp16, y = text_mask)[name = string("first_45_cast_fp16")];
            tensor<fp16, [1, 256, 64]> input_31_cast_fp16 = mul(x = first_45_cast_fp16, y = text_mask)[name = string("input_31_cast_fp16")];
            tensor<int32, [6]> input_33_pad_0 = const()[name = string("input_33_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            string input_33_mode_0 = const()[name = string("input_33_mode_0"), val = string("replicate")];
            fp16 const_3_to_fp16 = const()[name = string("const_3_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 256, 72]> input_33_cast_fp16 = pad(constant_val = const_3_to_fp16, mode = input_33_mode_0, pad = input_33_pad_0, x = input_31_cast_fp16)[name = string("input_33_cast_fp16")];
            string first_47_pad_type_0 = const()[name = string("first_47_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_47_dilations_0 = const()[name = string("first_47_dilations_0"), val = tensor<int32, [1]>([2])];
            int32 first_47_groups_0 = const()[name = string("first_47_groups_0"), val = int32(256)];
            tensor<int32, [1]> first_47_strides_0 = const()[name = string("first_47_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_47_pad_0 = const()[name = string("first_47_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [256, 1, 5]> text_encoder_convnext_convnext_3_dwconv_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_3_dwconv_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7428224)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_3_dwconv_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_3_dwconv_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7430848)))];
            tensor<fp16, [1, 256, 64]> first_47_cast_fp16 = conv(bias = text_encoder_convnext_convnext_3_dwconv_Conv_bias_to_fp16, dilations = first_47_dilations_0, groups = first_47_groups_0, pad = first_47_pad_0, pad_type = first_47_pad_type_0, strides = first_47_strides_0, weight = text_encoder_convnext_convnext_3_dwconv_Conv_weight_to_fp16, x = input_33_cast_fp16)[name = string("first_47_cast_fp16")];
            tensor<fp16, [1, 256, 64]> input_tensor_55_cast_fp16 = mul(x = first_47_cast_fp16, y = text_mask)[name = string("input_tensor_55_cast_fp16")];
            tensor<int32, [3]> var_677 = const()[name = string("op_677"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_57_axes_0 = const()[name = string("input_tensor_57_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_convnext_convnext_3_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_3_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7431424)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_3_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_3_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7432000)))];
            fp16 var_680_to_fp16 = const()[name = string("op_680_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 64, 256]> input_35_cast_fp16 = transpose(perm = var_677, x = input_tensor_55_cast_fp16)[name = string("transpose_40")];
            tensor<fp16, [1, 64, 256]> input_tensor_57_cast_fp16 = layer_norm(axes = input_tensor_57_axes_0, beta = text_encoder_convnext_convnext_3_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_680_to_fp16, gamma = text_encoder_convnext_convnext_3_norm_norm_LayerNormalization_weight_to_fp16, x = input_35_cast_fp16)[name = string("input_tensor_57_cast_fp16")];
            tensor<int32, [3]> var_689 = const()[name = string("op_689"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_49_pad_type_0 = const()[name = string("first_49_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_49_strides_0 = const()[name = string("first_49_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_49_pad_0 = const()[name = string("first_49_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_49_dilations_0 = const()[name = string("first_49_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_49_groups_0 = const()[name = string("first_49_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_convnext_convnext_3_pwconv1_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_3_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7432576)))];
            tensor<fp16, [1024]> text_encoder_convnext_convnext_3_pwconv1_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_3_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7956928)))];
            tensor<fp16, [1, 256, 64]> input_37_cast_fp16 = transpose(perm = var_689, x = input_tensor_57_cast_fp16)[name = string("transpose_39")];
            tensor<fp16, [1, 1024, 64]> first_49_cast_fp16 = conv(bias = text_encoder_convnext_convnext_3_pwconv1_Conv_bias_to_fp16, dilations = first_49_dilations_0, groups = first_49_groups_0, pad = first_49_pad_0, pad_type = first_49_pad_type_0, strides = first_49_strides_0, weight = text_encoder_convnext_convnext_3_pwconv1_Conv_weight_to_fp16, x = input_37_cast_fp16)[name = string("first_49_cast_fp16")];
            string input_39_mode_0 = const()[name = string("input_39_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 1024, 64]> input_39_cast_fp16 = gelu(mode = input_39_mode_0, x = first_49_cast_fp16)[name = string("input_39_cast_fp16")];
            string second_45_pad_type_0 = const()[name = string("second_45_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_45_strides_0 = const()[name = string("second_45_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_45_pad_0 = const()[name = string("second_45_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_45_dilations_0 = const()[name = string("second_45_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_45_groups_0 = const()[name = string("second_45_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> second_47_weight_0_to_fp16 = const()[name = string("second_47_weight_0_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(7959040)))];
            tensor<fp16, [256]> second_47_bias_0_to_fp16 = const()[name = string("second_47_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8483392)))];
            tensor<fp16, [1, 256, 64]> second_47_cast_fp16 = conv(bias = second_47_bias_0_to_fp16, dilations = second_45_dilations_0, groups = second_45_groups_0, pad = second_45_pad_0, pad_type = second_45_pad_type_0, strides = second_45_strides_0, weight = second_47_weight_0_to_fp16, x = input_39_cast_fp16)[name = string("second_47_cast_fp16")];
            tensor<fp16, [1, 256, 64]> first_57_cast_fp16 = add(x = input_31_cast_fp16, y = second_47_cast_fp16)[name = string("first_57_cast_fp16")];
            tensor<fp16, [1, 256, 64]> first_59_cast_fp16 = mul(x = first_57_cast_fp16, y = text_mask)[name = string("first_59_cast_fp16")];
            tensor<fp16, [1, 256, 64]> input_41_cast_fp16 = mul(x = first_59_cast_fp16, y = text_mask)[name = string("input_41_cast_fp16")];
            tensor<int32, [6]> input_43_pad_0 = const()[name = string("input_43_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 8, 8])];
            string input_43_mode_0 = const()[name = string("input_43_mode_0"), val = string("replicate")];
            fp16 const_4_to_fp16 = const()[name = string("const_4_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 256, 80]> input_43_cast_fp16 = pad(constant_val = const_4_to_fp16, mode = input_43_mode_0, pad = input_43_pad_0, x = input_41_cast_fp16)[name = string("input_43_cast_fp16")];
            string first_61_pad_type_0 = const()[name = string("first_61_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_61_dilations_0 = const()[name = string("first_61_dilations_0"), val = tensor<int32, [1]>([4])];
            int32 first_61_groups_0 = const()[name = string("first_61_groups_0"), val = int32(256)];
            tensor<int32, [1]> first_61_strides_0 = const()[name = string("first_61_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_61_pad_0 = const()[name = string("first_61_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [256, 1, 5]> text_encoder_convnext_convnext_4_dwconv_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_4_dwconv_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8483968)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_4_dwconv_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_4_dwconv_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8486592)))];
            tensor<fp16, [1, 256, 64]> first_61_cast_fp16 = conv(bias = text_encoder_convnext_convnext_4_dwconv_Conv_bias_to_fp16, dilations = first_61_dilations_0, groups = first_61_groups_0, pad = first_61_pad_0, pad_type = first_61_pad_type_0, strides = first_61_strides_0, weight = text_encoder_convnext_convnext_4_dwconv_Conv_weight_to_fp16, x = input_43_cast_fp16)[name = string("first_61_cast_fp16")];
            tensor<fp16, [1, 256, 64]> input_tensor_69_cast_fp16 = mul(x = first_61_cast_fp16, y = text_mask)[name = string("input_tensor_69_cast_fp16")];
            tensor<int32, [3]> var_746 = const()[name = string("op_746"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_71_axes_0 = const()[name = string("input_tensor_71_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_convnext_convnext_4_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_4_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8487168)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_4_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_4_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8487744)))];
            fp16 var_749_to_fp16 = const()[name = string("op_749_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 64, 256]> input_45_cast_fp16 = transpose(perm = var_746, x = input_tensor_69_cast_fp16)[name = string("transpose_38")];
            tensor<fp16, [1, 64, 256]> input_tensor_71_cast_fp16 = layer_norm(axes = input_tensor_71_axes_0, beta = text_encoder_convnext_convnext_4_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_749_to_fp16, gamma = text_encoder_convnext_convnext_4_norm_norm_LayerNormalization_weight_to_fp16, x = input_45_cast_fp16)[name = string("input_tensor_71_cast_fp16")];
            tensor<int32, [3]> var_758 = const()[name = string("op_758"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_63_pad_type_0 = const()[name = string("first_63_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_63_strides_0 = const()[name = string("first_63_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_63_pad_0 = const()[name = string("first_63_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_63_dilations_0 = const()[name = string("first_63_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_63_groups_0 = const()[name = string("first_63_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_convnext_convnext_4_pwconv1_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_4_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(8488320)))];
            tensor<fp16, [1024]> text_encoder_convnext_convnext_4_pwconv1_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_4_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9012672)))];
            tensor<fp16, [1, 256, 64]> input_47_cast_fp16 = transpose(perm = var_758, x = input_tensor_71_cast_fp16)[name = string("transpose_37")];
            tensor<fp16, [1, 1024, 64]> first_63_cast_fp16 = conv(bias = text_encoder_convnext_convnext_4_pwconv1_Conv_bias_to_fp16, dilations = first_63_dilations_0, groups = first_63_groups_0, pad = first_63_pad_0, pad_type = first_63_pad_type_0, strides = first_63_strides_0, weight = text_encoder_convnext_convnext_4_pwconv1_Conv_weight_to_fp16, x = input_47_cast_fp16)[name = string("first_63_cast_fp16")];
            string input_49_mode_0 = const()[name = string("input_49_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 1024, 64]> input_49_cast_fp16 = gelu(mode = input_49_mode_0, x = first_63_cast_fp16)[name = string("input_49_cast_fp16")];
            string second_57_pad_type_0 = const()[name = string("second_57_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_57_strides_0 = const()[name = string("second_57_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_57_pad_0 = const()[name = string("second_57_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_57_dilations_0 = const()[name = string("second_57_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_57_groups_0 = const()[name = string("second_57_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> second_59_weight_0_to_fp16 = const()[name = string("second_59_weight_0_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9014784)))];
            tensor<fp16, [256]> second_59_bias_0_to_fp16 = const()[name = string("second_59_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9539136)))];
            tensor<fp16, [1, 256, 64]> second_59_cast_fp16 = conv(bias = second_59_bias_0_to_fp16, dilations = second_57_dilations_0, groups = second_57_groups_0, pad = second_57_pad_0, pad_type = second_57_pad_type_0, strides = second_57_strides_0, weight = second_59_weight_0_to_fp16, x = input_49_cast_fp16)[name = string("second_59_cast_fp16")];
            tensor<fp16, [1, 256, 64]> first_71_cast_fp16 = add(x = input_41_cast_fp16, y = second_59_cast_fp16)[name = string("first_71_cast_fp16")];
            tensor<fp16, [1, 256, 64]> first_73_cast_fp16 = mul(x = first_71_cast_fp16, y = text_mask)[name = string("first_73_cast_fp16")];
            tensor<fp16, [1, 256, 64]> input_51_cast_fp16 = mul(x = first_73_cast_fp16, y = text_mask)[name = string("input_51_cast_fp16")];
            tensor<int32, [6]> input_53_pad_0 = const()[name = string("input_53_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 8, 8])];
            string input_53_mode_0 = const()[name = string("input_53_mode_0"), val = string("replicate")];
            fp16 const_5_to_fp16 = const()[name = string("const_5_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 256, 80]> input_53_cast_fp16 = pad(constant_val = const_5_to_fp16, mode = input_53_mode_0, pad = input_53_pad_0, x = input_51_cast_fp16)[name = string("input_53_cast_fp16")];
            string first_75_pad_type_0 = const()[name = string("first_75_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_75_dilations_0 = const()[name = string("first_75_dilations_0"), val = tensor<int32, [1]>([4])];
            int32 first_75_groups_0 = const()[name = string("first_75_groups_0"), val = int32(256)];
            tensor<int32, [1]> first_75_strides_0 = const()[name = string("first_75_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_75_pad_0 = const()[name = string("first_75_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<fp16, [256, 1, 5]> text_encoder_convnext_convnext_5_dwconv_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_5_dwconv_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1, 5]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9539712)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_5_dwconv_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_5_dwconv_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9542336)))];
            tensor<fp16, [1, 256, 64]> first_75_cast_fp16 = conv(bias = text_encoder_convnext_convnext_5_dwconv_Conv_bias_to_fp16, dilations = first_75_dilations_0, groups = first_75_groups_0, pad = first_75_pad_0, pad_type = first_75_pad_type_0, strides = first_75_strides_0, weight = text_encoder_convnext_convnext_5_dwconv_Conv_weight_to_fp16, x = input_53_cast_fp16)[name = string("first_75_cast_fp16")];
            tensor<fp16, [1, 256, 64]> input_tensor_83_cast_fp16 = mul(x = first_75_cast_fp16, y = text_mask)[name = string("input_tensor_83_cast_fp16")];
            tensor<int32, [3]> var_815 = const()[name = string("op_815"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_85_axes_0 = const()[name = string("input_tensor_85_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_convnext_convnext_5_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_5_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9542912)))];
            tensor<fp16, [256]> text_encoder_convnext_convnext_5_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_5_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9543488)))];
            fp16 var_818_to_fp16 = const()[name = string("op_818_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 64, 256]> input_55_cast_fp16 = transpose(perm = var_815, x = input_tensor_83_cast_fp16)[name = string("transpose_36")];
