program(1.0)
[buildInfo = dict<tensor<string, []>, tensor<string, []>>({{"coremlc-component-MIL", "3600.16.1"}, {"coremlc-version", "3600.22.1"}, {"coremltools-component-torch", "2.7.0"}, {"coremltools-source-dialect", "TorchScript"}, {"coremltools-version", "9.0b1"}})]
{
    func main<ios17>(tensor<fp32, [1, 128, 1501]> mel, tensor<int32, [1]> mel_length) {
            tensor<int32, []> var_30 = const()[name = tensor<string, []>("op_30"), val = tensor<int32, []>(-1)];
            tensor<int32, [3]> x_1_perm_0 = const()[name = tensor<string, []>("x_1_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> mel_to_fp16_dtype_0 = const()[name = tensor<string, []>("mel_to_fp16_dtype_0"), val = tensor<string, []>("fp16")];
            tensor<string, []> var_102_to_fp16_dtype_0 = const()[name = tensor<string, []>("op_102_to_fp16_dtype_0"), val = tensor<string, []>("fp16")];
            tensor<fp16, []> var_103_promoted_to_fp16 = const()[name = tensor<string, []>("op_103_promoted_to_fp16"), val = tensor<fp16, []>(-0x1p+0)];
            tensor<fp16, [1]> mel_length_to_fp16 = cast(dtype = var_102_to_fp16_dtype_0, x = mel_length)[name = tensor<string, []>("cast_301")];
            tensor<fp16, [1]> var_104_cast_fp16 = add(x = mel_length_to_fp16, y = var_103_promoted_to_fp16)[name = tensor<string, []>("op_104_cast_fp16")];
            tensor<fp16, []> _inversed_106_y_0_to_fp16 = const()[name = tensor<string, []>("_inversed_106_y_0_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1]> _inversed_106_cast_fp16 = mul(x = var_104_cast_fp16, y = _inversed_106_y_0_to_fp16)[name = tensor<string, []>("_inversed_106_cast_fp16")];
            tensor<fp16, []> var_107_to_fp16 = const()[name = tensor<string, []>("op_107_to_fp16"), val = tensor<fp16, []>(0x1p+0)];
            tensor<fp16, [1]> lengths_1_cast_fp16 = add(x = _inversed_106_cast_fp16, y = var_107_to_fp16)[name = tensor<string, []>("lengths_1_cast_fp16")];
            tensor<fp16, [1]> lengths_3_cast_fp16 = floor(x = lengths_1_cast_fp16)[name = tensor<string, []>("lengths_3_cast_fp16")];
            tensor<fp16, []> var_111_promoted_to_fp16 = const()[name = tensor<string, []>("op_111_promoted_to_fp16"), val = tensor<fp16, []>(-0x1p+0)];
            tensor<fp16, [1]> var_112_cast_fp16 = add(x = lengths_3_cast_fp16, y = var_111_promoted_to_fp16)[name = tensor<string, []>("op_112_cast_fp16")];
            tensor<fp16, []> _inversed_114_y_0_to_fp16 = const()[name = tensor<string, []>("_inversed_114_y_0_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1]> _inversed_114_cast_fp16 = mul(x = var_112_cast_fp16, y = _inversed_114_y_0_to_fp16)[name = tensor<string, []>("_inversed_114_cast_fp16")];
            tensor<fp16, []> var_115_to_fp16 = const()[name = tensor<string, []>("op_115_to_fp16"), val = tensor<fp16, []>(0x1p+0)];
            tensor<fp16, [1]> lengths_7_cast_fp16 = add(x = _inversed_114_cast_fp16, y = var_115_to_fp16)[name = tensor<string, []>("lengths_7_cast_fp16")];
            tensor<fp16, [1]> lengths_9_cast_fp16 = floor(x = lengths_7_cast_fp16)[name = tensor<string, []>("lengths_9_cast_fp16")];
            tensor<fp16, []> var_119_promoted_to_fp16 = const()[name = tensor<string, []>("op_119_promoted_to_fp16"), val = tensor<fp16, []>(-0x1p+0)];
            tensor<fp16, [1]> var_120_cast_fp16 = add(x = lengths_9_cast_fp16, y = var_119_promoted_to_fp16)[name = tensor<string, []>("op_120_cast_fp16")];
            tensor<fp16, []> _inversed_122_y_0_to_fp16 = const()[name = tensor<string, []>("_inversed_122_y_0_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1]> _inversed_122_cast_fp16 = mul(x = var_120_cast_fp16, y = _inversed_122_y_0_to_fp16)[name = tensor<string, []>("_inversed_122_cast_fp16")];
            tensor<fp16, []> var_123_to_fp16 = const()[name = tensor<string, []>("op_123_to_fp16"), val = tensor<fp16, []>(0x1p+0)];
            tensor<fp16, [1]> lengths_13_cast_fp16 = add(x = _inversed_122_cast_fp16, y = var_123_to_fp16)[name = tensor<string, []>("lengths_13_cast_fp16")];
            tensor<fp16, [1]> lengths_cast_fp16 = floor(x = lengths_13_cast_fp16)[name = tensor<string, []>("lengths_cast_fp16")];
            tensor<int32, [1]> input_1_axes_0 = const()[name = tensor<string, []>("input_1_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1, 128, 1501]> mel_to_fp16 = cast(dtype = mel_to_fp16_dtype_0, x = mel)[name = tensor<string, []>("cast_302")];
            tensor<fp16, [1, 1501, 128]> x_1_cast_fp16 = transpose(perm = x_1_perm_0, x = mel_to_fp16)[name = tensor<string, []>("transpose_386")];
            tensor<fp16, [1, 1, 1501, 128]> input_1_cast_fp16 = expand_dims(axes = input_1_axes_0, x = x_1_cast_fp16)[name = tensor<string, []>("input_1_cast_fp16")];
            tensor<string, []> input_3_pad_type_0 = const()[name = tensor<string, []>("input_3_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_3_pad_0 = const()[name = tensor<string, []>("input_3_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_3_strides_0 = const()[name = tensor<string, []>("input_3_strides_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [2]> input_3_dilations_0 = const()[name = tensor<string, []>("input_3_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_3_groups_0 = const()[name = tensor<string, []>("input_3_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 1, 3, 3]> encoder_pre_encode_conv_0_weight_to_fp16 = const()[name = tensor<string, []>("encoder_pre_encode_conv_0_weight_to_fp16"), val = tensor<fp16, [256, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(64)))];
            tensor<fp16, [256]> encoder_pre_encode_conv_0_bias_to_fp16 = const()[name = tensor<string, []>("encoder_pre_encode_conv_0_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4736)))];
            tensor<fp16, [1, 256, 751, 64]> input_3_cast_fp16 = conv(bias = encoder_pre_encode_conv_0_bias_to_fp16, dilations = input_3_dilations_0, groups = input_3_groups_0, pad = input_3_pad_0, pad_type = input_3_pad_type_0, strides = input_3_strides_0, weight = encoder_pre_encode_conv_0_weight_to_fp16, x = input_1_cast_fp16)[name = tensor<string, []>("input_3_cast_fp16")];
            tensor<fp16, [1, 256, 751, 64]> input_5_cast_fp16 = relu(x = input_3_cast_fp16)[name = tensor<string, []>("input_5_cast_fp16")];
            tensor<string, []> input_7_pad_type_0 = const()[name = tensor<string, []>("input_7_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_7_pad_0 = const()[name = tensor<string, []>("input_7_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_7_strides_0 = const()[name = tensor<string, []>("input_7_strides_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, []> input_7_groups_0 = const()[name = tensor<string, []>("input_7_groups_0"), val = tensor<int32, []>(256)];
            tensor<int32, [2]> input_7_dilations_0 = const()[name = tensor<string, []>("input_7_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [256, 1, 3, 3]> encoder_pre_encode_conv_2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_pre_encode_conv_2_weight_to_fp16"), val = tensor<fp16, [256, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5312)))];
            tensor<fp16, [256]> encoder_pre_encode_conv_2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_pre_encode_conv_2_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9984)))];
            tensor<fp16, [1, 256, 376, 32]> input_7_cast_fp16 = conv(bias = encoder_pre_encode_conv_2_bias_to_fp16, dilations = input_7_dilations_0, groups = input_7_groups_0, pad = input_7_pad_0, pad_type = input_7_pad_type_0, strides = input_7_strides_0, weight = encoder_pre_encode_conv_2_weight_to_fp16, x = input_5_cast_fp16)[name = tensor<string, []>("input_7_cast_fp16")];
            tensor<string, []> input_9_pad_type_0 = const()[name = tensor<string, []>("input_9_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [2]> input_9_strides_0 = const()[name = tensor<string, []>("input_9_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_9_pad_0 = const()[name = tensor<string, []>("input_9_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> input_9_dilations_0 = const()[name = tensor<string, []>("input_9_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_9_groups_0 = const()[name = tensor<string, []>("input_9_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 1, 1]> encoder_pre_encode_conv_3_weight_to_fp16 = const()[name = tensor<string, []>("encoder_pre_encode_conv_3_weight_to_fp16"), val = tensor<fp16, [256, 256, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10560)))];
            tensor<fp16, [256]> encoder_pre_encode_conv_3_bias_to_fp16 = const()[name = tensor<string, []>("encoder_pre_encode_conv_3_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(141696)))];
            tensor<fp16, [1, 256, 376, 32]> input_9_cast_fp16 = conv(bias = encoder_pre_encode_conv_3_bias_to_fp16, dilations = input_9_dilations_0, groups = input_9_groups_0, pad = input_9_pad_0, pad_type = input_9_pad_type_0, strides = input_9_strides_0, weight = encoder_pre_encode_conv_3_weight_to_fp16, x = input_7_cast_fp16)[name = tensor<string, []>("input_9_cast_fp16")];
            tensor<fp16, [1, 256, 376, 32]> input_11_cast_fp16 = relu(x = input_9_cast_fp16)[name = tensor<string, []>("input_11_cast_fp16")];
            tensor<string, []> input_13_pad_type_0 = const()[name = tensor<string, []>("input_13_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_13_pad_0 = const()[name = tensor<string, []>("input_13_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_13_strides_0 = const()[name = tensor<string, []>("input_13_strides_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, []> input_13_groups_0 = const()[name = tensor<string, []>("input_13_groups_0"), val = tensor<int32, []>(256)];
            tensor<int32, [2]> input_13_dilations_0 = const()[name = tensor<string, []>("input_13_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [256, 1, 3, 3]> encoder_pre_encode_conv_5_weight_to_fp16 = const()[name = tensor<string, []>("encoder_pre_encode_conv_5_weight_to_fp16"), val = tensor<fp16, [256, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(142272)))];
            tensor<fp16, [256]> encoder_pre_encode_conv_5_bias_to_fp16 = const()[name = tensor<string, []>("encoder_pre_encode_conv_5_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(146944)))];
            tensor<fp16, [1, 256, 188, 16]> input_13_cast_fp16 = conv(bias = encoder_pre_encode_conv_5_bias_to_fp16, dilations = input_13_dilations_0, groups = input_13_groups_0, pad = input_13_pad_0, pad_type = input_13_pad_type_0, strides = input_13_strides_0, weight = encoder_pre_encode_conv_5_weight_to_fp16, x = input_11_cast_fp16)[name = tensor<string, []>("input_13_cast_fp16")];
            tensor<string, []> input_15_pad_type_0 = const()[name = tensor<string, []>("input_15_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [2]> input_15_strides_0 = const()[name = tensor<string, []>("input_15_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_15_pad_0 = const()[name = tensor<string, []>("input_15_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> input_15_dilations_0 = const()[name = tensor<string, []>("input_15_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_15_groups_0 = const()[name = tensor<string, []>("input_15_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 1, 1]> encoder_pre_encode_conv_6_weight_to_fp16 = const()[name = tensor<string, []>("encoder_pre_encode_conv_6_weight_to_fp16"), val = tensor<fp16, [256, 256, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(147520)))];
            tensor<fp16, [256]> encoder_pre_encode_conv_6_bias_to_fp16 = const()[name = tensor<string, []>("encoder_pre_encode_conv_6_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(278656)))];
            tensor<fp16, [1, 256, 188, 16]> input_15_cast_fp16 = conv(bias = encoder_pre_encode_conv_6_bias_to_fp16, dilations = input_15_dilations_0, groups = input_15_groups_0, pad = input_15_pad_0, pad_type = input_15_pad_type_0, strides = input_15_strides_0, weight = encoder_pre_encode_conv_6_weight_to_fp16, x = input_13_cast_fp16)[name = tensor<string, []>("input_15_cast_fp16")];
            tensor<fp16, [1, 256, 188, 16]> x_3_cast_fp16 = relu(x = input_15_cast_fp16)[name = tensor<string, []>("x_3_cast_fp16")];
            tensor<int32, [4]> var_173_perm_0 = const()[name = tensor<string, []>("op_173_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_174 = const()[name = tensor<string, []>("op_174"), val = tensor<int32, [3]>([1, 188, -1])];
            tensor<fp16, [1, 188, 256, 16]> var_173_cast_fp16 = transpose(perm = var_173_perm_0, x = x_3_cast_fp16)[name = tensor<string, []>("transpose_385")];
            tensor<fp16, [1, 188, 4096]> input_17_cast_fp16 = reshape(shape = var_174, x = var_173_cast_fp16)[name = tensor<string, []>("input_17_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_pre_encode_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_pre_encode_out_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(279232)))];
            tensor<fp16, [1024]> encoder_pre_encode_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_pre_encode_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8667904)))];
            tensor<fp16, [1, 188, 1024]> linear_0_cast_fp16 = linear(bias = encoder_pre_encode_out_bias_to_fp16, weight = encoder_pre_encode_out_weight_to_fp16, x = input_17_cast_fp16)[name = tensor<string, []>("linear_0_cast_fp16")];
            tensor<string, []> padding_length_dtype_0 = const()[name = tensor<string, []>("padding_length_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [1, 188]> expand_dims_0 = const()[name = tensor<string, []>("expand_dims_0"), val = tensor<int32, [1, 188]>([[0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187]])];
            tensor<int32, [1]> var_212_axes_0 = const()[name = tensor<string, []>("op_212_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<int32, [1]> encoder_length = cast(dtype = padding_length_dtype_0, x = lengths_cast_fp16)[name = tensor<string, []>("cast_300")];
            tensor<int32, [1, 1]> var_212 = expand_dims(axes = var_212_axes_0, x = encoder_length)[name = tensor<string, []>("op_212")];
            tensor<bool, [1, 188]> pad_mask_1 = less(x = expand_dims_0, y = var_212)[name = tensor<string, []>("pad_mask_1")];
            tensor<int32, [1]> var_214_axes_0 = const()[name = tensor<string, []>("op_214_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<bool, [1, 1, 188]> var_214 = expand_dims(axes = var_214_axes_0, x = pad_mask_1)[name = tensor<string, []>("op_214")];
            tensor<int32, [3]> var_215 = const()[name = tensor<string, []>("op_215"), val = tensor<int32, [3]>([1, 188, 1])];
            tensor<bool, [1, 188, 188]> pad_mask_for_att_mask_1 = tile(reps = var_215, x = var_214)[name = tensor<string, []>("pad_mask_for_att_mask_1")];
            tensor<int32, [3]> var_217_perm_0 = const()[name = tensor<string, []>("op_217_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, [1, 188, 188]> var_217 = transpose(perm = var_217_perm_0, x = pad_mask_for_att_mask_1)[name = tensor<string, []>("transpose_384")];
            tensor<bool, [1, 188, 188]> pad_mask_for_att_mask = logical_and(x = pad_mask_for_att_mask_1, y = var_217)[name = tensor<string, []>("pad_mask_for_att_mask")];
            tensor<bool, [1, 188, 188]> const_7 = const()[name = tensor<string, []>("const_7"), val = tensor<bool, [1, 188, 188]>([[[true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, true, 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true, true, true, true, true, true, true, true]]])];
            tensor<bool, [1, 188, 188]> att_mask = logical_and(x = pad_mask_for_att_mask, y = const_7)[name = tensor<string, []>("att_mask")];
            tensor<bool, [1, 188, 188]> mask_1 = logical_not(x = att_mask)[name = tensor<string, []>("mask_1")];
            tensor<bool, [1, 188]> pad_mask = logical_not(x = pad_mask_1)[name = tensor<string, []>("pad_mask")];
            tensor<int32, [1]> input_21_axes_0 = const()[name = tensor<string, []>("input_21_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_0_norm_feed_forward1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_0_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8670016)))];
            tensor<fp16, [1024]> encoder_layers_0_norm_feed_forward1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_0_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8672128)))];
            tensor<fp16, []> var_9_to_fp16 = const()[name = tensor<string, []>("op_9_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 188, 1024]> input_21_cast_fp16 = layer_norm(axes = input_21_axes_0, beta = encoder_layers_0_norm_feed_forward1_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_0_norm_feed_forward1_weight_to_fp16, x = linear_0_cast_fp16)[name = tensor<string, []>("input_21_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_0_feed_forward1_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_0_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8674240)))];
            tensor<fp16, [4096]> encoder_layers_0_feed_forward1_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_0_feed_forward1_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(17062912)))];
            tensor<fp16, [1, 188, 4096]> linear_1_cast_fp16 = linear(bias = encoder_layers_0_feed_forward1_linear1_bias_to_fp16, weight = encoder_layers_0_feed_forward1_linear1_weight_to_fp16, x = input_21_cast_fp16)[name = tensor<string, []>("linear_1_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_25_cast_fp16 = silu(x = linear_1_cast_fp16)[name = tensor<string, []>("input_25_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_0_feed_forward1_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_0_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(17071168)))];
            tensor<fp16, [1024]> encoder_layers_0_feed_forward1_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_0_feed_forward1_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(25459840)))];
            tensor<fp16, [1, 188, 1024]> linear_2_cast_fp16 = linear(bias = encoder_layers_0_feed_forward1_linear2_bias_to_fp16, weight = encoder_layers_0_feed_forward1_linear2_weight_to_fp16, x = input_25_cast_fp16)[name = tensor<string, []>("linear_2_cast_fp16")];
            tensor<fp16, []> var_250_to_fp16 = const()[name = tensor<string, []>("op_250_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_251_cast_fp16 = mul(x = linear_2_cast_fp16, y = var_250_to_fp16)[name = tensor<string, []>("op_251_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_31_cast_fp16 = add(x = linear_0_cast_fp16, y = var_251_cast_fp16)[name = tensor<string, []>("input_31_cast_fp16")];
            tensor<int32, [1]> query_1_axes_0 = const()[name = tensor<string, []>("query_1_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_0_norm_self_att_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_0_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(25461952)))];
            tensor<fp16, [1024]> encoder_layers_0_norm_self_att_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_0_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(25464064)))];
            tensor<fp16, [1, 188, 1024]> query_1_cast_fp16 = layer_norm(axes = query_1_axes_0, beta = encoder_layers_0_norm_self_att_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_0_norm_self_att_weight_to_fp16, x = input_31_cast_fp16)[name = tensor<string, []>("query_1_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_0_self_attn_linear_q_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_0_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(25466176)))];
            tensor<fp16, [1024]> encoder_layers_0_self_attn_linear_q_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_0_self_attn_linear_q_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(27563392)))];
            tensor<fp16, [1, 188, 1024]> linear_3_cast_fp16 = linear(bias = encoder_layers_0_self_attn_linear_q_bias_to_fp16, weight = encoder_layers_0_self_attn_linear_q_weight_to_fp16, x = query_1_cast_fp16)[name = tensor<string, []>("linear_3_cast_fp16")];
            tensor<int32, [4]> var_268 = const()[name = tensor<string, []>("op_268"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_1_cast_fp16 = reshape(shape = var_268, x = linear_3_cast_fp16)[name = tensor<string, []>("q_1_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_0_self_attn_linear_k_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_0_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(27565504)))];
            tensor<fp16, [1024]> encoder_layers_0_self_attn_linear_k_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_0_self_attn_linear_k_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(29662720)))];
            tensor<fp16, [1, 188, 1024]> linear_4_cast_fp16 = linear(bias = encoder_layers_0_self_attn_linear_k_bias_to_fp16, weight = encoder_layers_0_self_attn_linear_k_weight_to_fp16, x = query_1_cast_fp16)[name = tensor<string, []>("linear_4_cast_fp16")];
            tensor<int32, [4]> var_273 = const()[name = tensor<string, []>("op_273"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_1_cast_fp16 = reshape(shape = var_273, x = linear_4_cast_fp16)[name = tensor<string, []>("k_1_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_0_self_attn_linear_v_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_0_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(29664832)))];
            tensor<fp16, [1024]> encoder_layers_0_self_attn_linear_v_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_0_self_attn_linear_v_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(31762048)))];
            tensor<fp16, [1, 188, 1024]> linear_5_cast_fp16 = linear(bias = encoder_layers_0_self_attn_linear_v_bias_to_fp16, weight = encoder_layers_0_self_attn_linear_v_weight_to_fp16, x = query_1_cast_fp16)[name = tensor<string, []>("linear_5_cast_fp16")];
            tensor<int32, [4]> var_278 = const()[name = tensor<string, []>("op_278"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_1_cast_fp16 = reshape(shape = var_278, x = linear_5_cast_fp16)[name = tensor<string, []>("v_1_cast_fp16")];
            tensor<int32, [4]> value_3_perm_0 = const()[name = tensor<string, []>("value_3_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> encoder_layers_0_self_attn_pos_bias_u_to_fp16 = const()[name = tensor<string, []>("encoder_layers_0_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(31764160)))];
            tensor<fp16, [1, 188, 8, 128]> var_290_cast_fp16 = add(x = q_1_cast_fp16, y = encoder_layers_0_self_attn_pos_bias_u_to_fp16)[name = tensor<string, []>("op_290_cast_fp16")];
            tensor<fp16, [8, 128]> encoder_layers_0_self_attn_pos_bias_v_to_fp16 = const()[name = tensor<string, []>("encoder_layers_0_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(31766272)))];
            tensor<fp16, [1, 188, 8, 128]> var_292_cast_fp16 = add(x = q_1_cast_fp16, y = encoder_layers_0_self_attn_pos_bias_v_to_fp16)[name = tensor<string, []>("op_292_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_1_perm_0 = const()[name = tensor<string, []>("q_with_bias_v_1_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<bool, []> x_7_transpose_x_0 = const()[name = tensor<string, []>("x_7_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_7_transpose_y_0 = const()[name = tensor<string, []>("x_7_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 128, 375]> var_294_to_fp16 = const()[name = tensor<string, []>("op_294_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(31768384)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_1_cast_fp16 = transpose(perm = q_with_bias_v_1_perm_0, x = var_292_cast_fp16)[name = tensor<string, []>("transpose_382")];
            tensor<fp16, [1, 8, 188, 375]> x_7_cast_fp16 = matmul(transpose_x = x_7_transpose_x_0, transpose_y = x_7_transpose_y_0, x = q_with_bias_v_1_cast_fp16, y = var_294_to_fp16)[name = tensor<string, []>("x_7_cast_fp16")];
            tensor<int32, [8]> x_9_pad_0 = const()[name = tensor<string, []>("x_9_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            tensor<string, []> x_9_mode_0 = const()[name = tensor<string, []>("x_9_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_14_to_fp16 = const()[name = tensor<string, []>("const_14_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_9_cast_fp16 = pad(constant_val = const_14_to_fp16, mode = x_9_mode_0, pad = x_9_pad_0, x = x_7_cast_fp16)[name = tensor<string, []>("x_9_cast_fp16")];
            tensor<int32, [4]> var_302 = const()[name = tensor<string, []>("op_302"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_11_cast_fp16 = reshape(shape = var_302, x = x_9_cast_fp16)[name = tensor<string, []>("x_11_cast_fp16")];
            tensor<int32, [4]> var_306_begin_0 = const()[name = tensor<string, []>("op_306_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_306_end_0 = const()[name = tensor<string, []>("op_306_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_306_end_mask_0 = const()[name = tensor<string, []>("op_306_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_306_cast_fp16 = slice_by_index(begin = var_306_begin_0, end = var_306_end_0, end_mask = var_306_end_mask_0, x = x_11_cast_fp16)[name = tensor<string, []>("op_306_cast_fp16")];
            tensor<int32, [4]> var_307 = const()[name = tensor<string, []>("op_307"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_1_cast_fp16 = reshape(shape = var_307, x = var_306_cast_fp16)[name = tensor<string, []>("matrix_bd_1_cast_fp16")];
            tensor<bool, []> matrix_ac_1_transpose_x_0 = const()[name = tensor<string, []>("matrix_ac_1_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> matrix_ac_1_transpose_y_0 = const()[name = tensor<string, []>("matrix_ac_1_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<int32, [4]> transpose_96_perm_0 = const()[name = tensor<string, []>("transpose_96_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_97_perm_0 = const()[name = tensor<string, []>("transpose_97_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_97 = transpose(perm = transpose_97_perm_0, x = k_1_cast_fp16)[name = tensor<string, []>("transpose_380")];
            tensor<fp16, [1, 8, 188, 128]> transpose_96 = transpose(perm = transpose_96_perm_0, x = var_290_cast_fp16)[name = tensor<string, []>("transpose_381")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_1_cast_fp16 = matmul(transpose_x = matrix_ac_1_transpose_x_0, transpose_y = matrix_ac_1_transpose_y_0, x = transpose_96, y = transpose_97)[name = tensor<string, []>("matrix_ac_1_cast_fp16")];
            tensor<int32, [4]> matrix_bd_3_begin_0 = const()[name = tensor<string, []>("matrix_bd_3_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_3_end_0 = const()[name = tensor<string, []>("matrix_bd_3_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_3_end_mask_0 = const()[name = tensor<string, []>("matrix_bd_3_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_3_cast_fp16 = slice_by_index(begin = matrix_bd_3_begin_0, end = matrix_bd_3_end_0, end_mask = matrix_bd_3_end_mask_0, x = matrix_bd_1_cast_fp16)[name = tensor<string, []>("matrix_bd_3_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_316_cast_fp16 = add(x = matrix_ac_1_cast_fp16, y = matrix_bd_3_cast_fp16)[name = tensor<string, []>("op_316_cast_fp16")];
            tensor<fp16, []> _inversed_scores_1_y_0_to_fp16 = const()[name = tensor<string, []>("_inversed_scores_1_y_0_to_fp16"), val = tensor<fp16, []>(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_1_cast_fp16 = mul(x = var_316_cast_fp16, y = _inversed_scores_1_y_0_to_fp16)[name = tensor<string, []>("_inversed_scores_1_cast_fp16")];
            tensor<int32, [1]> mask_3_axes_0 = const()[name = tensor<string, []>("mask_3_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<bool, [1, 1, 188, 188]> mask_3 = expand_dims(axes = mask_3_axes_0, x = mask_1)[name = tensor<string, []>("mask_3")];
            tensor<fp16, []> var_12_to_fp16 = const()[name = tensor<string, []>("op_12_to_fp16"), val = tensor<fp16, []>(-0x1.388p+13)];
            tensor<fp16, [1, 8, 188, 188]> scores_3_cast_fp16 = select(a = var_12_to_fp16, b = _inversed_scores_1_cast_fp16, cond = mask_3)[name = tensor<string, []>("scores_3_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_322_cast_fp16 = softmax(axis = var_30, x = scores_3_cast_fp16)[name = tensor<string, []>("op_322_cast_fp16")];
            tensor<fp16, []> var_11_to_fp16 = const()[name = tensor<string, []>("op_11_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 8, 188, 188]> input_33_cast_fp16 = select(a = var_11_to_fp16, b = var_322_cast_fp16, cond = mask_3)[name = tensor<string, []>("input_33_cast_fp16")];
            tensor<bool, []> x_13_transpose_x_0 = const()[name = tensor<string, []>("x_13_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_13_transpose_y_0 = const()[name = tensor<string, []>("x_13_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 188, 128]> value_3_cast_fp16 = transpose(perm = value_3_perm_0, x = v_1_cast_fp16)[name = tensor<string, []>("transpose_383")];
            tensor<fp16, [1, 8, 188, 128]> x_13_cast_fp16 = matmul(transpose_x = x_13_transpose_x_0, transpose_y = x_13_transpose_y_0, x = input_33_cast_fp16, y = value_3_cast_fp16)[name = tensor<string, []>("x_13_cast_fp16")];
            tensor<int32, [4]> var_326_perm_0 = const()[name = tensor<string, []>("op_326_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_327 = const()[name = tensor<string, []>("op_327"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_326_cast_fp16 = transpose(perm = var_326_perm_0, x = x_13_cast_fp16)[name = tensor<string, []>("transpose_379")];
            tensor<fp16, [1, 188, 1024]> input_35_cast_fp16 = reshape(shape = var_327, x = var_326_cast_fp16)[name = tensor<string, []>("input_35_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_0_self_attn_linear_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_0_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(32536448)))];
            tensor<fp16, [1024]> encoder_layers_0_self_attn_linear_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_0_self_attn_linear_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(34633664)))];
            tensor<fp16, [1, 188, 1024]> linear_7_cast_fp16 = linear(bias = encoder_layers_0_self_attn_linear_out_bias_to_fp16, weight = encoder_layers_0_self_attn_linear_out_weight_to_fp16, x = input_35_cast_fp16)[name = tensor<string, []>("linear_7_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_39_cast_fp16 = add(x = input_31_cast_fp16, y = linear_7_cast_fp16)[name = tensor<string, []>("input_39_cast_fp16")];
            tensor<int32, [1]> x_17_axes_0 = const()[name = tensor<string, []>("x_17_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_0_norm_conv_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_0_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(34635776)))];
            tensor<fp16, [1024]> encoder_layers_0_norm_conv_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_0_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(34637888)))];
            tensor<fp16, [1, 188, 1024]> x_17_cast_fp16 = layer_norm(axes = x_17_axes_0, beta = encoder_layers_0_norm_conv_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_0_norm_conv_weight_to_fp16, x = input_39_cast_fp16)[name = tensor<string, []>("x_17_cast_fp16")];
            tensor<int32, [3]> input_41_perm_0 = const()[name = tensor<string, []>("input_41_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> input_43_pad_type_0 = const()[name = tensor<string, []>("input_43_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_43_strides_0 = const()[name = tensor<string, []>("input_43_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_43_pad_0 = const()[name = tensor<string, []>("input_43_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_43_dilations_0 = const()[name = tensor<string, []>("input_43_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_43_groups_0 = const()[name = tensor<string, []>("input_43_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [2048, 1024, 1]> encoder_layers_0_conv_pointwise_conv1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_0_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(34640000)))];