            tensor<fp16, [1, 64, 256]> input_tensor_85_cast_fp16 = layer_norm(axes = input_tensor_85_axes_0, beta = text_encoder_convnext_convnext_5_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_818_to_fp16, gamma = text_encoder_convnext_convnext_5_norm_norm_LayerNormalization_weight_to_fp16, x = input_55_cast_fp16)[name = string("input_tensor_85_cast_fp16")];
            tensor<int32, [3]> var_827 = const()[name = string("op_827"), val = tensor<int32, [3]>([0, 2, 1])];
            string first_77_pad_type_0 = const()[name = string("first_77_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_77_strides_0 = const()[name = string("first_77_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_77_pad_0 = const()[name = string("first_77_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_77_dilations_0 = const()[name = string("first_77_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_77_groups_0 = const()[name = string("first_77_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_convnext_convnext_5_pwconv1_Conv_weight_to_fp16 = const()[name = string("text_encoder_convnext_convnext_5_pwconv1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(9544064)))];
            tensor<fp16, [1024]> text_encoder_convnext_convnext_5_pwconv1_Conv_bias_to_fp16 = const()[name = string("text_encoder_convnext_convnext_5_pwconv1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10068416)))];
            tensor<fp16, [1, 256, 64]> input_57_cast_fp16 = transpose(perm = var_827, x = input_tensor_85_cast_fp16)[name = string("transpose_35")];
            tensor<fp16, [1, 1024, 64]> first_77_cast_fp16 = conv(bias = text_encoder_convnext_convnext_5_pwconv1_Conv_bias_to_fp16, dilations = first_77_dilations_0, groups = first_77_groups_0, pad = first_77_pad_0, pad_type = first_77_pad_type_0, strides = first_77_strides_0, weight = text_encoder_convnext_convnext_5_pwconv1_Conv_weight_to_fp16, x = input_57_cast_fp16)[name = string("first_77_cast_fp16")];
            string input_59_mode_0 = const()[name = string("input_59_mode_0"), val = string("EXACT")];
            tensor<fp16, [1, 1024, 64]> input_59_cast_fp16 = gelu(mode = input_59_mode_0, x = first_77_cast_fp16)[name = string("input_59_cast_fp16")];
            string second_69_pad_type_0 = const()[name = string("second_69_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_69_strides_0 = const()[name = string("second_69_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_69_pad_0 = const()[name = string("second_69_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_69_dilations_0 = const()[name = string("second_69_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_69_groups_0 = const()[name = string("second_69_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> second_71_weight_0_to_fp16 = const()[name = string("second_71_weight_0_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10070528)))];
            tensor<fp16, [256]> second_71_bias_0_to_fp16 = const()[name = string("second_71_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10594880)))];
            tensor<fp16, [1, 256, 64]> second_71_cast_fp16 = conv(bias = second_71_bias_0_to_fp16, dilations = second_69_dilations_0, groups = second_69_groups_0, pad = second_69_pad_0, pad_type = second_69_pad_type_0, strides = second_69_strides_0, weight = second_71_weight_0_to_fp16, x = input_59_cast_fp16)[name = string("second_71_cast_fp16")];
            tensor<fp16, [1, 256, 64]> first_85_cast_fp16 = add(x = input_51_cast_fp16, y = second_71_cast_fp16)[name = string("first_85_cast_fp16")];
            tensor<fp16, [1, 256, 64]> first_89_cast_fp16 = mul(x = first_85_cast_fp16, y = text_mask)[name = string("first_89_cast_fp16")];
            tensor<int32, [1]> first_87_axes_0 = const()[name = string("first_87_axes_0"), val = tensor<int32, [1]>([2])];
            tensor<fp16, [1, 1, 1, 64]> first_87_cast_fp16 = expand_dims(axes = first_87_axes_0, x = text_mask)[name = string("first_87_cast_fp16")];
            tensor<int32, [1]> second_73_axes_0 = const()[name = string("second_73_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1, 1, 64, 1]> second_73_cast_fp16 = expand_dims(axes = second_73_axes_0, x = text_mask)[name = string("second_73_cast_fp16")];
            tensor<fp16, [1, 1, 64, 64]> x_45_cast_fp16 = mul(x = first_87_cast_fp16, y = second_73_cast_fp16)[name = string("x_45_cast_fp16")];
            tensor<fp16, [1, 256, 64]> input_61_cast_fp16 = mul(x = first_89_cast_fp16, y = text_mask)[name = string("input_61_cast_fp16")];
            string input_tensor_97_pad_type_0 = const()[name = string("input_tensor_97_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_97_strides_0 = const()[name = string("input_tensor_97_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_97_pad_0 = const()[name = string("input_tensor_97_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_97_dilations_0 = const()[name = string("input_tensor_97_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_97_groups_0 = const()[name = string("input_tensor_97_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_0_conv_q_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_q_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10595456)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_0_conv_q_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_q_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10726592)))];
            tensor<fp16, [1, 256, 64]> input_tensor_97_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_0_conv_q_Conv_bias_to_fp16, dilations = input_tensor_97_dilations_0, groups = input_tensor_97_groups_0, pad = input_tensor_97_pad_0, pad_type = input_tensor_97_pad_type_0, strides = input_tensor_97_strides_0, weight = text_encoder_attn_encoder_attn_layers_0_conv_q_Conv_weight_to_fp16, x = input_61_cast_fp16)[name = string("input_tensor_97_cast_fp16")];
            string input_tensor_89_pad_type_0 = const()[name = string("input_tensor_89_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_89_strides_0 = const()[name = string("input_tensor_89_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_89_pad_0 = const()[name = string("input_tensor_89_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_89_dilations_0 = const()[name = string("input_tensor_89_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_89_groups_0 = const()[name = string("input_tensor_89_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_0_conv_k_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_k_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10727168)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_0_conv_k_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_k_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10858304)))];
            tensor<fp16, [1, 256, 64]> input_tensor_89_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_0_conv_k_Conv_bias_to_fp16, dilations = input_tensor_89_dilations_0, groups = input_tensor_89_groups_0, pad = input_tensor_89_pad_0, pad_type = input_tensor_89_pad_type_0, strides = input_tensor_89_strides_0, weight = text_encoder_attn_encoder_attn_layers_0_conv_k_Conv_weight_to_fp16, x = input_61_cast_fp16)[name = string("input_tensor_89_cast_fp16")];
            string input_tensor_109_pad_type_0 = const()[name = string("input_tensor_109_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_109_strides_0 = const()[name = string("input_tensor_109_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_109_pad_0 = const()[name = string("input_tensor_109_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_109_dilations_0 = const()[name = string("input_tensor_109_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_109_groups_0 = const()[name = string("input_tensor_109_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_0_conv_v_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_v_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10858880)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_0_conv_v_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_v_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(10990016)))];
            tensor<fp16, [1, 256, 64]> input_tensor_109_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_0_conv_v_Conv_bias_to_fp16, dilations = input_tensor_109_dilations_0, groups = input_tensor_109_groups_0, pad = input_tensor_109_pad_0, pad_type = input_tensor_109_pad_type_0, strides = input_tensor_109_strides_0, weight = text_encoder_attn_encoder_attn_layers_0_conv_v_Conv_weight_to_fp16, x = input_61_cast_fp16)[name = string("input_tensor_109_cast_fp16")];
            tensor<int32, [4]> var_973 = const()[name = string("op_973"), val = tensor<int32, [4]>([1, 4, 64, 64])];
            tensor<fp16, [1, 4, 64, 64]> input_tensor_105_cast_fp16 = reshape(shape = var_973, x = input_tensor_97_cast_fp16)[name = string("input_tensor_105_cast_fp16")];
            tensor<int32, [4]> var_979 = const()[name = string("op_979"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [4]> var_1005 = const()[name = string("op_1005"), val = tensor<int32, [4]>([1, 4, 64, 64])];
            tensor<fp16, [1, 4, 64, 64]> y_1_cast_fp16 = reshape(shape = var_1005, x = input_tensor_89_cast_fp16)[name = string("y_1_cast_fp16")];
            tensor<int32, [4]> var_1017 = const()[name = string("op_1017"), val = tensor<int32, [4]>([1, 4, 64, 64])];
            tensor<fp16, [1, 4, 64, 64]> input_tensor_111_cast_fp16 = reshape(shape = var_1017, x = input_tensor_109_cast_fp16)[name = string("input_tensor_111_cast_fp16")];
            fp16 _inversed_x_25_y_0_to_fp16 = const()[name = string("_inversed_x_25_y_0_to_fp16"), val = fp16(0x1p-3)];
            tensor<fp16, [1, 4, 64, 64]> first_91_cast_fp16 = transpose(perm = var_979, x = input_tensor_105_cast_fp16)[name = string("transpose_34")];
            tensor<fp16, [1, 4, 64, 64]> _inversed_x_25_cast_fp16 = mul(x = first_91_cast_fp16, y = _inversed_x_25_y_0_to_fp16)[name = string("_inversed_x_25_cast_fp16")];
            bool first_107_transpose_x_0 = const()[name = string("first_107_transpose_x_0"), val = bool(false)];
            bool first_107_transpose_y_0 = const()[name = string("first_107_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 4, 64, 64]> first_107_cast_fp16 = matmul(transpose_x = first_107_transpose_x_0, transpose_y = first_107_transpose_y_0, x = _inversed_x_25_cast_fp16, y = y_1_cast_fp16)[name = string("first_107_cast_fp16")];
            bool input_tensor_143_transpose_x_0 = const()[name = string("input_tensor_143_transpose_x_0"), val = bool(false)];
            bool input_tensor_143_transpose_y_0 = const()[name = string("input_tensor_143_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 64, 127]> y_3_to_fp16 = const()[name = string("y_3_to_fp16"), val = tensor<fp16, [1, 1, 64, 127]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17877760)))];
            tensor<fp16, [1, 4, 64, 127]> input_tensor_143_cast_fp16 = matmul(transpose_x = input_tensor_143_transpose_x_0, transpose_y = input_tensor_143_transpose_y_0, x = _inversed_x_25_cast_fp16, y = y_3_to_fp16)[name = string("input_tensor_143_cast_fp16")];
            tensor<int32, [8]> input_tensor_165_pad_0 = const()[name = string("input_tensor_165_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 1])];
            string input_tensor_165_mode_0 = const()[name = string("input_tensor_165_mode_0"), val = string("constant")];
            fp16 const_23_to_fp16 = const()[name = string("const_23_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 64, 128]> input_tensor_165_cast_fp16 = pad(constant_val = const_23_to_fp16, mode = input_tensor_165_mode_0, pad = input_tensor_165_pad_0, x = input_tensor_143_cast_fp16)[name = string("input_tensor_165_cast_fp16")];
            tensor<int32, [3]> var_1140 = const()[name = string("op_1140"), val = tensor<int32, [3]>([1, 4, 8192])];
            tensor<fp16, [1, 4, 8192]> input_69_cast_fp16 = reshape(shape = var_1140, x = input_tensor_165_cast_fp16)[name = string("input_69_cast_fp16")];
            tensor<int32, [6]> input_tensor_187_pad_0 = const()[name = string("input_tensor_187_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 0, 63])];
            string input_tensor_187_mode_0 = const()[name = string("input_tensor_187_mode_0"), val = string("constant")];
            fp16 const_24_to_fp16 = const()[name = string("const_24_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 8255]> input_tensor_187_cast_fp16 = pad(constant_val = const_24_to_fp16, mode = input_tensor_187_mode_0, pad = input_tensor_187_pad_0, x = input_69_cast_fp16)[name = string("input_tensor_187_cast_fp16")];
            tensor<int32, [4]> var_1175 = const()[name = string("op_1175"), val = tensor<int32, [4]>([1, 4, 65, 127])];
            tensor<fp16, [1, 4, 65, 127]> x_41_cast_fp16 = reshape(shape = var_1175, x = input_tensor_187_cast_fp16)[name = string("x_41_cast_fp16")];
            tensor<int32, [4]> x_43_begin_0 = const()[name = string("x_43_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> x_43_end_0 = const()[name = string("x_43_end_0"), val = tensor<int32, [4]>([1, 4, 64, 127])];
            tensor<bool, [4]> x_43_end_mask_0 = const()[name = string("x_43_end_mask_0"), val = tensor<bool, [4]>([true, true, false, true])];
            tensor<fp16, [1, 4, 64, 127]> x_43_cast_fp16 = slice_by_index(begin = x_43_begin_0, end = x_43_end_0, end_mask = x_43_end_mask_0, x = x_41_cast_fp16)[name = string("x_43_cast_fp16")];
            tensor<int32, [4]> second_97_begin_0 = const()[name = string("second_97_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 63])];
            tensor<int32, [4]> second_97_end_0 = const()[name = string("second_97_end_0"), val = tensor<int32, [4]>([1, 4, 64, 1])];
            tensor<bool, [4]> second_97_end_mask_0 = const()[name = string("second_97_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 64, 64]> second_97_cast_fp16 = slice_by_index(begin = second_97_begin_0, end = second_97_end_0, end_mask = second_97_end_mask_0, x = x_43_cast_fp16)[name = string("second_97_cast_fp16")];
            tensor<fp16, [1, 4, 64, 64]> y_7_cast_fp16 = add(x = first_107_cast_fp16, y = second_97_cast_fp16)[name = string("y_7_cast_fp16")];
            fp16 text_encoder_attn_encoder_attn_layers_0_Constant_87_value_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_Constant_87_value_to_fp16"), val = fp16(0x0p+0)];
            tensor<bool, [1, 1, 64, 64]> input_tensor_189_cast_fp16 = equal(x = x_45_cast_fp16, y = text_encoder_attn_encoder_attn_layers_0_Constant_87_value_to_fp16)[name = string("input_tensor_189_cast_fp16")];
            tensor<int32, [4]> condition_1_after_broadcast_reps_0 = const()[name = string("condition_1_after_broadcast_reps_0"), val = tensor<int32, [4]>([1, 4, 1, 1])];
            tensor<bool, [1, 4, 64, 64]> condition_1_after_broadcast = tile(reps = condition_1_after_broadcast_reps_0, x = input_tensor_189_cast_fp16)[name = string("condition_1_after_broadcast")];
            tensor<fp16, [1, 4, 64, 64]> text_encoder_attn_encoder_attn_layers_0_Constant_88_value_after_broadcast_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_Constant_88_value_after_broadcast_to_fp16"), val = tensor<fp16, [1, 4, 64, 64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17894080)))];
            tensor<fp16, [1, 4, 64, 64]> input_71_cast_fp16 = select(a = text_encoder_attn_encoder_attn_layers_0_Constant_88_value_after_broadcast_to_fp16, b = y_7_cast_fp16, cond = condition_1_after_broadcast)[name = string("input_71_cast_fp16")];
            int32 var_1218 = const()[name = string("op_1218"), val = int32(-1)];
            tensor<fp16, [1, 4, 64, 64]> x_49_cast_fp16 = softmax(axis = var_1218, x = input_71_cast_fp16)[name = string("x_49_cast_fp16")];
            bool first_119_transpose_x_1 = const()[name = string("first_119_transpose_x_1"), val = bool(false)];
            bool first_119_transpose_y_1 = const()[name = string("first_119_transpose_y_1"), val = bool(true)];
            tensor<fp16, [1, 4, 64, 64]> first_119_cast_fp16 = matmul(transpose_x = first_119_transpose_x_1, transpose_y = first_119_transpose_y_1, x = x_49_cast_fp16, y = input_tensor_111_cast_fp16)[name = string("first_119_cast_fp16")];
            tensor<int32, [8]> input_tensor_219_pad_0 = const()[name = string("input_tensor_219_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 63])];
            string input_tensor_219_mode_0 = const()[name = string("input_tensor_219_mode_0"), val = string("constant")];
            fp16 const_31_to_fp16 = const()[name = string("const_31_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 64, 127]> input_tensor_219_cast_fp16 = pad(constant_val = const_31_to_fp16, mode = input_tensor_219_mode_0, pad = input_tensor_219_pad_0, x = x_49_cast_fp16)[name = string("input_tensor_219_cast_fp16")];
            tensor<int32, [3]> var_1292 = const()[name = string("op_1292"), val = tensor<int32, [3]>([1, 4, 8128])];
            tensor<fp16, [1, 4, 8128]> input_73_cast_fp16 = reshape(shape = var_1292, x = input_tensor_219_cast_fp16)[name = string("input_73_cast_fp16")];
            tensor<int32, [6]> input_tensor_237_pad_0 = const()[name = string("input_tensor_237_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 64, 0])];
            string input_tensor_237_mode_0 = const()[name = string("input_tensor_237_mode_0"), val = string("constant")];
            fp16 const_32_to_fp16 = const()[name = string("const_32_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 8192]> input_tensor_237_cast_fp16 = pad(constant_val = const_32_to_fp16, mode = input_tensor_237_mode_0, pad = input_tensor_237_pad_0, x = input_73_cast_fp16)[name = string("input_tensor_237_cast_fp16")];
            tensor<int32, [4]> var_1322 = const()[name = string("op_1322"), val = tensor<int32, [4]>([1, 4, 64, 128])];
            tensor<fp16, [1, 4, 64, 128]> x_59_cast_fp16 = reshape(shape = var_1322, x = input_tensor_237_cast_fp16)[name = string("x_59_cast_fp16")];
            tensor<int32, [4]> x_67_begin_0 = const()[name = string("x_67_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 1])];
            tensor<int32, [4]> x_67_end_0 = const()[name = string("x_67_end_0"), val = tensor<int32, [4]>([1, 4, 64, 1])];
            tensor<bool, [4]> x_67_end_mask_0 = const()[name = string("x_67_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 64, 127]> x_67_cast_fp16 = slice_by_index(begin = x_67_begin_0, end = x_67_end_0, end_mask = x_67_end_mask_0, x = x_59_cast_fp16)[name = string("x_67_cast_fp16")];
            bool second_111_transpose_x_0 = const()[name = string("second_111_transpose_x_0"), val = bool(false)];
            bool second_111_transpose_y_0 = const()[name = string("second_111_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 127, 64]> y_11_to_fp16 = const()[name = string("y_11_to_fp16"), val = tensor<fp16, [1, 1, 127, 64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17926912)))];
            tensor<fp16, [1, 4, 64, 64]> second_111_cast_fp16 = matmul(transpose_x = second_111_transpose_x_0, transpose_y = second_111_transpose_y_0, x = x_67_cast_fp16, y = y_11_to_fp16)[name = string("second_111_cast_fp16")];
            tensor<fp16, [1, 4, 64, 64]> input_tensor_255_cast_fp16 = add(x = first_119_cast_fp16, y = second_111_cast_fp16)[name = string("input_tensor_255_cast_fp16")];
            tensor<int32, [4]> var_1369 = const()[name = string("op_1369"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [3]> var_1388 = const()[name = string("op_1388"), val = tensor<int32, [3]>([1, 256, 64])];
            tensor<fp16, [1, 4, 64, 64]> input_tensor_259_cast_fp16 = transpose(perm = var_1369, x = input_tensor_255_cast_fp16)[name = string("transpose_33")];
            tensor<fp16, [1, 256, 64]> input_77_cast_fp16 = reshape(shape = var_1388, x = input_tensor_259_cast_fp16)[name = string("input_77_cast_fp16")];
            string second_113_pad_type_0 = const()[name = string("second_113_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_113_strides_0 = const()[name = string("second_113_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_113_pad_0 = const()[name = string("second_113_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_113_dilations_0 = const()[name = string("second_113_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_113_groups_0 = const()[name = string("second_113_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_0_conv_o_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_o_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11000768)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_0_conv_o_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_0_conv_o_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11131904)))];
            tensor<fp16, [1, 256, 64]> second_113_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_0_conv_o_Conv_bias_to_fp16, dilations = second_113_dilations_0, groups = second_113_groups_0, pad = second_113_pad_0, pad_type = second_113_pad_type_0, strides = second_113_strides_0, weight = text_encoder_attn_encoder_attn_layers_0_conv_o_Conv_weight_to_fp16, x = input_77_cast_fp16)[name = string("second_113_cast_fp16")];
            tensor<fp16, [1, 256, 64]> input_tensor_261_cast_fp16 = add(x = input_61_cast_fp16, y = second_113_cast_fp16)[name = string("input_tensor_261_cast_fp16")];
            tensor<int32, [3]> var_1406 = const()[name = string("op_1406"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_263_axes_0 = const()[name = string("input_tensor_263_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_0_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_0_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11132480)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_0_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_0_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11133056)))];
            fp16 var_1409_to_fp16 = const()[name = string("op_1409_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 64, 256]> input_79_cast_fp16 = transpose(perm = var_1406, x = input_tensor_261_cast_fp16)[name = string("transpose_32")];
            tensor<fp16, [1, 64, 256]> input_tensor_263_cast_fp16 = layer_norm(axes = input_tensor_263_axes_0, beta = text_encoder_attn_encoder_norm_layers_1_0_norm_LayerNormalization_bias_to_fp16, epsilon = var_1409_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_1_0_norm_LayerNormalization_weight_to_fp16, x = input_79_cast_fp16)[name = string("input_tensor_263_cast_fp16")];
            tensor<int32, [3]> var_1418 = const()[name = string("op_1418"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 256, 64]> first_121_cast_fp16 = transpose(perm = var_1418, x = input_tensor_263_cast_fp16)[name = string("transpose_31")];
            tensor<fp16, [1, 256, 64]> input_81_cast_fp16 = mul(x = first_121_cast_fp16, y = text_mask)[name = string("input_81_cast_fp16")];
            string input_83_pad_type_0 = const()[name = string("input_83_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_83_strides_0 = const()[name = string("input_83_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_83_pad_0 = const()[name = string("input_83_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_83_dilations_0 = const()[name = string("input_83_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_83_groups_0 = const()[name = string("input_83_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_attn_encoder_ffn_layers_0_conv_1_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_0_conv_1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11133632)))];
            tensor<fp16, [1024]> text_encoder_attn_encoder_ffn_layers_0_conv_1_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_0_conv_1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11657984)))];
            tensor<fp16, [1, 1024, 64]> input_83_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_0_conv_1_Conv_bias_to_fp16, dilations = input_83_dilations_0, groups = input_83_groups_0, pad = input_83_pad_0, pad_type = input_83_pad_type_0, strides = input_83_strides_0, weight = text_encoder_attn_encoder_ffn_layers_0_conv_1_Conv_weight_to_fp16, x = input_81_cast_fp16)[name = string("input_83_cast_fp16")];
            tensor<fp16, [1, 1024, 64]> first_123_cast_fp16 = relu(x = input_83_cast_fp16)[name = string("first_123_cast_fp16")];
            tensor<fp16, [1, 1024, 64]> input_85_cast_fp16 = mul(x = first_123_cast_fp16, y = text_mask)[name = string("input_85_cast_fp16")];
            string first_125_pad_type_0 = const()[name = string("first_125_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_125_strides_0 = const()[name = string("first_125_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_125_pad_0 = const()[name = string("first_125_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_125_dilations_0 = const()[name = string("first_125_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_125_groups_0 = const()[name = string("first_125_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> text_encoder_attn_encoder_ffn_layers_0_conv_2_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_0_conv_2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(11660096)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_ffn_layers_0_conv_2_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_0_conv_2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12184448)))];
            tensor<fp16, [1, 256, 64]> first_125_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_0_conv_2_Conv_bias_to_fp16, dilations = first_125_dilations_0, groups = first_125_groups_0, pad = first_125_pad_0, pad_type = first_125_pad_type_0, strides = first_125_strides_0, weight = text_encoder_attn_encoder_ffn_layers_0_conv_2_Conv_weight_to_fp16, x = input_85_cast_fp16)[name = string("first_125_cast_fp16")];
            tensor<fp16, [1, 256, 64]> second_115_cast_fp16 = mul(x = first_125_cast_fp16, y = text_mask)[name = string("second_115_cast_fp16")];
            tensor<fp16, [1, 256, 64]> input_tensor_265_cast_fp16 = add(x = first_121_cast_fp16, y = second_115_cast_fp16)[name = string("input_tensor_265_cast_fp16")];
            tensor<int32, [3]> var_1451 = const()[name = string("op_1451"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_267_axes_0 = const()[name = string("input_tensor_267_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_0_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_0_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12185024)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_0_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_0_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12185600)))];
            fp16 var_1454_to_fp16 = const()[name = string("op_1454_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 64, 256]> input_87_cast_fp16 = transpose(perm = var_1451, x = input_tensor_265_cast_fp16)[name = string("transpose_30")];
            tensor<fp16, [1, 64, 256]> input_tensor_267_cast_fp16 = layer_norm(axes = input_tensor_267_axes_0, beta = text_encoder_attn_encoder_norm_layers_2_0_norm_LayerNormalization_bias_to_fp16, epsilon = var_1454_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_2_0_norm_LayerNormalization_weight_to_fp16, x = input_87_cast_fp16)[name = string("input_tensor_267_cast_fp16")];
            tensor<int32, [3]> var_1463 = const()[name = string("op_1463"), val = tensor<int32, [3]>([0, 2, 1])];
            string input_tensor_277_pad_type_0 = const()[name = string("input_tensor_277_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_277_strides_0 = const()[name = string("input_tensor_277_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_277_pad_0 = const()[name = string("input_tensor_277_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_277_dilations_0 = const()[name = string("input_tensor_277_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_277_groups_0 = const()[name = string("input_tensor_277_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_1_conv_q_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_q_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12186176)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_1_conv_q_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_q_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12317312)))];
            tensor<fp16, [1, 256, 64]> input_89_cast_fp16 = transpose(perm = var_1463, x = input_tensor_267_cast_fp16)[name = string("transpose_29")];
            tensor<fp16, [1, 256, 64]> input_tensor_277_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_1_conv_q_Conv_bias_to_fp16, dilations = input_tensor_277_dilations_0, groups = input_tensor_277_groups_0, pad = input_tensor_277_pad_0, pad_type = input_tensor_277_pad_type_0, strides = input_tensor_277_strides_0, weight = text_encoder_attn_encoder_attn_layers_1_conv_q_Conv_weight_to_fp16, x = input_89_cast_fp16)[name = string("input_tensor_277_cast_fp16")];
            string input_tensor_269_pad_type_0 = const()[name = string("input_tensor_269_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_269_strides_0 = const()[name = string("input_tensor_269_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_269_pad_0 = const()[name = string("input_tensor_269_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_269_dilations_0 = const()[name = string("input_tensor_269_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_269_groups_0 = const()[name = string("input_tensor_269_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_1_conv_k_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_k_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12317888)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_1_conv_k_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_k_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12449024)))];
            tensor<fp16, [1, 256, 64]> input_tensor_269_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_1_conv_k_Conv_bias_to_fp16, dilations = input_tensor_269_dilations_0, groups = input_tensor_269_groups_0, pad = input_tensor_269_pad_0, pad_type = input_tensor_269_pad_type_0, strides = input_tensor_269_strides_0, weight = text_encoder_attn_encoder_attn_layers_1_conv_k_Conv_weight_to_fp16, x = input_89_cast_fp16)[name = string("input_tensor_269_cast_fp16")];
            string input_tensor_289_pad_type_0 = const()[name = string("input_tensor_289_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_289_strides_0 = const()[name = string("input_tensor_289_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_289_pad_0 = const()[name = string("input_tensor_289_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_289_dilations_0 = const()[name = string("input_tensor_289_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_289_groups_0 = const()[name = string("input_tensor_289_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_1_conv_v_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_v_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12449600)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_1_conv_v_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_v_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12580736)))];
            tensor<fp16, [1, 256, 64]> input_tensor_289_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_1_conv_v_Conv_bias_to_fp16, dilations = input_tensor_289_dilations_0, groups = input_tensor_289_groups_0, pad = input_tensor_289_pad_0, pad_type = input_tensor_289_pad_type_0, strides = input_tensor_289_strides_0, weight = text_encoder_attn_encoder_attn_layers_1_conv_v_Conv_weight_to_fp16, x = input_89_cast_fp16)[name = string("input_tensor_289_cast_fp16")];
            tensor<int32, [4]> var_1571 = const()[name = string("op_1571"), val = tensor<int32, [4]>([1, 4, 64, 64])];
            tensor<fp16, [1, 4, 64, 64]> input_tensor_285_cast_fp16 = reshape(shape = var_1571, x = input_tensor_277_cast_fp16)[name = string("input_tensor_285_cast_fp16")];
            tensor<int32, [4]> var_1577 = const()[name = string("op_1577"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [4]> var_1603 = const()[name = string("op_1603"), val = tensor<int32, [4]>([1, 4, 64, 64])];
            tensor<fp16, [1, 4, 64, 64]> y_13_cast_fp16 = reshape(shape = var_1603, x = input_tensor_269_cast_fp16)[name = string("y_13_cast_fp16")];
            tensor<int32, [4]> var_1615 = const()[name = string("op_1615"), val = tensor<int32, [4]>([1, 4, 64, 64])];