            tensor<fp16, [2048]> encoder_layers_0_conv_pointwise_conv1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_0_conv_pointwise_conv1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(38834368)))];
            tensor<fp16, [1, 1024, 188]> input_41_cast_fp16 = transpose(perm = input_41_perm_0, x = x_17_cast_fp16)[name = tensor<string, []>("transpose_378")];
            tensor<fp16, [1, 2048, 188]> input_43_cast_fp16 = conv(bias = encoder_layers_0_conv_pointwise_conv1_bias_to_fp16, dilations = input_43_dilations_0, groups = input_43_groups_0, pad = input_43_pad_0, pad_type = input_43_pad_type_0, strides = input_43_strides_0, weight = encoder_layers_0_conv_pointwise_conv1_weight_to_fp16, x = input_41_cast_fp16)[name = tensor<string, []>("input_43_cast_fp16")];
            tensor<int32, []> x_19_split_num_splits_0 = const()[name = tensor<string, []>("x_19_split_num_splits_0"), val = tensor<int32, []>(2)];
            tensor<int32, []> x_19_split_axis_0 = const()[name = tensor<string, []>("x_19_split_axis_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1, 1024, 188]> x_19_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_19_split_cast_fp16_1 = split(axis = x_19_split_axis_0, num_splits = x_19_split_num_splits_0, x = input_43_cast_fp16)[name = tensor<string, []>("x_19_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_19_split_1_sigmoid_cast_fp16 = sigmoid(x = x_19_split_cast_fp16_1)[name = tensor<string, []>("x_19_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_19_cast_fp16 = mul(x = x_19_split_cast_fp16_0, y = x_19_split_1_sigmoid_cast_fp16)[name = tensor<string, []>("x_19_cast_fp16")];
            tensor<int32, [1]> var_351_axes_0 = const()[name = tensor<string, []>("op_351_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<bool, [1, 1, 188]> var_351 = expand_dims(axes = var_351_axes_0, x = pad_mask)[name = tensor<string, []>("op_351")];
            tensor<fp16, [1, 1024, 188]> input_45_cast_fp16 = select(a = var_11_to_fp16, b = x_19_cast_fp16, cond = var_351)[name = tensor<string, []>("input_45_cast_fp16")];
            tensor<int32, [6]> input_47_pad_0 = const()[name = tensor<string, []>("input_47_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            tensor<string, []> input_47_mode_0 = const()[name = tensor<string, []>("input_47_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_17_to_fp16 = const()[name = tensor<string, []>("const_17_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_47_cast_fp16 = pad(constant_val = const_17_to_fp16, mode = input_47_mode_0, pad = input_47_pad_0, x = input_45_cast_fp16)[name = tensor<string, []>("input_47_cast_fp16")];
            tensor<string, []> input_49_pad_type_0 = const()[name = tensor<string, []>("input_49_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, []> input_49_groups_0 = const()[name = tensor<string, []>("input_49_groups_0"), val = tensor<int32, []>(1024)];
            tensor<int32, [1]> input_49_strides_0 = const()[name = tensor<string, []>("input_49_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_49_pad_0 = const()[name = tensor<string, []>("input_49_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_49_dilations_0 = const()[name = tensor<string, []>("input_49_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_328_to_fp16 = const()[name = tensor<string, []>("const_328_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(38838528)))];
            tensor<fp16, [1024]> const_329_to_fp16 = const()[name = tensor<string, []>("const_329_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(38857024)))];
            tensor<fp16, [1, 1024, 188]> input_51_cast_fp16 = conv(bias = const_329_to_fp16, dilations = input_49_dilations_0, groups = input_49_groups_0, pad = input_49_pad_0, pad_type = input_49_pad_type_0, strides = input_49_strides_0, weight = const_328_to_fp16, x = input_47_cast_fp16)[name = tensor<string, []>("input_51_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_53_cast_fp16 = silu(x = input_51_cast_fp16)[name = tensor<string, []>("input_53_cast_fp16")];
            tensor<string, []> x_21_pad_type_0 = const()[name = tensor<string, []>("x_21_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> x_21_strides_0 = const()[name = tensor<string, []>("x_21_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_21_pad_0 = const()[name = tensor<string, []>("x_21_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_21_dilations_0 = const()[name = tensor<string, []>("x_21_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> x_21_groups_0 = const()[name = tensor<string, []>("x_21_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1024, 1024, 1]> encoder_layers_0_conv_pointwise_conv2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_0_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(38859136)))];
            tensor<fp16, [1024]> encoder_layers_0_conv_pointwise_conv2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_0_conv_pointwise_conv2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(40956352)))];
            tensor<fp16, [1, 1024, 188]> x_21_cast_fp16 = conv(bias = encoder_layers_0_conv_pointwise_conv2_bias_to_fp16, dilations = x_21_dilations_0, groups = x_21_groups_0, pad = x_21_pad_0, pad_type = x_21_pad_type_0, strides = x_21_strides_0, weight = encoder_layers_0_conv_pointwise_conv2_weight_to_fp16, x = input_53_cast_fp16)[name = tensor<string, []>("x_21_cast_fp16")];
            tensor<int32, [3]> input_55_perm_0 = const()[name = tensor<string, []>("input_55_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_55_cast_fp16 = transpose(perm = input_55_perm_0, x = x_21_cast_fp16)[name = tensor<string, []>("transpose_377")];
            tensor<fp16, [1, 188, 1024]> input_57_cast_fp16 = add(x = input_39_cast_fp16, y = input_55_cast_fp16)[name = tensor<string, []>("input_57_cast_fp16")];
            tensor<int32, [1]> input_59_axes_0 = const()[name = tensor<string, []>("input_59_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_0_norm_feed_forward2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_0_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(40958464)))];
            tensor<fp16, [1024]> encoder_layers_0_norm_feed_forward2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_0_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(40960576)))];
            tensor<fp16, [1, 188, 1024]> input_59_cast_fp16 = layer_norm(axes = input_59_axes_0, beta = encoder_layers_0_norm_feed_forward2_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_0_norm_feed_forward2_weight_to_fp16, x = input_57_cast_fp16)[name = tensor<string, []>("input_59_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_0_feed_forward2_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_0_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(40962688)))];
            tensor<fp16, [4096]> encoder_layers_0_feed_forward2_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_0_feed_forward2_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(49351360)))];
            tensor<fp16, [1, 188, 4096]> linear_8_cast_fp16 = linear(bias = encoder_layers_0_feed_forward2_linear1_bias_to_fp16, weight = encoder_layers_0_feed_forward2_linear1_weight_to_fp16, x = input_59_cast_fp16)[name = tensor<string, []>("linear_8_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_63_cast_fp16 = silu(x = linear_8_cast_fp16)[name = tensor<string, []>("input_63_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_0_feed_forward2_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_0_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(49359616)))];
            tensor<fp16, [1024]> encoder_layers_0_feed_forward2_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_0_feed_forward2_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(57748288)))];
            tensor<fp16, [1, 188, 1024]> linear_9_cast_fp16 = linear(bias = encoder_layers_0_feed_forward2_linear2_bias_to_fp16, weight = encoder_layers_0_feed_forward2_linear2_weight_to_fp16, x = input_63_cast_fp16)[name = tensor<string, []>("linear_9_cast_fp16")];
            tensor<fp16, []> var_393_to_fp16 = const()[name = tensor<string, []>("op_393_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_394_cast_fp16 = mul(x = linear_9_cast_fp16, y = var_393_to_fp16)[name = tensor<string, []>("op_394_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_69_cast_fp16 = add(x = input_57_cast_fp16, y = var_394_cast_fp16)[name = tensor<string, []>("input_69_cast_fp16")];
            tensor<int32, [1]> input_71_axes_0 = const()[name = tensor<string, []>("input_71_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_0_norm_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_0_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(57750400)))];
            tensor<fp16, [1024]> encoder_layers_0_norm_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_0_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(57752512)))];
            tensor<fp16, [1, 188, 1024]> input_71_cast_fp16 = layer_norm(axes = input_71_axes_0, beta = encoder_layers_0_norm_out_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_0_norm_out_weight_to_fp16, x = input_69_cast_fp16)[name = tensor<string, []>("input_71_cast_fp16")];
            tensor<int32, [1]> input_73_axes_0 = const()[name = tensor<string, []>("input_73_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_1_norm_feed_forward1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_1_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(57754624)))];
            tensor<fp16, [1024]> encoder_layers_1_norm_feed_forward1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_1_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(57756736)))];
            tensor<fp16, [1, 188, 1024]> input_73_cast_fp16 = layer_norm(axes = input_73_axes_0, beta = encoder_layers_1_norm_feed_forward1_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_1_norm_feed_forward1_weight_to_fp16, x = input_71_cast_fp16)[name = tensor<string, []>("input_73_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_1_feed_forward1_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_1_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(57758848)))];
            tensor<fp16, [4096]> encoder_layers_1_feed_forward1_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_1_feed_forward1_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(66147520)))];
            tensor<fp16, [1, 188, 4096]> linear_10_cast_fp16 = linear(bias = encoder_layers_1_feed_forward1_linear1_bias_to_fp16, weight = encoder_layers_1_feed_forward1_linear1_weight_to_fp16, x = input_73_cast_fp16)[name = tensor<string, []>("linear_10_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_77_cast_fp16 = silu(x = linear_10_cast_fp16)[name = tensor<string, []>("input_77_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_1_feed_forward1_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_1_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(66155776)))];
            tensor<fp16, [1024]> encoder_layers_1_feed_forward1_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_1_feed_forward1_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(74544448)))];
            tensor<fp16, [1, 188, 1024]> linear_11_cast_fp16 = linear(bias = encoder_layers_1_feed_forward1_linear2_bias_to_fp16, weight = encoder_layers_1_feed_forward1_linear2_weight_to_fp16, x = input_77_cast_fp16)[name = tensor<string, []>("linear_11_cast_fp16")];
            tensor<fp16, []> var_424_to_fp16 = const()[name = tensor<string, []>("op_424_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_425_cast_fp16 = mul(x = linear_11_cast_fp16, y = var_424_to_fp16)[name = tensor<string, []>("op_425_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_83_cast_fp16 = add(x = input_71_cast_fp16, y = var_425_cast_fp16)[name = tensor<string, []>("input_83_cast_fp16")];
            tensor<int32, [1]> query_3_axes_0 = const()[name = tensor<string, []>("query_3_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_1_norm_self_att_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_1_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(74546560)))];
            tensor<fp16, [1024]> encoder_layers_1_norm_self_att_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_1_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(74548672)))];
            tensor<fp16, [1, 188, 1024]> query_3_cast_fp16 = layer_norm(axes = query_3_axes_0, beta = encoder_layers_1_norm_self_att_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_1_norm_self_att_weight_to_fp16, x = input_83_cast_fp16)[name = tensor<string, []>("query_3_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_1_self_attn_linear_q_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_1_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(74550784)))];
            tensor<fp16, [1024]> encoder_layers_1_self_attn_linear_q_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_1_self_attn_linear_q_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(76648000)))];
            tensor<fp16, [1, 188, 1024]> linear_12_cast_fp16 = linear(bias = encoder_layers_1_self_attn_linear_q_bias_to_fp16, weight = encoder_layers_1_self_attn_linear_q_weight_to_fp16, x = query_3_cast_fp16)[name = tensor<string, []>("linear_12_cast_fp16")];
            tensor<int32, [4]> var_442 = const()[name = tensor<string, []>("op_442"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_7_cast_fp16 = reshape(shape = var_442, x = linear_12_cast_fp16)[name = tensor<string, []>("q_7_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_1_self_attn_linear_k_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_1_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(76650112)))];
            tensor<fp16, [1024]> encoder_layers_1_self_attn_linear_k_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_1_self_attn_linear_k_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(78747328)))];
            tensor<fp16, [1, 188, 1024]> linear_13_cast_fp16 = linear(bias = encoder_layers_1_self_attn_linear_k_bias_to_fp16, weight = encoder_layers_1_self_attn_linear_k_weight_to_fp16, x = query_3_cast_fp16)[name = tensor<string, []>("linear_13_cast_fp16")];
            tensor<int32, [4]> var_447 = const()[name = tensor<string, []>("op_447"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_5_cast_fp16 = reshape(shape = var_447, x = linear_13_cast_fp16)[name = tensor<string, []>("k_5_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_1_self_attn_linear_v_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_1_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(78749440)))];
            tensor<fp16, [1024]> encoder_layers_1_self_attn_linear_v_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_1_self_attn_linear_v_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(80846656)))];
            tensor<fp16, [1, 188, 1024]> linear_14_cast_fp16 = linear(bias = encoder_layers_1_self_attn_linear_v_bias_to_fp16, weight = encoder_layers_1_self_attn_linear_v_weight_to_fp16, x = query_3_cast_fp16)[name = tensor<string, []>("linear_14_cast_fp16")];
            tensor<int32, [4]> var_452 = const()[name = tensor<string, []>("op_452"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_3_cast_fp16 = reshape(shape = var_452, x = linear_14_cast_fp16)[name = tensor<string, []>("v_3_cast_fp16")];
            tensor<int32, [4]> value_5_perm_0 = const()[name = tensor<string, []>("value_5_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> encoder_layers_1_self_attn_pos_bias_u_to_fp16 = const()[name = tensor<string, []>("encoder_layers_1_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(80848768)))];
            tensor<fp16, [1, 188, 8, 128]> var_464_cast_fp16 = add(x = q_7_cast_fp16, y = encoder_layers_1_self_attn_pos_bias_u_to_fp16)[name = tensor<string, []>("op_464_cast_fp16")];
            tensor<fp16, [8, 128]> encoder_layers_1_self_attn_pos_bias_v_to_fp16 = const()[name = tensor<string, []>("encoder_layers_1_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(80850880)))];
            tensor<fp16, [1, 188, 8, 128]> var_466_cast_fp16 = add(x = q_7_cast_fp16, y = encoder_layers_1_self_attn_pos_bias_v_to_fp16)[name = tensor<string, []>("op_466_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_3_perm_0 = const()[name = tensor<string, []>("q_with_bias_v_3_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<bool, []> x_29_transpose_x_0 = const()[name = tensor<string, []>("x_29_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_29_transpose_y_0 = const()[name = tensor<string, []>("x_29_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 128, 375]> var_468_to_fp16 = const()[name = tensor<string, []>("op_468_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(80852992)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_3_cast_fp16 = transpose(perm = q_with_bias_v_3_perm_0, x = var_466_cast_fp16)[name = tensor<string, []>("transpose_375")];
            tensor<fp16, [1, 8, 188, 375]> x_29_cast_fp16 = matmul(transpose_x = x_29_transpose_x_0, transpose_y = x_29_transpose_y_0, x = q_with_bias_v_3_cast_fp16, y = var_468_to_fp16)[name = tensor<string, []>("x_29_cast_fp16")];
            tensor<int32, [8]> x_31_pad_0 = const()[name = tensor<string, []>("x_31_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            tensor<string, []> x_31_mode_0 = const()[name = tensor<string, []>("x_31_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_24_to_fp16 = const()[name = tensor<string, []>("const_24_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_31_cast_fp16 = pad(constant_val = const_24_to_fp16, mode = x_31_mode_0, pad = x_31_pad_0, x = x_29_cast_fp16)[name = tensor<string, []>("x_31_cast_fp16")];
            tensor<int32, [4]> var_476 = const()[name = tensor<string, []>("op_476"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_33_cast_fp16 = reshape(shape = var_476, x = x_31_cast_fp16)[name = tensor<string, []>("x_33_cast_fp16")];
            tensor<int32, [4]> var_480_begin_0 = const()[name = tensor<string, []>("op_480_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_480_end_0 = const()[name = tensor<string, []>("op_480_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_480_end_mask_0 = const()[name = tensor<string, []>("op_480_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_480_cast_fp16 = slice_by_index(begin = var_480_begin_0, end = var_480_end_0, end_mask = var_480_end_mask_0, x = x_33_cast_fp16)[name = tensor<string, []>("op_480_cast_fp16")];
            tensor<int32, [4]> var_481 = const()[name = tensor<string, []>("op_481"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_5_cast_fp16 = reshape(shape = var_481, x = var_480_cast_fp16)[name = tensor<string, []>("matrix_bd_5_cast_fp16")];
            tensor<bool, []> matrix_ac_3_transpose_x_0 = const()[name = tensor<string, []>("matrix_ac_3_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> matrix_ac_3_transpose_y_0 = const()[name = tensor<string, []>("matrix_ac_3_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<int32, [4]> transpose_98_perm_0 = const()[name = tensor<string, []>("transpose_98_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_99_perm_0 = const()[name = tensor<string, []>("transpose_99_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_99 = transpose(perm = transpose_99_perm_0, x = k_5_cast_fp16)[name = tensor<string, []>("transpose_373")];
            tensor<fp16, [1, 8, 188, 128]> transpose_98 = transpose(perm = transpose_98_perm_0, x = var_464_cast_fp16)[name = tensor<string, []>("transpose_374")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_3_cast_fp16 = matmul(transpose_x = matrix_ac_3_transpose_x_0, transpose_y = matrix_ac_3_transpose_y_0, x = transpose_98, y = transpose_99)[name = tensor<string, []>("matrix_ac_3_cast_fp16")];
            tensor<int32, [4]> matrix_bd_7_begin_0 = const()[name = tensor<string, []>("matrix_bd_7_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_7_end_0 = const()[name = tensor<string, []>("matrix_bd_7_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_7_end_mask_0 = const()[name = tensor<string, []>("matrix_bd_7_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_7_cast_fp16 = slice_by_index(begin = matrix_bd_7_begin_0, end = matrix_bd_7_end_0, end_mask = matrix_bd_7_end_mask_0, x = matrix_bd_5_cast_fp16)[name = tensor<string, []>("matrix_bd_7_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_490_cast_fp16 = add(x = matrix_ac_3_cast_fp16, y = matrix_bd_7_cast_fp16)[name = tensor<string, []>("op_490_cast_fp16")];
            tensor<fp16, []> _inversed_scores_5_y_0_to_fp16 = const()[name = tensor<string, []>("_inversed_scores_5_y_0_to_fp16"), val = tensor<fp16, []>(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_5_cast_fp16 = mul(x = var_490_cast_fp16, y = _inversed_scores_5_y_0_to_fp16)[name = tensor<string, []>("_inversed_scores_5_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_7_cast_fp16 = select(a = var_12_to_fp16, b = _inversed_scores_5_cast_fp16, cond = mask_3)[name = tensor<string, []>("scores_7_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_496_cast_fp16 = softmax(axis = var_30, x = scores_7_cast_fp16)[name = tensor<string, []>("op_496_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_85_cast_fp16 = select(a = var_11_to_fp16, b = var_496_cast_fp16, cond = mask_3)[name = tensor<string, []>("input_85_cast_fp16")];
            tensor<bool, []> x_35_transpose_x_0 = const()[name = tensor<string, []>("x_35_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_35_transpose_y_0 = const()[name = tensor<string, []>("x_35_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 188, 128]> value_5_cast_fp16 = transpose(perm = value_5_perm_0, x = v_3_cast_fp16)[name = tensor<string, []>("transpose_376")];
            tensor<fp16, [1, 8, 188, 128]> x_35_cast_fp16 = matmul(transpose_x = x_35_transpose_x_0, transpose_y = x_35_transpose_y_0, x = input_85_cast_fp16, y = value_5_cast_fp16)[name = tensor<string, []>("x_35_cast_fp16")];
            tensor<int32, [4]> var_500_perm_0 = const()[name = tensor<string, []>("op_500_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_501 = const()[name = tensor<string, []>("op_501"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_500_cast_fp16 = transpose(perm = var_500_perm_0, x = x_35_cast_fp16)[name = tensor<string, []>("transpose_372")];
            tensor<fp16, [1, 188, 1024]> input_87_cast_fp16 = reshape(shape = var_501, x = var_500_cast_fp16)[name = tensor<string, []>("input_87_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_1_self_attn_linear_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_1_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(81621056)))];
            tensor<fp16, [1024]> encoder_layers_1_self_attn_linear_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_1_self_attn_linear_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(83718272)))];
            tensor<fp16, [1, 188, 1024]> linear_16_cast_fp16 = linear(bias = encoder_layers_1_self_attn_linear_out_bias_to_fp16, weight = encoder_layers_1_self_attn_linear_out_weight_to_fp16, x = input_87_cast_fp16)[name = tensor<string, []>("linear_16_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_91_cast_fp16 = add(x = input_83_cast_fp16, y = linear_16_cast_fp16)[name = tensor<string, []>("input_91_cast_fp16")];
            tensor<int32, [1]> x_39_axes_0 = const()[name = tensor<string, []>("x_39_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_1_norm_conv_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_1_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(83720384)))];
            tensor<fp16, [1024]> encoder_layers_1_norm_conv_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_1_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(83722496)))];
            tensor<fp16, [1, 188, 1024]> x_39_cast_fp16 = layer_norm(axes = x_39_axes_0, beta = encoder_layers_1_norm_conv_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_1_norm_conv_weight_to_fp16, x = input_91_cast_fp16)[name = tensor<string, []>("x_39_cast_fp16")];
            tensor<int32, [3]> input_93_perm_0 = const()[name = tensor<string, []>("input_93_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> input_95_pad_type_0 = const()[name = tensor<string, []>("input_95_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_95_strides_0 = const()[name = tensor<string, []>("input_95_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_95_pad_0 = const()[name = tensor<string, []>("input_95_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_95_dilations_0 = const()[name = tensor<string, []>("input_95_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_95_groups_0 = const()[name = tensor<string, []>("input_95_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [2048, 1024, 1]> encoder_layers_1_conv_pointwise_conv1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_1_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(83724608)))];
            tensor<fp16, [2048]> encoder_layers_1_conv_pointwise_conv1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_1_conv_pointwise_conv1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(87918976)))];
            tensor<fp16, [1, 1024, 188]> input_93_cast_fp16 = transpose(perm = input_93_perm_0, x = x_39_cast_fp16)[name = tensor<string, []>("transpose_371")];
            tensor<fp16, [1, 2048, 188]> input_95_cast_fp16 = conv(bias = encoder_layers_1_conv_pointwise_conv1_bias_to_fp16, dilations = input_95_dilations_0, groups = input_95_groups_0, pad = input_95_pad_0, pad_type = input_95_pad_type_0, strides = input_95_strides_0, weight = encoder_layers_1_conv_pointwise_conv1_weight_to_fp16, x = input_93_cast_fp16)[name = tensor<string, []>("input_95_cast_fp16")];
            tensor<int32, []> x_41_split_num_splits_0 = const()[name = tensor<string, []>("x_41_split_num_splits_0"), val = tensor<int32, []>(2)];
            tensor<int32, []> x_41_split_axis_0 = const()[name = tensor<string, []>("x_41_split_axis_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1, 1024, 188]> x_41_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_41_split_cast_fp16_1 = split(axis = x_41_split_axis_0, num_splits = x_41_split_num_splits_0, x = input_95_cast_fp16)[name = tensor<string, []>("x_41_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_41_split_1_sigmoid_cast_fp16 = sigmoid(x = x_41_split_cast_fp16_1)[name = tensor<string, []>("x_41_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_41_cast_fp16 = mul(x = x_41_split_cast_fp16_0, y = x_41_split_1_sigmoid_cast_fp16)[name = tensor<string, []>("x_41_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_97_cast_fp16 = select(a = var_11_to_fp16, b = x_41_cast_fp16, cond = var_351)[name = tensor<string, []>("input_97_cast_fp16")];
            tensor<int32, [6]> input_99_pad_0 = const()[name = tensor<string, []>("input_99_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            tensor<string, []> input_99_mode_0 = const()[name = tensor<string, []>("input_99_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_27_to_fp16 = const()[name = tensor<string, []>("const_27_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_99_cast_fp16 = pad(constant_val = const_27_to_fp16, mode = input_99_mode_0, pad = input_99_pad_0, x = input_97_cast_fp16)[name = tensor<string, []>("input_99_cast_fp16")];
            tensor<string, []> input_101_pad_type_0 = const()[name = tensor<string, []>("input_101_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, []> input_101_groups_0 = const()[name = tensor<string, []>("input_101_groups_0"), val = tensor<int32, []>(1024)];
            tensor<int32, [1]> input_101_strides_0 = const()[name = tensor<string, []>("input_101_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_101_pad_0 = const()[name = tensor<string, []>("input_101_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_101_dilations_0 = const()[name = tensor<string, []>("input_101_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_330_to_fp16 = const()[name = tensor<string, []>("const_330_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(87923136)))];
            tensor<fp16, [1024]> const_331_to_fp16 = const()[name = tensor<string, []>("const_331_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(87941632)))];
            tensor<fp16, [1, 1024, 188]> input_103_cast_fp16 = conv(bias = const_331_to_fp16, dilations = input_101_dilations_0, groups = input_101_groups_0, pad = input_101_pad_0, pad_type = input_101_pad_type_0, strides = input_101_strides_0, weight = const_330_to_fp16, x = input_99_cast_fp16)[name = tensor<string, []>("input_103_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_105_cast_fp16 = silu(x = input_103_cast_fp16)[name = tensor<string, []>("input_105_cast_fp16")];
            tensor<string, []> x_43_pad_type_0 = const()[name = tensor<string, []>("x_43_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> x_43_strides_0 = const()[name = tensor<string, []>("x_43_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_43_pad_0 = const()[name = tensor<string, []>("x_43_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_43_dilations_0 = const()[name = tensor<string, []>("x_43_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> x_43_groups_0 = const()[name = tensor<string, []>("x_43_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1024, 1024, 1]> encoder_layers_1_conv_pointwise_conv2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_1_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(87943744)))];
            tensor<fp16, [1024]> encoder_layers_1_conv_pointwise_conv2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_1_conv_pointwise_conv2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(90040960)))];
            tensor<fp16, [1, 1024, 188]> x_43_cast_fp16 = conv(bias = encoder_layers_1_conv_pointwise_conv2_bias_to_fp16, dilations = x_43_dilations_0, groups = x_43_groups_0, pad = x_43_pad_0, pad_type = x_43_pad_type_0, strides = x_43_strides_0, weight = encoder_layers_1_conv_pointwise_conv2_weight_to_fp16, x = input_105_cast_fp16)[name = tensor<string, []>("x_43_cast_fp16")];
            tensor<int32, [3]> input_107_perm_0 = const()[name = tensor<string, []>("input_107_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_107_cast_fp16 = transpose(perm = input_107_perm_0, x = x_43_cast_fp16)[name = tensor<string, []>("transpose_370")];
            tensor<fp16, [1, 188, 1024]> input_109_cast_fp16 = add(x = input_91_cast_fp16, y = input_107_cast_fp16)[name = tensor<string, []>("input_109_cast_fp16")];
            tensor<int32, [1]> input_111_axes_0 = const()[name = tensor<string, []>("input_111_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_1_norm_feed_forward2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_1_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(90043072)))];
            tensor<fp16, [1024]> encoder_layers_1_norm_feed_forward2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_1_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(90045184)))];
            tensor<fp16, [1, 188, 1024]> input_111_cast_fp16 = layer_norm(axes = input_111_axes_0, beta = encoder_layers_1_norm_feed_forward2_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_1_norm_feed_forward2_weight_to_fp16, x = input_109_cast_fp16)[name = tensor<string, []>("input_111_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_1_feed_forward2_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_1_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(90047296)))];
            tensor<fp16, [4096]> encoder_layers_1_feed_forward2_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_1_feed_forward2_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(98435968)))];
            tensor<fp16, [1, 188, 4096]> linear_17_cast_fp16 = linear(bias = encoder_layers_1_feed_forward2_linear1_bias_to_fp16, weight = encoder_layers_1_feed_forward2_linear1_weight_to_fp16, x = input_111_cast_fp16)[name = tensor<string, []>("linear_17_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_115_cast_fp16 = silu(x = linear_17_cast_fp16)[name = tensor<string, []>("input_115_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_1_feed_forward2_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_1_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(98444224)))];
            tensor<fp16, [1024]> encoder_layers_1_feed_forward2_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_1_feed_forward2_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(106832896)))];