            tensor<fp16, [1, 4, 64, 64]> input_tensor_291_cast_fp16 = reshape(shape = var_1615, x = input_tensor_289_cast_fp16)[name = string("input_tensor_291_cast_fp16")];
            fp16 _inversed_x_69_y_0_to_fp16 = const()[name = string("_inversed_x_69_y_0_to_fp16"), val = fp16(0x1p-3)];
            tensor<fp16, [1, 4, 64, 64]> first_127_cast_fp16 = transpose(perm = var_1577, x = input_tensor_285_cast_fp16)[name = string("transpose_28")];
            tensor<fp16, [1, 4, 64, 64]> _inversed_x_69_cast_fp16 = mul(x = first_127_cast_fp16, y = _inversed_x_69_y_0_to_fp16)[name = string("_inversed_x_69_cast_fp16")];
            bool first_143_transpose_x_0 = const()[name = string("first_143_transpose_x_0"), val = bool(false)];
            bool first_143_transpose_y_0 = const()[name = string("first_143_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 4, 64, 64]> first_143_cast_fp16 = matmul(transpose_x = first_143_transpose_x_0, transpose_y = first_143_transpose_y_0, x = _inversed_x_69_cast_fp16, y = y_13_cast_fp16)[name = string("first_143_cast_fp16")];
            bool input_tensor_323_transpose_x_0 = const()[name = string("input_tensor_323_transpose_x_0"), val = bool(false)];
            bool input_tensor_323_transpose_y_0 = const()[name = string("input_tensor_323_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 64, 127]> y_15_to_fp16 = const()[name = string("y_15_to_fp16"), val = tensor<fp16, [1, 1, 64, 127]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17943232)))];
            tensor<fp16, [1, 4, 64, 127]> input_tensor_323_cast_fp16 = matmul(transpose_x = input_tensor_323_transpose_x_0, transpose_y = input_tensor_323_transpose_y_0, x = _inversed_x_69_cast_fp16, y = y_15_to_fp16)[name = string("input_tensor_323_cast_fp16")];
            tensor<int32, [8]> input_tensor_345_pad_0 = const()[name = string("input_tensor_345_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 1])];
            string input_tensor_345_mode_0 = const()[name = string("input_tensor_345_mode_0"), val = string("constant")];
            fp16 const_51_to_fp16 = const()[name = string("const_51_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 64, 128]> input_tensor_345_cast_fp16 = pad(constant_val = const_51_to_fp16, mode = input_tensor_345_mode_0, pad = input_tensor_345_pad_0, x = input_tensor_323_cast_fp16)[name = string("input_tensor_345_cast_fp16")];
            tensor<int32, [3]> var_1738 = const()[name = string("op_1738"), val = tensor<int32, [3]>([1, 4, 8192])];
            tensor<fp16, [1, 4, 8192]> input_97_cast_fp16 = reshape(shape = var_1738, x = input_tensor_345_cast_fp16)[name = string("input_97_cast_fp16")];
            tensor<int32, [6]> input_tensor_367_pad_0 = const()[name = string("input_tensor_367_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 0, 63])];
            string input_tensor_367_mode_0 = const()[name = string("input_tensor_367_mode_0"), val = string("constant")];
            fp16 const_52_to_fp16 = const()[name = string("const_52_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 8255]> input_tensor_367_cast_fp16 = pad(constant_val = const_52_to_fp16, mode = input_tensor_367_mode_0, pad = input_tensor_367_pad_0, x = input_97_cast_fp16)[name = string("input_tensor_367_cast_fp16")];
            tensor<int32, [4]> var_1773 = const()[name = string("op_1773"), val = tensor<int32, [4]>([1, 4, 65, 127])];
            tensor<fp16, [1, 4, 65, 127]> x_85_cast_fp16 = reshape(shape = var_1773, x = input_tensor_367_cast_fp16)[name = string("x_85_cast_fp16")];
            tensor<int32, [4]> x_87_begin_0 = const()[name = string("x_87_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> x_87_end_0 = const()[name = string("x_87_end_0"), val = tensor<int32, [4]>([1, 4, 64, 127])];
            tensor<bool, [4]> x_87_end_mask_0 = const()[name = string("x_87_end_mask_0"), val = tensor<bool, [4]>([true, true, false, true])];
            tensor<fp16, [1, 4, 64, 127]> x_87_cast_fp16 = slice_by_index(begin = x_87_begin_0, end = x_87_end_0, end_mask = x_87_end_mask_0, x = x_85_cast_fp16)[name = string("x_87_cast_fp16")];
            tensor<int32, [4]> second_139_begin_0 = const()[name = string("second_139_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 63])];
            tensor<int32, [4]> second_139_end_0 = const()[name = string("second_139_end_0"), val = tensor<int32, [4]>([1, 4, 64, 1])];
            tensor<bool, [4]> second_139_end_mask_0 = const()[name = string("second_139_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 64, 64]> second_139_cast_fp16 = slice_by_index(begin = second_139_begin_0, end = second_139_end_0, end_mask = second_139_end_mask_0, x = x_87_cast_fp16)[name = string("second_139_cast_fp16")];
            tensor<fp16, [1, 4, 64, 64]> y_17_cast_fp16 = add(x = first_143_cast_fp16, y = second_139_cast_fp16)[name = string("y_17_cast_fp16")];
            tensor<fp16, [1, 4, 64, 64]> input_99_cast_fp16 = select(a = text_encoder_attn_encoder_attn_layers_0_Constant_88_value_after_broadcast_to_fp16, b = y_17_cast_fp16, cond = condition_1_after_broadcast)[name = string("input_99_cast_fp16")];
            int32 var_1815 = const()[name = string("op_1815"), val = int32(-1)];
            tensor<fp16, [1, 4, 64, 64]> x_91_cast_fp16 = softmax(axis = var_1815, x = input_99_cast_fp16)[name = string("x_91_cast_fp16")];
            bool first_155_transpose_x_1 = const()[name = string("first_155_transpose_x_1"), val = bool(false)];
            bool first_155_transpose_y_1 = const()[name = string("first_155_transpose_y_1"), val = bool(true)];
            tensor<fp16, [1, 4, 64, 64]> first_155_cast_fp16 = matmul(transpose_x = first_155_transpose_x_1, transpose_y = first_155_transpose_y_1, x = x_91_cast_fp16, y = input_tensor_291_cast_fp16)[name = string("first_155_cast_fp16")];
            tensor<int32, [8]> input_tensor_397_pad_0 = const()[name = string("input_tensor_397_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 63])];
            string input_tensor_397_mode_0 = const()[name = string("input_tensor_397_mode_0"), val = string("constant")];
            fp16 const_59_to_fp16 = const()[name = string("const_59_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 64, 127]> input_tensor_397_cast_fp16 = pad(constant_val = const_59_to_fp16, mode = input_tensor_397_mode_0, pad = input_tensor_397_pad_0, x = x_91_cast_fp16)[name = string("input_tensor_397_cast_fp16")];
            tensor<int32, [3]> var_1889 = const()[name = string("op_1889"), val = tensor<int32, [3]>([1, 4, 8128])];
            tensor<fp16, [1, 4, 8128]> input_101_cast_fp16 = reshape(shape = var_1889, x = input_tensor_397_cast_fp16)[name = string("input_101_cast_fp16")];
            tensor<int32, [6]> input_tensor_415_pad_0 = const()[name = string("input_tensor_415_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 64, 0])];
            string input_tensor_415_mode_0 = const()[name = string("input_tensor_415_mode_0"), val = string("constant")];
            fp16 const_60_to_fp16 = const()[name = string("const_60_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 8192]> input_tensor_415_cast_fp16 = pad(constant_val = const_60_to_fp16, mode = input_tensor_415_mode_0, pad = input_tensor_415_pad_0, x = input_101_cast_fp16)[name = string("input_tensor_415_cast_fp16")];
            tensor<int32, [4]> var_1919 = const()[name = string("op_1919"), val = tensor<int32, [4]>([1, 4, 64, 128])];
            tensor<fp16, [1, 4, 64, 128]> x_101_cast_fp16 = reshape(shape = var_1919, x = input_tensor_415_cast_fp16)[name = string("x_101_cast_fp16")];
            tensor<int32, [4]> x_109_begin_0 = const()[name = string("x_109_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 1])];
            tensor<int32, [4]> x_109_end_0 = const()[name = string("x_109_end_0"), val = tensor<int32, [4]>([1, 4, 64, 1])];
            tensor<bool, [4]> x_109_end_mask_0 = const()[name = string("x_109_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 64, 127]> x_109_cast_fp16 = slice_by_index(begin = x_109_begin_0, end = x_109_end_0, end_mask = x_109_end_mask_0, x = x_101_cast_fp16)[name = string("x_109_cast_fp16")];
            bool second_153_transpose_x_0 = const()[name = string("second_153_transpose_x_0"), val = bool(false)];
            bool second_153_transpose_y_0 = const()[name = string("second_153_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 127, 64]> y_21_to_fp16 = const()[name = string("y_21_to_fp16"), val = tensor<fp16, [1, 1, 127, 64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17959552)))];
            tensor<fp16, [1, 4, 64, 64]> second_153_cast_fp16 = matmul(transpose_x = second_153_transpose_x_0, transpose_y = second_153_transpose_y_0, x = x_109_cast_fp16, y = y_21_to_fp16)[name = string("second_153_cast_fp16")];
            tensor<fp16, [1, 4, 64, 64]> input_tensor_433_cast_fp16 = add(x = first_155_cast_fp16, y = second_153_cast_fp16)[name = string("input_tensor_433_cast_fp16")];
            tensor<int32, [4]> var_1966 = const()[name = string("op_1966"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [3]> var_1985 = const()[name = string("op_1985"), val = tensor<int32, [3]>([1, 256, 64])];
            tensor<fp16, [1, 4, 64, 64]> input_tensor_437_cast_fp16 = transpose(perm = var_1966, x = input_tensor_433_cast_fp16)[name = string("transpose_27")];
            tensor<fp16, [1, 256, 64]> input_105_cast_fp16 = reshape(shape = var_1985, x = input_tensor_437_cast_fp16)[name = string("input_105_cast_fp16")];
            string second_155_pad_type_0 = const()[name = string("second_155_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_155_strides_0 = const()[name = string("second_155_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_155_pad_0 = const()[name = string("second_155_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_155_dilations_0 = const()[name = string("second_155_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_155_groups_0 = const()[name = string("second_155_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_1_conv_o_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_o_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12589376)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_1_conv_o_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_1_conv_o_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12720512)))];
            tensor<fp16, [1, 256, 64]> second_155_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_1_conv_o_Conv_bias_to_fp16, dilations = second_155_dilations_0, groups = second_155_groups_0, pad = second_155_pad_0, pad_type = second_155_pad_type_0, strides = second_155_strides_0, weight = text_encoder_attn_encoder_attn_layers_1_conv_o_Conv_weight_to_fp16, x = input_105_cast_fp16)[name = string("second_155_cast_fp16")];
            tensor<fp16, [1, 256, 64]> input_tensor_439_cast_fp16 = add(x = input_89_cast_fp16, y = second_155_cast_fp16)[name = string("input_tensor_439_cast_fp16")];
            tensor<int32, [3]> var_2003 = const()[name = string("op_2003"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_441_axes_0 = const()[name = string("input_tensor_441_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_1_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_1_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12721088)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_1_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_1_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12721664)))];
            fp16 var_2006_to_fp16 = const()[name = string("op_2006_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 64, 256]> input_107_cast_fp16 = transpose(perm = var_2003, x = input_tensor_439_cast_fp16)[name = string("transpose_26")];
            tensor<fp16, [1, 64, 256]> input_tensor_441_cast_fp16 = layer_norm(axes = input_tensor_441_axes_0, beta = text_encoder_attn_encoder_norm_layers_1_1_norm_LayerNormalization_bias_to_fp16, epsilon = var_2006_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_1_1_norm_LayerNormalization_weight_to_fp16, x = input_107_cast_fp16)[name = string("input_tensor_441_cast_fp16")];
            tensor<int32, [3]> var_2015 = const()[name = string("op_2015"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 256, 64]> first_157_cast_fp16 = transpose(perm = var_2015, x = input_tensor_441_cast_fp16)[name = string("transpose_25")];
            tensor<fp16, [1, 256, 64]> input_109_cast_fp16 = mul(x = first_157_cast_fp16, y = text_mask)[name = string("input_109_cast_fp16")];
            string input_111_pad_type_0 = const()[name = string("input_111_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_111_strides_0 = const()[name = string("input_111_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_111_pad_0 = const()[name = string("input_111_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_111_dilations_0 = const()[name = string("input_111_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_111_groups_0 = const()[name = string("input_111_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_attn_encoder_ffn_layers_1_conv_1_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_1_conv_1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(12722240)))];
            tensor<fp16, [1024]> text_encoder_attn_encoder_ffn_layers_1_conv_1_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_1_conv_1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13246592)))];
            tensor<fp16, [1, 1024, 64]> input_111_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_1_conv_1_Conv_bias_to_fp16, dilations = input_111_dilations_0, groups = input_111_groups_0, pad = input_111_pad_0, pad_type = input_111_pad_type_0, strides = input_111_strides_0, weight = text_encoder_attn_encoder_ffn_layers_1_conv_1_Conv_weight_to_fp16, x = input_109_cast_fp16)[name = string("input_111_cast_fp16")];
            tensor<fp16, [1, 1024, 64]> first_159_cast_fp16 = relu(x = input_111_cast_fp16)[name = string("first_159_cast_fp16")];
            tensor<fp16, [1, 1024, 64]> input_113_cast_fp16 = mul(x = first_159_cast_fp16, y = text_mask)[name = string("input_113_cast_fp16")];
            string first_161_pad_type_0 = const()[name = string("first_161_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_161_strides_0 = const()[name = string("first_161_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_161_pad_0 = const()[name = string("first_161_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_161_dilations_0 = const()[name = string("first_161_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_161_groups_0 = const()[name = string("first_161_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> text_encoder_attn_encoder_ffn_layers_1_conv_2_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_1_conv_2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13248704)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_ffn_layers_1_conv_2_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_1_conv_2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13773056)))];
            tensor<fp16, [1, 256, 64]> first_161_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_1_conv_2_Conv_bias_to_fp16, dilations = first_161_dilations_0, groups = first_161_groups_0, pad = first_161_pad_0, pad_type = first_161_pad_type_0, strides = first_161_strides_0, weight = text_encoder_attn_encoder_ffn_layers_1_conv_2_Conv_weight_to_fp16, x = input_113_cast_fp16)[name = string("first_161_cast_fp16")];
            tensor<fp16, [1, 256, 64]> second_157_cast_fp16 = mul(x = first_161_cast_fp16, y = text_mask)[name = string("second_157_cast_fp16")];
            tensor<fp16, [1, 256, 64]> input_tensor_443_cast_fp16 = add(x = first_157_cast_fp16, y = second_157_cast_fp16)[name = string("input_tensor_443_cast_fp16")];
            tensor<int32, [3]> var_2048 = const()[name = string("op_2048"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_445_axes_0 = const()[name = string("input_tensor_445_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_1_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_1_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13773632)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_1_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_1_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13774208)))];
            fp16 var_2051_to_fp16 = const()[name = string("op_2051_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 64, 256]> input_115_cast_fp16 = transpose(perm = var_2048, x = input_tensor_443_cast_fp16)[name = string("transpose_24")];
            tensor<fp16, [1, 64, 256]> input_tensor_445_cast_fp16 = layer_norm(axes = input_tensor_445_axes_0, beta = text_encoder_attn_encoder_norm_layers_2_1_norm_LayerNormalization_bias_to_fp16, epsilon = var_2051_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_2_1_norm_LayerNormalization_weight_to_fp16, x = input_115_cast_fp16)[name = string("input_tensor_445_cast_fp16")];
            tensor<int32, [3]> var_2060 = const()[name = string("op_2060"), val = tensor<int32, [3]>([0, 2, 1])];
            string input_tensor_455_pad_type_0 = const()[name = string("input_tensor_455_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_455_strides_0 = const()[name = string("input_tensor_455_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_455_pad_0 = const()[name = string("input_tensor_455_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_455_dilations_0 = const()[name = string("input_tensor_455_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_455_groups_0 = const()[name = string("input_tensor_455_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_2_conv_q_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_q_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13774784)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_2_conv_q_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_q_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13905920)))];
            tensor<fp16, [1, 256, 64]> input_117_cast_fp16 = transpose(perm = var_2060, x = input_tensor_445_cast_fp16)[name = string("transpose_23")];
            tensor<fp16, [1, 256, 64]> input_tensor_455_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_2_conv_q_Conv_bias_to_fp16, dilations = input_tensor_455_dilations_0, groups = input_tensor_455_groups_0, pad = input_tensor_455_pad_0, pad_type = input_tensor_455_pad_type_0, strides = input_tensor_455_strides_0, weight = text_encoder_attn_encoder_attn_layers_2_conv_q_Conv_weight_to_fp16, x = input_117_cast_fp16)[name = string("input_tensor_455_cast_fp16")];
            string input_tensor_447_pad_type_0 = const()[name = string("input_tensor_447_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_447_strides_0 = const()[name = string("input_tensor_447_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_447_pad_0 = const()[name = string("input_tensor_447_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_447_dilations_0 = const()[name = string("input_tensor_447_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_447_groups_0 = const()[name = string("input_tensor_447_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_2_conv_k_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_k_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(13906496)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_2_conv_k_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_k_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14037632)))];
            tensor<fp16, [1, 256, 64]> input_tensor_447_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_2_conv_k_Conv_bias_to_fp16, dilations = input_tensor_447_dilations_0, groups = input_tensor_447_groups_0, pad = input_tensor_447_pad_0, pad_type = input_tensor_447_pad_type_0, strides = input_tensor_447_strides_0, weight = text_encoder_attn_encoder_attn_layers_2_conv_k_Conv_weight_to_fp16, x = input_117_cast_fp16)[name = string("input_tensor_447_cast_fp16")];
            string input_tensor_467_pad_type_0 = const()[name = string("input_tensor_467_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_467_strides_0 = const()[name = string("input_tensor_467_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_467_pad_0 = const()[name = string("input_tensor_467_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_467_dilations_0 = const()[name = string("input_tensor_467_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_467_groups_0 = const()[name = string("input_tensor_467_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_2_conv_v_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_v_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14038208)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_2_conv_v_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_v_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14169344)))];
            tensor<fp16, [1, 256, 64]> input_tensor_467_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_2_conv_v_Conv_bias_to_fp16, dilations = input_tensor_467_dilations_0, groups = input_tensor_467_groups_0, pad = input_tensor_467_pad_0, pad_type = input_tensor_467_pad_type_0, strides = input_tensor_467_strides_0, weight = text_encoder_attn_encoder_attn_layers_2_conv_v_Conv_weight_to_fp16, x = input_117_cast_fp16)[name = string("input_tensor_467_cast_fp16")];
            tensor<int32, [4]> var_2168 = const()[name = string("op_2168"), val = tensor<int32, [4]>([1, 4, 64, 64])];
            tensor<fp16, [1, 4, 64, 64]> input_tensor_463_cast_fp16 = reshape(shape = var_2168, x = input_tensor_455_cast_fp16)[name = string("input_tensor_463_cast_fp16")];
            tensor<int32, [4]> var_2174 = const()[name = string("op_2174"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [4]> var_2200 = const()[name = string("op_2200"), val = tensor<int32, [4]>([1, 4, 64, 64])];
            tensor<fp16, [1, 4, 64, 64]> y_23_cast_fp16 = reshape(shape = var_2200, x = input_tensor_447_cast_fp16)[name = string("y_23_cast_fp16")];
            tensor<int32, [4]> var_2212 = const()[name = string("op_2212"), val = tensor<int32, [4]>([1, 4, 64, 64])];
            tensor<fp16, [1, 4, 64, 64]> input_tensor_469_cast_fp16 = reshape(shape = var_2212, x = input_tensor_467_cast_fp16)[name = string("input_tensor_469_cast_fp16")];
            fp16 _inversed_x_111_y_0_to_fp16 = const()[name = string("_inversed_x_111_y_0_to_fp16"), val = fp16(0x1p-3)];
            tensor<fp16, [1, 4, 64, 64]> first_163_cast_fp16 = transpose(perm = var_2174, x = input_tensor_463_cast_fp16)[name = string("transpose_22")];
            tensor<fp16, [1, 4, 64, 64]> _inversed_x_111_cast_fp16 = mul(x = first_163_cast_fp16, y = _inversed_x_111_y_0_to_fp16)[name = string("_inversed_x_111_cast_fp16")];
            bool first_179_transpose_x_0 = const()[name = string("first_179_transpose_x_0"), val = bool(false)];
            bool first_179_transpose_y_0 = const()[name = string("first_179_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 4, 64, 64]> first_179_cast_fp16 = matmul(transpose_x = first_179_transpose_x_0, transpose_y = first_179_transpose_y_0, x = _inversed_x_111_cast_fp16, y = y_23_cast_fp16)[name = string("first_179_cast_fp16")];
            bool input_tensor_501_transpose_x_0 = const()[name = string("input_tensor_501_transpose_x_0"), val = bool(false)];
            bool input_tensor_501_transpose_y_0 = const()[name = string("input_tensor_501_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 64, 127]> y_25_to_fp16 = const()[name = string("y_25_to_fp16"), val = tensor<fp16, [1, 1, 64, 127]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17975872)))];
            tensor<fp16, [1, 4, 64, 127]> input_tensor_501_cast_fp16 = matmul(transpose_x = input_tensor_501_transpose_x_0, transpose_y = input_tensor_501_transpose_y_0, x = _inversed_x_111_cast_fp16, y = y_25_to_fp16)[name = string("input_tensor_501_cast_fp16")];
            tensor<int32, [8]> input_tensor_523_pad_0 = const()[name = string("input_tensor_523_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 1])];
            string input_tensor_523_mode_0 = const()[name = string("input_tensor_523_mode_0"), val = string("constant")];
            fp16 const_79_to_fp16 = const()[name = string("const_79_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 64, 128]> input_tensor_523_cast_fp16 = pad(constant_val = const_79_to_fp16, mode = input_tensor_523_mode_0, pad = input_tensor_523_pad_0, x = input_tensor_501_cast_fp16)[name = string("input_tensor_523_cast_fp16")];
            tensor<int32, [3]> var_2335 = const()[name = string("op_2335"), val = tensor<int32, [3]>([1, 4, 8192])];
            tensor<fp16, [1, 4, 8192]> input_125_cast_fp16 = reshape(shape = var_2335, x = input_tensor_523_cast_fp16)[name = string("input_125_cast_fp16")];
            tensor<int32, [6]> input_tensor_545_pad_0 = const()[name = string("input_tensor_545_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 0, 63])];
            string input_tensor_545_mode_0 = const()[name = string("input_tensor_545_mode_0"), val = string("constant")];
            fp16 const_80_to_fp16 = const()[name = string("const_80_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 8255]> input_tensor_545_cast_fp16 = pad(constant_val = const_80_to_fp16, mode = input_tensor_545_mode_0, pad = input_tensor_545_pad_0, x = input_125_cast_fp16)[name = string("input_tensor_545_cast_fp16")];
            tensor<int32, [4]> var_2370 = const()[name = string("op_2370"), val = tensor<int32, [4]>([1, 4, 65, 127])];
            tensor<fp16, [1, 4, 65, 127]> x_127_cast_fp16 = reshape(shape = var_2370, x = input_tensor_545_cast_fp16)[name = string("x_127_cast_fp16")];
            tensor<int32, [4]> x_129_begin_0 = const()[name = string("x_129_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> x_129_end_0 = const()[name = string("x_129_end_0"), val = tensor<int32, [4]>([1, 4, 64, 127])];
            tensor<bool, [4]> x_129_end_mask_0 = const()[name = string("x_129_end_mask_0"), val = tensor<bool, [4]>([true, true, false, true])];
            tensor<fp16, [1, 4, 64, 127]> x_129_cast_fp16 = slice_by_index(begin = x_129_begin_0, end = x_129_end_0, end_mask = x_129_end_mask_0, x = x_127_cast_fp16)[name = string("x_129_cast_fp16")];
            tensor<int32, [4]> second_181_begin_0 = const()[name = string("second_181_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 63])];
            tensor<int32, [4]> second_181_end_0 = const()[name = string("second_181_end_0"), val = tensor<int32, [4]>([1, 4, 64, 1])];
            tensor<bool, [4]> second_181_end_mask_0 = const()[name = string("second_181_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 64, 64]> second_181_cast_fp16 = slice_by_index(begin = second_181_begin_0, end = second_181_end_0, end_mask = second_181_end_mask_0, x = x_129_cast_fp16)[name = string("second_181_cast_fp16")];
            tensor<fp16, [1, 4, 64, 64]> y_27_cast_fp16 = add(x = first_179_cast_fp16, y = second_181_cast_fp16)[name = string("y_27_cast_fp16")];
            tensor<fp16, [1, 4, 64, 64]> input_127_cast_fp16 = select(a = text_encoder_attn_encoder_attn_layers_0_Constant_88_value_after_broadcast_to_fp16, b = y_27_cast_fp16, cond = condition_1_after_broadcast)[name = string("input_127_cast_fp16")];
            int32 var_2412 = const()[name = string("op_2412"), val = int32(-1)];
            tensor<fp16, [1, 4, 64, 64]> x_133_cast_fp16 = softmax(axis = var_2412, x = input_127_cast_fp16)[name = string("x_133_cast_fp16")];
            bool first_191_transpose_x_1 = const()[name = string("first_191_transpose_x_1"), val = bool(false)];
            bool first_191_transpose_y_1 = const()[name = string("first_191_transpose_y_1"), val = bool(true)];
            tensor<fp16, [1, 4, 64, 64]> first_191_cast_fp16 = matmul(transpose_x = first_191_transpose_x_1, transpose_y = first_191_transpose_y_1, x = x_133_cast_fp16, y = input_tensor_469_cast_fp16)[name = string("first_191_cast_fp16")];
            tensor<int32, [8]> input_tensor_575_pad_0 = const()[name = string("input_tensor_575_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 63])];
            string input_tensor_575_mode_0 = const()[name = string("input_tensor_575_mode_0"), val = string("constant")];
            fp16 const_87_to_fp16 = const()[name = string("const_87_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 64, 127]> input_tensor_575_cast_fp16 = pad(constant_val = const_87_to_fp16, mode = input_tensor_575_mode_0, pad = input_tensor_575_pad_0, x = x_133_cast_fp16)[name = string("input_tensor_575_cast_fp16")];
            tensor<int32, [3]> var_2486 = const()[name = string("op_2486"), val = tensor<int32, [3]>([1, 4, 8128])];
            tensor<fp16, [1, 4, 8128]> input_129_cast_fp16 = reshape(shape = var_2486, x = input_tensor_575_cast_fp16)[name = string("input_129_cast_fp16")];
            tensor<int32, [6]> input_tensor_593_pad_0 = const()[name = string("input_tensor_593_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 64, 0])];
            string input_tensor_593_mode_0 = const()[name = string("input_tensor_593_mode_0"), val = string("constant")];
            fp16 const_88_to_fp16 = const()[name = string("const_88_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 8192]> input_tensor_593_cast_fp16 = pad(constant_val = const_88_to_fp16, mode = input_tensor_593_mode_0, pad = input_tensor_593_pad_0, x = input_129_cast_fp16)[name = string("input_tensor_593_cast_fp16")];
            tensor<int32, [4]> var_2516 = const()[name = string("op_2516"), val = tensor<int32, [4]>([1, 4, 64, 128])];
            tensor<fp16, [1, 4, 64, 128]> x_143_cast_fp16 = reshape(shape = var_2516, x = input_tensor_593_cast_fp16)[name = string("x_143_cast_fp16")];
            tensor<int32, [4]> x_151_begin_0 = const()[name = string("x_151_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 1])];
            tensor<int32, [4]> x_151_end_0 = const()[name = string("x_151_end_0"), val = tensor<int32, [4]>([1, 4, 64, 1])];
            tensor<bool, [4]> x_151_end_mask_0 = const()[name = string("x_151_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 64, 127]> x_151_cast_fp16 = slice_by_index(begin = x_151_begin_0, end = x_151_end_0, end_mask = x_151_end_mask_0, x = x_143_cast_fp16)[name = string("x_151_cast_fp16")];
            bool second_195_transpose_x_0 = const()[name = string("second_195_transpose_x_0"), val = bool(false)];
            bool second_195_transpose_y_0 = const()[name = string("second_195_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 127, 64]> y_31_to_fp16 = const()[name = string("y_31_to_fp16"), val = tensor<fp16, [1, 1, 127, 64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17992192)))];
            tensor<fp16, [1, 4, 64, 64]> second_195_cast_fp16 = matmul(transpose_x = second_195_transpose_x_0, transpose_y = second_195_transpose_y_0, x = x_151_cast_fp16, y = y_31_to_fp16)[name = string("second_195_cast_fp16")];
            tensor<fp16, [1, 4, 64, 64]> input_tensor_611_cast_fp16 = add(x = first_191_cast_fp16, y = second_195_cast_fp16)[name = string("input_tensor_611_cast_fp16")];
            tensor<int32, [4]> var_2563 = const()[name = string("op_2563"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [3]> var_2582 = const()[name = string("op_2582"), val = tensor<int32, [3]>([1, 256, 64])];
            tensor<fp16, [1, 4, 64, 64]> input_tensor_615_cast_fp16 = transpose(perm = var_2563, x = input_tensor_611_cast_fp16)[name = string("transpose_21")];
            tensor<fp16, [1, 256, 64]> input_133_cast_fp16 = reshape(shape = var_2582, x = input_tensor_615_cast_fp16)[name = string("input_133_cast_fp16")];
            string second_197_pad_type_0 = const()[name = string("second_197_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_197_strides_0 = const()[name = string("second_197_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_197_pad_0 = const()[name = string("second_197_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_197_dilations_0 = const()[name = string("second_197_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_197_groups_0 = const()[name = string("second_197_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_2_conv_o_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_o_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14177984)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_2_conv_o_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_2_conv_o_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14309120)))];