            tensor<fp16, [1, 188, 1024]> linear_18_cast_fp16 = linear(bias = encoder_layers_1_feed_forward2_linear2_bias_to_fp16, weight = encoder_layers_1_feed_forward2_linear2_weight_to_fp16, x = input_115_cast_fp16)[name = tensor<string, []>("linear_18_cast_fp16")];
            tensor<fp16, []> var_567_to_fp16 = const()[name = tensor<string, []>("op_567_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_568_cast_fp16 = mul(x = linear_18_cast_fp16, y = var_567_to_fp16)[name = tensor<string, []>("op_568_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_121_cast_fp16 = add(x = input_109_cast_fp16, y = var_568_cast_fp16)[name = tensor<string, []>("input_121_cast_fp16")];
            tensor<int32, [1]> input_123_axes_0 = const()[name = tensor<string, []>("input_123_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_1_norm_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_1_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(106835008)))];
            tensor<fp16, [1024]> encoder_layers_1_norm_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_1_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(106837120)))];
            tensor<fp16, [1, 188, 1024]> input_123_cast_fp16 = layer_norm(axes = input_123_axes_0, beta = encoder_layers_1_norm_out_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_1_norm_out_weight_to_fp16, x = input_121_cast_fp16)[name = tensor<string, []>("input_123_cast_fp16")];
            tensor<int32, [1]> input_125_axes_0 = const()[name = tensor<string, []>("input_125_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_2_norm_feed_forward1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_2_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(106839232)))];
            tensor<fp16, [1024]> encoder_layers_2_norm_feed_forward1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_2_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(106841344)))];
            tensor<fp16, [1, 188, 1024]> input_125_cast_fp16 = layer_norm(axes = input_125_axes_0, beta = encoder_layers_2_norm_feed_forward1_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_2_norm_feed_forward1_weight_to_fp16, x = input_123_cast_fp16)[name = tensor<string, []>("input_125_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_2_feed_forward1_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_2_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(106843456)))];
            tensor<fp16, [4096]> encoder_layers_2_feed_forward1_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_2_feed_forward1_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(115232128)))];
            tensor<fp16, [1, 188, 4096]> linear_19_cast_fp16 = linear(bias = encoder_layers_2_feed_forward1_linear1_bias_to_fp16, weight = encoder_layers_2_feed_forward1_linear1_weight_to_fp16, x = input_125_cast_fp16)[name = tensor<string, []>("linear_19_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_129_cast_fp16 = silu(x = linear_19_cast_fp16)[name = tensor<string, []>("input_129_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_2_feed_forward1_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_2_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(115240384)))];
            tensor<fp16, [1024]> encoder_layers_2_feed_forward1_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_2_feed_forward1_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(123629056)))];
            tensor<fp16, [1, 188, 1024]> linear_20_cast_fp16 = linear(bias = encoder_layers_2_feed_forward1_linear2_bias_to_fp16, weight = encoder_layers_2_feed_forward1_linear2_weight_to_fp16, x = input_129_cast_fp16)[name = tensor<string, []>("linear_20_cast_fp16")];
            tensor<fp16, []> var_598_to_fp16 = const()[name = tensor<string, []>("op_598_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_599_cast_fp16 = mul(x = linear_20_cast_fp16, y = var_598_to_fp16)[name = tensor<string, []>("op_599_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_135_cast_fp16 = add(x = input_123_cast_fp16, y = var_599_cast_fp16)[name = tensor<string, []>("input_135_cast_fp16")];
            tensor<int32, [1]> query_5_axes_0 = const()[name = tensor<string, []>("query_5_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_2_norm_self_att_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_2_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(123631168)))];
            tensor<fp16, [1024]> encoder_layers_2_norm_self_att_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_2_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(123633280)))];
            tensor<fp16, [1, 188, 1024]> query_5_cast_fp16 = layer_norm(axes = query_5_axes_0, beta = encoder_layers_2_norm_self_att_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_2_norm_self_att_weight_to_fp16, x = input_135_cast_fp16)[name = tensor<string, []>("query_5_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_2_self_attn_linear_q_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_2_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(123635392)))];
            tensor<fp16, [1024]> encoder_layers_2_self_attn_linear_q_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_2_self_attn_linear_q_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(125732608)))];
            tensor<fp16, [1, 188, 1024]> linear_21_cast_fp16 = linear(bias = encoder_layers_2_self_attn_linear_q_bias_to_fp16, weight = encoder_layers_2_self_attn_linear_q_weight_to_fp16, x = query_5_cast_fp16)[name = tensor<string, []>("linear_21_cast_fp16")];
            tensor<int32, [4]> var_616 = const()[name = tensor<string, []>("op_616"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_13_cast_fp16 = reshape(shape = var_616, x = linear_21_cast_fp16)[name = tensor<string, []>("q_13_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_2_self_attn_linear_k_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_2_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(125734720)))];
            tensor<fp16, [1024]> encoder_layers_2_self_attn_linear_k_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_2_self_attn_linear_k_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(127831936)))];
            tensor<fp16, [1, 188, 1024]> linear_22_cast_fp16 = linear(bias = encoder_layers_2_self_attn_linear_k_bias_to_fp16, weight = encoder_layers_2_self_attn_linear_k_weight_to_fp16, x = query_5_cast_fp16)[name = tensor<string, []>("linear_22_cast_fp16")];
            tensor<int32, [4]> var_621 = const()[name = tensor<string, []>("op_621"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_9_cast_fp16 = reshape(shape = var_621, x = linear_22_cast_fp16)[name = tensor<string, []>("k_9_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_2_self_attn_linear_v_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_2_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(127834048)))];
            tensor<fp16, [1024]> encoder_layers_2_self_attn_linear_v_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_2_self_attn_linear_v_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(129931264)))];
            tensor<fp16, [1, 188, 1024]> linear_23_cast_fp16 = linear(bias = encoder_layers_2_self_attn_linear_v_bias_to_fp16, weight = encoder_layers_2_self_attn_linear_v_weight_to_fp16, x = query_5_cast_fp16)[name = tensor<string, []>("linear_23_cast_fp16")];
            tensor<int32, [4]> var_626 = const()[name = tensor<string, []>("op_626"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_5_cast_fp16 = reshape(shape = var_626, x = linear_23_cast_fp16)[name = tensor<string, []>("v_5_cast_fp16")];
            tensor<int32, [4]> value_7_perm_0 = const()[name = tensor<string, []>("value_7_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> encoder_layers_2_self_attn_pos_bias_u_to_fp16 = const()[name = tensor<string, []>("encoder_layers_2_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(129933376)))];
            tensor<fp16, [1, 188, 8, 128]> var_638_cast_fp16 = add(x = q_13_cast_fp16, y = encoder_layers_2_self_attn_pos_bias_u_to_fp16)[name = tensor<string, []>("op_638_cast_fp16")];
            tensor<fp16, [8, 128]> encoder_layers_2_self_attn_pos_bias_v_to_fp16 = const()[name = tensor<string, []>("encoder_layers_2_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(129935488)))];
            tensor<fp16, [1, 188, 8, 128]> var_640_cast_fp16 = add(x = q_13_cast_fp16, y = encoder_layers_2_self_attn_pos_bias_v_to_fp16)[name = tensor<string, []>("op_640_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_5_perm_0 = const()[name = tensor<string, []>("q_with_bias_v_5_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<bool, []> x_51_transpose_x_0 = const()[name = tensor<string, []>("x_51_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_51_transpose_y_0 = const()[name = tensor<string, []>("x_51_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 128, 375]> var_642_to_fp16 = const()[name = tensor<string, []>("op_642_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(129937600)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_5_cast_fp16 = transpose(perm = q_with_bias_v_5_perm_0, x = var_640_cast_fp16)[name = tensor<string, []>("transpose_368")];
            tensor<fp16, [1, 8, 188, 375]> x_51_cast_fp16 = matmul(transpose_x = x_51_transpose_x_0, transpose_y = x_51_transpose_y_0, x = q_with_bias_v_5_cast_fp16, y = var_642_to_fp16)[name = tensor<string, []>("x_51_cast_fp16")];
            tensor<int32, [8]> x_53_pad_0 = const()[name = tensor<string, []>("x_53_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            tensor<string, []> x_53_mode_0 = const()[name = tensor<string, []>("x_53_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_34_to_fp16 = const()[name = tensor<string, []>("const_34_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_53_cast_fp16 = pad(constant_val = const_34_to_fp16, mode = x_53_mode_0, pad = x_53_pad_0, x = x_51_cast_fp16)[name = tensor<string, []>("x_53_cast_fp16")];
            tensor<int32, [4]> var_650 = const()[name = tensor<string, []>("op_650"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_55_cast_fp16 = reshape(shape = var_650, x = x_53_cast_fp16)[name = tensor<string, []>("x_55_cast_fp16")];
            tensor<int32, [4]> var_654_begin_0 = const()[name = tensor<string, []>("op_654_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_654_end_0 = const()[name = tensor<string, []>("op_654_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_654_end_mask_0 = const()[name = tensor<string, []>("op_654_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_654_cast_fp16 = slice_by_index(begin = var_654_begin_0, end = var_654_end_0, end_mask = var_654_end_mask_0, x = x_55_cast_fp16)[name = tensor<string, []>("op_654_cast_fp16")];
            tensor<int32, [4]> var_655 = const()[name = tensor<string, []>("op_655"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_9_cast_fp16 = reshape(shape = var_655, x = var_654_cast_fp16)[name = tensor<string, []>("matrix_bd_9_cast_fp16")];
            tensor<bool, []> matrix_ac_5_transpose_x_0 = const()[name = tensor<string, []>("matrix_ac_5_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> matrix_ac_5_transpose_y_0 = const()[name = tensor<string, []>("matrix_ac_5_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<int32, [4]> transpose_100_perm_0 = const()[name = tensor<string, []>("transpose_100_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_101_perm_0 = const()[name = tensor<string, []>("transpose_101_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_101 = transpose(perm = transpose_101_perm_0, x = k_9_cast_fp16)[name = tensor<string, []>("transpose_366")];
            tensor<fp16, [1, 8, 188, 128]> transpose_100 = transpose(perm = transpose_100_perm_0, x = var_638_cast_fp16)[name = tensor<string, []>("transpose_367")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_5_cast_fp16 = matmul(transpose_x = matrix_ac_5_transpose_x_0, transpose_y = matrix_ac_5_transpose_y_0, x = transpose_100, y = transpose_101)[name = tensor<string, []>("matrix_ac_5_cast_fp16")];
            tensor<int32, [4]> matrix_bd_11_begin_0 = const()[name = tensor<string, []>("matrix_bd_11_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_11_end_0 = const()[name = tensor<string, []>("matrix_bd_11_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_11_end_mask_0 = const()[name = tensor<string, []>("matrix_bd_11_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_11_cast_fp16 = slice_by_index(begin = matrix_bd_11_begin_0, end = matrix_bd_11_end_0, end_mask = matrix_bd_11_end_mask_0, x = matrix_bd_9_cast_fp16)[name = tensor<string, []>("matrix_bd_11_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_664_cast_fp16 = add(x = matrix_ac_5_cast_fp16, y = matrix_bd_11_cast_fp16)[name = tensor<string, []>("op_664_cast_fp16")];
            tensor<fp16, []> _inversed_scores_9_y_0_to_fp16 = const()[name = tensor<string, []>("_inversed_scores_9_y_0_to_fp16"), val = tensor<fp16, []>(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_9_cast_fp16 = mul(x = var_664_cast_fp16, y = _inversed_scores_9_y_0_to_fp16)[name = tensor<string, []>("_inversed_scores_9_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_11_cast_fp16 = select(a = var_12_to_fp16, b = _inversed_scores_9_cast_fp16, cond = mask_3)[name = tensor<string, []>("scores_11_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_670_cast_fp16 = softmax(axis = var_30, x = scores_11_cast_fp16)[name = tensor<string, []>("op_670_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_137_cast_fp16 = select(a = var_11_to_fp16, b = var_670_cast_fp16, cond = mask_3)[name = tensor<string, []>("input_137_cast_fp16")];
            tensor<bool, []> x_57_transpose_x_0 = const()[name = tensor<string, []>("x_57_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_57_transpose_y_0 = const()[name = tensor<string, []>("x_57_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 188, 128]> value_7_cast_fp16 = transpose(perm = value_7_perm_0, x = v_5_cast_fp16)[name = tensor<string, []>("transpose_369")];
            tensor<fp16, [1, 8, 188, 128]> x_57_cast_fp16 = matmul(transpose_x = x_57_transpose_x_0, transpose_y = x_57_transpose_y_0, x = input_137_cast_fp16, y = value_7_cast_fp16)[name = tensor<string, []>("x_57_cast_fp16")];
            tensor<int32, [4]> var_674_perm_0 = const()[name = tensor<string, []>("op_674_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_675 = const()[name = tensor<string, []>("op_675"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_674_cast_fp16 = transpose(perm = var_674_perm_0, x = x_57_cast_fp16)[name = tensor<string, []>("transpose_365")];
            tensor<fp16, [1, 188, 1024]> input_139_cast_fp16 = reshape(shape = var_675, x = var_674_cast_fp16)[name = tensor<string, []>("input_139_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_2_self_attn_linear_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_2_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(130705664)))];
            tensor<fp16, [1024]> encoder_layers_2_self_attn_linear_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_2_self_attn_linear_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(132802880)))];
            tensor<fp16, [1, 188, 1024]> linear_25_cast_fp16 = linear(bias = encoder_layers_2_self_attn_linear_out_bias_to_fp16, weight = encoder_layers_2_self_attn_linear_out_weight_to_fp16, x = input_139_cast_fp16)[name = tensor<string, []>("linear_25_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_143_cast_fp16 = add(x = input_135_cast_fp16, y = linear_25_cast_fp16)[name = tensor<string, []>("input_143_cast_fp16")];
            tensor<int32, [1]> x_61_axes_0 = const()[name = tensor<string, []>("x_61_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_2_norm_conv_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_2_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(132804992)))];
            tensor<fp16, [1024]> encoder_layers_2_norm_conv_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_2_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(132807104)))];
            tensor<fp16, [1, 188, 1024]> x_61_cast_fp16 = layer_norm(axes = x_61_axes_0, beta = encoder_layers_2_norm_conv_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_2_norm_conv_weight_to_fp16, x = input_143_cast_fp16)[name = tensor<string, []>("x_61_cast_fp16")];
            tensor<int32, [3]> input_145_perm_0 = const()[name = tensor<string, []>("input_145_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> input_147_pad_type_0 = const()[name = tensor<string, []>("input_147_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_147_strides_0 = const()[name = tensor<string, []>("input_147_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_147_pad_0 = const()[name = tensor<string, []>("input_147_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_147_dilations_0 = const()[name = tensor<string, []>("input_147_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_147_groups_0 = const()[name = tensor<string, []>("input_147_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [2048, 1024, 1]> encoder_layers_2_conv_pointwise_conv1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_2_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(132809216)))];
            tensor<fp16, [2048]> encoder_layers_2_conv_pointwise_conv1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_2_conv_pointwise_conv1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(137003584)))];
            tensor<fp16, [1, 1024, 188]> input_145_cast_fp16 = transpose(perm = input_145_perm_0, x = x_61_cast_fp16)[name = tensor<string, []>("transpose_364")];
            tensor<fp16, [1, 2048, 188]> input_147_cast_fp16 = conv(bias = encoder_layers_2_conv_pointwise_conv1_bias_to_fp16, dilations = input_147_dilations_0, groups = input_147_groups_0, pad = input_147_pad_0, pad_type = input_147_pad_type_0, strides = input_147_strides_0, weight = encoder_layers_2_conv_pointwise_conv1_weight_to_fp16, x = input_145_cast_fp16)[name = tensor<string, []>("input_147_cast_fp16")];
            tensor<int32, []> x_63_split_num_splits_0 = const()[name = tensor<string, []>("x_63_split_num_splits_0"), val = tensor<int32, []>(2)];
            tensor<int32, []> x_63_split_axis_0 = const()[name = tensor<string, []>("x_63_split_axis_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1, 1024, 188]> x_63_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_63_split_cast_fp16_1 = split(axis = x_63_split_axis_0, num_splits = x_63_split_num_splits_0, x = input_147_cast_fp16)[name = tensor<string, []>("x_63_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_63_split_1_sigmoid_cast_fp16 = sigmoid(x = x_63_split_cast_fp16_1)[name = tensor<string, []>("x_63_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_63_cast_fp16 = mul(x = x_63_split_cast_fp16_0, y = x_63_split_1_sigmoid_cast_fp16)[name = tensor<string, []>("x_63_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_149_cast_fp16 = select(a = var_11_to_fp16, b = x_63_cast_fp16, cond = var_351)[name = tensor<string, []>("input_149_cast_fp16")];
            tensor<int32, [6]> input_151_pad_0 = const()[name = tensor<string, []>("input_151_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            tensor<string, []> input_151_mode_0 = const()[name = tensor<string, []>("input_151_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_37_to_fp16 = const()[name = tensor<string, []>("const_37_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_151_cast_fp16 = pad(constant_val = const_37_to_fp16, mode = input_151_mode_0, pad = input_151_pad_0, x = input_149_cast_fp16)[name = tensor<string, []>("input_151_cast_fp16")];
            tensor<string, []> input_153_pad_type_0 = const()[name = tensor<string, []>("input_153_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, []> input_153_groups_0 = const()[name = tensor<string, []>("input_153_groups_0"), val = tensor<int32, []>(1024)];
            tensor<int32, [1]> input_153_strides_0 = const()[name = tensor<string, []>("input_153_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_153_pad_0 = const()[name = tensor<string, []>("input_153_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_153_dilations_0 = const()[name = tensor<string, []>("input_153_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_332_to_fp16 = const()[name = tensor<string, []>("const_332_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(137007744)))];
            tensor<fp16, [1024]> const_333_to_fp16 = const()[name = tensor<string, []>("const_333_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(137026240)))];
            tensor<fp16, [1, 1024, 188]> input_155_cast_fp16 = conv(bias = const_333_to_fp16, dilations = input_153_dilations_0, groups = input_153_groups_0, pad = input_153_pad_0, pad_type = input_153_pad_type_0, strides = input_153_strides_0, weight = const_332_to_fp16, x = input_151_cast_fp16)[name = tensor<string, []>("input_155_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_157_cast_fp16 = silu(x = input_155_cast_fp16)[name = tensor<string, []>("input_157_cast_fp16")];
            tensor<string, []> x_65_pad_type_0 = const()[name = tensor<string, []>("x_65_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> x_65_strides_0 = const()[name = tensor<string, []>("x_65_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_65_pad_0 = const()[name = tensor<string, []>("x_65_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_65_dilations_0 = const()[name = tensor<string, []>("x_65_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> x_65_groups_0 = const()[name = tensor<string, []>("x_65_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1024, 1024, 1]> encoder_layers_2_conv_pointwise_conv2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_2_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(137028352)))];
            tensor<fp16, [1024]> encoder_layers_2_conv_pointwise_conv2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_2_conv_pointwise_conv2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(139125568)))];
            tensor<fp16, [1, 1024, 188]> x_65_cast_fp16 = conv(bias = encoder_layers_2_conv_pointwise_conv2_bias_to_fp16, dilations = x_65_dilations_0, groups = x_65_groups_0, pad = x_65_pad_0, pad_type = x_65_pad_type_0, strides = x_65_strides_0, weight = encoder_layers_2_conv_pointwise_conv2_weight_to_fp16, x = input_157_cast_fp16)[name = tensor<string, []>("x_65_cast_fp16")];
            tensor<int32, [3]> input_159_perm_0 = const()[name = tensor<string, []>("input_159_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_159_cast_fp16 = transpose(perm = input_159_perm_0, x = x_65_cast_fp16)[name = tensor<string, []>("transpose_363")];
            tensor<fp16, [1, 188, 1024]> input_161_cast_fp16 = add(x = input_143_cast_fp16, y = input_159_cast_fp16)[name = tensor<string, []>("input_161_cast_fp16")];
            tensor<int32, [1]> input_163_axes_0 = const()[name = tensor<string, []>("input_163_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_2_norm_feed_forward2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_2_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(139127680)))];
            tensor<fp16, [1024]> encoder_layers_2_norm_feed_forward2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_2_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(139129792)))];
            tensor<fp16, [1, 188, 1024]> input_163_cast_fp16 = layer_norm(axes = input_163_axes_0, beta = encoder_layers_2_norm_feed_forward2_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_2_norm_feed_forward2_weight_to_fp16, x = input_161_cast_fp16)[name = tensor<string, []>("input_163_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_2_feed_forward2_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_2_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(139131904)))];
            tensor<fp16, [4096]> encoder_layers_2_feed_forward2_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_2_feed_forward2_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(147520576)))];
            tensor<fp16, [1, 188, 4096]> linear_26_cast_fp16 = linear(bias = encoder_layers_2_feed_forward2_linear1_bias_to_fp16, weight = encoder_layers_2_feed_forward2_linear1_weight_to_fp16, x = input_163_cast_fp16)[name = tensor<string, []>("linear_26_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_167_cast_fp16 = silu(x = linear_26_cast_fp16)[name = tensor<string, []>("input_167_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_2_feed_forward2_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_2_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(147528832)))];
            tensor<fp16, [1024]> encoder_layers_2_feed_forward2_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_2_feed_forward2_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(155917504)))];
            tensor<fp16, [1, 188, 1024]> linear_27_cast_fp16 = linear(bias = encoder_layers_2_feed_forward2_linear2_bias_to_fp16, weight = encoder_layers_2_feed_forward2_linear2_weight_to_fp16, x = input_167_cast_fp16)[name = tensor<string, []>("linear_27_cast_fp16")];
            tensor<fp16, []> var_741_to_fp16 = const()[name = tensor<string, []>("op_741_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_742_cast_fp16 = mul(x = linear_27_cast_fp16, y = var_741_to_fp16)[name = tensor<string, []>("op_742_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_173_cast_fp16 = add(x = input_161_cast_fp16, y = var_742_cast_fp16)[name = tensor<string, []>("input_173_cast_fp16")];
            tensor<int32, [1]> input_175_axes_0 = const()[name = tensor<string, []>("input_175_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_2_norm_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_2_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(155919616)))];
            tensor<fp16, [1024]> encoder_layers_2_norm_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_2_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(155921728)))];
            tensor<fp16, [1, 188, 1024]> input_175_cast_fp16 = layer_norm(axes = input_175_axes_0, beta = encoder_layers_2_norm_out_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_2_norm_out_weight_to_fp16, x = input_173_cast_fp16)[name = tensor<string, []>("input_175_cast_fp16")];
            tensor<int32, [1]> input_177_axes_0 = const()[name = tensor<string, []>("input_177_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_3_norm_feed_forward1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_3_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(155923840)))];
            tensor<fp16, [1024]> encoder_layers_3_norm_feed_forward1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_3_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(155925952)))];
            tensor<fp16, [1, 188, 1024]> input_177_cast_fp16 = layer_norm(axes = input_177_axes_0, beta = encoder_layers_3_norm_feed_forward1_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_3_norm_feed_forward1_weight_to_fp16, x = input_175_cast_fp16)[name = tensor<string, []>("input_177_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_3_feed_forward1_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_3_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(155928064)))];
            tensor<fp16, [4096]> encoder_layers_3_feed_forward1_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_3_feed_forward1_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(164316736)))];
            tensor<fp16, [1, 188, 4096]> linear_28_cast_fp16 = linear(bias = encoder_layers_3_feed_forward1_linear1_bias_to_fp16, weight = encoder_layers_3_feed_forward1_linear1_weight_to_fp16, x = input_177_cast_fp16)[name = tensor<string, []>("linear_28_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_181_cast_fp16 = silu(x = linear_28_cast_fp16)[name = tensor<string, []>("input_181_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_3_feed_forward1_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_3_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(164324992)))];
            tensor<fp16, [1024]> encoder_layers_3_feed_forward1_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_3_feed_forward1_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(172713664)))];
            tensor<fp16, [1, 188, 1024]> linear_29_cast_fp16 = linear(bias = encoder_layers_3_feed_forward1_linear2_bias_to_fp16, weight = encoder_layers_3_feed_forward1_linear2_weight_to_fp16, x = input_181_cast_fp16)[name = tensor<string, []>("linear_29_cast_fp16")];
            tensor<fp16, []> var_772_to_fp16 = const()[name = tensor<string, []>("op_772_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_773_cast_fp16 = mul(x = linear_29_cast_fp16, y = var_772_to_fp16)[name = tensor<string, []>("op_773_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_187_cast_fp16 = add(x = input_175_cast_fp16, y = var_773_cast_fp16)[name = tensor<string, []>("input_187_cast_fp16")];
            tensor<int32, [1]> query_7_axes_0 = const()[name = tensor<string, []>("query_7_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_3_norm_self_att_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_3_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(172715776)))];
            tensor<fp16, [1024]> encoder_layers_3_norm_self_att_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_3_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(172717888)))];
            tensor<fp16, [1, 188, 1024]> query_7_cast_fp16 = layer_norm(axes = query_7_axes_0, beta = encoder_layers_3_norm_self_att_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_3_norm_self_att_weight_to_fp16, x = input_187_cast_fp16)[name = tensor<string, []>("query_7_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_3_self_attn_linear_q_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_3_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(172720000)))];
            tensor<fp16, [1024]> encoder_layers_3_self_attn_linear_q_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_3_self_attn_linear_q_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(174817216)))];
            tensor<fp16, [1, 188, 1024]> linear_30_cast_fp16 = linear(bias = encoder_layers_3_self_attn_linear_q_bias_to_fp16, weight = encoder_layers_3_self_attn_linear_q_weight_to_fp16, x = query_7_cast_fp16)[name = tensor<string, []>("linear_30_cast_fp16")];
            tensor<int32, [4]> var_790 = const()[name = tensor<string, []>("op_790"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_19_cast_fp16 = reshape(shape = var_790, x = linear_30_cast_fp16)[name = tensor<string, []>("q_19_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_3_self_attn_linear_k_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_3_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(174819328)))];
            tensor<fp16, [1024]> encoder_layers_3_self_attn_linear_k_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_3_self_attn_linear_k_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(176916544)))];
            tensor<fp16, [1, 188, 1024]> linear_31_cast_fp16 = linear(bias = encoder_layers_3_self_attn_linear_k_bias_to_fp16, weight = encoder_layers_3_self_attn_linear_k_weight_to_fp16, x = query_7_cast_fp16)[name = tensor<string, []>("linear_31_cast_fp16")];
            tensor<int32, [4]> var_795 = const()[name = tensor<string, []>("op_795"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_13_cast_fp16 = reshape(shape = var_795, x = linear_31_cast_fp16)[name = tensor<string, []>("k_13_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_3_self_attn_linear_v_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_3_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(176918656)))];
            tensor<fp16, [1024]> encoder_layers_3_self_attn_linear_v_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_3_self_attn_linear_v_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(179015872)))];
            tensor<fp16, [1, 188, 1024]> linear_32_cast_fp16 = linear(bias = encoder_layers_3_self_attn_linear_v_bias_to_fp16, weight = encoder_layers_3_self_attn_linear_v_weight_to_fp16, x = query_7_cast_fp16)[name = tensor<string, []>("linear_32_cast_fp16")];