            tensor<fp16, [1, 256, 64]> second_197_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_2_conv_o_Conv_bias_to_fp16, dilations = second_197_dilations_0, groups = second_197_groups_0, pad = second_197_pad_0, pad_type = second_197_pad_type_0, strides = second_197_strides_0, weight = text_encoder_attn_encoder_attn_layers_2_conv_o_Conv_weight_to_fp16, x = input_133_cast_fp16)[name = string("second_197_cast_fp16")];
            tensor<fp16, [1, 256, 64]> input_tensor_617_cast_fp16 = add(x = input_117_cast_fp16, y = second_197_cast_fp16)[name = string("input_tensor_617_cast_fp16")];
            tensor<int32, [3]> var_2600 = const()[name = string("op_2600"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_619_axes_0 = const()[name = string("input_tensor_619_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_2_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_2_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14309696)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_2_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_2_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14310272)))];
            fp16 var_2603_to_fp16 = const()[name = string("op_2603_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 64, 256]> input_135_cast_fp16 = transpose(perm = var_2600, x = input_tensor_617_cast_fp16)[name = string("transpose_20")];
            tensor<fp16, [1, 64, 256]> input_tensor_619_cast_fp16 = layer_norm(axes = input_tensor_619_axes_0, beta = text_encoder_attn_encoder_norm_layers_1_2_norm_LayerNormalization_bias_to_fp16, epsilon = var_2603_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_1_2_norm_LayerNormalization_weight_to_fp16, x = input_135_cast_fp16)[name = string("input_tensor_619_cast_fp16")];
            tensor<int32, [3]> var_2612 = const()[name = string("op_2612"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 256, 64]> first_193_cast_fp16 = transpose(perm = var_2612, x = input_tensor_619_cast_fp16)[name = string("transpose_19")];
            tensor<fp16, [1, 256, 64]> input_137_cast_fp16 = mul(x = first_193_cast_fp16, y = text_mask)[name = string("input_137_cast_fp16")];
            string input_139_pad_type_0 = const()[name = string("input_139_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_139_strides_0 = const()[name = string("input_139_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_139_pad_0 = const()[name = string("input_139_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_139_dilations_0 = const()[name = string("input_139_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_139_groups_0 = const()[name = string("input_139_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_attn_encoder_ffn_layers_2_conv_1_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_2_conv_1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14310848)))];
            tensor<fp16, [1024]> text_encoder_attn_encoder_ffn_layers_2_conv_1_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_2_conv_1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14835200)))];
            tensor<fp16, [1, 1024, 64]> input_139_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_2_conv_1_Conv_bias_to_fp16, dilations = input_139_dilations_0, groups = input_139_groups_0, pad = input_139_pad_0, pad_type = input_139_pad_type_0, strides = input_139_strides_0, weight = text_encoder_attn_encoder_ffn_layers_2_conv_1_Conv_weight_to_fp16, x = input_137_cast_fp16)[name = string("input_139_cast_fp16")];
            tensor<fp16, [1, 1024, 64]> first_195_cast_fp16 = relu(x = input_139_cast_fp16)[name = string("first_195_cast_fp16")];
            tensor<fp16, [1, 1024, 64]> input_141_cast_fp16 = mul(x = first_195_cast_fp16, y = text_mask)[name = string("input_141_cast_fp16")];
            string first_197_pad_type_0 = const()[name = string("first_197_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_197_strides_0 = const()[name = string("first_197_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_197_pad_0 = const()[name = string("first_197_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_197_dilations_0 = const()[name = string("first_197_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_197_groups_0 = const()[name = string("first_197_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> text_encoder_attn_encoder_ffn_layers_2_conv_2_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_2_conv_2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(14837312)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_ffn_layers_2_conv_2_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_2_conv_2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15361664)))];
            tensor<fp16, [1, 256, 64]> first_197_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_2_conv_2_Conv_bias_to_fp16, dilations = first_197_dilations_0, groups = first_197_groups_0, pad = first_197_pad_0, pad_type = first_197_pad_type_0, strides = first_197_strides_0, weight = text_encoder_attn_encoder_ffn_layers_2_conv_2_Conv_weight_to_fp16, x = input_141_cast_fp16)[name = string("first_197_cast_fp16")];
            tensor<fp16, [1, 256, 64]> second_199_cast_fp16 = mul(x = first_197_cast_fp16, y = text_mask)[name = string("second_199_cast_fp16")];
            tensor<fp16, [1, 256, 64]> input_tensor_621_cast_fp16 = add(x = first_193_cast_fp16, y = second_199_cast_fp16)[name = string("input_tensor_621_cast_fp16")];
            tensor<int32, [3]> var_2645 = const()[name = string("op_2645"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_623_axes_0 = const()[name = string("input_tensor_623_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_2_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_2_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15362240)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_2_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_2_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15362816)))];
            fp16 var_2648_to_fp16 = const()[name = string("op_2648_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 64, 256]> input_143_cast_fp16 = transpose(perm = var_2645, x = input_tensor_621_cast_fp16)[name = string("transpose_18")];
            tensor<fp16, [1, 64, 256]> input_tensor_623_cast_fp16 = layer_norm(axes = input_tensor_623_axes_0, beta = text_encoder_attn_encoder_norm_layers_2_2_norm_LayerNormalization_bias_to_fp16, epsilon = var_2648_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_2_2_norm_LayerNormalization_weight_to_fp16, x = input_143_cast_fp16)[name = string("input_tensor_623_cast_fp16")];
            tensor<int32, [3]> var_2657 = const()[name = string("op_2657"), val = tensor<int32, [3]>([0, 2, 1])];
            string input_tensor_633_pad_type_0 = const()[name = string("input_tensor_633_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_633_strides_0 = const()[name = string("input_tensor_633_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_633_pad_0 = const()[name = string("input_tensor_633_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_633_dilations_0 = const()[name = string("input_tensor_633_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_633_groups_0 = const()[name = string("input_tensor_633_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_3_conv_q_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_q_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15363392)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_3_conv_q_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_q_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15494528)))];
            tensor<fp16, [1, 256, 64]> input_145_cast_fp16 = transpose(perm = var_2657, x = input_tensor_623_cast_fp16)[name = string("transpose_17")];
            tensor<fp16, [1, 256, 64]> input_tensor_633_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_3_conv_q_Conv_bias_to_fp16, dilations = input_tensor_633_dilations_0, groups = input_tensor_633_groups_0, pad = input_tensor_633_pad_0, pad_type = input_tensor_633_pad_type_0, strides = input_tensor_633_strides_0, weight = text_encoder_attn_encoder_attn_layers_3_conv_q_Conv_weight_to_fp16, x = input_145_cast_fp16)[name = string("input_tensor_633_cast_fp16")];
            string input_tensor_625_pad_type_0 = const()[name = string("input_tensor_625_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_625_strides_0 = const()[name = string("input_tensor_625_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_625_pad_0 = const()[name = string("input_tensor_625_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_625_dilations_0 = const()[name = string("input_tensor_625_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_625_groups_0 = const()[name = string("input_tensor_625_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_3_conv_k_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_k_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15495104)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_3_conv_k_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_k_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15626240)))];
            tensor<fp16, [1, 256, 64]> input_tensor_625_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_3_conv_k_Conv_bias_to_fp16, dilations = input_tensor_625_dilations_0, groups = input_tensor_625_groups_0, pad = input_tensor_625_pad_0, pad_type = input_tensor_625_pad_type_0, strides = input_tensor_625_strides_0, weight = text_encoder_attn_encoder_attn_layers_3_conv_k_Conv_weight_to_fp16, x = input_145_cast_fp16)[name = string("input_tensor_625_cast_fp16")];
            string input_tensor_645_pad_type_0 = const()[name = string("input_tensor_645_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_tensor_645_strides_0 = const()[name = string("input_tensor_645_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_tensor_645_pad_0 = const()[name = string("input_tensor_645_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_tensor_645_dilations_0 = const()[name = string("input_tensor_645_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_tensor_645_groups_0 = const()[name = string("input_tensor_645_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_3_conv_v_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_v_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15626816)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_3_conv_v_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_v_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15757952)))];
            tensor<fp16, [1, 256, 64]> input_tensor_645_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_3_conv_v_Conv_bias_to_fp16, dilations = input_tensor_645_dilations_0, groups = input_tensor_645_groups_0, pad = input_tensor_645_pad_0, pad_type = input_tensor_645_pad_type_0, strides = input_tensor_645_strides_0, weight = text_encoder_attn_encoder_attn_layers_3_conv_v_Conv_weight_to_fp16, x = input_145_cast_fp16)[name = string("input_tensor_645_cast_fp16")];
            tensor<int32, [4]> var_2765 = const()[name = string("op_2765"), val = tensor<int32, [4]>([1, 4, 64, 64])];
            tensor<fp16, [1, 4, 64, 64]> input_tensor_641_cast_fp16 = reshape(shape = var_2765, x = input_tensor_633_cast_fp16)[name = string("input_tensor_641_cast_fp16")];
            tensor<int32, [4]> var_2771 = const()[name = string("op_2771"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [4]> var_2797 = const()[name = string("op_2797"), val = tensor<int32, [4]>([1, 4, 64, 64])];
            tensor<fp16, [1, 4, 64, 64]> y_33_cast_fp16 = reshape(shape = var_2797, x = input_tensor_625_cast_fp16)[name = string("y_33_cast_fp16")];
            tensor<int32, [4]> var_2809 = const()[name = string("op_2809"), val = tensor<int32, [4]>([1, 4, 64, 64])];
            tensor<fp16, [1, 4, 64, 64]> input_tensor_647_cast_fp16 = reshape(shape = var_2809, x = input_tensor_645_cast_fp16)[name = string("input_tensor_647_cast_fp16")];
            fp16 _inversed_x_153_y_0_to_fp16 = const()[name = string("_inversed_x_153_y_0_to_fp16"), val = fp16(0x1p-3)];
            tensor<fp16, [1, 4, 64, 64]> first_199_cast_fp16 = transpose(perm = var_2771, x = input_tensor_641_cast_fp16)[name = string("transpose_16")];
            tensor<fp16, [1, 4, 64, 64]> _inversed_x_153_cast_fp16 = mul(x = first_199_cast_fp16, y = _inversed_x_153_y_0_to_fp16)[name = string("_inversed_x_153_cast_fp16")];
            bool first_215_transpose_x_0 = const()[name = string("first_215_transpose_x_0"), val = bool(false)];
            bool first_215_transpose_y_0 = const()[name = string("first_215_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 4, 64, 64]> first_215_cast_fp16 = matmul(transpose_x = first_215_transpose_x_0, transpose_y = first_215_transpose_y_0, x = _inversed_x_153_cast_fp16, y = y_33_cast_fp16)[name = string("first_215_cast_fp16")];
            bool input_tensor_679_transpose_x_0 = const()[name = string("input_tensor_679_transpose_x_0"), val = bool(false)];
            bool input_tensor_679_transpose_y_0 = const()[name = string("input_tensor_679_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 64, 127]> y_35_to_fp16 = const()[name = string("y_35_to_fp16"), val = tensor<fp16, [1, 1, 64, 127]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(18008512)))];
            tensor<fp16, [1, 4, 64, 127]> input_tensor_679_cast_fp16 = matmul(transpose_x = input_tensor_679_transpose_x_0, transpose_y = input_tensor_679_transpose_y_0, x = _inversed_x_153_cast_fp16, y = y_35_to_fp16)[name = string("input_tensor_679_cast_fp16")];
            tensor<int32, [8]> input_tensor_701_pad_0 = const()[name = string("input_tensor_701_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 1])];
            string input_tensor_701_mode_0 = const()[name = string("input_tensor_701_mode_0"), val = string("constant")];
            fp16 const_107_to_fp16 = const()[name = string("const_107_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 64, 128]> input_tensor_701_cast_fp16 = pad(constant_val = const_107_to_fp16, mode = input_tensor_701_mode_0, pad = input_tensor_701_pad_0, x = input_tensor_679_cast_fp16)[name = string("input_tensor_701_cast_fp16")];
            tensor<int32, [3]> var_2932 = const()[name = string("op_2932"), val = tensor<int32, [3]>([1, 4, 8192])];
            tensor<fp16, [1, 4, 8192]> input_153_cast_fp16 = reshape(shape = var_2932, x = input_tensor_701_cast_fp16)[name = string("input_153_cast_fp16")];
            tensor<int32, [6]> input_tensor_723_pad_0 = const()[name = string("input_tensor_723_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 0, 63])];
            string input_tensor_723_mode_0 = const()[name = string("input_tensor_723_mode_0"), val = string("constant")];
            fp16 const_108_to_fp16 = const()[name = string("const_108_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 8255]> input_tensor_723_cast_fp16 = pad(constant_val = const_108_to_fp16, mode = input_tensor_723_mode_0, pad = input_tensor_723_pad_0, x = input_153_cast_fp16)[name = string("input_tensor_723_cast_fp16")];
            tensor<int32, [4]> var_2967 = const()[name = string("op_2967"), val = tensor<int32, [4]>([1, 4, 65, 127])];
            tensor<fp16, [1, 4, 65, 127]> x_169_cast_fp16 = reshape(shape = var_2967, x = input_tensor_723_cast_fp16)[name = string("x_169_cast_fp16")];
            tensor<int32, [4]> x_171_begin_0 = const()[name = string("x_171_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> x_171_end_0 = const()[name = string("x_171_end_0"), val = tensor<int32, [4]>([1, 4, 64, 127])];
            tensor<bool, [4]> x_171_end_mask_0 = const()[name = string("x_171_end_mask_0"), val = tensor<bool, [4]>([true, true, false, true])];
            tensor<fp16, [1, 4, 64, 127]> x_171_cast_fp16 = slice_by_index(begin = x_171_begin_0, end = x_171_end_0, end_mask = x_171_end_mask_0, x = x_169_cast_fp16)[name = string("x_171_cast_fp16")];
            tensor<int32, [4]> second_223_begin_0 = const()[name = string("second_223_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 63])];
            tensor<int32, [4]> second_223_end_0 = const()[name = string("second_223_end_0"), val = tensor<int32, [4]>([1, 4, 64, 1])];