            tensor<int32, [4]> var_800 = const()[name = tensor<string, []>("op_800"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_7_cast_fp16 = reshape(shape = var_800, x = linear_32_cast_fp16)[name = tensor<string, []>("v_7_cast_fp16")];
            tensor<int32, [4]> value_9_perm_0 = const()[name = tensor<string, []>("value_9_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> encoder_layers_3_self_attn_pos_bias_u_to_fp16 = const()[name = tensor<string, []>("encoder_layers_3_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(179017984)))];
            tensor<fp16, [1, 188, 8, 128]> var_812_cast_fp16 = add(x = q_19_cast_fp16, y = encoder_layers_3_self_attn_pos_bias_u_to_fp16)[name = tensor<string, []>("op_812_cast_fp16")];
            tensor<fp16, [8, 128]> encoder_layers_3_self_attn_pos_bias_v_to_fp16 = const()[name = tensor<string, []>("encoder_layers_3_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(179020096)))];
            tensor<fp16, [1, 188, 8, 128]> var_814_cast_fp16 = add(x = q_19_cast_fp16, y = encoder_layers_3_self_attn_pos_bias_v_to_fp16)[name = tensor<string, []>("op_814_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_7_perm_0 = const()[name = tensor<string, []>("q_with_bias_v_7_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<bool, []> x_73_transpose_x_0 = const()[name = tensor<string, []>("x_73_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_73_transpose_y_0 = const()[name = tensor<string, []>("x_73_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 128, 375]> var_816_to_fp16 = const()[name = tensor<string, []>("op_816_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(179022208)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_7_cast_fp16 = transpose(perm = q_with_bias_v_7_perm_0, x = var_814_cast_fp16)[name = tensor<string, []>("transpose_361")];
            tensor<fp16, [1, 8, 188, 375]> x_73_cast_fp16 = matmul(transpose_x = x_73_transpose_x_0, transpose_y = x_73_transpose_y_0, x = q_with_bias_v_7_cast_fp16, y = var_816_to_fp16)[name = tensor<string, []>("x_73_cast_fp16")];
            tensor<int32, [8]> x_75_pad_0 = const()[name = tensor<string, []>("x_75_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            tensor<string, []> x_75_mode_0 = const()[name = tensor<string, []>("x_75_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_44_to_fp16 = const()[name = tensor<string, []>("const_44_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_75_cast_fp16 = pad(constant_val = const_44_to_fp16, mode = x_75_mode_0, pad = x_75_pad_0, x = x_73_cast_fp16)[name = tensor<string, []>("x_75_cast_fp16")];
            tensor<int32, [4]> var_824 = const()[name = tensor<string, []>("op_824"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_77_cast_fp16 = reshape(shape = var_824, x = x_75_cast_fp16)[name = tensor<string, []>("x_77_cast_fp16")];
            tensor<int32, [4]> var_828_begin_0 = const()[name = tensor<string, []>("op_828_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_828_end_0 = const()[name = tensor<string, []>("op_828_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_828_end_mask_0 = const()[name = tensor<string, []>("op_828_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_828_cast_fp16 = slice_by_index(begin = var_828_begin_0, end = var_828_end_0, end_mask = var_828_end_mask_0, x = x_77_cast_fp16)[name = tensor<string, []>("op_828_cast_fp16")];
            tensor<int32, [4]> var_829 = const()[name = tensor<string, []>("op_829"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_13_cast_fp16 = reshape(shape = var_829, x = var_828_cast_fp16)[name = tensor<string, []>("matrix_bd_13_cast_fp16")];
            tensor<bool, []> matrix_ac_7_transpose_x_0 = const()[name = tensor<string, []>("matrix_ac_7_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> matrix_ac_7_transpose_y_0 = const()[name = tensor<string, []>("matrix_ac_7_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<int32, [4]> transpose_102_perm_0 = const()[name = tensor<string, []>("transpose_102_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_103_perm_0 = const()[name = tensor<string, []>("transpose_103_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_103 = transpose(perm = transpose_103_perm_0, x = k_13_cast_fp16)[name = tensor<string, []>("transpose_359")];
            tensor<fp16, [1, 8, 188, 128]> transpose_102 = transpose(perm = transpose_102_perm_0, x = var_812_cast_fp16)[name = tensor<string, []>("transpose_360")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_7_cast_fp16 = matmul(transpose_x = matrix_ac_7_transpose_x_0, transpose_y = matrix_ac_7_transpose_y_0, x = transpose_102, y = transpose_103)[name = tensor<string, []>("matrix_ac_7_cast_fp16")];
            tensor<int32, [4]> matrix_bd_15_begin_0 = const()[name = tensor<string, []>("matrix_bd_15_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_15_end_0 = const()[name = tensor<string, []>("matrix_bd_15_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_15_end_mask_0 = const()[name = tensor<string, []>("matrix_bd_15_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_15_cast_fp16 = slice_by_index(begin = matrix_bd_15_begin_0, end = matrix_bd_15_end_0, end_mask = matrix_bd_15_end_mask_0, x = matrix_bd_13_cast_fp16)[name = tensor<string, []>("matrix_bd_15_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_838_cast_fp16 = add(x = matrix_ac_7_cast_fp16, y = matrix_bd_15_cast_fp16)[name = tensor<string, []>("op_838_cast_fp16")];
            tensor<fp16, []> _inversed_scores_13_y_0_to_fp16 = const()[name = tensor<string, []>("_inversed_scores_13_y_0_to_fp16"), val = tensor<fp16, []>(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_13_cast_fp16 = mul(x = var_838_cast_fp16, y = _inversed_scores_13_y_0_to_fp16)[name = tensor<string, []>("_inversed_scores_13_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_15_cast_fp16 = select(a = var_12_to_fp16, b = _inversed_scores_13_cast_fp16, cond = mask_3)[name = tensor<string, []>("scores_15_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_844_cast_fp16 = softmax(axis = var_30, x = scores_15_cast_fp16)[name = tensor<string, []>("op_844_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_189_cast_fp16 = select(a = var_11_to_fp16, b = var_844_cast_fp16, cond = mask_3)[name = tensor<string, []>("input_189_cast_fp16")];
            tensor<bool, []> x_79_transpose_x_0 = const()[name = tensor<string, []>("x_79_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_79_transpose_y_0 = const()[name = tensor<string, []>("x_79_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 188, 128]> value_9_cast_fp16 = transpose(perm = value_9_perm_0, x = v_7_cast_fp16)[name = tensor<string, []>("transpose_362")];
            tensor<fp16, [1, 8, 188, 128]> x_79_cast_fp16 = matmul(transpose_x = x_79_transpose_x_0, transpose_y = x_79_transpose_y_0, x = input_189_cast_fp16, y = value_9_cast_fp16)[name = tensor<string, []>("x_79_cast_fp16")];
            tensor<int32, [4]> var_848_perm_0 = const()[name = tensor<string, []>("op_848_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_849 = const()[name = tensor<string, []>("op_849"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_848_cast_fp16 = transpose(perm = var_848_perm_0, x = x_79_cast_fp16)[name = tensor<string, []>("transpose_358")];
            tensor<fp16, [1, 188, 1024]> input_191_cast_fp16 = reshape(shape = var_849, x = var_848_cast_fp16)[name = tensor<string, []>("input_191_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_3_self_attn_linear_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_3_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(179790272)))];
            tensor<fp16, [1024]> encoder_layers_3_self_attn_linear_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_3_self_attn_linear_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(181887488)))];
            tensor<fp16, [1, 188, 1024]> linear_34_cast_fp16 = linear(bias = encoder_layers_3_self_attn_linear_out_bias_to_fp16, weight = encoder_layers_3_self_attn_linear_out_weight_to_fp16, x = input_191_cast_fp16)[name = tensor<string, []>("linear_34_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_195_cast_fp16 = add(x = input_187_cast_fp16, y = linear_34_cast_fp16)[name = tensor<string, []>("input_195_cast_fp16")];
            tensor<int32, [1]> x_83_axes_0 = const()[name = tensor<string, []>("x_83_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_3_norm_conv_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_3_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(181889600)))];
            tensor<fp16, [1024]> encoder_layers_3_norm_conv_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_3_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(181891712)))];
            tensor<fp16, [1, 188, 1024]> x_83_cast_fp16 = layer_norm(axes = x_83_axes_0, beta = encoder_layers_3_norm_conv_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_3_norm_conv_weight_to_fp16, x = input_195_cast_fp16)[name = tensor<string, []>("x_83_cast_fp16")];
            tensor<int32, [3]> input_197_perm_0 = const()[name = tensor<string, []>("input_197_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> input_199_pad_type_0 = const()[name = tensor<string, []>("input_199_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_199_strides_0 = const()[name = tensor<string, []>("input_199_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_199_pad_0 = const()[name = tensor<string, []>("input_199_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_199_dilations_0 = const()[name = tensor<string, []>("input_199_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_199_groups_0 = const()[name = tensor<string, []>("input_199_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [2048, 1024, 1]> encoder_layers_3_conv_pointwise_conv1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_3_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(181893824)))];
            tensor<fp16, [2048]> encoder_layers_3_conv_pointwise_conv1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_3_conv_pointwise_conv1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(186088192)))];
            tensor<fp16, [1, 1024, 188]> input_197_cast_fp16 = transpose(perm = input_197_perm_0, x = x_83_cast_fp16)[name = tensor<string, []>("transpose_357")];
            tensor<fp16, [1, 2048, 188]> input_199_cast_fp16 = conv(bias = encoder_layers_3_conv_pointwise_conv1_bias_to_fp16, dilations = input_199_dilations_0, groups = input_199_groups_0, pad = input_199_pad_0, pad_type = input_199_pad_type_0, strides = input_199_strides_0, weight = encoder_layers_3_conv_pointwise_conv1_weight_to_fp16, x = input_197_cast_fp16)[name = tensor<string, []>("input_199_cast_fp16")];
            tensor<int32, []> x_85_split_num_splits_0 = const()[name = tensor<string, []>("x_85_split_num_splits_0"), val = tensor<int32, []>(2)];
            tensor<int32, []> x_85_split_axis_0 = const()[name = tensor<string, []>("x_85_split_axis_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1, 1024, 188]> x_85_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_85_split_cast_fp16_1 = split(axis = x_85_split_axis_0, num_splits = x_85_split_num_splits_0, x = input_199_cast_fp16)[name = tensor<string, []>("x_85_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_85_split_1_sigmoid_cast_fp16 = sigmoid(x = x_85_split_cast_fp16_1)[name = tensor<string, []>("x_85_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_85_cast_fp16 = mul(x = x_85_split_cast_fp16_0, y = x_85_split_1_sigmoid_cast_fp16)[name = tensor<string, []>("x_85_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_201_cast_fp16 = select(a = var_11_to_fp16, b = x_85_cast_fp16, cond = var_351)[name = tensor<string, []>("input_201_cast_fp16")];
            tensor<int32, [6]> input_203_pad_0 = const()[name = tensor<string, []>("input_203_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            tensor<string, []> input_203_mode_0 = const()[name = tensor<string, []>("input_203_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_47_to_fp16 = const()[name = tensor<string, []>("const_47_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_203_cast_fp16 = pad(constant_val = const_47_to_fp16, mode = input_203_mode_0, pad = input_203_pad_0, x = input_201_cast_fp16)[name = tensor<string, []>("input_203_cast_fp16")];
            tensor<string, []> input_205_pad_type_0 = const()[name = tensor<string, []>("input_205_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, []> input_205_groups_0 = const()[name = tensor<string, []>("input_205_groups_0"), val = tensor<int32, []>(1024)];
            tensor<int32, [1]> input_205_strides_0 = const()[name = tensor<string, []>("input_205_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_205_pad_0 = const()[name = tensor<string, []>("input_205_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_205_dilations_0 = const()[name = tensor<string, []>("input_205_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_334_to_fp16 = const()[name = tensor<string, []>("const_334_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(186092352)))];
            tensor<fp16, [1024]> const_335_to_fp16 = const()[name = tensor<string, []>("const_335_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(186110848)))];
            tensor<fp16, [1, 1024, 188]> input_207_cast_fp16 = conv(bias = const_335_to_fp16, dilations = input_205_dilations_0, groups = input_205_groups_0, pad = input_205_pad_0, pad_type = input_205_pad_type_0, strides = input_205_strides_0, weight = const_334_to_fp16, x = input_203_cast_fp16)[name = tensor<string, []>("input_207_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_209_cast_fp16 = silu(x = input_207_cast_fp16)[name = tensor<string, []>("input_209_cast_fp16")];
            tensor<string, []> x_87_pad_type_0 = const()[name = tensor<string, []>("x_87_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> x_87_strides_0 = const()[name = tensor<string, []>("x_87_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_87_pad_0 = const()[name = tensor<string, []>("x_87_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_87_dilations_0 = const()[name = tensor<string, []>("x_87_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> x_87_groups_0 = const()[name = tensor<string, []>("x_87_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1024, 1024, 1]> encoder_layers_3_conv_pointwise_conv2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_3_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(186112960)))];
            tensor<fp16, [1024]> encoder_layers_3_conv_pointwise_conv2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_3_conv_pointwise_conv2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(188210176)))];
            tensor<fp16, [1, 1024, 188]> x_87_cast_fp16 = conv(bias = encoder_layers_3_conv_pointwise_conv2_bias_to_fp16, dilations = x_87_dilations_0, groups = x_87_groups_0, pad = x_87_pad_0, pad_type = x_87_pad_type_0, strides = x_87_strides_0, weight = encoder_layers_3_conv_pointwise_conv2_weight_to_fp16, x = input_209_cast_fp16)[name = tensor<string, []>("x_87_cast_fp16")];
            tensor<int32, [3]> input_211_perm_0 = const()[name = tensor<string, []>("input_211_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_211_cast_fp16 = transpose(perm = input_211_perm_0, x = x_87_cast_fp16)[name = tensor<string, []>("transpose_356")];
            tensor<fp16, [1, 188, 1024]> input_213_cast_fp16 = add(x = input_195_cast_fp16, y = input_211_cast_fp16)[name = tensor<string, []>("input_213_cast_fp16")];
            tensor<int32, [1]> input_215_axes_0 = const()[name = tensor<string, []>("input_215_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_3_norm_feed_forward2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_3_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(188212288)))];
            tensor<fp16, [1024]> encoder_layers_3_norm_feed_forward2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_3_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(188214400)))];
            tensor<fp16, [1, 188, 1024]> input_215_cast_fp16 = layer_norm(axes = input_215_axes_0, beta = encoder_layers_3_norm_feed_forward2_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_3_norm_feed_forward2_weight_to_fp16, x = input_213_cast_fp16)[name = tensor<string, []>("input_215_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_3_feed_forward2_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_3_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(188216512)))];
            tensor<fp16, [4096]> encoder_layers_3_feed_forward2_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_3_feed_forward2_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(196605184)))];
            tensor<fp16, [1, 188, 4096]> linear_35_cast_fp16 = linear(bias = encoder_layers_3_feed_forward2_linear1_bias_to_fp16, weight = encoder_layers_3_feed_forward2_linear1_weight_to_fp16, x = input_215_cast_fp16)[name = tensor<string, []>("linear_35_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_219_cast_fp16 = silu(x = linear_35_cast_fp16)[name = tensor<string, []>("input_219_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_3_feed_forward2_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_3_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(196613440)))];
            tensor<fp16, [1024]> encoder_layers_3_feed_forward2_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_3_feed_forward2_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(205002112)))];
            tensor<fp16, [1, 188, 1024]> linear_36_cast_fp16 = linear(bias = encoder_layers_3_feed_forward2_linear2_bias_to_fp16, weight = encoder_layers_3_feed_forward2_linear2_weight_to_fp16, x = input_219_cast_fp16)[name = tensor<string, []>("linear_36_cast_fp16")];
            tensor<fp16, []> var_915_to_fp16 = const()[name = tensor<string, []>("op_915_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_916_cast_fp16 = mul(x = linear_36_cast_fp16, y = var_915_to_fp16)[name = tensor<string, []>("op_916_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_225_cast_fp16 = add(x = input_213_cast_fp16, y = var_916_cast_fp16)[name = tensor<string, []>("input_225_cast_fp16")];
            tensor<int32, [1]> input_227_axes_0 = const()[name = tensor<string, []>("input_227_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_3_norm_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_3_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(205004224)))];
            tensor<fp16, [1024]> encoder_layers_3_norm_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_3_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(205006336)))];
            tensor<fp16, [1, 188, 1024]> input_227_cast_fp16 = layer_norm(axes = input_227_axes_0, beta = encoder_layers_3_norm_out_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_3_norm_out_weight_to_fp16, x = input_225_cast_fp16)[name = tensor<string, []>("input_227_cast_fp16")];
            tensor<int32, [1]> input_229_axes_0 = const()[name = tensor<string, []>("input_229_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_4_norm_feed_forward1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_4_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(205008448)))];
            tensor<fp16, [1024]> encoder_layers_4_norm_feed_forward1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_4_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(205010560)))];
            tensor<fp16, [1, 188, 1024]> input_229_cast_fp16 = layer_norm(axes = input_229_axes_0, beta = encoder_layers_4_norm_feed_forward1_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_4_norm_feed_forward1_weight_to_fp16, x = input_227_cast_fp16)[name = tensor<string, []>("input_229_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_4_feed_forward1_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_4_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(205012672)))];
            tensor<fp16, [4096]> encoder_layers_4_feed_forward1_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_4_feed_forward1_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(213401344)))];
            tensor<fp16, [1, 188, 4096]> linear_37_cast_fp16 = linear(bias = encoder_layers_4_feed_forward1_linear1_bias_to_fp16, weight = encoder_layers_4_feed_forward1_linear1_weight_to_fp16, x = input_229_cast_fp16)[name = tensor<string, []>("linear_37_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_233_cast_fp16 = silu(x = linear_37_cast_fp16)[name = tensor<string, []>("input_233_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_4_feed_forward1_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_4_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(213409600)))];
            tensor<fp16, [1024]> encoder_layers_4_feed_forward1_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_4_feed_forward1_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(221798272)))];
            tensor<fp16, [1, 188, 1024]> linear_38_cast_fp16 = linear(bias = encoder_layers_4_feed_forward1_linear2_bias_to_fp16, weight = encoder_layers_4_feed_forward1_linear2_weight_to_fp16, x = input_233_cast_fp16)[name = tensor<string, []>("linear_38_cast_fp16")];
            tensor<fp16, []> var_946_to_fp16 = const()[name = tensor<string, []>("op_946_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_947_cast_fp16 = mul(x = linear_38_cast_fp16, y = var_946_to_fp16)[name = tensor<string, []>("op_947_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_239_cast_fp16 = add(x = input_227_cast_fp16, y = var_947_cast_fp16)[name = tensor<string, []>("input_239_cast_fp16")];
            tensor<int32, [1]> query_9_axes_0 = const()[name = tensor<string, []>("query_9_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_4_norm_self_att_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_4_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(221800384)))];
            tensor<fp16, [1024]> encoder_layers_4_norm_self_att_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_4_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(221802496)))];
            tensor<fp16, [1, 188, 1024]> query_9_cast_fp16 = layer_norm(axes = query_9_axes_0, beta = encoder_layers_4_norm_self_att_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_4_norm_self_att_weight_to_fp16, x = input_239_cast_fp16)[name = tensor<string, []>("query_9_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_4_self_attn_linear_q_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_4_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(221804608)))];
            tensor<fp16, [1024]> encoder_layers_4_self_attn_linear_q_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_4_self_attn_linear_q_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(223901824)))];
            tensor<fp16, [1, 188, 1024]> linear_39_cast_fp16 = linear(bias = encoder_layers_4_self_attn_linear_q_bias_to_fp16, weight = encoder_layers_4_self_attn_linear_q_weight_to_fp16, x = query_9_cast_fp16)[name = tensor<string, []>("linear_39_cast_fp16")];
            tensor<int32, [4]> var_964 = const()[name = tensor<string, []>("op_964"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_25_cast_fp16 = reshape(shape = var_964, x = linear_39_cast_fp16)[name = tensor<string, []>("q_25_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_4_self_attn_linear_k_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_4_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(223903936)))];
            tensor<fp16, [1024]> encoder_layers_4_self_attn_linear_k_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_4_self_attn_linear_k_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(226001152)))];
            tensor<fp16, [1, 188, 1024]> linear_40_cast_fp16 = linear(bias = encoder_layers_4_self_attn_linear_k_bias_to_fp16, weight = encoder_layers_4_self_attn_linear_k_weight_to_fp16, x = query_9_cast_fp16)[name = tensor<string, []>("linear_40_cast_fp16")];
            tensor<int32, [4]> var_969 = const()[name = tensor<string, []>("op_969"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_17_cast_fp16 = reshape(shape = var_969, x = linear_40_cast_fp16)[name = tensor<string, []>("k_17_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_4_self_attn_linear_v_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_4_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(226003264)))];
            tensor<fp16, [1024]> encoder_layers_4_self_attn_linear_v_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_4_self_attn_linear_v_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(228100480)))];
            tensor<fp16, [1, 188, 1024]> linear_41_cast_fp16 = linear(bias = encoder_layers_4_self_attn_linear_v_bias_to_fp16, weight = encoder_layers_4_self_attn_linear_v_weight_to_fp16, x = query_9_cast_fp16)[name = tensor<string, []>("linear_41_cast_fp16")];
            tensor<int32, [4]> var_974 = const()[name = tensor<string, []>("op_974"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_9_cast_fp16 = reshape(shape = var_974, x = linear_41_cast_fp16)[name = tensor<string, []>("v_9_cast_fp16")];
            tensor<int32, [4]> value_11_perm_0 = const()[name = tensor<string, []>("value_11_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> encoder_layers_4_self_attn_pos_bias_u_to_fp16 = const()[name = tensor<string, []>("encoder_layers_4_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(228102592)))];
            tensor<fp16, [1, 188, 8, 128]> var_986_cast_fp16 = add(x = q_25_cast_fp16, y = encoder_layers_4_self_attn_pos_bias_u_to_fp16)[name = tensor<string, []>("op_986_cast_fp16")];
            tensor<fp16, [8, 128]> encoder_layers_4_self_attn_pos_bias_v_to_fp16 = const()[name = tensor<string, []>("encoder_layers_4_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(228104704)))];
            tensor<fp16, [1, 188, 8, 128]> var_988_cast_fp16 = add(x = q_25_cast_fp16, y = encoder_layers_4_self_attn_pos_bias_v_to_fp16)[name = tensor<string, []>("op_988_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_9_perm_0 = const()[name = tensor<string, []>("q_with_bias_v_9_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<bool, []> x_95_transpose_x_0 = const()[name = tensor<string, []>("x_95_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_95_transpose_y_0 = const()[name = tensor<string, []>("x_95_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 128, 375]> var_990_to_fp16 = const()[name = tensor<string, []>("op_990_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(228106816)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_9_cast_fp16 = transpose(perm = q_with_bias_v_9_perm_0, x = var_988_cast_fp16)[name = tensor<string, []>("transpose_354")];
            tensor<fp16, [1, 8, 188, 375]> x_95_cast_fp16 = matmul(transpose_x = x_95_transpose_x_0, transpose_y = x_95_transpose_y_0, x = q_with_bias_v_9_cast_fp16, y = var_990_to_fp16)[name = tensor<string, []>("x_95_cast_fp16")];
            tensor<int32, [8]> x_97_pad_0 = const()[name = tensor<string, []>("x_97_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            tensor<string, []> x_97_mode_0 = const()[name = tensor<string, []>("x_97_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_54_to_fp16 = const()[name = tensor<string, []>("const_54_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_97_cast_fp16 = pad(constant_val = const_54_to_fp16, mode = x_97_mode_0, pad = x_97_pad_0, x = x_95_cast_fp16)[name = tensor<string, []>("x_97_cast_fp16")];
            tensor<int32, [4]> var_998 = const()[name = tensor<string, []>("op_998"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_99_cast_fp16 = reshape(shape = var_998, x = x_97_cast_fp16)[name = tensor<string, []>("x_99_cast_fp16")];
            tensor<int32, [4]> var_1002_begin_0 = const()[name = tensor<string, []>("op_1002_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_1002_end_0 = const()[name = tensor<string, []>("op_1002_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_1002_end_mask_0 = const()[name = tensor<string, []>("op_1002_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_1002_cast_fp16 = slice_by_index(begin = var_1002_begin_0, end = var_1002_end_0, end_mask = var_1002_end_mask_0, x = x_99_cast_fp16)[name = tensor<string, []>("op_1002_cast_fp16")];
            tensor<int32, [4]> var_1003 = const()[name = tensor<string, []>("op_1003"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_17_cast_fp16 = reshape(shape = var_1003, x = var_1002_cast_fp16)[name = tensor<string, []>("matrix_bd_17_cast_fp16")];
            tensor<bool, []> matrix_ac_9_transpose_x_0 = const()[name = tensor<string, []>("matrix_ac_9_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> matrix_ac_9_transpose_y_0 = const()[name = tensor<string, []>("matrix_ac_9_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<int32, [4]> transpose_104_perm_0 = const()[name = tensor<string, []>("transpose_104_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_105_perm_0 = const()[name = tensor<string, []>("transpose_105_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_105 = transpose(perm = transpose_105_perm_0, x = k_17_cast_fp16)[name = tensor<string, []>("transpose_352")];
            tensor<fp16, [1, 8, 188, 128]> transpose_104 = transpose(perm = transpose_104_perm_0, x = var_986_cast_fp16)[name = tensor<string, []>("transpose_353")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_9_cast_fp16 = matmul(transpose_x = matrix_ac_9_transpose_x_0, transpose_y = matrix_ac_9_transpose_y_0, x = transpose_104, y = transpose_105)[name = tensor<string, []>("matrix_ac_9_cast_fp16")];
            tensor<int32, [4]> matrix_bd_19_begin_0 = const()[name = tensor<string, []>("matrix_bd_19_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_19_end_0 = const()[name = tensor<string, []>("matrix_bd_19_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_19_end_mask_0 = const()[name = tensor<string, []>("matrix_bd_19_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_19_cast_fp16 = slice_by_index(begin = matrix_bd_19_begin_0, end = matrix_bd_19_end_0, end_mask = matrix_bd_19_end_mask_0, x = matrix_bd_17_cast_fp16)[name = tensor<string, []>("matrix_bd_19_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_1012_cast_fp16 = add(x = matrix_ac_9_cast_fp16, y = matrix_bd_19_cast_fp16)[name = tensor<string, []>("op_1012_cast_fp16")];
            tensor<fp16, []> _inversed_scores_17_y_0_to_fp16 = const()[name = tensor<string, []>("_inversed_scores_17_y_0_to_fp16"), val = tensor<fp16, []>(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_17_cast_fp16 = mul(x = var_1012_cast_fp16, y = _inversed_scores_17_y_0_to_fp16)[name = tensor<string, []>("_inversed_scores_17_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_19_cast_fp16 = select(a = var_12_to_fp16, b = _inversed_scores_17_cast_fp16, cond = mask_3)[name = tensor<string, []>("scores_19_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_1018_cast_fp16 = softmax(axis = var_30, x = scores_19_cast_fp16)[name = tensor<string, []>("op_1018_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_241_cast_fp16 = select(a = var_11_to_fp16, b = var_1018_cast_fp16, cond = mask_3)[name = tensor<string, []>("input_241_cast_fp16")];
            tensor<bool, []> x_101_transpose_x_0 = const()[name = tensor<string, []>("x_101_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_101_transpose_y_0 = const()[name = tensor<string, []>("x_101_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 188, 128]> value_11_cast_fp16 = transpose(perm = value_11_perm_0, x = v_9_cast_fp16)[name = tensor<string, []>("transpose_355")];
            tensor<fp16, [1, 8, 188, 128]> x_101_cast_fp16 = matmul(transpose_x = x_101_transpose_x_0, transpose_y = x_101_transpose_y_0, x = input_241_cast_fp16, y = value_11_cast_fp16)[name = tensor<string, []>("x_101_cast_fp16")];
            tensor<int32, [4]> var_1022_perm_0 = const()[name = tensor<string, []>("op_1022_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1023 = const()[name = tensor<string, []>("op_1023"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_1022_cast_fp16 = transpose(perm = var_1022_perm_0, x = x_101_cast_fp16)[name = tensor<string, []>("transpose_351")];
            tensor<fp16, [1, 188, 1024]> input_243_cast_fp16 = reshape(shape = var_1023, x = var_1022_cast_fp16)[name = tensor<string, []>("input_243_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_4_self_attn_linear_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_4_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(228874880)))];
            tensor<fp16, [1024]> encoder_layers_4_self_attn_linear_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_4_self_attn_linear_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(230972096)))];
            tensor<fp16, [1, 188, 1024]> linear_43_cast_fp16 = linear(bias = encoder_layers_4_self_attn_linear_out_bias_to_fp16, weight = encoder_layers_4_self_attn_linear_out_weight_to_fp16, x = input_243_cast_fp16)[name = tensor<string, []>("linear_43_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_247_cast_fp16 = add(x = input_239_cast_fp16, y = linear_43_cast_fp16)[name = tensor<string, []>("input_247_cast_fp16")];
            tensor<int32, [1]> x_105_axes_0 = const()[name = tensor<string, []>("x_105_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_4_norm_conv_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_4_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(230974208)))];
            tensor<fp16, [1024]> encoder_layers_4_norm_conv_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_4_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(230976320)))];
            tensor<fp16, [1, 188, 1024]> x_105_cast_fp16 = layer_norm(axes = x_105_axes_0, beta = encoder_layers_4_norm_conv_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_4_norm_conv_weight_to_fp16, x = input_247_cast_fp16)[name = tensor<string, []>("x_105_cast_fp16")];
            tensor<int32, [3]> input_249_perm_0 = const()[name = tensor<string, []>("input_249_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> input_251_pad_type_0 = const()[name = tensor<string, []>("input_251_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_251_strides_0 = const()[name = tensor<string, []>("input_251_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_251_pad_0 = const()[name = tensor<string, []>("input_251_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_251_dilations_0 = const()[name = tensor<string, []>("input_251_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_251_groups_0 = const()[name = tensor<string, []>("input_251_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [2048, 1024, 1]> encoder_layers_4_conv_pointwise_conv1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_4_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(230978432)))];
            tensor<fp16, [2048]> encoder_layers_4_conv_pointwise_conv1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_4_conv_pointwise_conv1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(235172800)))];
            tensor<fp16, [1, 1024, 188]> input_249_cast_fp16 = transpose(perm = input_249_perm_0, x = x_105_cast_fp16)[name = tensor<string, []>("transpose_350")];
            tensor<fp16, [1, 2048, 188]> input_251_cast_fp16 = conv(bias = encoder_layers_4_conv_pointwise_conv1_bias_to_fp16, dilations = input_251_dilations_0, groups = input_251_groups_0, pad = input_251_pad_0, pad_type = input_251_pad_type_0, strides = input_251_strides_0, weight = encoder_layers_4_conv_pointwise_conv1_weight_to_fp16, x = input_249_cast_fp16)[name = tensor<string, []>("input_251_cast_fp16")];
            tensor<int32, []> x_107_split_num_splits_0 = const()[name = tensor<string, []>("x_107_split_num_splits_0"), val = tensor<int32, []>(2)];
            tensor<int32, []> x_107_split_axis_0 = const()[name = tensor<string, []>("x_107_split_axis_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1, 1024, 188]> x_107_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_107_split_cast_fp16_1 = split(axis = x_107_split_axis_0, num_splits = x_107_split_num_splits_0, x = input_251_cast_fp16)[name = tensor<string, []>("x_107_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_107_split_1_sigmoid_cast_fp16 = sigmoid(x = x_107_split_cast_fp16_1)[name = tensor<string, []>("x_107_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_107_cast_fp16 = mul(x = x_107_split_cast_fp16_0, y = x_107_split_1_sigmoid_cast_fp16)[name = tensor<string, []>("x_107_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_253_cast_fp16 = select(a = var_11_to_fp16, b = x_107_cast_fp16, cond = var_351)[name = tensor<string, []>("input_253_cast_fp16")];
            tensor<int32, [6]> input_255_pad_0 = const()[name = tensor<string, []>("input_255_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            tensor<string, []> input_255_mode_0 = const()[name = tensor<string, []>("input_255_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_57_to_fp16 = const()[name = tensor<string, []>("const_57_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_255_cast_fp16 = pad(constant_val = const_57_to_fp16, mode = input_255_mode_0, pad = input_255_pad_0, x = input_253_cast_fp16)[name = tensor<string, []>("input_255_cast_fp16")];
            tensor<string, []> input_257_pad_type_0 = const()[name = tensor<string, []>("input_257_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, []> input_257_groups_0 = const()[name = tensor<string, []>("input_257_groups_0"), val = tensor<int32, []>(1024)];
            tensor<int32, [1]> input_257_strides_0 = const()[name = tensor<string, []>("input_257_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_257_pad_0 = const()[name = tensor<string, []>("input_257_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_257_dilations_0 = const()[name = tensor<string, []>("input_257_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_336_to_fp16 = const()[name = tensor<string, []>("const_336_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(235176960)))];
            tensor<fp16, [1024]> const_337_to_fp16 = const()[name = tensor<string, []>("const_337_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(235195456)))];
            tensor<fp16, [1, 1024, 188]> input_259_cast_fp16 = conv(bias = const_337_to_fp16, dilations = input_257_dilations_0, groups = input_257_groups_0, pad = input_257_pad_0, pad_type = input_257_pad_type_0, strides = input_257_strides_0, weight = const_336_to_fp16, x = input_255_cast_fp16)[name = tensor<string, []>("input_259_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_261_cast_fp16 = silu(x = input_259_cast_fp16)[name = tensor<string, []>("input_261_cast_fp16")];
            tensor<string, []> x_109_pad_type_0 = const()[name = tensor<string, []>("x_109_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> x_109_strides_0 = const()[name = tensor<string, []>("x_109_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_109_pad_0 = const()[name = tensor<string, []>("x_109_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_109_dilations_0 = const()[name = tensor<string, []>("x_109_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> x_109_groups_0 = const()[name = tensor<string, []>("x_109_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1024, 1024, 1]> encoder_layers_4_conv_pointwise_conv2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_4_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(235197568)))];
            tensor<fp16, [1024]> encoder_layers_4_conv_pointwise_conv2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_4_conv_pointwise_conv2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(237294784)))];
            tensor<fp16, [1, 1024, 188]> x_109_cast_fp16 = conv(bias = encoder_layers_4_conv_pointwise_conv2_bias_to_fp16, dilations = x_109_dilations_0, groups = x_109_groups_0, pad = x_109_pad_0, pad_type = x_109_pad_type_0, strides = x_109_strides_0, weight = encoder_layers_4_conv_pointwise_conv2_weight_to_fp16, x = input_261_cast_fp16)[name = tensor<string, []>("x_109_cast_fp16")];
            tensor<int32, [3]> input_263_perm_0 = const()[name = tensor<string, []>("input_263_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_263_cast_fp16 = transpose(perm = input_263_perm_0, x = x_109_cast_fp16)[name = tensor<string, []>("transpose_349")];
            tensor<fp16, [1, 188, 1024]> input_265_cast_fp16 = add(x = input_247_cast_fp16, y = input_263_cast_fp16)[name = tensor<string, []>("input_265_cast_fp16")];
            tensor<int32, [1]> input_267_axes_0 = const()[name = tensor<string, []>("input_267_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_4_norm_feed_forward2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_4_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(237296896)))];
            tensor<fp16, [1024]> encoder_layers_4_norm_feed_forward2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_4_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(237299008)))];
            tensor<fp16, [1, 188, 1024]> input_267_cast_fp16 = layer_norm(axes = input_267_axes_0, beta = encoder_layers_4_norm_feed_forward2_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_4_norm_feed_forward2_weight_to_fp16, x = input_265_cast_fp16)[name = tensor<string, []>("input_267_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_4_feed_forward2_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_4_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(237301120)))];
            tensor<fp16, [4096]> encoder_layers_4_feed_forward2_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_4_feed_forward2_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(245689792)))];
            tensor<fp16, [1, 188, 4096]> linear_44_cast_fp16 = linear(bias = encoder_layers_4_feed_forward2_linear1_bias_to_fp16, weight = encoder_layers_4_feed_forward2_linear1_weight_to_fp16, x = input_267_cast_fp16)[name = tensor<string, []>("linear_44_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_271_cast_fp16 = silu(x = linear_44_cast_fp16)[name = tensor<string, []>("input_271_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_4_feed_forward2_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_4_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(245698048)))];
            tensor<fp16, [1024]> encoder_layers_4_feed_forward2_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_4_feed_forward2_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(254086720)))];
            tensor<fp16, [1, 188, 1024]> linear_45_cast_fp16 = linear(bias = encoder_layers_4_feed_forward2_linear2_bias_to_fp16, weight = encoder_layers_4_feed_forward2_linear2_weight_to_fp16, x = input_271_cast_fp16)[name = tensor<string, []>("linear_45_cast_fp16")];
            tensor<fp16, []> var_1089_to_fp16 = const()[name = tensor<string, []>("op_1089_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_1090_cast_fp16 = mul(x = linear_45_cast_fp16, y = var_1089_to_fp16)[name = tensor<string, []>("op_1090_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_277_cast_fp16 = add(x = input_265_cast_fp16, y = var_1090_cast_fp16)[name = tensor<string, []>("input_277_cast_fp16")];
            tensor<int32, [1]> input_279_axes_0 = const()[name = tensor<string, []>("input_279_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_4_norm_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_4_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(254088832)))];
            tensor<fp16, [1024]> encoder_layers_4_norm_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_4_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(254090944)))];
            tensor<fp16, [1, 188, 1024]> input_279_cast_fp16 = layer_norm(axes = input_279_axes_0, beta = encoder_layers_4_norm_out_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_4_norm_out_weight_to_fp16, x = input_277_cast_fp16)[name = tensor<string, []>("input_279_cast_fp16")];
            tensor<int32, [1]> input_281_axes_0 = const()[name = tensor<string, []>("input_281_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_5_norm_feed_forward1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_5_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(254093056)))];
            tensor<fp16, [1024]> encoder_layers_5_norm_feed_forward1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_5_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(254095168)))];
            tensor<fp16, [1, 188, 1024]> input_281_cast_fp16 = layer_norm(axes = input_281_axes_0, beta = encoder_layers_5_norm_feed_forward1_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_5_norm_feed_forward1_weight_to_fp16, x = input_279_cast_fp16)[name = tensor<string, []>("input_281_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_5_feed_forward1_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_5_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(254097280)))];
            tensor<fp16, [4096]> encoder_layers_5_feed_forward1_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_5_feed_forward1_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(262485952)))];
            tensor<fp16, [1, 188, 4096]> linear_46_cast_fp16 = linear(bias = encoder_layers_5_feed_forward1_linear1_bias_to_fp16, weight = encoder_layers_5_feed_forward1_linear1_weight_to_fp16, x = input_281_cast_fp16)[name = tensor<string, []>("linear_46_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_285_cast_fp16 = silu(x = linear_46_cast_fp16)[name = tensor<string, []>("input_285_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_5_feed_forward1_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_5_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(262494208)))];
            tensor<fp16, [1024]> encoder_layers_5_feed_forward1_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_5_feed_forward1_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(270882880)))];
            tensor<fp16, [1, 188, 1024]> linear_47_cast_fp16 = linear(bias = encoder_layers_5_feed_forward1_linear2_bias_to_fp16, weight = encoder_layers_5_feed_forward1_linear2_weight_to_fp16, x = input_285_cast_fp16)[name = tensor<string, []>("linear_47_cast_fp16")];
            tensor<fp16, []> var_1120_to_fp16 = const()[name = tensor<string, []>("op_1120_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_1121_cast_fp16 = mul(x = linear_47_cast_fp16, y = var_1120_to_fp16)[name = tensor<string, []>("op_1121_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_291_cast_fp16 = add(x = input_279_cast_fp16, y = var_1121_cast_fp16)[name = tensor<string, []>("input_291_cast_fp16")];
            tensor<int32, [1]> query_11_axes_0 = const()[name = tensor<string, []>("query_11_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_5_norm_self_att_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_5_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(270884992)))];
            tensor<fp16, [1024]> encoder_layers_5_norm_self_att_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_5_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(270887104)))];
            tensor<fp16, [1, 188, 1024]> query_11_cast_fp16 = layer_norm(axes = query_11_axes_0, beta = encoder_layers_5_norm_self_att_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_5_norm_self_att_weight_to_fp16, x = input_291_cast_fp16)[name = tensor<string, []>("query_11_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_5_self_attn_linear_q_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_5_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(270889216)))];
            tensor<fp16, [1024]> encoder_layers_5_self_attn_linear_q_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_5_self_attn_linear_q_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(272986432)))];
            tensor<fp16, [1, 188, 1024]> linear_48_cast_fp16 = linear(bias = encoder_layers_5_self_attn_linear_q_bias_to_fp16, weight = encoder_layers_5_self_attn_linear_q_weight_to_fp16, x = query_11_cast_fp16)[name = tensor<string, []>("linear_48_cast_fp16")];
            tensor<int32, [4]> var_1138 = const()[name = tensor<string, []>("op_1138"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_31_cast_fp16 = reshape(shape = var_1138, x = linear_48_cast_fp16)[name = tensor<string, []>("q_31_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_5_self_attn_linear_k_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_5_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(272988544)))];
            tensor<fp16, [1024]> encoder_layers_5_self_attn_linear_k_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_5_self_attn_linear_k_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(275085760)))];
            tensor<fp16, [1, 188, 1024]> linear_49_cast_fp16 = linear(bias = encoder_layers_5_self_attn_linear_k_bias_to_fp16, weight = encoder_layers_5_self_attn_linear_k_weight_to_fp16, x = query_11_cast_fp16)[name = tensor<string, []>("linear_49_cast_fp16")];
            tensor<int32, [4]> var_1143 = const()[name = tensor<string, []>("op_1143"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_21_cast_fp16 = reshape(shape = var_1143, x = linear_49_cast_fp16)[name = tensor<string, []>("k_21_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_5_self_attn_linear_v_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_5_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(275087872)))];
            tensor<fp16, [1024]> encoder_layers_5_self_attn_linear_v_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_5_self_attn_linear_v_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(277185088)))];
            tensor<fp16, [1, 188, 1024]> linear_50_cast_fp16 = linear(bias = encoder_layers_5_self_attn_linear_v_bias_to_fp16, weight = encoder_layers_5_self_attn_linear_v_weight_to_fp16, x = query_11_cast_fp16)[name = tensor<string, []>("linear_50_cast_fp16")];
            tensor<int32, [4]> var_1148 = const()[name = tensor<string, []>("op_1148"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_11_cast_fp16 = reshape(shape = var_1148, x = linear_50_cast_fp16)[name = tensor<string, []>("v_11_cast_fp16")];
            tensor<int32, [4]> value_13_perm_0 = const()[name = tensor<string, []>("value_13_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> encoder_layers_5_self_attn_pos_bias_u_to_fp16 = const()[name = tensor<string, []>("encoder_layers_5_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(277187200)))];
            tensor<fp16, [1, 188, 8, 128]> var_1160_cast_fp16 = add(x = q_31_cast_fp16, y = encoder_layers_5_self_attn_pos_bias_u_to_fp16)[name = tensor<string, []>("op_1160_cast_fp16")];
            tensor<fp16, [8, 128]> encoder_layers_5_self_attn_pos_bias_v_to_fp16 = const()[name = tensor<string, []>("encoder_layers_5_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(277189312)))];
            tensor<fp16, [1, 188, 8, 128]> var_1162_cast_fp16 = add(x = q_31_cast_fp16, y = encoder_layers_5_self_attn_pos_bias_v_to_fp16)[name = tensor<string, []>("op_1162_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_11_perm_0 = const()[name = tensor<string, []>("q_with_bias_v_11_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<bool, []> x_117_transpose_x_0 = const()[name = tensor<string, []>("x_117_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_117_transpose_y_0 = const()[name = tensor<string, []>("x_117_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 128, 375]> var_1164_to_fp16 = const()[name = tensor<string, []>("op_1164_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(277191424)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_11_cast_fp16 = transpose(perm = q_with_bias_v_11_perm_0, x = var_1162_cast_fp16)[name = tensor<string, []>("transpose_347")];
            tensor<fp16, [1, 8, 188, 375]> x_117_cast_fp16 = matmul(transpose_x = x_117_transpose_x_0, transpose_y = x_117_transpose_y_0, x = q_with_bias_v_11_cast_fp16, y = var_1164_to_fp16)[name = tensor<string, []>("x_117_cast_fp16")];
            tensor<int32, [8]> x_119_pad_0 = const()[name = tensor<string, []>("x_119_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            tensor<string, []> x_119_mode_0 = const()[name = tensor<string, []>("x_119_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_64_to_fp16 = const()[name = tensor<string, []>("const_64_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_119_cast_fp16 = pad(constant_val = const_64_to_fp16, mode = x_119_mode_0, pad = x_119_pad_0, x = x_117_cast_fp16)[name = tensor<string, []>("x_119_cast_fp16")];
            tensor<int32, [4]> var_1172 = const()[name = tensor<string, []>("op_1172"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_121_cast_fp16 = reshape(shape = var_1172, x = x_119_cast_fp16)[name = tensor<string, []>("x_121_cast_fp16")];
            tensor<int32, [4]> var_1176_begin_0 = const()[name = tensor<string, []>("op_1176_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_1176_end_0 = const()[name = tensor<string, []>("op_1176_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_1176_end_mask_0 = const()[name = tensor<string, []>("op_1176_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_1176_cast_fp16 = slice_by_index(begin = var_1176_begin_0, end = var_1176_end_0, end_mask = var_1176_end_mask_0, x = x_121_cast_fp16)[name = tensor<string, []>("op_1176_cast_fp16")];
            tensor<int32, [4]> var_1177 = const()[name = tensor<string, []>("op_1177"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_21_cast_fp16 = reshape(shape = var_1177, x = var_1176_cast_fp16)[name = tensor<string, []>("matrix_bd_21_cast_fp16")];
            tensor<bool, []> matrix_ac_11_transpose_x_0 = const()[name = tensor<string, []>("matrix_ac_11_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> matrix_ac_11_transpose_y_0 = const()[name = tensor<string, []>("matrix_ac_11_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<int32, [4]> transpose_106_perm_0 = const()[name = tensor<string, []>("transpose_106_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_107_perm_0 = const()[name = tensor<string, []>("transpose_107_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_107 = transpose(perm = transpose_107_perm_0, x = k_21_cast_fp16)[name = tensor<string, []>("transpose_345")];
            tensor<fp16, [1, 8, 188, 128]> transpose_106 = transpose(perm = transpose_106_perm_0, x = var_1160_cast_fp16)[name = tensor<string, []>("transpose_346")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_11_cast_fp16 = matmul(transpose_x = matrix_ac_11_transpose_x_0, transpose_y = matrix_ac_11_transpose_y_0, x = transpose_106, y = transpose_107)[name = tensor<string, []>("matrix_ac_11_cast_fp16")];
            tensor<int32, [4]> matrix_bd_23_begin_0 = const()[name = tensor<string, []>("matrix_bd_23_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_23_end_0 = const()[name = tensor<string, []>("matrix_bd_23_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_23_end_mask_0 = const()[name = tensor<string, []>("matrix_bd_23_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_23_cast_fp16 = slice_by_index(begin = matrix_bd_23_begin_0, end = matrix_bd_23_end_0, end_mask = matrix_bd_23_end_mask_0, x = matrix_bd_21_cast_fp16)[name = tensor<string, []>("matrix_bd_23_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_1186_cast_fp16 = add(x = matrix_ac_11_cast_fp16, y = matrix_bd_23_cast_fp16)[name = tensor<string, []>("op_1186_cast_fp16")];
            tensor<fp16, []> _inversed_scores_21_y_0_to_fp16 = const()[name = tensor<string, []>("_inversed_scores_21_y_0_to_fp16"), val = tensor<fp16, []>(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_21_cast_fp16 = mul(x = var_1186_cast_fp16, y = _inversed_scores_21_y_0_to_fp16)[name = tensor<string, []>("_inversed_scores_21_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_23_cast_fp16 = select(a = var_12_to_fp16, b = _inversed_scores_21_cast_fp16, cond = mask_3)[name = tensor<string, []>("scores_23_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_1192_cast_fp16 = softmax(axis = var_30, x = scores_23_cast_fp16)[name = tensor<string, []>("op_1192_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_293_cast_fp16 = select(a = var_11_to_fp16, b = var_1192_cast_fp16, cond = mask_3)[name = tensor<string, []>("input_293_cast_fp16")];
            tensor<bool, []> x_123_transpose_x_0 = const()[name = tensor<string, []>("x_123_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_123_transpose_y_0 = const()[name = tensor<string, []>("x_123_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 188, 128]> value_13_cast_fp16 = transpose(perm = value_13_perm_0, x = v_11_cast_fp16)[name = tensor<string, []>("transpose_348")];
            tensor<fp16, [1, 8, 188, 128]> x_123_cast_fp16 = matmul(transpose_x = x_123_transpose_x_0, transpose_y = x_123_transpose_y_0, x = input_293_cast_fp16, y = value_13_cast_fp16)[name = tensor<string, []>("x_123_cast_fp16")];
            tensor<int32, [4]> var_1196_perm_0 = const()[name = tensor<string, []>("op_1196_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1197 = const()[name = tensor<string, []>("op_1197"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_1196_cast_fp16 = transpose(perm = var_1196_perm_0, x = x_123_cast_fp16)[name = tensor<string, []>("transpose_344")];
            tensor<fp16, [1, 188, 1024]> input_295_cast_fp16 = reshape(shape = var_1197, x = var_1196_cast_fp16)[name = tensor<string, []>("input_295_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_5_self_attn_linear_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_5_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(277959488)))];
            tensor<fp16, [1024]> encoder_layers_5_self_attn_linear_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_5_self_attn_linear_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(280056704)))];
            tensor<fp16, [1, 188, 1024]> linear_52_cast_fp16 = linear(bias = encoder_layers_5_self_attn_linear_out_bias_to_fp16, weight = encoder_layers_5_self_attn_linear_out_weight_to_fp16, x = input_295_cast_fp16)[name = tensor<string, []>("linear_52_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_299_cast_fp16 = add(x = input_291_cast_fp16, y = linear_52_cast_fp16)[name = tensor<string, []>("input_299_cast_fp16")];
            tensor<int32, [1]> x_127_axes_0 = const()[name = tensor<string, []>("x_127_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_5_norm_conv_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_5_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(280058816)))];
            tensor<fp16, [1024]> encoder_layers_5_norm_conv_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_5_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(280060928)))];
            tensor<fp16, [1, 188, 1024]> x_127_cast_fp16 = layer_norm(axes = x_127_axes_0, beta = encoder_layers_5_norm_conv_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_5_norm_conv_weight_to_fp16, x = input_299_cast_fp16)[name = tensor<string, []>("x_127_cast_fp16")];
            tensor<int32, [3]> input_301_perm_0 = const()[name = tensor<string, []>("input_301_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> input_303_pad_type_0 = const()[name = tensor<string, []>("input_303_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_303_strides_0 = const()[name = tensor<string, []>("input_303_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_303_pad_0 = const()[name = tensor<string, []>("input_303_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_303_dilations_0 = const()[name = tensor<string, []>("input_303_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_303_groups_0 = const()[name = tensor<string, []>("input_303_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [2048, 1024, 1]> encoder_layers_5_conv_pointwise_conv1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_5_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(280063040)))];
            tensor<fp16, [2048]> encoder_layers_5_conv_pointwise_conv1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_5_conv_pointwise_conv1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(284257408)))];
            tensor<fp16, [1, 1024, 188]> input_301_cast_fp16 = transpose(perm = input_301_perm_0, x = x_127_cast_fp16)[name = tensor<string, []>("transpose_343")];
            tensor<fp16, [1, 2048, 188]> input_303_cast_fp16 = conv(bias = encoder_layers_5_conv_pointwise_conv1_bias_to_fp16, dilations = input_303_dilations_0, groups = input_303_groups_0, pad = input_303_pad_0, pad_type = input_303_pad_type_0, strides = input_303_strides_0, weight = encoder_layers_5_conv_pointwise_conv1_weight_to_fp16, x = input_301_cast_fp16)[name = tensor<string, []>("input_303_cast_fp16")];
            tensor<int32, []> x_129_split_num_splits_0 = const()[name = tensor<string, []>("x_129_split_num_splits_0"), val = tensor<int32, []>(2)];
            tensor<int32, []> x_129_split_axis_0 = const()[name = tensor<string, []>("x_129_split_axis_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1, 1024, 188]> x_129_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_129_split_cast_fp16_1 = split(axis = x_129_split_axis_0, num_splits = x_129_split_num_splits_0, x = input_303_cast_fp16)[name = tensor<string, []>("x_129_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_129_split_1_sigmoid_cast_fp16 = sigmoid(x = x_129_split_cast_fp16_1)[name = tensor<string, []>("x_129_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_129_cast_fp16 = mul(x = x_129_split_cast_fp16_0, y = x_129_split_1_sigmoid_cast_fp16)[name = tensor<string, []>("x_129_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_305_cast_fp16 = select(a = var_11_to_fp16, b = x_129_cast_fp16, cond = var_351)[name = tensor<string, []>("input_305_cast_fp16")];
            tensor<int32, [6]> input_307_pad_0 = const()[name = tensor<string, []>("input_307_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            tensor<string, []> input_307_mode_0 = const()[name = tensor<string, []>("input_307_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_67_to_fp16 = const()[name = tensor<string, []>("const_67_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_307_cast_fp16 = pad(constant_val = const_67_to_fp16, mode = input_307_mode_0, pad = input_307_pad_0, x = input_305_cast_fp16)[name = tensor<string, []>("input_307_cast_fp16")];
            tensor<string, []> input_309_pad_type_0 = const()[name = tensor<string, []>("input_309_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, []> input_309_groups_0 = const()[name = tensor<string, []>("input_309_groups_0"), val = tensor<int32, []>(1024)];
            tensor<int32, [1]> input_309_strides_0 = const()[name = tensor<string, []>("input_309_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_309_pad_0 = const()[name = tensor<string, []>("input_309_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_309_dilations_0 = const()[name = tensor<string, []>("input_309_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_338_to_fp16 = const()[name = tensor<string, []>("const_338_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(284261568)))];
            tensor<fp16, [1024]> const_339_to_fp16 = const()[name = tensor<string, []>("const_339_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(284280064)))];
            tensor<fp16, [1, 1024, 188]> input_311_cast_fp16 = conv(bias = const_339_to_fp16, dilations = input_309_dilations_0, groups = input_309_groups_0, pad = input_309_pad_0, pad_type = input_309_pad_type_0, strides = input_309_strides_0, weight = const_338_to_fp16, x = input_307_cast_fp16)[name = tensor<string, []>("input_311_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_313_cast_fp16 = silu(x = input_311_cast_fp16)[name = tensor<string, []>("input_313_cast_fp16")];
            tensor<string, []> x_131_pad_type_0 = const()[name = tensor<string, []>("x_131_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> x_131_strides_0 = const()[name = tensor<string, []>("x_131_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_131_pad_0 = const()[name = tensor<string, []>("x_131_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_131_dilations_0 = const()[name = tensor<string, []>("x_131_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> x_131_groups_0 = const()[name = tensor<string, []>("x_131_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1024, 1024, 1]> encoder_layers_5_conv_pointwise_conv2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_5_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(284282176)))];
            tensor<fp16, [1024]> encoder_layers_5_conv_pointwise_conv2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_5_conv_pointwise_conv2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(286379392)))];