            tensor<bool, [4]> second_223_end_mask_0 = const()[name = string("second_223_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 64, 64]> second_223_cast_fp16 = slice_by_index(begin = second_223_begin_0, end = second_223_end_0, end_mask = second_223_end_mask_0, x = x_171_cast_fp16)[name = string("second_223_cast_fp16")];
            tensor<fp16, [1, 4, 64, 64]> y_37_cast_fp16 = add(x = first_215_cast_fp16, y = second_223_cast_fp16)[name = string("y_37_cast_fp16")];
            tensor<fp16, [1, 4, 64, 64]> input_155_cast_fp16 = select(a = text_encoder_attn_encoder_attn_layers_0_Constant_88_value_after_broadcast_to_fp16, b = y_37_cast_fp16, cond = condition_1_after_broadcast)[name = string("input_155_cast_fp16")];
            int32 var_3009 = const()[name = string("op_3009"), val = int32(-1)];
            tensor<fp16, [1, 4, 64, 64]> x_175_cast_fp16 = softmax(axis = var_3009, x = input_155_cast_fp16)[name = string("x_175_cast_fp16")];
            bool first_227_transpose_x_1 = const()[name = string("first_227_transpose_x_1"), val = bool(false)];
            bool first_227_transpose_y_1 = const()[name = string("first_227_transpose_y_1"), val = bool(true)];
            tensor<fp16, [1, 4, 64, 64]> first_227_cast_fp16 = matmul(transpose_x = first_227_transpose_x_1, transpose_y = first_227_transpose_y_1, x = x_175_cast_fp16, y = input_tensor_647_cast_fp16)[name = string("first_227_cast_fp16")];
            tensor<int32, [8]> input_tensor_753_pad_0 = const()[name = string("input_tensor_753_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 0, 63])];
            string input_tensor_753_mode_0 = const()[name = string("input_tensor_753_mode_0"), val = string("constant")];
            fp16 const_115_to_fp16 = const()[name = string("const_115_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 64, 127]> input_tensor_753_cast_fp16 = pad(constant_val = const_115_to_fp16, mode = input_tensor_753_mode_0, pad = input_tensor_753_pad_0, x = x_175_cast_fp16)[name = string("input_tensor_753_cast_fp16")];
            tensor<int32, [3]> var_3083 = const()[name = string("op_3083"), val = tensor<int32, [3]>([1, 4, 8128])];
            tensor<fp16, [1, 4, 8128]> input_157_cast_fp16 = reshape(shape = var_3083, x = input_tensor_753_cast_fp16)[name = string("input_157_cast_fp16")];
            tensor<int32, [6]> input_tensor_771_pad_0 = const()[name = string("input_tensor_771_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 64, 0])];
            string input_tensor_771_mode_0 = const()[name = string("input_tensor_771_mode_0"), val = string("constant")];
            fp16 const_116_to_fp16 = const()[name = string("const_116_to_fp16"), val = fp16(0x0p+0)];
            tensor<fp16, [1, 4, 8192]> input_tensor_771_cast_fp16 = pad(constant_val = const_116_to_fp16, mode = input_tensor_771_mode_0, pad = input_tensor_771_pad_0, x = input_157_cast_fp16)[name = string("input_tensor_771_cast_fp16")];
            tensor<int32, [4]> var_3113 = const()[name = string("op_3113"), val = tensor<int32, [4]>([1, 4, 64, 128])];
            tensor<fp16, [1, 4, 64, 128]> x_185_cast_fp16 = reshape(shape = var_3113, x = input_tensor_771_cast_fp16)[name = string("x_185_cast_fp16")];
            tensor<int32, [4]> x_193_begin_0 = const()[name = string("x_193_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 1])];
            tensor<int32, [4]> x_193_end_0 = const()[name = string("x_193_end_0"), val = tensor<int32, [4]>([1, 4, 64, 1])];
            tensor<bool, [4]> x_193_end_mask_0 = const()[name = string("x_193_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 4, 64, 127]> x_193_cast_fp16 = slice_by_index(begin = x_193_begin_0, end = x_193_end_0, end_mask = x_193_end_mask_0, x = x_185_cast_fp16)[name = string("x_193_cast_fp16")];
            bool second_237_transpose_x_0 = const()[name = string("second_237_transpose_x_0"), val = bool(false)];
            bool second_237_transpose_y_0 = const()[name = string("second_237_transpose_y_0"), val = bool(false)];
            tensor<fp16, [1, 1, 127, 64]> y_41_to_fp16 = const()[name = string("y_41_to_fp16"), val = tensor<fp16, [1, 1, 127, 64]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(18024832)))];
            tensor<fp16, [1, 4, 64, 64]> second_237_cast_fp16 = matmul(transpose_x = second_237_transpose_x_0, transpose_y = second_237_transpose_y_0, x = x_193_cast_fp16, y = y_41_to_fp16)[name = string("second_237_cast_fp16")];
            tensor<fp16, [1, 4, 64, 64]> input_tensor_789_cast_fp16 = add(x = first_227_cast_fp16, y = second_237_cast_fp16)[name = string("input_tensor_789_cast_fp16")];
            tensor<int32, [4]> var_3160 = const()[name = string("op_3160"), val = tensor<int32, [4]>([0, 1, 3, 2])];
            tensor<int32, [3]> var_3179 = const()[name = string("op_3179"), val = tensor<int32, [3]>([1, 256, 64])];
            tensor<fp16, [1, 4, 64, 64]> input_tensor_793_cast_fp16 = transpose(perm = var_3160, x = input_tensor_789_cast_fp16)[name = string("transpose_15")];
            tensor<fp16, [1, 256, 64]> input_161_cast_fp16 = reshape(shape = var_3179, x = input_tensor_793_cast_fp16)[name = string("input_161_cast_fp16")];
            string second_239_pad_type_0 = const()[name = string("second_239_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> second_239_strides_0 = const()[name = string("second_239_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> second_239_pad_0 = const()[name = string("second_239_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> second_239_dilations_0 = const()[name = string("second_239_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 second_239_groups_0 = const()[name = string("second_239_groups_0"), val = int32(1)];
            tensor<fp16, [256, 256, 1]> text_encoder_attn_encoder_attn_layers_3_conv_o_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_o_Conv_weight_to_fp16"), val = tensor<fp16, [256, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15766592)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_attn_layers_3_conv_o_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_attn_layers_3_conv_o_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15897728)))];
            tensor<fp16, [1, 256, 64]> second_239_cast_fp16 = conv(bias = text_encoder_attn_encoder_attn_layers_3_conv_o_Conv_bias_to_fp16, dilations = second_239_dilations_0, groups = second_239_groups_0, pad = second_239_pad_0, pad_type = second_239_pad_type_0, strides = second_239_strides_0, weight = text_encoder_attn_encoder_attn_layers_3_conv_o_Conv_weight_to_fp16, x = input_161_cast_fp16)[name = string("second_239_cast_fp16")];
            tensor<fp16, [1, 256, 64]> input_tensor_795_cast_fp16 = add(x = input_145_cast_fp16, y = second_239_cast_fp16)[name = string("input_tensor_795_cast_fp16")];
            tensor<int32, [3]> var_3197 = const()[name = string("op_3197"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_797_axes_0 = const()[name = string("input_tensor_797_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_3_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_3_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15898304)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_1_3_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_1_3_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15898880)))];
            fp16 var_3200_to_fp16 = const()[name = string("op_3200_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 64, 256]> input_163_cast_fp16 = transpose(perm = var_3197, x = input_tensor_795_cast_fp16)[name = string("transpose_14")];
            tensor<fp16, [1, 64, 256]> input_tensor_797_cast_fp16 = layer_norm(axes = input_tensor_797_axes_0, beta = text_encoder_attn_encoder_norm_layers_1_3_norm_LayerNormalization_bias_to_fp16, epsilon = var_3200_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_1_3_norm_LayerNormalization_weight_to_fp16, x = input_163_cast_fp16)[name = string("input_tensor_797_cast_fp16")];
            tensor<int32, [3]> var_3209 = const()[name = string("op_3209"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 256, 64]> first_229_cast_fp16 = transpose(perm = var_3209, x = input_tensor_797_cast_fp16)[name = string("transpose_13")];
            tensor<fp16, [1, 256, 64]> input_165_cast_fp16 = mul(x = first_229_cast_fp16, y = text_mask)[name = string("input_165_cast_fp16")];
            string input_167_pad_type_0 = const()[name = string("input_167_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> input_167_strides_0 = const()[name = string("input_167_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_167_pad_0 = const()[name = string("input_167_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_167_dilations_0 = const()[name = string("input_167_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 input_167_groups_0 = const()[name = string("input_167_groups_0"), val = int32(1)];
            tensor<fp16, [1024, 256, 1]> text_encoder_attn_encoder_ffn_layers_3_conv_1_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_3_conv_1_Conv_weight_to_fp16"), val = tensor<fp16, [1024, 256, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(15899456)))];
            tensor<fp16, [1024]> text_encoder_attn_encoder_ffn_layers_3_conv_1_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_3_conv_1_Conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16423808)))];
            tensor<fp16, [1, 1024, 64]> input_167_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_3_conv_1_Conv_bias_to_fp16, dilations = input_167_dilations_0, groups = input_167_groups_0, pad = input_167_pad_0, pad_type = input_167_pad_type_0, strides = input_167_strides_0, weight = text_encoder_attn_encoder_ffn_layers_3_conv_1_Conv_weight_to_fp16, x = input_165_cast_fp16)[name = string("input_167_cast_fp16")];
            tensor<fp16, [1, 1024, 64]> first_231_cast_fp16 = relu(x = input_167_cast_fp16)[name = string("first_231_cast_fp16")];
            tensor<fp16, [1, 1024, 64]> input_169_cast_fp16 = mul(x = first_231_cast_fp16, y = text_mask)[name = string("input_169_cast_fp16")];
            string first_233_pad_type_0 = const()[name = string("first_233_pad_type_0"), val = string("valid")];
            tensor<int32, [1]> first_233_strides_0 = const()[name = string("first_233_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> first_233_pad_0 = const()[name = string("first_233_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> first_233_dilations_0 = const()[name = string("first_233_dilations_0"), val = tensor<int32, [1]>([1])];
            int32 first_233_groups_0 = const()[name = string("first_233_groups_0"), val = int32(1)];
            tensor<fp16, [256, 1024, 1]> text_encoder_attn_encoder_ffn_layers_3_conv_2_Conv_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_3_conv_2_Conv_weight_to_fp16"), val = tensor<fp16, [256, 1024, 1]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16425920)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_ffn_layers_3_conv_2_Conv_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_ffn_layers_3_conv_2_Conv_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16950272)))];
            tensor<fp16, [1, 256, 64]> first_233_cast_fp16 = conv(bias = text_encoder_attn_encoder_ffn_layers_3_conv_2_Conv_bias_to_fp16, dilations = first_233_dilations_0, groups = first_233_groups_0, pad = first_233_pad_0, pad_type = first_233_pad_type_0, strides = first_233_strides_0, weight = text_encoder_attn_encoder_ffn_layers_3_conv_2_Conv_weight_to_fp16, x = input_169_cast_fp16)[name = string("first_233_cast_fp16")];
            tensor<fp16, [1, 256, 64]> second_241_cast_fp16 = mul(x = first_233_cast_fp16, y = text_mask)[name = string("second_241_cast_fp16")];
            tensor<fp16, [1, 256, 64]> input_tensor_799_cast_fp16 = add(x = first_229_cast_fp16, y = second_241_cast_fp16)[name = string("input_tensor_799_cast_fp16")];
            tensor<int32, [3]> var_3242 = const()[name = string("op_3242"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_tensor_801_axes_0 = const()[name = string("input_tensor_801_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_3_norm_LayerNormalization_weight_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_3_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16950848)))];
            tensor<fp16, [256]> text_encoder_attn_encoder_norm_layers_2_3_norm_LayerNormalization_bias_to_fp16 = const()[name = string("text_encoder_attn_encoder_norm_layers_2_3_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16951424)))];
            fp16 var_3245_to_fp16 = const()[name = string("op_3245_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 64, 256]> input_171_cast_fp16 = transpose(perm = var_3242, x = input_tensor_799_cast_fp16)[name = string("transpose_12")];
            tensor<fp16, [1, 64, 256]> input_tensor_801_cast_fp16 = layer_norm(axes = input_tensor_801_axes_0, beta = text_encoder_attn_encoder_norm_layers_2_3_norm_LayerNormalization_bias_to_fp16, epsilon = var_3245_to_fp16, gamma = text_encoder_attn_encoder_norm_layers_2_3_norm_LayerNormalization_weight_to_fp16, x = input_171_cast_fp16)[name = string("input_tensor_801_cast_fp16")];
            tensor<int32, [3]> var_3254 = const()[name = string("op_3254"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 256, 64]> first_235_cast_fp16 = transpose(perm = var_3254, x = input_tensor_801_cast_fp16)[name = string("transpose_11")];
            tensor<fp16, [1, 256, 64]> first_237_cast_fp16 = mul(x = first_235_cast_fp16, y = text_mask)[name = string("first_237_cast_fp16")];
            tensor<fp16, [1, 256, 64]> first_239_cast_fp16 = add(x = first_237_cast_fp16, y = first_89_cast_fp16)[name = string("first_239_cast_fp16")];
            tensor<fp16, [1, 256, 64]> input_tensor_807_cast_fp16 = mul(x = first_239_cast_fp16, y = text_mask)[name = string("input_tensor_807_cast_fp16")];
            tensor<int32, [3]> var_3299 = const()[name = string("op_3299"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [3]> var_3304 = const()[name = string("op_3304"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [256, 256]> var_3308_weight_0_to_fp16 = const()[name = string("op_3308_weight_0_to_fp16"), val = tensor<fp16, [256, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(16952000)))];
            tensor<fp16, [256]> var_3308_bias_0_to_fp16 = const()[name = string("op_3308_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17083136)))];
            tensor<fp16, [1, 64, 256]> x_195_cast_fp16 = transpose(perm = var_3299, x = input_tensor_807_cast_fp16)[name = string("transpose_10")];
            tensor<fp16, [1, 64, 256]> var_3308_cast_fp16 = linear(bias = var_3308_bias_0_to_fp16, weight = var_3308_weight_0_to_fp16, x = x_195_cast_fp16)[name = string("op_3308_cast_fp16")];
            tensor<fp16, [256, 256]> var_3314_weight_0_to_fp16 = const()[name = string("op_3314_weight_0_to_fp16"), val = tensor<fp16, [256, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17083712)))];
            tensor<fp16, [256]> var_3314_bias_0_to_fp16 = const()[name = string("op_3314_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17214848)))];
            tensor<fp16, [1, 50, 256]> var_3314_cast_fp16 = linear(bias = var_3314_bias_0_to_fp16, weight = var_3314_weight_0_to_fp16, x = style_ttl)[name = string("op_3314_cast_fp16")];
            tensor<int32, [2]> var_3317 = const()[name = string("op_3317"), val = tensor<int32, [2]>([128, 128])];
            int32 var_3318_axis_0 = const()[name = string("op_3318_axis_0"), val = int32(2)];
            tensor<fp16, [1, 64, 128]> var_3318_cast_fp16_0, tensor<fp16, [1, 64, 128]> var_3318_cast_fp16_1 = split(axis = var_3318_axis_0, split_sizes = var_3317, x = var_3308_cast_fp16)[name = string("op_3318_cast_fp16")];
            tensor<int32, [1]> var_3325_axes_0 = const()[name = string("op_3325_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 64, 128]> var_3325_cast_fp16 = expand_dims(axes = var_3325_axes_0, x = var_3318_cast_fp16_0)[name = string("op_3325_cast_fp16")];
            tensor<int32, [1]> var_3327_axes_0 = const()[name = string("op_3327_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 64, 128]> var_3327_cast_fp16 = expand_dims(axes = var_3327_axes_0, x = var_3318_cast_fp16_1)[name = string("op_3327_cast_fp16")];