            tensor<fp16, [1, 1024, 188]> x_131_cast_fp16 = conv(bias = encoder_layers_5_conv_pointwise_conv2_bias_to_fp16, dilations = x_131_dilations_0, groups = x_131_groups_0, pad = x_131_pad_0, pad_type = x_131_pad_type_0, strides = x_131_strides_0, weight = encoder_layers_5_conv_pointwise_conv2_weight_to_fp16, x = input_313_cast_fp16)[name = tensor<string, []>("x_131_cast_fp16")];
            tensor<int32, [3]> input_315_perm_0 = const()[name = tensor<string, []>("input_315_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_315_cast_fp16 = transpose(perm = input_315_perm_0, x = x_131_cast_fp16)[name = tensor<string, []>("transpose_342")];
            tensor<fp16, [1, 188, 1024]> input_317_cast_fp16 = add(x = input_299_cast_fp16, y = input_315_cast_fp16)[name = tensor<string, []>("input_317_cast_fp16")];
            tensor<int32, [1]> input_319_axes_0 = const()[name = tensor<string, []>("input_319_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_5_norm_feed_forward2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_5_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(286381504)))];
            tensor<fp16, [1024]> encoder_layers_5_norm_feed_forward2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_5_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(286383616)))];
            tensor<fp16, [1, 188, 1024]> input_319_cast_fp16 = layer_norm(axes = input_319_axes_0, beta = encoder_layers_5_norm_feed_forward2_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_5_norm_feed_forward2_weight_to_fp16, x = input_317_cast_fp16)[name = tensor<string, []>("input_319_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_5_feed_forward2_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_5_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(286385728)))];
            tensor<fp16, [4096]> encoder_layers_5_feed_forward2_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_5_feed_forward2_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(294774400)))];
            tensor<fp16, [1, 188, 4096]> linear_53_cast_fp16 = linear(bias = encoder_layers_5_feed_forward2_linear1_bias_to_fp16, weight = encoder_layers_5_feed_forward2_linear1_weight_to_fp16, x = input_319_cast_fp16)[name = tensor<string, []>("linear_53_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_323_cast_fp16 = silu(x = linear_53_cast_fp16)[name = tensor<string, []>("input_323_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_5_feed_forward2_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_5_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(294782656)))];
            tensor<fp16, [1024]> encoder_layers_5_feed_forward2_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_5_feed_forward2_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(303171328)))];
            tensor<fp16, [1, 188, 1024]> linear_54_cast_fp16 = linear(bias = encoder_layers_5_feed_forward2_linear2_bias_to_fp16, weight = encoder_layers_5_feed_forward2_linear2_weight_to_fp16, x = input_323_cast_fp16)[name = tensor<string, []>("linear_54_cast_fp16")];
            tensor<fp16, []> var_1263_to_fp16 = const()[name = tensor<string, []>("op_1263_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_1264_cast_fp16 = mul(x = linear_54_cast_fp16, y = var_1263_to_fp16)[name = tensor<string, []>("op_1264_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_329_cast_fp16 = add(x = input_317_cast_fp16, y = var_1264_cast_fp16)[name = tensor<string, []>("input_329_cast_fp16")];
            tensor<int32, [1]> input_331_axes_0 = const()[name = tensor<string, []>("input_331_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_5_norm_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_5_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(303173440)))];
            tensor<fp16, [1024]> encoder_layers_5_norm_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_5_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(303175552)))];
            tensor<fp16, [1, 188, 1024]> input_331_cast_fp16 = layer_norm(axes = input_331_axes_0, beta = encoder_layers_5_norm_out_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_5_norm_out_weight_to_fp16, x = input_329_cast_fp16)[name = tensor<string, []>("input_331_cast_fp16")];
            tensor<int32, [1]> input_333_axes_0 = const()[name = tensor<string, []>("input_333_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_6_norm_feed_forward1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_6_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(303177664)))];
            tensor<fp16, [1024]> encoder_layers_6_norm_feed_forward1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_6_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(303179776)))];
            tensor<fp16, [1, 188, 1024]> input_333_cast_fp16 = layer_norm(axes = input_333_axes_0, beta = encoder_layers_6_norm_feed_forward1_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_6_norm_feed_forward1_weight_to_fp16, x = input_331_cast_fp16)[name = tensor<string, []>("input_333_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_6_feed_forward1_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_6_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(303181888)))];
            tensor<fp16, [4096]> encoder_layers_6_feed_forward1_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_6_feed_forward1_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(311570560)))];
            tensor<fp16, [1, 188, 4096]> linear_55_cast_fp16 = linear(bias = encoder_layers_6_feed_forward1_linear1_bias_to_fp16, weight = encoder_layers_6_feed_forward1_linear1_weight_to_fp16, x = input_333_cast_fp16)[name = tensor<string, []>("linear_55_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_337_cast_fp16 = silu(x = linear_55_cast_fp16)[name = tensor<string, []>("input_337_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_6_feed_forward1_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_6_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(311578816)))];
            tensor<fp16, [1024]> encoder_layers_6_feed_forward1_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_6_feed_forward1_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(319967488)))];
            tensor<fp16, [1, 188, 1024]> linear_56_cast_fp16 = linear(bias = encoder_layers_6_feed_forward1_linear2_bias_to_fp16, weight = encoder_layers_6_feed_forward1_linear2_weight_to_fp16, x = input_337_cast_fp16)[name = tensor<string, []>("linear_56_cast_fp16")];
            tensor<fp16, []> var_1294_to_fp16 = const()[name = tensor<string, []>("op_1294_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_1295_cast_fp16 = mul(x = linear_56_cast_fp16, y = var_1294_to_fp16)[name = tensor<string, []>("op_1295_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_343_cast_fp16 = add(x = input_331_cast_fp16, y = var_1295_cast_fp16)[name = tensor<string, []>("input_343_cast_fp16")];
            tensor<int32, [1]> query_13_axes_0 = const()[name = tensor<string, []>("query_13_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_6_norm_self_att_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_6_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(319969600)))];
            tensor<fp16, [1024]> encoder_layers_6_norm_self_att_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_6_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(319971712)))];
            tensor<fp16, [1, 188, 1024]> query_13_cast_fp16 = layer_norm(axes = query_13_axes_0, beta = encoder_layers_6_norm_self_att_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_6_norm_self_att_weight_to_fp16, x = input_343_cast_fp16)[name = tensor<string, []>("query_13_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_6_self_attn_linear_q_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_6_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(319973824)))];
            tensor<fp16, [1024]> encoder_layers_6_self_attn_linear_q_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_6_self_attn_linear_q_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(322071040)))];
            tensor<fp16, [1, 188, 1024]> linear_57_cast_fp16 = linear(bias = encoder_layers_6_self_attn_linear_q_bias_to_fp16, weight = encoder_layers_6_self_attn_linear_q_weight_to_fp16, x = query_13_cast_fp16)[name = tensor<string, []>("linear_57_cast_fp16")];
            tensor<int32, [4]> var_1312 = const()[name = tensor<string, []>("op_1312"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_37_cast_fp16 = reshape(shape = var_1312, x = linear_57_cast_fp16)[name = tensor<string, []>("q_37_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_6_self_attn_linear_k_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_6_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(322073152)))];
            tensor<fp16, [1024]> encoder_layers_6_self_attn_linear_k_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_6_self_attn_linear_k_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(324170368)))];
            tensor<fp16, [1, 188, 1024]> linear_58_cast_fp16 = linear(bias = encoder_layers_6_self_attn_linear_k_bias_to_fp16, weight = encoder_layers_6_self_attn_linear_k_weight_to_fp16, x = query_13_cast_fp16)[name = tensor<string, []>("linear_58_cast_fp16")];
            tensor<int32, [4]> var_1317 = const()[name = tensor<string, []>("op_1317"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_25_cast_fp16 = reshape(shape = var_1317, x = linear_58_cast_fp16)[name = tensor<string, []>("k_25_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_6_self_attn_linear_v_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_6_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(324172480)))];
            tensor<fp16, [1024]> encoder_layers_6_self_attn_linear_v_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_6_self_attn_linear_v_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(326269696)))];
            tensor<fp16, [1, 188, 1024]> linear_59_cast_fp16 = linear(bias = encoder_layers_6_self_attn_linear_v_bias_to_fp16, weight = encoder_layers_6_self_attn_linear_v_weight_to_fp16, x = query_13_cast_fp16)[name = tensor<string, []>("linear_59_cast_fp16")];
            tensor<int32, [4]> var_1322 = const()[name = tensor<string, []>("op_1322"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_13_cast_fp16 = reshape(shape = var_1322, x = linear_59_cast_fp16)[name = tensor<string, []>("v_13_cast_fp16")];
            tensor<int32, [4]> value_15_perm_0 = const()[name = tensor<string, []>("value_15_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> encoder_layers_6_self_attn_pos_bias_u_to_fp16 = const()[name = tensor<string, []>("encoder_layers_6_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(326271808)))];
            tensor<fp16, [1, 188, 8, 128]> var_1334_cast_fp16 = add(x = q_37_cast_fp16, y = encoder_layers_6_self_attn_pos_bias_u_to_fp16)[name = tensor<string, []>("op_1334_cast_fp16")];
            tensor<fp16, [8, 128]> encoder_layers_6_self_attn_pos_bias_v_to_fp16 = const()[name = tensor<string, []>("encoder_layers_6_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(326273920)))];
            tensor<fp16, [1, 188, 8, 128]> var_1336_cast_fp16 = add(x = q_37_cast_fp16, y = encoder_layers_6_self_attn_pos_bias_v_to_fp16)[name = tensor<string, []>("op_1336_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_13_perm_0 = const()[name = tensor<string, []>("q_with_bias_v_13_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<bool, []> x_139_transpose_x_0 = const()[name = tensor<string, []>("x_139_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_139_transpose_y_0 = const()[name = tensor<string, []>("x_139_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 128, 375]> var_1338_to_fp16 = const()[name = tensor<string, []>("op_1338_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(326276032)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_13_cast_fp16 = transpose(perm = q_with_bias_v_13_perm_0, x = var_1336_cast_fp16)[name = tensor<string, []>("transpose_340")];
            tensor<fp16, [1, 8, 188, 375]> x_139_cast_fp16 = matmul(transpose_x = x_139_transpose_x_0, transpose_y = x_139_transpose_y_0, x = q_with_bias_v_13_cast_fp16, y = var_1338_to_fp16)[name = tensor<string, []>("x_139_cast_fp16")];
            tensor<int32, [8]> x_141_pad_0 = const()[name = tensor<string, []>("x_141_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            tensor<string, []> x_141_mode_0 = const()[name = tensor<string, []>("x_141_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_74_to_fp16 = const()[name = tensor<string, []>("const_74_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_141_cast_fp16 = pad(constant_val = const_74_to_fp16, mode = x_141_mode_0, pad = x_141_pad_0, x = x_139_cast_fp16)[name = tensor<string, []>("x_141_cast_fp16")];
            tensor<int32, [4]> var_1346 = const()[name = tensor<string, []>("op_1346"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_143_cast_fp16 = reshape(shape = var_1346, x = x_141_cast_fp16)[name = tensor<string, []>("x_143_cast_fp16")];
            tensor<int32, [4]> var_1350_begin_0 = const()[name = tensor<string, []>("op_1350_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_1350_end_0 = const()[name = tensor<string, []>("op_1350_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_1350_end_mask_0 = const()[name = tensor<string, []>("op_1350_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_1350_cast_fp16 = slice_by_index(begin = var_1350_begin_0, end = var_1350_end_0, end_mask = var_1350_end_mask_0, x = x_143_cast_fp16)[name = tensor<string, []>("op_1350_cast_fp16")];
            tensor<int32, [4]> var_1351 = const()[name = tensor<string, []>("op_1351"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_25_cast_fp16 = reshape(shape = var_1351, x = var_1350_cast_fp16)[name = tensor<string, []>("matrix_bd_25_cast_fp16")];
            tensor<bool, []> matrix_ac_13_transpose_x_0 = const()[name = tensor<string, []>("matrix_ac_13_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> matrix_ac_13_transpose_y_0 = const()[name = tensor<string, []>("matrix_ac_13_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<int32, [4]> transpose_108_perm_0 = const()[name = tensor<string, []>("transpose_108_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_109_perm_0 = const()[name = tensor<string, []>("transpose_109_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_109 = transpose(perm = transpose_109_perm_0, x = k_25_cast_fp16)[name = tensor<string, []>("transpose_338")];
            tensor<fp16, [1, 8, 188, 128]> transpose_108 = transpose(perm = transpose_108_perm_0, x = var_1334_cast_fp16)[name = tensor<string, []>("transpose_339")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_13_cast_fp16 = matmul(transpose_x = matrix_ac_13_transpose_x_0, transpose_y = matrix_ac_13_transpose_y_0, x = transpose_108, y = transpose_109)[name = tensor<string, []>("matrix_ac_13_cast_fp16")];
            tensor<int32, [4]> matrix_bd_27_begin_0 = const()[name = tensor<string, []>("matrix_bd_27_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_27_end_0 = const()[name = tensor<string, []>("matrix_bd_27_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_27_end_mask_0 = const()[name = tensor<string, []>("matrix_bd_27_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_27_cast_fp16 = slice_by_index(begin = matrix_bd_27_begin_0, end = matrix_bd_27_end_0, end_mask = matrix_bd_27_end_mask_0, x = matrix_bd_25_cast_fp16)[name = tensor<string, []>("matrix_bd_27_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_1360_cast_fp16 = add(x = matrix_ac_13_cast_fp16, y = matrix_bd_27_cast_fp16)[name = tensor<string, []>("op_1360_cast_fp16")];
            tensor<fp16, []> _inversed_scores_25_y_0_to_fp16 = const()[name = tensor<string, []>("_inversed_scores_25_y_0_to_fp16"), val = tensor<fp16, []>(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_25_cast_fp16 = mul(x = var_1360_cast_fp16, y = _inversed_scores_25_y_0_to_fp16)[name = tensor<string, []>("_inversed_scores_25_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_27_cast_fp16 = select(a = var_12_to_fp16, b = _inversed_scores_25_cast_fp16, cond = mask_3)[name = tensor<string, []>("scores_27_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_1366_cast_fp16 = softmax(axis = var_30, x = scores_27_cast_fp16)[name = tensor<string, []>("op_1366_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_345_cast_fp16 = select(a = var_11_to_fp16, b = var_1366_cast_fp16, cond = mask_3)[name = tensor<string, []>("input_345_cast_fp16")];
            tensor<bool, []> x_145_transpose_x_0 = const()[name = tensor<string, []>("x_145_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_145_transpose_y_0 = const()[name = tensor<string, []>("x_145_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 188, 128]> value_15_cast_fp16 = transpose(perm = value_15_perm_0, x = v_13_cast_fp16)[name = tensor<string, []>("transpose_341")];
            tensor<fp16, [1, 8, 188, 128]> x_145_cast_fp16 = matmul(transpose_x = x_145_transpose_x_0, transpose_y = x_145_transpose_y_0, x = input_345_cast_fp16, y = value_15_cast_fp16)[name = tensor<string, []>("x_145_cast_fp16")];
            tensor<int32, [4]> var_1370_perm_0 = const()[name = tensor<string, []>("op_1370_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1371 = const()[name = tensor<string, []>("op_1371"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_1370_cast_fp16 = transpose(perm = var_1370_perm_0, x = x_145_cast_fp16)[name = tensor<string, []>("transpose_337")];
            tensor<fp16, [1, 188, 1024]> input_347_cast_fp16 = reshape(shape = var_1371, x = var_1370_cast_fp16)[name = tensor<string, []>("input_347_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_6_self_attn_linear_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_6_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(327044096)))];
            tensor<fp16, [1024]> encoder_layers_6_self_attn_linear_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_6_self_attn_linear_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(329141312)))];
            tensor<fp16, [1, 188, 1024]> linear_61_cast_fp16 = linear(bias = encoder_layers_6_self_attn_linear_out_bias_to_fp16, weight = encoder_layers_6_self_attn_linear_out_weight_to_fp16, x = input_347_cast_fp16)[name = tensor<string, []>("linear_61_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_351_cast_fp16 = add(x = input_343_cast_fp16, y = linear_61_cast_fp16)[name = tensor<string, []>("input_351_cast_fp16")];
            tensor<int32, [1]> x_149_axes_0 = const()[name = tensor<string, []>("x_149_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_6_norm_conv_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_6_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(329143424)))];
            tensor<fp16, [1024]> encoder_layers_6_norm_conv_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_6_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(329145536)))];
            tensor<fp16, [1, 188, 1024]> x_149_cast_fp16 = layer_norm(axes = x_149_axes_0, beta = encoder_layers_6_norm_conv_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_6_norm_conv_weight_to_fp16, x = input_351_cast_fp16)[name = tensor<string, []>("x_149_cast_fp16")];
            tensor<int32, [3]> input_353_perm_0 = const()[name = tensor<string, []>("input_353_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> input_355_pad_type_0 = const()[name = tensor<string, []>("input_355_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_355_strides_0 = const()[name = tensor<string, []>("input_355_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_355_pad_0 = const()[name = tensor<string, []>("input_355_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_355_dilations_0 = const()[name = tensor<string, []>("input_355_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_355_groups_0 = const()[name = tensor<string, []>("input_355_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [2048, 1024, 1]> encoder_layers_6_conv_pointwise_conv1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_6_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(329147648)))];
            tensor<fp16, [2048]> encoder_layers_6_conv_pointwise_conv1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_6_conv_pointwise_conv1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(333342016)))];
            tensor<fp16, [1, 1024, 188]> input_353_cast_fp16 = transpose(perm = input_353_perm_0, x = x_149_cast_fp16)[name = tensor<string, []>("transpose_336")];
            tensor<fp16, [1, 2048, 188]> input_355_cast_fp16 = conv(bias = encoder_layers_6_conv_pointwise_conv1_bias_to_fp16, dilations = input_355_dilations_0, groups = input_355_groups_0, pad = input_355_pad_0, pad_type = input_355_pad_type_0, strides = input_355_strides_0, weight = encoder_layers_6_conv_pointwise_conv1_weight_to_fp16, x = input_353_cast_fp16)[name = tensor<string, []>("input_355_cast_fp16")];
            tensor<int32, []> x_151_split_num_splits_0 = const()[name = tensor<string, []>("x_151_split_num_splits_0"), val = tensor<int32, []>(2)];
            tensor<int32, []> x_151_split_axis_0 = const()[name = tensor<string, []>("x_151_split_axis_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1, 1024, 188]> x_151_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_151_split_cast_fp16_1 = split(axis = x_151_split_axis_0, num_splits = x_151_split_num_splits_0, x = input_355_cast_fp16)[name = tensor<string, []>("x_151_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_151_split_1_sigmoid_cast_fp16 = sigmoid(x = x_151_split_cast_fp16_1)[name = tensor<string, []>("x_151_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_151_cast_fp16 = mul(x = x_151_split_cast_fp16_0, y = x_151_split_1_sigmoid_cast_fp16)[name = tensor<string, []>("x_151_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_357_cast_fp16 = select(a = var_11_to_fp16, b = x_151_cast_fp16, cond = var_351)[name = tensor<string, []>("input_357_cast_fp16")];
            tensor<int32, [6]> input_359_pad_0 = const()[name = tensor<string, []>("input_359_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            tensor<string, []> input_359_mode_0 = const()[name = tensor<string, []>("input_359_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_77_to_fp16 = const()[name = tensor<string, []>("const_77_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_359_cast_fp16 = pad(constant_val = const_77_to_fp16, mode = input_359_mode_0, pad = input_359_pad_0, x = input_357_cast_fp16)[name = tensor<string, []>("input_359_cast_fp16")];
            tensor<string, []> input_361_pad_type_0 = const()[name = tensor<string, []>("input_361_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, []> input_361_groups_0 = const()[name = tensor<string, []>("input_361_groups_0"), val = tensor<int32, []>(1024)];
            tensor<int32, [1]> input_361_strides_0 = const()[name = tensor<string, []>("input_361_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_361_pad_0 = const()[name = tensor<string, []>("input_361_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_361_dilations_0 = const()[name = tensor<string, []>("input_361_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_340_to_fp16 = const()[name = tensor<string, []>("const_340_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(333346176)))];
            tensor<fp16, [1024]> const_341_to_fp16 = const()[name = tensor<string, []>("const_341_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(333364672)))];
            tensor<fp16, [1, 1024, 188]> input_363_cast_fp16 = conv(bias = const_341_to_fp16, dilations = input_361_dilations_0, groups = input_361_groups_0, pad = input_361_pad_0, pad_type = input_361_pad_type_0, strides = input_361_strides_0, weight = const_340_to_fp16, x = input_359_cast_fp16)[name = tensor<string, []>("input_363_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_365_cast_fp16 = silu(x = input_363_cast_fp16)[name = tensor<string, []>("input_365_cast_fp16")];
            tensor<string, []> x_153_pad_type_0 = const()[name = tensor<string, []>("x_153_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> x_153_strides_0 = const()[name = tensor<string, []>("x_153_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_153_pad_0 = const()[name = tensor<string, []>("x_153_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_153_dilations_0 = const()[name = tensor<string, []>("x_153_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> x_153_groups_0 = const()[name = tensor<string, []>("x_153_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1024, 1024, 1]> encoder_layers_6_conv_pointwise_conv2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_6_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(333366784)))];
            tensor<fp16, [1024]> encoder_layers_6_conv_pointwise_conv2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_6_conv_pointwise_conv2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(335464000)))];
            tensor<fp16, [1, 1024, 188]> x_153_cast_fp16 = conv(bias = encoder_layers_6_conv_pointwise_conv2_bias_to_fp16, dilations = x_153_dilations_0, groups = x_153_groups_0, pad = x_153_pad_0, pad_type = x_153_pad_type_0, strides = x_153_strides_0, weight = encoder_layers_6_conv_pointwise_conv2_weight_to_fp16, x = input_365_cast_fp16)[name = tensor<string, []>("x_153_cast_fp16")];
            tensor<int32, [3]> input_367_perm_0 = const()[name = tensor<string, []>("input_367_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_367_cast_fp16 = transpose(perm = input_367_perm_0, x = x_153_cast_fp16)[name = tensor<string, []>("transpose_335")];
            tensor<fp16, [1, 188, 1024]> input_369_cast_fp16 = add(x = input_351_cast_fp16, y = input_367_cast_fp16)[name = tensor<string, []>("input_369_cast_fp16")];
            tensor<int32, [1]> input_371_axes_0 = const()[name = tensor<string, []>("input_371_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_6_norm_feed_forward2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_6_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(335466112)))];
            tensor<fp16, [1024]> encoder_layers_6_norm_feed_forward2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_6_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(335468224)))];
            tensor<fp16, [1, 188, 1024]> input_371_cast_fp16 = layer_norm(axes = input_371_axes_0, beta = encoder_layers_6_norm_feed_forward2_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_6_norm_feed_forward2_weight_to_fp16, x = input_369_cast_fp16)[name = tensor<string, []>("input_371_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_6_feed_forward2_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_6_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(335470336)))];
            tensor<fp16, [4096]> encoder_layers_6_feed_forward2_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_6_feed_forward2_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(343859008)))];
            tensor<fp16, [1, 188, 4096]> linear_62_cast_fp16 = linear(bias = encoder_layers_6_feed_forward2_linear1_bias_to_fp16, weight = encoder_layers_6_feed_forward2_linear1_weight_to_fp16, x = input_371_cast_fp16)[name = tensor<string, []>("linear_62_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_375_cast_fp16 = silu(x = linear_62_cast_fp16)[name = tensor<string, []>("input_375_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_6_feed_forward2_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_6_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(343867264)))];
            tensor<fp16, [1024]> encoder_layers_6_feed_forward2_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_6_feed_forward2_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(352255936)))];
            tensor<fp16, [1, 188, 1024]> linear_63_cast_fp16 = linear(bias = encoder_layers_6_feed_forward2_linear2_bias_to_fp16, weight = encoder_layers_6_feed_forward2_linear2_weight_to_fp16, x = input_375_cast_fp16)[name = tensor<string, []>("linear_63_cast_fp16")];
            tensor<fp16, []> var_1437_to_fp16 = const()[name = tensor<string, []>("op_1437_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_1438_cast_fp16 = mul(x = linear_63_cast_fp16, y = var_1437_to_fp16)[name = tensor<string, []>("op_1438_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_381_cast_fp16 = add(x = input_369_cast_fp16, y = var_1438_cast_fp16)[name = tensor<string, []>("input_381_cast_fp16")];
            tensor<int32, [1]> input_383_axes_0 = const()[name = tensor<string, []>("input_383_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_6_norm_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_6_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(352258048)))];
            tensor<fp16, [1024]> encoder_layers_6_norm_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_6_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(352260160)))];
            tensor<fp16, [1, 188, 1024]> input_383_cast_fp16 = layer_norm(axes = input_383_axes_0, beta = encoder_layers_6_norm_out_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_6_norm_out_weight_to_fp16, x = input_381_cast_fp16)[name = tensor<string, []>("input_383_cast_fp16")];
            tensor<int32, [1]> input_385_axes_0 = const()[name = tensor<string, []>("input_385_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_7_norm_feed_forward1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_7_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(352262272)))];
            tensor<fp16, [1024]> encoder_layers_7_norm_feed_forward1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_7_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(352264384)))];
            tensor<fp16, [1, 188, 1024]> input_385_cast_fp16 = layer_norm(axes = input_385_axes_0, beta = encoder_layers_7_norm_feed_forward1_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_7_norm_feed_forward1_weight_to_fp16, x = input_383_cast_fp16)[name = tensor<string, []>("input_385_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_7_feed_forward1_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_7_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(352266496)))];
            tensor<fp16, [4096]> encoder_layers_7_feed_forward1_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_7_feed_forward1_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(360655168)))];
            tensor<fp16, [1, 188, 4096]> linear_64_cast_fp16 = linear(bias = encoder_layers_7_feed_forward1_linear1_bias_to_fp16, weight = encoder_layers_7_feed_forward1_linear1_weight_to_fp16, x = input_385_cast_fp16)[name = tensor<string, []>("linear_64_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_389_cast_fp16 = silu(x = linear_64_cast_fp16)[name = tensor<string, []>("input_389_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_7_feed_forward1_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_7_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(360663424)))];
            tensor<fp16, [1024]> encoder_layers_7_feed_forward1_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_7_feed_forward1_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(369052096)))];
            tensor<fp16, [1, 188, 1024]> linear_65_cast_fp16 = linear(bias = encoder_layers_7_feed_forward1_linear2_bias_to_fp16, weight = encoder_layers_7_feed_forward1_linear2_weight_to_fp16, x = input_389_cast_fp16)[name = tensor<string, []>("linear_65_cast_fp16")];
            tensor<fp16, []> var_1468_to_fp16 = const()[name = tensor<string, []>("op_1468_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_1469_cast_fp16 = mul(x = linear_65_cast_fp16, y = var_1468_to_fp16)[name = tensor<string, []>("op_1469_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_395_cast_fp16 = add(x = input_383_cast_fp16, y = var_1469_cast_fp16)[name = tensor<string, []>("input_395_cast_fp16")];
            tensor<int32, [1]> query_15_axes_0 = const()[name = tensor<string, []>("query_15_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_7_norm_self_att_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_7_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(369054208)))];
            tensor<fp16, [1024]> encoder_layers_7_norm_self_att_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_7_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(369056320)))];
            tensor<fp16, [1, 188, 1024]> query_15_cast_fp16 = layer_norm(axes = query_15_axes_0, beta = encoder_layers_7_norm_self_att_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_7_norm_self_att_weight_to_fp16, x = input_395_cast_fp16)[name = tensor<string, []>("query_15_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_7_self_attn_linear_q_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_7_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(369058432)))];
            tensor<fp16, [1024]> encoder_layers_7_self_attn_linear_q_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_7_self_attn_linear_q_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(371155648)))];
            tensor<fp16, [1, 188, 1024]> linear_66_cast_fp16 = linear(bias = encoder_layers_7_self_attn_linear_q_bias_to_fp16, weight = encoder_layers_7_self_attn_linear_q_weight_to_fp16, x = query_15_cast_fp16)[name = tensor<string, []>("linear_66_cast_fp16")];
            tensor<int32, [4]> var_1486 = const()[name = tensor<string, []>("op_1486"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_43_cast_fp16 = reshape(shape = var_1486, x = linear_66_cast_fp16)[name = tensor<string, []>("q_43_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_7_self_attn_linear_k_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_7_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(371157760)))];
            tensor<fp16, [1024]> encoder_layers_7_self_attn_linear_k_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_7_self_attn_linear_k_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(373254976)))];
            tensor<fp16, [1, 188, 1024]> linear_67_cast_fp16 = linear(bias = encoder_layers_7_self_attn_linear_k_bias_to_fp16, weight = encoder_layers_7_self_attn_linear_k_weight_to_fp16, x = query_15_cast_fp16)[name = tensor<string, []>("linear_67_cast_fp16")];
            tensor<int32, [4]> var_1491 = const()[name = tensor<string, []>("op_1491"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_29_cast_fp16 = reshape(shape = var_1491, x = linear_67_cast_fp16)[name = tensor<string, []>("k_29_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_7_self_attn_linear_v_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_7_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(373257088)))];
            tensor<fp16, [1024]> encoder_layers_7_self_attn_linear_v_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_7_self_attn_linear_v_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(375354304)))];
            tensor<fp16, [1, 188, 1024]> linear_68_cast_fp16 = linear(bias = encoder_layers_7_self_attn_linear_v_bias_to_fp16, weight = encoder_layers_7_self_attn_linear_v_weight_to_fp16, x = query_15_cast_fp16)[name = tensor<string, []>("linear_68_cast_fp16")];
            tensor<int32, [4]> var_1496 = const()[name = tensor<string, []>("op_1496"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_15_cast_fp16 = reshape(shape = var_1496, x = linear_68_cast_fp16)[name = tensor<string, []>("v_15_cast_fp16")];
            tensor<int32, [4]> value_17_perm_0 = const()[name = tensor<string, []>("value_17_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> encoder_layers_7_self_attn_pos_bias_u_to_fp16 = const()[name = tensor<string, []>("encoder_layers_7_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(375356416)))];
            tensor<fp16, [1, 188, 8, 128]> var_1508_cast_fp16 = add(x = q_43_cast_fp16, y = encoder_layers_7_self_attn_pos_bias_u_to_fp16)[name = tensor<string, []>("op_1508_cast_fp16")];
            tensor<fp16, [8, 128]> encoder_layers_7_self_attn_pos_bias_v_to_fp16 = const()[name = tensor<string, []>("encoder_layers_7_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(375358528)))];
            tensor<fp16, [1, 188, 8, 128]> var_1510_cast_fp16 = add(x = q_43_cast_fp16, y = encoder_layers_7_self_attn_pos_bias_v_to_fp16)[name = tensor<string, []>("op_1510_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_15_perm_0 = const()[name = tensor<string, []>("q_with_bias_v_15_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<bool, []> x_161_transpose_x_0 = const()[name = tensor<string, []>("x_161_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_161_transpose_y_0 = const()[name = tensor<string, []>("x_161_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 128, 375]> var_1512_to_fp16 = const()[name = tensor<string, []>("op_1512_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(375360640)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_15_cast_fp16 = transpose(perm = q_with_bias_v_15_perm_0, x = var_1510_cast_fp16)[name = tensor<string, []>("transpose_333")];
            tensor<fp16, [1, 8, 188, 375]> x_161_cast_fp16 = matmul(transpose_x = x_161_transpose_x_0, transpose_y = x_161_transpose_y_0, x = q_with_bias_v_15_cast_fp16, y = var_1512_to_fp16)[name = tensor<string, []>("x_161_cast_fp16")];
            tensor<int32, [8]> x_163_pad_0 = const()[name = tensor<string, []>("x_163_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            tensor<string, []> x_163_mode_0 = const()[name = tensor<string, []>("x_163_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_84_to_fp16 = const()[name = tensor<string, []>("const_84_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_163_cast_fp16 = pad(constant_val = const_84_to_fp16, mode = x_163_mode_0, pad = x_163_pad_0, x = x_161_cast_fp16)[name = tensor<string, []>("x_163_cast_fp16")];
            tensor<int32, [4]> var_1520 = const()[name = tensor<string, []>("op_1520"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_165_cast_fp16 = reshape(shape = var_1520, x = x_163_cast_fp16)[name = tensor<string, []>("x_165_cast_fp16")];
            tensor<int32, [4]> var_1524_begin_0 = const()[name = tensor<string, []>("op_1524_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_1524_end_0 = const()[name = tensor<string, []>("op_1524_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_1524_end_mask_0 = const()[name = tensor<string, []>("op_1524_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_1524_cast_fp16 = slice_by_index(begin = var_1524_begin_0, end = var_1524_end_0, end_mask = var_1524_end_mask_0, x = x_165_cast_fp16)[name = tensor<string, []>("op_1524_cast_fp16")];
            tensor<int32, [4]> var_1525 = const()[name = tensor<string, []>("op_1525"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_29_cast_fp16 = reshape(shape = var_1525, x = var_1524_cast_fp16)[name = tensor<string, []>("matrix_bd_29_cast_fp16")];
            tensor<bool, []> matrix_ac_15_transpose_x_0 = const()[name = tensor<string, []>("matrix_ac_15_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> matrix_ac_15_transpose_y_0 = const()[name = tensor<string, []>("matrix_ac_15_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<int32, [4]> transpose_110_perm_0 = const()[name = tensor<string, []>("transpose_110_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_111_perm_0 = const()[name = tensor<string, []>("transpose_111_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_111 = transpose(perm = transpose_111_perm_0, x = k_29_cast_fp16)[name = tensor<string, []>("transpose_331")];
            tensor<fp16, [1, 8, 188, 128]> transpose_110 = transpose(perm = transpose_110_perm_0, x = var_1508_cast_fp16)[name = tensor<string, []>("transpose_332")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_15_cast_fp16 = matmul(transpose_x = matrix_ac_15_transpose_x_0, transpose_y = matrix_ac_15_transpose_y_0, x = transpose_110, y = transpose_111)[name = tensor<string, []>("matrix_ac_15_cast_fp16")];
            tensor<int32, [4]> matrix_bd_31_begin_0 = const()[name = tensor<string, []>("matrix_bd_31_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_31_end_0 = const()[name = tensor<string, []>("matrix_bd_31_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_31_end_mask_0 = const()[name = tensor<string, []>("matrix_bd_31_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_31_cast_fp16 = slice_by_index(begin = matrix_bd_31_begin_0, end = matrix_bd_31_end_0, end_mask = matrix_bd_31_end_mask_0, x = matrix_bd_29_cast_fp16)[name = tensor<string, []>("matrix_bd_31_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_1534_cast_fp16 = add(x = matrix_ac_15_cast_fp16, y = matrix_bd_31_cast_fp16)[name = tensor<string, []>("op_1534_cast_fp16")];
            tensor<fp16, []> _inversed_scores_29_y_0_to_fp16 = const()[name = tensor<string, []>("_inversed_scores_29_y_0_to_fp16"), val = tensor<fp16, []>(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_29_cast_fp16 = mul(x = var_1534_cast_fp16, y = _inversed_scores_29_y_0_to_fp16)[name = tensor<string, []>("_inversed_scores_29_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_31_cast_fp16 = select(a = var_12_to_fp16, b = _inversed_scores_29_cast_fp16, cond = mask_3)[name = tensor<string, []>("scores_31_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_1540_cast_fp16 = softmax(axis = var_30, x = scores_31_cast_fp16)[name = tensor<string, []>("op_1540_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_397_cast_fp16 = select(a = var_11_to_fp16, b = var_1540_cast_fp16, cond = mask_3)[name = tensor<string, []>("input_397_cast_fp16")];
            tensor<bool, []> x_167_transpose_x_0 = const()[name = tensor<string, []>("x_167_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_167_transpose_y_0 = const()[name = tensor<string, []>("x_167_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 188, 128]> value_17_cast_fp16 = transpose(perm = value_17_perm_0, x = v_15_cast_fp16)[name = tensor<string, []>("transpose_334")];
            tensor<fp16, [1, 8, 188, 128]> x_167_cast_fp16 = matmul(transpose_x = x_167_transpose_x_0, transpose_y = x_167_transpose_y_0, x = input_397_cast_fp16, y = value_17_cast_fp16)[name = tensor<string, []>("x_167_cast_fp16")];
            tensor<int32, [4]> var_1544_perm_0 = const()[name = tensor<string, []>("op_1544_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1545 = const()[name = tensor<string, []>("op_1545"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_1544_cast_fp16 = transpose(perm = var_1544_perm_0, x = x_167_cast_fp16)[name = tensor<string, []>("transpose_330")];
            tensor<fp16, [1, 188, 1024]> input_399_cast_fp16 = reshape(shape = var_1545, x = var_1544_cast_fp16)[name = tensor<string, []>("input_399_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_7_self_attn_linear_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_7_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(376128704)))];
            tensor<fp16, [1024]> encoder_layers_7_self_attn_linear_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_7_self_attn_linear_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(378225920)))];
            tensor<fp16, [1, 188, 1024]> linear_70_cast_fp16 = linear(bias = encoder_layers_7_self_attn_linear_out_bias_to_fp16, weight = encoder_layers_7_self_attn_linear_out_weight_to_fp16, x = input_399_cast_fp16)[name = tensor<string, []>("linear_70_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_403_cast_fp16 = add(x = input_395_cast_fp16, y = linear_70_cast_fp16)[name = tensor<string, []>("input_403_cast_fp16")];
            tensor<int32, [1]> x_171_axes_0 = const()[name = tensor<string, []>("x_171_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_7_norm_conv_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_7_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(378228032)))];
            tensor<fp16, [1024]> encoder_layers_7_norm_conv_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_7_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(378230144)))];
            tensor<fp16, [1, 188, 1024]> x_171_cast_fp16 = layer_norm(axes = x_171_axes_0, beta = encoder_layers_7_norm_conv_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_7_norm_conv_weight_to_fp16, x = input_403_cast_fp16)[name = tensor<string, []>("x_171_cast_fp16")];
            tensor<int32, [3]> input_405_perm_0 = const()[name = tensor<string, []>("input_405_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> input_407_pad_type_0 = const()[name = tensor<string, []>("input_407_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_407_strides_0 = const()[name = tensor<string, []>("input_407_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_407_pad_0 = const()[name = tensor<string, []>("input_407_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_407_dilations_0 = const()[name = tensor<string, []>("input_407_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_407_groups_0 = const()[name = tensor<string, []>("input_407_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [2048, 1024, 1]> encoder_layers_7_conv_pointwise_conv1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_7_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(378232256)))];
            tensor<fp16, [2048]> encoder_layers_7_conv_pointwise_conv1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_7_conv_pointwise_conv1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(382426624)))];
            tensor<fp16, [1, 1024, 188]> input_405_cast_fp16 = transpose(perm = input_405_perm_0, x = x_171_cast_fp16)[name = tensor<string, []>("transpose_329")];
            tensor<fp16, [1, 2048, 188]> input_407_cast_fp16 = conv(bias = encoder_layers_7_conv_pointwise_conv1_bias_to_fp16, dilations = input_407_dilations_0, groups = input_407_groups_0, pad = input_407_pad_0, pad_type = input_407_pad_type_0, strides = input_407_strides_0, weight = encoder_layers_7_conv_pointwise_conv1_weight_to_fp16, x = input_405_cast_fp16)[name = tensor<string, []>("input_407_cast_fp16")];
            tensor<int32, []> x_173_split_num_splits_0 = const()[name = tensor<string, []>("x_173_split_num_splits_0"), val = tensor<int32, []>(2)];
            tensor<int32, []> x_173_split_axis_0 = const()[name = tensor<string, []>("x_173_split_axis_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1, 1024, 188]> x_173_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_173_split_cast_fp16_1 = split(axis = x_173_split_axis_0, num_splits = x_173_split_num_splits_0, x = input_407_cast_fp16)[name = tensor<string, []>("x_173_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_173_split_1_sigmoid_cast_fp16 = sigmoid(x = x_173_split_cast_fp16_1)[name = tensor<string, []>("x_173_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_173_cast_fp16 = mul(x = x_173_split_cast_fp16_0, y = x_173_split_1_sigmoid_cast_fp16)[name = tensor<string, []>("x_173_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_409_cast_fp16 = select(a = var_11_to_fp16, b = x_173_cast_fp16, cond = var_351)[name = tensor<string, []>("input_409_cast_fp16")];
            tensor<int32, [6]> input_411_pad_0 = const()[name = tensor<string, []>("input_411_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            tensor<string, []> input_411_mode_0 = const()[name = tensor<string, []>("input_411_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_87_to_fp16 = const()[name = tensor<string, []>("const_87_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_411_cast_fp16 = pad(constant_val = const_87_to_fp16, mode = input_411_mode_0, pad = input_411_pad_0, x = input_409_cast_fp16)[name = tensor<string, []>("input_411_cast_fp16")];
            tensor<string, []> input_413_pad_type_0 = const()[name = tensor<string, []>("input_413_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, []> input_413_groups_0 = const()[name = tensor<string, []>("input_413_groups_0"), val = tensor<int32, []>(1024)];
            tensor<int32, [1]> input_413_strides_0 = const()[name = tensor<string, []>("input_413_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_413_pad_0 = const()[name = tensor<string, []>("input_413_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_413_dilations_0 = const()[name = tensor<string, []>("input_413_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_342_to_fp16 = const()[name = tensor<string, []>("const_342_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(382430784)))];
            tensor<fp16, [1024]> const_343_to_fp16 = const()[name = tensor<string, []>("const_343_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(382449280)))];
            tensor<fp16, [1, 1024, 188]> input_415_cast_fp16 = conv(bias = const_343_to_fp16, dilations = input_413_dilations_0, groups = input_413_groups_0, pad = input_413_pad_0, pad_type = input_413_pad_type_0, strides = input_413_strides_0, weight = const_342_to_fp16, x = input_411_cast_fp16)[name = tensor<string, []>("input_415_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_417_cast_fp16 = silu(x = input_415_cast_fp16)[name = tensor<string, []>("input_417_cast_fp16")];
            tensor<string, []> x_175_pad_type_0 = const()[name = tensor<string, []>("x_175_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> x_175_strides_0 = const()[name = tensor<string, []>("x_175_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_175_pad_0 = const()[name = tensor<string, []>("x_175_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_175_dilations_0 = const()[name = tensor<string, []>("x_175_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> x_175_groups_0 = const()[name = tensor<string, []>("x_175_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1024, 1024, 1]> encoder_layers_7_conv_pointwise_conv2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_7_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(382451392)))];
            tensor<fp16, [1024]> encoder_layers_7_conv_pointwise_conv2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_7_conv_pointwise_conv2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(384548608)))];
            tensor<fp16, [1, 1024, 188]> x_175_cast_fp16 = conv(bias = encoder_layers_7_conv_pointwise_conv2_bias_to_fp16, dilations = x_175_dilations_0, groups = x_175_groups_0, pad = x_175_pad_0, pad_type = x_175_pad_type_0, strides = x_175_strides_0, weight = encoder_layers_7_conv_pointwise_conv2_weight_to_fp16, x = input_417_cast_fp16)[name = tensor<string, []>("x_175_cast_fp16")];
            tensor<int32, [3]> input_419_perm_0 = const()[name = tensor<string, []>("input_419_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_419_cast_fp16 = transpose(perm = input_419_perm_0, x = x_175_cast_fp16)[name = tensor<string, []>("transpose_328")];
            tensor<fp16, [1, 188, 1024]> input_421_cast_fp16 = add(x = input_403_cast_fp16, y = input_419_cast_fp16)[name = tensor<string, []>("input_421_cast_fp16")];
            tensor<int32, [1]> input_423_axes_0 = const()[name = tensor<string, []>("input_423_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_7_norm_feed_forward2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_7_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(384550720)))];
            tensor<fp16, [1024]> encoder_layers_7_norm_feed_forward2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_7_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(384552832)))];
            tensor<fp16, [1, 188, 1024]> input_423_cast_fp16 = layer_norm(axes = input_423_axes_0, beta = encoder_layers_7_norm_feed_forward2_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_7_norm_feed_forward2_weight_to_fp16, x = input_421_cast_fp16)[name = tensor<string, []>("input_423_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_7_feed_forward2_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_7_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(384554944)))];
            tensor<fp16, [4096]> encoder_layers_7_feed_forward2_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_7_feed_forward2_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(392943616)))];
            tensor<fp16, [1, 188, 4096]> linear_71_cast_fp16 = linear(bias = encoder_layers_7_feed_forward2_linear1_bias_to_fp16, weight = encoder_layers_7_feed_forward2_linear1_weight_to_fp16, x = input_423_cast_fp16)[name = tensor<string, []>("linear_71_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_427_cast_fp16 = silu(x = linear_71_cast_fp16)[name = tensor<string, []>("input_427_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_7_feed_forward2_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_7_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(392951872)))];
            tensor<fp16, [1024]> encoder_layers_7_feed_forward2_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_7_feed_forward2_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(401340544)))];
            tensor<fp16, [1, 188, 1024]> linear_72_cast_fp16 = linear(bias = encoder_layers_7_feed_forward2_linear2_bias_to_fp16, weight = encoder_layers_7_feed_forward2_linear2_weight_to_fp16, x = input_427_cast_fp16)[name = tensor<string, []>("linear_72_cast_fp16")];
            tensor<fp16, []> var_1611_to_fp16 = const()[name = tensor<string, []>("op_1611_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_1612_cast_fp16 = mul(x = linear_72_cast_fp16, y = var_1611_to_fp16)[name = tensor<string, []>("op_1612_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_433_cast_fp16 = add(x = input_421_cast_fp16, y = var_1612_cast_fp16)[name = tensor<string, []>("input_433_cast_fp16")];
            tensor<int32, [1]> input_435_axes_0 = const()[name = tensor<string, []>("input_435_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_7_norm_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_7_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(401342656)))];
            tensor<fp16, [1024]> encoder_layers_7_norm_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_7_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(401344768)))];
            tensor<fp16, [1, 188, 1024]> input_435_cast_fp16 = layer_norm(axes = input_435_axes_0, beta = encoder_layers_7_norm_out_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_7_norm_out_weight_to_fp16, x = input_433_cast_fp16)[name = tensor<string, []>("input_435_cast_fp16")];
            tensor<int32, [1]> input_437_axes_0 = const()[name = tensor<string, []>("input_437_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_8_norm_feed_forward1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_8_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(401346880)))];
            tensor<fp16, [1024]> encoder_layers_8_norm_feed_forward1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_8_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(401348992)))];
            tensor<fp16, [1, 188, 1024]> input_437_cast_fp16 = layer_norm(axes = input_437_axes_0, beta = encoder_layers_8_norm_feed_forward1_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_8_norm_feed_forward1_weight_to_fp16, x = input_435_cast_fp16)[name = tensor<string, []>("input_437_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_8_feed_forward1_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_8_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(401351104)))];
            tensor<fp16, [4096]> encoder_layers_8_feed_forward1_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_8_feed_forward1_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(409739776)))];
            tensor<fp16, [1, 188, 4096]> linear_73_cast_fp16 = linear(bias = encoder_layers_8_feed_forward1_linear1_bias_to_fp16, weight = encoder_layers_8_feed_forward1_linear1_weight_to_fp16, x = input_437_cast_fp16)[name = tensor<string, []>("linear_73_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_441_cast_fp16 = silu(x = linear_73_cast_fp16)[name = tensor<string, []>("input_441_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_8_feed_forward1_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_8_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(409748032)))];
            tensor<fp16, [1024]> encoder_layers_8_feed_forward1_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_8_feed_forward1_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(418136704)))];
            tensor<fp16, [1, 188, 1024]> linear_74_cast_fp16 = linear(bias = encoder_layers_8_feed_forward1_linear2_bias_to_fp16, weight = encoder_layers_8_feed_forward1_linear2_weight_to_fp16, x = input_441_cast_fp16)[name = tensor<string, []>("linear_74_cast_fp16")];
            tensor<fp16, []> var_1642_to_fp16 = const()[name = tensor<string, []>("op_1642_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_1643_cast_fp16 = mul(x = linear_74_cast_fp16, y = var_1642_to_fp16)[name = tensor<string, []>("op_1643_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_447_cast_fp16 = add(x = input_435_cast_fp16, y = var_1643_cast_fp16)[name = tensor<string, []>("input_447_cast_fp16")];
            tensor<int32, [1]> query_17_axes_0 = const()[name = tensor<string, []>("query_17_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_8_norm_self_att_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_8_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(418138816)))];
            tensor<fp16, [1024]> encoder_layers_8_norm_self_att_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_8_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(418140928)))];
            tensor<fp16, [1, 188, 1024]> query_17_cast_fp16 = layer_norm(axes = query_17_axes_0, beta = encoder_layers_8_norm_self_att_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_8_norm_self_att_weight_to_fp16, x = input_447_cast_fp16)[name = tensor<string, []>("query_17_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_8_self_attn_linear_q_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_8_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(418143040)))];
            tensor<fp16, [1024]> encoder_layers_8_self_attn_linear_q_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_8_self_attn_linear_q_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(420240256)))];
            tensor<fp16, [1, 188, 1024]> linear_75_cast_fp16 = linear(bias = encoder_layers_8_self_attn_linear_q_bias_to_fp16, weight = encoder_layers_8_self_attn_linear_q_weight_to_fp16, x = query_17_cast_fp16)[name = tensor<string, []>("linear_75_cast_fp16")];
            tensor<int32, [4]> var_1660 = const()[name = tensor<string, []>("op_1660"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_49_cast_fp16 = reshape(shape = var_1660, x = linear_75_cast_fp16)[name = tensor<string, []>("q_49_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_8_self_attn_linear_k_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_8_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(420242368)))];
            tensor<fp16, [1024]> encoder_layers_8_self_attn_linear_k_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_8_self_attn_linear_k_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(422339584)))];
            tensor<fp16, [1, 188, 1024]> linear_76_cast_fp16 = linear(bias = encoder_layers_8_self_attn_linear_k_bias_to_fp16, weight = encoder_layers_8_self_attn_linear_k_weight_to_fp16, x = query_17_cast_fp16)[name = tensor<string, []>("linear_76_cast_fp16")];
            tensor<int32, [4]> var_1665 = const()[name = tensor<string, []>("op_1665"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_33_cast_fp16 = reshape(shape = var_1665, x = linear_76_cast_fp16)[name = tensor<string, []>("k_33_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_8_self_attn_linear_v_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_8_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(422341696)))];
            tensor<fp16, [1024]> encoder_layers_8_self_attn_linear_v_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_8_self_attn_linear_v_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(424438912)))];
            tensor<fp16, [1, 188, 1024]> linear_77_cast_fp16 = linear(bias = encoder_layers_8_self_attn_linear_v_bias_to_fp16, weight = encoder_layers_8_self_attn_linear_v_weight_to_fp16, x = query_17_cast_fp16)[name = tensor<string, []>("linear_77_cast_fp16")];
            tensor<int32, [4]> var_1670 = const()[name = tensor<string, []>("op_1670"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_17_cast_fp16 = reshape(shape = var_1670, x = linear_77_cast_fp16)[name = tensor<string, []>("v_17_cast_fp16")];
            tensor<int32, [4]> value_19_perm_0 = const()[name = tensor<string, []>("value_19_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> encoder_layers_8_self_attn_pos_bias_u_to_fp16 = const()[name = tensor<string, []>("encoder_layers_8_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(424441024)))];
            tensor<fp16, [1, 188, 8, 128]> var_1682_cast_fp16 = add(x = q_49_cast_fp16, y = encoder_layers_8_self_attn_pos_bias_u_to_fp16)[name = tensor<string, []>("op_1682_cast_fp16")];
            tensor<fp16, [8, 128]> encoder_layers_8_self_attn_pos_bias_v_to_fp16 = const()[name = tensor<string, []>("encoder_layers_8_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(424443136)))];
            tensor<fp16, [1, 188, 8, 128]> var_1684_cast_fp16 = add(x = q_49_cast_fp16, y = encoder_layers_8_self_attn_pos_bias_v_to_fp16)[name = tensor<string, []>("op_1684_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_17_perm_0 = const()[name = tensor<string, []>("q_with_bias_v_17_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<bool, []> x_183_transpose_x_0 = const()[name = tensor<string, []>("x_183_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_183_transpose_y_0 = const()[name = tensor<string, []>("x_183_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 128, 375]> var_1686_to_fp16 = const()[name = tensor<string, []>("op_1686_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(424445248)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_17_cast_fp16 = transpose(perm = q_with_bias_v_17_perm_0, x = var_1684_cast_fp16)[name = tensor<string, []>("transpose_326")];
            tensor<fp16, [1, 8, 188, 375]> x_183_cast_fp16 = matmul(transpose_x = x_183_transpose_x_0, transpose_y = x_183_transpose_y_0, x = q_with_bias_v_17_cast_fp16, y = var_1686_to_fp16)[name = tensor<string, []>("x_183_cast_fp16")];
            tensor<int32, [8]> x_185_pad_0 = const()[name = tensor<string, []>("x_185_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            tensor<string, []> x_185_mode_0 = const()[name = tensor<string, []>("x_185_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_94_to_fp16 = const()[name = tensor<string, []>("const_94_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_185_cast_fp16 = pad(constant_val = const_94_to_fp16, mode = x_185_mode_0, pad = x_185_pad_0, x = x_183_cast_fp16)[name = tensor<string, []>("x_185_cast_fp16")];
            tensor<int32, [4]> var_1694 = const()[name = tensor<string, []>("op_1694"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_187_cast_fp16 = reshape(shape = var_1694, x = x_185_cast_fp16)[name = tensor<string, []>("x_187_cast_fp16")];
            tensor<int32, [4]> var_1698_begin_0 = const()[name = tensor<string, []>("op_1698_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_1698_end_0 = const()[name = tensor<string, []>("op_1698_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_1698_end_mask_0 = const()[name = tensor<string, []>("op_1698_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_1698_cast_fp16 = slice_by_index(begin = var_1698_begin_0, end = var_1698_end_0, end_mask = var_1698_end_mask_0, x = x_187_cast_fp16)[name = tensor<string, []>("op_1698_cast_fp16")];
            tensor<int32, [4]> var_1699 = const()[name = tensor<string, []>("op_1699"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_33_cast_fp16 = reshape(shape = var_1699, x = var_1698_cast_fp16)[name = tensor<string, []>("matrix_bd_33_cast_fp16")];
            tensor<bool, []> matrix_ac_17_transpose_x_0 = const()[name = tensor<string, []>("matrix_ac_17_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> matrix_ac_17_transpose_y_0 = const()[name = tensor<string, []>("matrix_ac_17_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<int32, [4]> transpose_112_perm_0 = const()[name = tensor<string, []>("transpose_112_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_113_perm_0 = const()[name = tensor<string, []>("transpose_113_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_113 = transpose(perm = transpose_113_perm_0, x = k_33_cast_fp16)[name = tensor<string, []>("transpose_324")];
            tensor<fp16, [1, 8, 188, 128]> transpose_112 = transpose(perm = transpose_112_perm_0, x = var_1682_cast_fp16)[name = tensor<string, []>("transpose_325")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_17_cast_fp16 = matmul(transpose_x = matrix_ac_17_transpose_x_0, transpose_y = matrix_ac_17_transpose_y_0, x = transpose_112, y = transpose_113)[name = tensor<string, []>("matrix_ac_17_cast_fp16")];