            int32 var_3328 = const()[name = string("op_3328"), val = int32(0)];
            bool x_199_interleave_0 = const()[name = string("x_199_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 1, 64, 128]> x_199_cast_fp16 = concat(axis = var_3328, interleave = x_199_interleave_0, values = (var_3325_cast_fp16, var_3327_cast_fp16))[name = string("x_199_cast_fp16")];
            tensor<int32, [2]> var_3349 = const()[name = string("op_3349"), val = tensor<int32, [2]>([128, 128])];
            int32 var_3350_axis_0 = const()[name = string("op_3350_axis_0"), val = int32(2)];
            tensor<fp16, [1, 50, 128]> var_3350_cast_fp16_0, tensor<fp16, [1, 50, 128]> var_3350_cast_fp16_1 = split(axis = var_3350_axis_0, split_sizes = var_3349, x = var_3314_cast_fp16)[name = string("op_3350_cast_fp16")];
            tensor<int32, [1]> var_3357_axes_0 = const()[name = string("op_3357_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 50, 128]> var_3357_cast_fp16 = expand_dims(axes = var_3357_axes_0, x = var_3350_cast_fp16_0)[name = string("op_3357_cast_fp16")];
            tensor<int32, [1]> var_3359_axes_0 = const()[name = string("op_3359_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 50, 128]> var_3359_cast_fp16 = expand_dims(axes = var_3359_axes_0, x = var_3350_cast_fp16_1)[name = string("op_3359_cast_fp16")];
            int32 var_3360 = const()[name = string("op_3360"), val = int32(0)];
            bool y_55_interleave_0 = const()[name = string("y_55_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 1, 50, 128]> y_55_cast_fp16 = concat(axis = var_3360, interleave = y_55_interleave_0, values = (var_3357_cast_fp16, var_3359_cast_fp16))[name = string("y_55_cast_fp16")];
            bool first_247_transpose_x_0 = const()[name = string("first_247_transpose_x_0"), val = bool(false)];
            bool first_247_transpose_y_0 = const()[name = string("first_247_transpose_y_0"), val = bool(false)];
            tensor<fp16, [2, 1, 128, 50]> y_49_to_fp16 = const()[name = string("y_49_to_fp16"), val = tensor<fp16, [2, 1, 128, 50]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17215424)))];
            tensor<fp16, [2, 1, 64, 50]> first_247_cast_fp16 = matmul(transpose_x = first_247_transpose_x_0, transpose_y = first_247_transpose_y_0, x = x_199_cast_fp16, y = y_49_to_fp16)[name = string("first_247_cast_fp16")];
            fp16 _inversed_input_173_y_0_to_fp16 = const()[name = string("_inversed_input_173_y_0_to_fp16"), val = fp16(0x1p-4)];
            tensor<fp16, [2, 1, 64, 50]> _inversed_input_173_cast_fp16 = mul(x = first_247_cast_fp16, y = _inversed_input_173_y_0_to_fp16)[name = string("_inversed_input_173_cast_fp16")];
            int32 var_3373 = const()[name = string("op_3373"), val = int32(3)];
            tensor<fp16, [2, 1, 64, 50]> y_53_cast_fp16 = softmax(axis = var_3373, x = _inversed_input_173_cast_fp16)[name = string("y_53_cast_fp16")];
            tensor<int32, [1]> x_201_axes_0 = const()[name = string("x_201_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 64, 1]> input_tensor_825_cast_fp16 = transpose(perm = var_3304, x = text_mask)[name = string("transpose_9")];
            tensor<fp16, [1, 1, 64, 1]> x_201_cast_fp16 = expand_dims(axes = x_201_axes_0, x = input_tensor_825_cast_fp16)[name = string("x_201_cast_fp16")];
            fp16 speech_prompted_text_encoder_attention1_Constant_11_value_to_fp16 = const()[name = string("speech_prompted_text_encoder_attention1_Constant_11_value_to_fp16"), val = fp16(0x0p+0)];
            tensor<bool, [1, 1, 64, 1]> input_tensor_827_cast_fp16 = equal(x = x_201_cast_fp16, y = speech_prompted_text_encoder_attention1_Constant_11_value_to_fp16)[name = string("input_tensor_827_cast_fp16")];
            tensor<int32, [4]> condition_9_after_broadcast_reps_0 = const()[name = string("condition_9_after_broadcast_reps_0"), val = tensor<int32, [4]>([2, 1, 1, 50])];
            tensor<bool, [2, 1, 64, 50]> condition_9_after_broadcast = tile(reps = condition_9_after_broadcast_reps_0, x = input_tensor_827_cast_fp16)[name = string("condition_9_after_broadcast")];
            tensor<fp16, [2, 1, 64, 50]> speech_prompted_text_encoder_attention1_Constant_12_value_after_broadcast_to_fp16 = const()[name = string("speech_prompted_text_encoder_attention1_Constant_12_value_after_broadcast_to_fp16"), val = tensor<fp16, [2, 1, 64, 50]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(18041152)))];
            tensor<fp16, [2, 1, 64, 50]> x_205_cast_fp16 = select(a = speech_prompted_text_encoder_attention1_Constant_12_value_after_broadcast_to_fp16, b = y_53_cast_fp16, cond = condition_9_after_broadcast)[name = string("x_205_cast_fp16")];
            bool var_3383_transpose_x_0 = const()[name = string("op_3383_transpose_x_0"), val = bool(false)];
            bool var_3383_transpose_y_0 = const()[name = string("op_3383_transpose_y_0"), val = bool(false)];
            tensor<fp16, [2, 1, 64, 128]> var_3383_cast_fp16 = matmul(transpose_x = var_3383_transpose_x_0, transpose_y = var_3383_transpose_y_0, x = x_205_cast_fp16, y = y_55_cast_fp16)[name = string("op_3383_cast_fp16")];
            tensor<int32, [2]> var_3386 = const()[name = string("op_3386"), val = tensor<int32, [2]>([1, 1])];
            int32 var_3387_axis_0 = const()[name = string("op_3387_axis_0"), val = int32(0)];
            tensor<fp16, [1, 1, 64, 128]> var_3387_cast_fp16_0, tensor<fp16, [1, 1, 64, 128]> var_3387_cast_fp16_1 = split(axis = var_3387_axis_0, split_sizes = var_3386, x = var_3383_cast_fp16)[name = string("op_3387_cast_fp16")];
            int32 var_3393 = const()[name = string("op_3393"), val = int32(3)];
            bool result_1_interleave_0 = const()[name = string("result_1_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 1, 64, 256]> result_1_cast_fp16 = concat(axis = var_3393, interleave = result_1_interleave_0, values = (var_3387_cast_fp16_0, var_3387_cast_fp16_1))[name = string("result_1_cast_fp16")];
            tensor<int32, [1]> x_207_axes_0 = const()[name = string("x_207_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 64, 256]> x_207_cast_fp16 = squeeze(axes = x_207_axes_0, x = result_1_cast_fp16)[name = string("x_207_cast_fp16")];
            tensor<fp16, [256, 256]> first_251_weight_0_to_fp16 = const()[name = string("first_251_weight_0_to_fp16"), val = tensor<fp16, [256, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17244352)))];
            tensor<fp16, [256]> first_251_bias_0_to_fp16 = const()[name = string("first_251_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17375488)))];
            tensor<fp16, [1, 64, 256]> first_251_cast_fp16 = linear(bias = first_251_bias_0_to_fp16, weight = first_251_weight_0_to_fp16, x = x_207_cast_fp16)[name = string("first_251_cast_fp16")];
            tensor<fp16, [1, 64, 256]> first_253_cast_fp16 = mul(x = first_251_cast_fp16, y = input_tensor_825_cast_fp16)[name = string("first_253_cast_fp16")];
            tensor<fp16, [1, 64, 256]> x_209_cast_fp16 = add(x = first_253_cast_fp16, y = x_195_cast_fp16)[name = string("x_209_cast_fp16")];
            tensor<fp16, [256, 256]> var_3413_weight_0_to_fp16 = const()[name = string("op_3413_weight_0_to_fp16"), val = tensor<fp16, [256, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17376064)))];
            tensor<fp16, [256]> var_3413_bias_0_to_fp16 = const()[name = string("op_3413_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17507200)))];
            tensor<fp16, [1, 64, 256]> var_3413_cast_fp16 = linear(bias = var_3413_bias_0_to_fp16, weight = var_3413_weight_0_to_fp16, x = x_209_cast_fp16)[name = string("op_3413_cast_fp16")];
            tensor<fp16, [256, 256]> var_3419_weight_0_to_fp16 = const()[name = string("op_3419_weight_0_to_fp16"), val = tensor<fp16, [256, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17507776)))];
            tensor<fp16, [256]> var_3419_bias_0_to_fp16 = const()[name = string("op_3419_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17638912)))];
            tensor<fp16, [1, 50, 256]> var_3419_cast_fp16 = linear(bias = var_3419_bias_0_to_fp16, weight = var_3419_weight_0_to_fp16, x = style_ttl)[name = string("op_3419_cast_fp16")];
            tensor<int32, [2]> var_3422 = const()[name = string("op_3422"), val = tensor<int32, [2]>([128, 128])];
            int32 var_3423_axis_0 = const()[name = string("op_3423_axis_0"), val = int32(2)];
            tensor<fp16, [1, 64, 128]> var_3423_cast_fp16_0, tensor<fp16, [1, 64, 128]> var_3423_cast_fp16_1 = split(axis = var_3423_axis_0, split_sizes = var_3422, x = var_3413_cast_fp16)[name = string("op_3423_cast_fp16")];
            tensor<int32, [1]> var_3430_axes_0 = const()[name = string("op_3430_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 64, 128]> var_3430_cast_fp16 = expand_dims(axes = var_3430_axes_0, x = var_3423_cast_fp16_0)[name = string("op_3430_cast_fp16")];
            tensor<int32, [1]> var_3432_axes_0 = const()[name = string("op_3432_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 64, 128]> var_3432_cast_fp16 = expand_dims(axes = var_3432_axes_0, x = var_3423_cast_fp16_1)[name = string("op_3432_cast_fp16")];
            int32 var_3433 = const()[name = string("op_3433"), val = int32(0)];
            bool x_211_interleave_0 = const()[name = string("x_211_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 1, 64, 128]> x_211_cast_fp16 = concat(axis = var_3433, interleave = x_211_interleave_0, values = (var_3430_cast_fp16, var_3432_cast_fp16))[name = string("x_211_cast_fp16")];
            tensor<int32, [2]> var_3454 = const()[name = string("op_3454"), val = tensor<int32, [2]>([128, 128])];
            int32 var_3455_axis_0 = const()[name = string("op_3455_axis_0"), val = int32(2)];
            tensor<fp16, [1, 50, 128]> var_3455_cast_fp16_0, tensor<fp16, [1, 50, 128]> var_3455_cast_fp16_1 = split(axis = var_3455_axis_0, split_sizes = var_3454, x = var_3419_cast_fp16)[name = string("op_3455_cast_fp16")];
            tensor<int32, [1]> var_3462_axes_0 = const()[name = string("op_3462_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 50, 128]> var_3462_cast_fp16 = expand_dims(axes = var_3462_axes_0, x = var_3455_cast_fp16_0)[name = string("op_3462_cast_fp16")];
            tensor<int32, [1]> var_3464_axes_0 = const()[name = string("op_3464_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 1, 50, 128]> var_3464_cast_fp16 = expand_dims(axes = var_3464_axes_0, x = var_3455_cast_fp16_1)[name = string("op_3464_cast_fp16")];
            int32 var_3465 = const()[name = string("op_3465"), val = int32(0)];
            bool y_69_interleave_0 = const()[name = string("y_69_interleave_0"), val = bool(false)];
            tensor<fp16, [2, 1, 50, 128]> y_69_cast_fp16 = concat(axis = var_3465, interleave = y_69_interleave_0, values = (var_3462_cast_fp16, var_3464_cast_fp16))[name = string("y_69_cast_fp16")];
            bool first_261_transpose_x_0 = const()[name = string("first_261_transpose_x_0"), val = bool(false)];
            bool first_261_transpose_y_0 = const()[name = string("first_261_transpose_y_0"), val = bool(false)];
            tensor<fp16, [2, 1, 128, 50]> y_65_to_fp16 = const()[name = string("y_65_to_fp16"), val = tensor<fp16, [2, 1, 128, 50]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17639488)))];
            tensor<fp16, [2, 1, 64, 50]> first_261_cast_fp16 = matmul(transpose_x = first_261_transpose_x_0, transpose_y = first_261_transpose_y_0, x = x_211_cast_fp16, y = y_65_to_fp16)[name = string("first_261_cast_fp16")];
            fp16 _inversed_input_175_y_0_to_fp16 = const()[name = string("_inversed_input_175_y_0_to_fp16"), val = fp16(0x1p-4)];
            tensor<fp16, [2, 1, 64, 50]> _inversed_input_175_cast_fp16 = mul(x = first_261_cast_fp16, y = _inversed_input_175_y_0_to_fp16)[name = string("_inversed_input_175_cast_fp16")];
            int32 var_3478 = const()[name = string("op_3478"), val = int32(3)];
            tensor<fp16, [2, 1, 64, 50]> y_67_cast_fp16 = softmax(axis = var_3478, x = _inversed_input_175_cast_fp16)[name = string("y_67_cast_fp16")];
            tensor<fp16, [2, 1, 64, 50]> x_215_cast_fp16 = select(a = speech_prompted_text_encoder_attention1_Constant_12_value_after_broadcast_to_fp16, b = y_67_cast_fp16, cond = condition_9_after_broadcast)[name = string("x_215_cast_fp16")];
            bool var_3485_transpose_x_0 = const()[name = string("op_3485_transpose_x_0"), val = bool(false)];
            bool var_3485_transpose_y_0 = const()[name = string("op_3485_transpose_y_0"), val = bool(false)];
            tensor<fp16, [2, 1, 64, 128]> var_3485_cast_fp16 = matmul(transpose_x = var_3485_transpose_x_0, transpose_y = var_3485_transpose_y_0, x = x_215_cast_fp16, y = y_69_cast_fp16)[name = string("op_3485_cast_fp16")];
            tensor<int32, [2]> var_3488 = const()[name = string("op_3488"), val = tensor<int32, [2]>([1, 1])];
            int32 var_3489_axis_0 = const()[name = string("op_3489_axis_0"), val = int32(0)];
            tensor<fp16, [1, 1, 64, 128]> var_3489_cast_fp16_0, tensor<fp16, [1, 1, 64, 128]> var_3489_cast_fp16_1 = split(axis = var_3489_axis_0, split_sizes = var_3488, x = var_3485_cast_fp16)[name = string("op_3489_cast_fp16")];
            int32 var_3495 = const()[name = string("op_3495"), val = int32(3)];
            bool result_interleave_0 = const()[name = string("result_interleave_0"), val = bool(false)];
            tensor<fp16, [1, 1, 64, 256]> result_cast_fp16 = concat(axis = var_3495, interleave = result_interleave_0, values = (var_3489_cast_fp16_0, var_3489_cast_fp16_1))[name = string("result_cast_fp16")];
            tensor<int32, [1]> x_axes_0 = const()[name = string("x_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp16, [1, 64, 256]> x_cast_fp16 = squeeze(axes = x_axes_0, x = result_cast_fp16)[name = string("x_cast_fp16")];
            tensor<fp16, [256, 256]> first_265_weight_0_to_fp16 = const()[name = string("first_265_weight_0_to_fp16"), val = tensor<fp16, [256, 256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17665152)))];
            tensor<fp16, [256]> first_265_bias_0_to_fp16 = const()[name = string("first_265_bias_0_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17796288)))];
            tensor<fp16, [1, 64, 256]> first_265_cast_fp16 = linear(bias = first_265_bias_0_to_fp16, weight = first_265_weight_0_to_fp16, x = x_cast_fp16)[name = string("first_265_cast_fp16")];
            tensor<fp16, [1, 64, 256]> first_267_cast_fp16 = mul(x = first_265_cast_fp16, y = input_tensor_825_cast_fp16)[name = string("first_267_cast_fp16")];
            tensor<fp16, [1, 64, 256]> input_cast_fp16 = add(x = first_267_cast_fp16, y = x_195_cast_fp16)[name = string("input_cast_fp16")];
            tensor<int32, [1]> input_tensor_axes_0 = const()[name = string("input_tensor_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [256]> speech_prompted_text_encoder_norm_norm_LayerNormalization_weight_to_fp16 = const()[name = string("speech_prompted_text_encoder_norm_norm_LayerNormalization_weight_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17796864)))];
            tensor<fp16, [256]> speech_prompted_text_encoder_norm_norm_LayerNormalization_bias_to_fp16 = const()[name = string("speech_prompted_text_encoder_norm_norm_LayerNormalization_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = string("@model_path/weights/weight.bin"), offset = uint64(17797440)))];
            fp16 var_3514_to_fp16 = const()[name = string("op_3514_to_fp16"), val = fp16(0x1.1p-20)];
            tensor<fp16, [1, 64, 256]> input_tensor_cast_fp16 = layer_norm(axes = input_tensor_axes_0, beta = speech_prompted_text_encoder_norm_norm_LayerNormalization_bias_to_fp16, epsilon = var_3514_to_fp16, gamma = speech_prompted_text_encoder_norm_norm_LayerNormalization_weight_to_fp16, x = input_cast_fp16)[name = string("input_tensor_cast_fp16")];
            tensor<int32, [3]> var_3523 = const()[name = string("op_3523"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 256, 64]> first_cast_fp16 = transpose(perm = var_3523, x = input_tensor_cast_fp16)[name = string("transpose_8")];
            tensor<fp16, [1, 256, 64]> text_emb = mul(x = first_cast_fp16, y = text_mask)[name = string("op_3525_cast_fp16")];
        } -> (text_emb);
}