            tensor<int32, [4]> matrix_bd_35_begin_0 = const()[name = tensor<string, []>("matrix_bd_35_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_35_end_0 = const()[name = tensor<string, []>("matrix_bd_35_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_35_end_mask_0 = const()[name = tensor<string, []>("matrix_bd_35_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_35_cast_fp16 = slice_by_index(begin = matrix_bd_35_begin_0, end = matrix_bd_35_end_0, end_mask = matrix_bd_35_end_mask_0, x = matrix_bd_33_cast_fp16)[name = tensor<string, []>("matrix_bd_35_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_1708_cast_fp16 = add(x = matrix_ac_17_cast_fp16, y = matrix_bd_35_cast_fp16)[name = tensor<string, []>("op_1708_cast_fp16")];
            tensor<fp16, []> _inversed_scores_33_y_0_to_fp16 = const()[name = tensor<string, []>("_inversed_scores_33_y_0_to_fp16"), val = tensor<fp16, []>(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_33_cast_fp16 = mul(x = var_1708_cast_fp16, y = _inversed_scores_33_y_0_to_fp16)[name = tensor<string, []>("_inversed_scores_33_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_35_cast_fp16 = select(a = var_12_to_fp16, b = _inversed_scores_33_cast_fp16, cond = mask_3)[name = tensor<string, []>("scores_35_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_1714_cast_fp16 = softmax(axis = var_30, x = scores_35_cast_fp16)[name = tensor<string, []>("op_1714_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_449_cast_fp16 = select(a = var_11_to_fp16, b = var_1714_cast_fp16, cond = mask_3)[name = tensor<string, []>("input_449_cast_fp16")];
            tensor<bool, []> x_189_transpose_x_0 = const()[name = tensor<string, []>("x_189_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_189_transpose_y_0 = const()[name = tensor<string, []>("x_189_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 188, 128]> value_19_cast_fp16 = transpose(perm = value_19_perm_0, x = v_17_cast_fp16)[name = tensor<string, []>("transpose_327")];
            tensor<fp16, [1, 8, 188, 128]> x_189_cast_fp16 = matmul(transpose_x = x_189_transpose_x_0, transpose_y = x_189_transpose_y_0, x = input_449_cast_fp16, y = value_19_cast_fp16)[name = tensor<string, []>("x_189_cast_fp16")];
            tensor<int32, [4]> var_1718_perm_0 = const()[name = tensor<string, []>("op_1718_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1719 = const()[name = tensor<string, []>("op_1719"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_1718_cast_fp16 = transpose(perm = var_1718_perm_0, x = x_189_cast_fp16)[name = tensor<string, []>("transpose_323")];
            tensor<fp16, [1, 188, 1024]> input_451_cast_fp16 = reshape(shape = var_1719, x = var_1718_cast_fp16)[name = tensor<string, []>("input_451_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_8_self_attn_linear_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_8_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(425213312)))];
            tensor<fp16, [1024]> encoder_layers_8_self_attn_linear_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_8_self_attn_linear_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(427310528)))];
            tensor<fp16, [1, 188, 1024]> linear_79_cast_fp16 = linear(bias = encoder_layers_8_self_attn_linear_out_bias_to_fp16, weight = encoder_layers_8_self_attn_linear_out_weight_to_fp16, x = input_451_cast_fp16)[name = tensor<string, []>("linear_79_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_455_cast_fp16 = add(x = input_447_cast_fp16, y = linear_79_cast_fp16)[name = tensor<string, []>("input_455_cast_fp16")];
            tensor<int32, [1]> x_193_axes_0 = const()[name = tensor<string, []>("x_193_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_8_norm_conv_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_8_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(427312640)))];
            tensor<fp16, [1024]> encoder_layers_8_norm_conv_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_8_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(427314752)))];
            tensor<fp16, [1, 188, 1024]> x_193_cast_fp16 = layer_norm(axes = x_193_axes_0, beta = encoder_layers_8_norm_conv_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_8_norm_conv_weight_to_fp16, x = input_455_cast_fp16)[name = tensor<string, []>("x_193_cast_fp16")];
            tensor<int32, [3]> input_457_perm_0 = const()[name = tensor<string, []>("input_457_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> input_459_pad_type_0 = const()[name = tensor<string, []>("input_459_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_459_strides_0 = const()[name = tensor<string, []>("input_459_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_459_pad_0 = const()[name = tensor<string, []>("input_459_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_459_dilations_0 = const()[name = tensor<string, []>("input_459_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_459_groups_0 = const()[name = tensor<string, []>("input_459_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [2048, 1024, 1]> encoder_layers_8_conv_pointwise_conv1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_8_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(427316864)))];
            tensor<fp16, [2048]> encoder_layers_8_conv_pointwise_conv1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_8_conv_pointwise_conv1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(431511232)))];
            tensor<fp16, [1, 1024, 188]> input_457_cast_fp16 = transpose(perm = input_457_perm_0, x = x_193_cast_fp16)[name = tensor<string, []>("transpose_322")];
            tensor<fp16, [1, 2048, 188]> input_459_cast_fp16 = conv(bias = encoder_layers_8_conv_pointwise_conv1_bias_to_fp16, dilations = input_459_dilations_0, groups = input_459_groups_0, pad = input_459_pad_0, pad_type = input_459_pad_type_0, strides = input_459_strides_0, weight = encoder_layers_8_conv_pointwise_conv1_weight_to_fp16, x = input_457_cast_fp16)[name = tensor<string, []>("input_459_cast_fp16")];
            tensor<int32, []> x_195_split_num_splits_0 = const()[name = tensor<string, []>("x_195_split_num_splits_0"), val = tensor<int32, []>(2)];
            tensor<int32, []> x_195_split_axis_0 = const()[name = tensor<string, []>("x_195_split_axis_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1, 1024, 188]> x_195_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_195_split_cast_fp16_1 = split(axis = x_195_split_axis_0, num_splits = x_195_split_num_splits_0, x = input_459_cast_fp16)[name = tensor<string, []>("x_195_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_195_split_1_sigmoid_cast_fp16 = sigmoid(x = x_195_split_cast_fp16_1)[name = tensor<string, []>("x_195_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_195_cast_fp16 = mul(x = x_195_split_cast_fp16_0, y = x_195_split_1_sigmoid_cast_fp16)[name = tensor<string, []>("x_195_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_461_cast_fp16 = select(a = var_11_to_fp16, b = x_195_cast_fp16, cond = var_351)[name = tensor<string, []>("input_461_cast_fp16")];
            tensor<int32, [6]> input_463_pad_0 = const()[name = tensor<string, []>("input_463_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            tensor<string, []> input_463_mode_0 = const()[name = tensor<string, []>("input_463_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_97_to_fp16 = const()[name = tensor<string, []>("const_97_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_463_cast_fp16 = pad(constant_val = const_97_to_fp16, mode = input_463_mode_0, pad = input_463_pad_0, x = input_461_cast_fp16)[name = tensor<string, []>("input_463_cast_fp16")];
            tensor<string, []> input_465_pad_type_0 = const()[name = tensor<string, []>("input_465_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, []> input_465_groups_0 = const()[name = tensor<string, []>("input_465_groups_0"), val = tensor<int32, []>(1024)];
            tensor<int32, [1]> input_465_strides_0 = const()[name = tensor<string, []>("input_465_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_465_pad_0 = const()[name = tensor<string, []>("input_465_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_465_dilations_0 = const()[name = tensor<string, []>("input_465_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_344_to_fp16 = const()[name = tensor<string, []>("const_344_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(431515392)))];
            tensor<fp16, [1024]> const_345_to_fp16 = const()[name = tensor<string, []>("const_345_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(431533888)))];
            tensor<fp16, [1, 1024, 188]> input_467_cast_fp16 = conv(bias = const_345_to_fp16, dilations = input_465_dilations_0, groups = input_465_groups_0, pad = input_465_pad_0, pad_type = input_465_pad_type_0, strides = input_465_strides_0, weight = const_344_to_fp16, x = input_463_cast_fp16)[name = tensor<string, []>("input_467_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_469_cast_fp16 = silu(x = input_467_cast_fp16)[name = tensor<string, []>("input_469_cast_fp16")];
            tensor<string, []> x_197_pad_type_0 = const()[name = tensor<string, []>("x_197_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> x_197_strides_0 = const()[name = tensor<string, []>("x_197_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_197_pad_0 = const()[name = tensor<string, []>("x_197_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_197_dilations_0 = const()[name = tensor<string, []>("x_197_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> x_197_groups_0 = const()[name = tensor<string, []>("x_197_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1024, 1024, 1]> encoder_layers_8_conv_pointwise_conv2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_8_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(431536000)))];
            tensor<fp16, [1024]> encoder_layers_8_conv_pointwise_conv2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_8_conv_pointwise_conv2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(433633216)))];
            tensor<fp16, [1, 1024, 188]> x_197_cast_fp16 = conv(bias = encoder_layers_8_conv_pointwise_conv2_bias_to_fp16, dilations = x_197_dilations_0, groups = x_197_groups_0, pad = x_197_pad_0, pad_type = x_197_pad_type_0, strides = x_197_strides_0, weight = encoder_layers_8_conv_pointwise_conv2_weight_to_fp16, x = input_469_cast_fp16)[name = tensor<string, []>("x_197_cast_fp16")];
            tensor<int32, [3]> input_471_perm_0 = const()[name = tensor<string, []>("input_471_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_471_cast_fp16 = transpose(perm = input_471_perm_0, x = x_197_cast_fp16)[name = tensor<string, []>("transpose_321")];
            tensor<fp16, [1, 188, 1024]> input_473_cast_fp16 = add(x = input_455_cast_fp16, y = input_471_cast_fp16)[name = tensor<string, []>("input_473_cast_fp16")];
            tensor<int32, [1]> input_475_axes_0 = const()[name = tensor<string, []>("input_475_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_8_norm_feed_forward2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_8_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(433635328)))];
            tensor<fp16, [1024]> encoder_layers_8_norm_feed_forward2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_8_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(433637440)))];
            tensor<fp16, [1, 188, 1024]> input_475_cast_fp16 = layer_norm(axes = input_475_axes_0, beta = encoder_layers_8_norm_feed_forward2_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_8_norm_feed_forward2_weight_to_fp16, x = input_473_cast_fp16)[name = tensor<string, []>("input_475_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_8_feed_forward2_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_8_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(433639552)))];
            tensor<fp16, [4096]> encoder_layers_8_feed_forward2_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_8_feed_forward2_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(442028224)))];
            tensor<fp16, [1, 188, 4096]> linear_80_cast_fp16 = linear(bias = encoder_layers_8_feed_forward2_linear1_bias_to_fp16, weight = encoder_layers_8_feed_forward2_linear1_weight_to_fp16, x = input_475_cast_fp16)[name = tensor<string, []>("linear_80_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_479_cast_fp16 = silu(x = linear_80_cast_fp16)[name = tensor<string, []>("input_479_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_8_feed_forward2_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_8_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(442036480)))];
            tensor<fp16, [1024]> encoder_layers_8_feed_forward2_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_8_feed_forward2_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(450425152)))];
            tensor<fp16, [1, 188, 1024]> linear_81_cast_fp16 = linear(bias = encoder_layers_8_feed_forward2_linear2_bias_to_fp16, weight = encoder_layers_8_feed_forward2_linear2_weight_to_fp16, x = input_479_cast_fp16)[name = tensor<string, []>("linear_81_cast_fp16")];
            tensor<fp16, []> var_1785_to_fp16 = const()[name = tensor<string, []>("op_1785_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_1786_cast_fp16 = mul(x = linear_81_cast_fp16, y = var_1785_to_fp16)[name = tensor<string, []>("op_1786_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_485_cast_fp16 = add(x = input_473_cast_fp16, y = var_1786_cast_fp16)[name = tensor<string, []>("input_485_cast_fp16")];
            tensor<int32, [1]> input_487_axes_0 = const()[name = tensor<string, []>("input_487_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_8_norm_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_8_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(450427264)))];
            tensor<fp16, [1024]> encoder_layers_8_norm_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_8_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(450429376)))];
            tensor<fp16, [1, 188, 1024]> input_487_cast_fp16 = layer_norm(axes = input_487_axes_0, beta = encoder_layers_8_norm_out_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_8_norm_out_weight_to_fp16, x = input_485_cast_fp16)[name = tensor<string, []>("input_487_cast_fp16")];
            tensor<int32, [1]> input_489_axes_0 = const()[name = tensor<string, []>("input_489_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_9_norm_feed_forward1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_9_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(450431488)))];
            tensor<fp16, [1024]> encoder_layers_9_norm_feed_forward1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_9_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(450433600)))];
            tensor<fp16, [1, 188, 1024]> input_489_cast_fp16 = layer_norm(axes = input_489_axes_0, beta = encoder_layers_9_norm_feed_forward1_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_9_norm_feed_forward1_weight_to_fp16, x = input_487_cast_fp16)[name = tensor<string, []>("input_489_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_9_feed_forward1_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_9_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(450435712)))];
            tensor<fp16, [4096]> encoder_layers_9_feed_forward1_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_9_feed_forward1_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(458824384)))];
            tensor<fp16, [1, 188, 4096]> linear_82_cast_fp16 = linear(bias = encoder_layers_9_feed_forward1_linear1_bias_to_fp16, weight = encoder_layers_9_feed_forward1_linear1_weight_to_fp16, x = input_489_cast_fp16)[name = tensor<string, []>("linear_82_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_493_cast_fp16 = silu(x = linear_82_cast_fp16)[name = tensor<string, []>("input_493_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_9_feed_forward1_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_9_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(458832640)))];
            tensor<fp16, [1024]> encoder_layers_9_feed_forward1_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_9_feed_forward1_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(467221312)))];
            tensor<fp16, [1, 188, 1024]> linear_83_cast_fp16 = linear(bias = encoder_layers_9_feed_forward1_linear2_bias_to_fp16, weight = encoder_layers_9_feed_forward1_linear2_weight_to_fp16, x = input_493_cast_fp16)[name = tensor<string, []>("linear_83_cast_fp16")];
            tensor<fp16, []> var_1816_to_fp16 = const()[name = tensor<string, []>("op_1816_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_1817_cast_fp16 = mul(x = linear_83_cast_fp16, y = var_1816_to_fp16)[name = tensor<string, []>("op_1817_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_499_cast_fp16 = add(x = input_487_cast_fp16, y = var_1817_cast_fp16)[name = tensor<string, []>("input_499_cast_fp16")];
            tensor<int32, [1]> query_19_axes_0 = const()[name = tensor<string, []>("query_19_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_9_norm_self_att_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_9_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(467223424)))];
            tensor<fp16, [1024]> encoder_layers_9_norm_self_att_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_9_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(467225536)))];
            tensor<fp16, [1, 188, 1024]> query_19_cast_fp16 = layer_norm(axes = query_19_axes_0, beta = encoder_layers_9_norm_self_att_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_9_norm_self_att_weight_to_fp16, x = input_499_cast_fp16)[name = tensor<string, []>("query_19_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_9_self_attn_linear_q_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_9_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(467227648)))];
            tensor<fp16, [1024]> encoder_layers_9_self_attn_linear_q_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_9_self_attn_linear_q_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(469324864)))];
            tensor<fp16, [1, 188, 1024]> linear_84_cast_fp16 = linear(bias = encoder_layers_9_self_attn_linear_q_bias_to_fp16, weight = encoder_layers_9_self_attn_linear_q_weight_to_fp16, x = query_19_cast_fp16)[name = tensor<string, []>("linear_84_cast_fp16")];
            tensor<int32, [4]> var_1834 = const()[name = tensor<string, []>("op_1834"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_55_cast_fp16 = reshape(shape = var_1834, x = linear_84_cast_fp16)[name = tensor<string, []>("q_55_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_9_self_attn_linear_k_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_9_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(469326976)))];
            tensor<fp16, [1024]> encoder_layers_9_self_attn_linear_k_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_9_self_attn_linear_k_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(471424192)))];
            tensor<fp16, [1, 188, 1024]> linear_85_cast_fp16 = linear(bias = encoder_layers_9_self_attn_linear_k_bias_to_fp16, weight = encoder_layers_9_self_attn_linear_k_weight_to_fp16, x = query_19_cast_fp16)[name = tensor<string, []>("linear_85_cast_fp16")];
            tensor<int32, [4]> var_1839 = const()[name = tensor<string, []>("op_1839"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_37_cast_fp16 = reshape(shape = var_1839, x = linear_85_cast_fp16)[name = tensor<string, []>("k_37_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_9_self_attn_linear_v_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_9_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(471426304)))];
            tensor<fp16, [1024]> encoder_layers_9_self_attn_linear_v_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_9_self_attn_linear_v_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(473523520)))];
            tensor<fp16, [1, 188, 1024]> linear_86_cast_fp16 = linear(bias = encoder_layers_9_self_attn_linear_v_bias_to_fp16, weight = encoder_layers_9_self_attn_linear_v_weight_to_fp16, x = query_19_cast_fp16)[name = tensor<string, []>("linear_86_cast_fp16")];
            tensor<int32, [4]> var_1844 = const()[name = tensor<string, []>("op_1844"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_19_cast_fp16 = reshape(shape = var_1844, x = linear_86_cast_fp16)[name = tensor<string, []>("v_19_cast_fp16")];
            tensor<int32, [4]> value_21_perm_0 = const()[name = tensor<string, []>("value_21_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> encoder_layers_9_self_attn_pos_bias_u_to_fp16 = const()[name = tensor<string, []>("encoder_layers_9_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(473525632)))];
            tensor<fp16, [1, 188, 8, 128]> var_1856_cast_fp16 = add(x = q_55_cast_fp16, y = encoder_layers_9_self_attn_pos_bias_u_to_fp16)[name = tensor<string, []>("op_1856_cast_fp16")];
            tensor<fp16, [8, 128]> encoder_layers_9_self_attn_pos_bias_v_to_fp16 = const()[name = tensor<string, []>("encoder_layers_9_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(473527744)))];
            tensor<fp16, [1, 188, 8, 128]> var_1858_cast_fp16 = add(x = q_55_cast_fp16, y = encoder_layers_9_self_attn_pos_bias_v_to_fp16)[name = tensor<string, []>("op_1858_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_19_perm_0 = const()[name = tensor<string, []>("q_with_bias_v_19_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<bool, []> x_205_transpose_x_0 = const()[name = tensor<string, []>("x_205_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_205_transpose_y_0 = const()[name = tensor<string, []>("x_205_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 128, 375]> var_1860_to_fp16 = const()[name = tensor<string, []>("op_1860_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(473529856)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_19_cast_fp16 = transpose(perm = q_with_bias_v_19_perm_0, x = var_1858_cast_fp16)[name = tensor<string, []>("transpose_319")];
            tensor<fp16, [1, 8, 188, 375]> x_205_cast_fp16 = matmul(transpose_x = x_205_transpose_x_0, transpose_y = x_205_transpose_y_0, x = q_with_bias_v_19_cast_fp16, y = var_1860_to_fp16)[name = tensor<string, []>("x_205_cast_fp16")];
            tensor<int32, [8]> x_207_pad_0 = const()[name = tensor<string, []>("x_207_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            tensor<string, []> x_207_mode_0 = const()[name = tensor<string, []>("x_207_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_104_to_fp16 = const()[name = tensor<string, []>("const_104_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_207_cast_fp16 = pad(constant_val = const_104_to_fp16, mode = x_207_mode_0, pad = x_207_pad_0, x = x_205_cast_fp16)[name = tensor<string, []>("x_207_cast_fp16")];
            tensor<int32, [4]> var_1868 = const()[name = tensor<string, []>("op_1868"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_209_cast_fp16 = reshape(shape = var_1868, x = x_207_cast_fp16)[name = tensor<string, []>("x_209_cast_fp16")];
            tensor<int32, [4]> var_1872_begin_0 = const()[name = tensor<string, []>("op_1872_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_1872_end_0 = const()[name = tensor<string, []>("op_1872_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_1872_end_mask_0 = const()[name = tensor<string, []>("op_1872_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_1872_cast_fp16 = slice_by_index(begin = var_1872_begin_0, end = var_1872_end_0, end_mask = var_1872_end_mask_0, x = x_209_cast_fp16)[name = tensor<string, []>("op_1872_cast_fp16")];
            tensor<int32, [4]> var_1873 = const()[name = tensor<string, []>("op_1873"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_37_cast_fp16 = reshape(shape = var_1873, x = var_1872_cast_fp16)[name = tensor<string, []>("matrix_bd_37_cast_fp16")];
            tensor<bool, []> matrix_ac_19_transpose_x_0 = const()[name = tensor<string, []>("matrix_ac_19_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> matrix_ac_19_transpose_y_0 = const()[name = tensor<string, []>("matrix_ac_19_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<int32, [4]> transpose_114_perm_0 = const()[name = tensor<string, []>("transpose_114_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_115_perm_0 = const()[name = tensor<string, []>("transpose_115_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_115 = transpose(perm = transpose_115_perm_0, x = k_37_cast_fp16)[name = tensor<string, []>("transpose_317")];
            tensor<fp16, [1, 8, 188, 128]> transpose_114 = transpose(perm = transpose_114_perm_0, x = var_1856_cast_fp16)[name = tensor<string, []>("transpose_318")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_19_cast_fp16 = matmul(transpose_x = matrix_ac_19_transpose_x_0, transpose_y = matrix_ac_19_transpose_y_0, x = transpose_114, y = transpose_115)[name = tensor<string, []>("matrix_ac_19_cast_fp16")];
            tensor<int32, [4]> matrix_bd_39_begin_0 = const()[name = tensor<string, []>("matrix_bd_39_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_39_end_0 = const()[name = tensor<string, []>("matrix_bd_39_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_39_end_mask_0 = const()[name = tensor<string, []>("matrix_bd_39_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_39_cast_fp16 = slice_by_index(begin = matrix_bd_39_begin_0, end = matrix_bd_39_end_0, end_mask = matrix_bd_39_end_mask_0, x = matrix_bd_37_cast_fp16)[name = tensor<string, []>("matrix_bd_39_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_1882_cast_fp16 = add(x = matrix_ac_19_cast_fp16, y = matrix_bd_39_cast_fp16)[name = tensor<string, []>("op_1882_cast_fp16")];
            tensor<fp16, []> _inversed_scores_37_y_0_to_fp16 = const()[name = tensor<string, []>("_inversed_scores_37_y_0_to_fp16"), val = tensor<fp16, []>(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_37_cast_fp16 = mul(x = var_1882_cast_fp16, y = _inversed_scores_37_y_0_to_fp16)[name = tensor<string, []>("_inversed_scores_37_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_39_cast_fp16 = select(a = var_12_to_fp16, b = _inversed_scores_37_cast_fp16, cond = mask_3)[name = tensor<string, []>("scores_39_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_1888_cast_fp16 = softmax(axis = var_30, x = scores_39_cast_fp16)[name = tensor<string, []>("op_1888_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_501_cast_fp16 = select(a = var_11_to_fp16, b = var_1888_cast_fp16, cond = mask_3)[name = tensor<string, []>("input_501_cast_fp16")];
            tensor<bool, []> x_211_transpose_x_0 = const()[name = tensor<string, []>("x_211_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_211_transpose_y_0 = const()[name = tensor<string, []>("x_211_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 188, 128]> value_21_cast_fp16 = transpose(perm = value_21_perm_0, x = v_19_cast_fp16)[name = tensor<string, []>("transpose_320")];
            tensor<fp16, [1, 8, 188, 128]> x_211_cast_fp16 = matmul(transpose_x = x_211_transpose_x_0, transpose_y = x_211_transpose_y_0, x = input_501_cast_fp16, y = value_21_cast_fp16)[name = tensor<string, []>("x_211_cast_fp16")];
            tensor<int32, [4]> var_1892_perm_0 = const()[name = tensor<string, []>("op_1892_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1893 = const()[name = tensor<string, []>("op_1893"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_1892_cast_fp16 = transpose(perm = var_1892_perm_0, x = x_211_cast_fp16)[name = tensor<string, []>("transpose_316")];
            tensor<fp16, [1, 188, 1024]> input_503_cast_fp16 = reshape(shape = var_1893, x = var_1892_cast_fp16)[name = tensor<string, []>("input_503_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_9_self_attn_linear_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_9_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(474297920)))];
            tensor<fp16, [1024]> encoder_layers_9_self_attn_linear_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_9_self_attn_linear_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(476395136)))];
            tensor<fp16, [1, 188, 1024]> linear_88_cast_fp16 = linear(bias = encoder_layers_9_self_attn_linear_out_bias_to_fp16, weight = encoder_layers_9_self_attn_linear_out_weight_to_fp16, x = input_503_cast_fp16)[name = tensor<string, []>("linear_88_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_507_cast_fp16 = add(x = input_499_cast_fp16, y = linear_88_cast_fp16)[name = tensor<string, []>("input_507_cast_fp16")];
            tensor<int32, [1]> x_215_axes_0 = const()[name = tensor<string, []>("x_215_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_9_norm_conv_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_9_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(476397248)))];
            tensor<fp16, [1024]> encoder_layers_9_norm_conv_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_9_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(476399360)))];
            tensor<fp16, [1, 188, 1024]> x_215_cast_fp16 = layer_norm(axes = x_215_axes_0, beta = encoder_layers_9_norm_conv_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_9_norm_conv_weight_to_fp16, x = input_507_cast_fp16)[name = tensor<string, []>("x_215_cast_fp16")];
            tensor<int32, [3]> input_509_perm_0 = const()[name = tensor<string, []>("input_509_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> input_511_pad_type_0 = const()[name = tensor<string, []>("input_511_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_511_strides_0 = const()[name = tensor<string, []>("input_511_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_511_pad_0 = const()[name = tensor<string, []>("input_511_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_511_dilations_0 = const()[name = tensor<string, []>("input_511_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_511_groups_0 = const()[name = tensor<string, []>("input_511_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [2048, 1024, 1]> encoder_layers_9_conv_pointwise_conv1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_9_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(476401472)))];
            tensor<fp16, [2048]> encoder_layers_9_conv_pointwise_conv1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_9_conv_pointwise_conv1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(480595840)))];
            tensor<fp16, [1, 1024, 188]> input_509_cast_fp16 = transpose(perm = input_509_perm_0, x = x_215_cast_fp16)[name = tensor<string, []>("transpose_315")];
            tensor<fp16, [1, 2048, 188]> input_511_cast_fp16 = conv(bias = encoder_layers_9_conv_pointwise_conv1_bias_to_fp16, dilations = input_511_dilations_0, groups = input_511_groups_0, pad = input_511_pad_0, pad_type = input_511_pad_type_0, strides = input_511_strides_0, weight = encoder_layers_9_conv_pointwise_conv1_weight_to_fp16, x = input_509_cast_fp16)[name = tensor<string, []>("input_511_cast_fp16")];
            tensor<int32, []> x_217_split_num_splits_0 = const()[name = tensor<string, []>("x_217_split_num_splits_0"), val = tensor<int32, []>(2)];
            tensor<int32, []> x_217_split_axis_0 = const()[name = tensor<string, []>("x_217_split_axis_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1, 1024, 188]> x_217_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_217_split_cast_fp16_1 = split(axis = x_217_split_axis_0, num_splits = x_217_split_num_splits_0, x = input_511_cast_fp16)[name = tensor<string, []>("x_217_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_217_split_1_sigmoid_cast_fp16 = sigmoid(x = x_217_split_cast_fp16_1)[name = tensor<string, []>("x_217_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_217_cast_fp16 = mul(x = x_217_split_cast_fp16_0, y = x_217_split_1_sigmoid_cast_fp16)[name = tensor<string, []>("x_217_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_513_cast_fp16 = select(a = var_11_to_fp16, b = x_217_cast_fp16, cond = var_351)[name = tensor<string, []>("input_513_cast_fp16")];
            tensor<int32, [6]> input_515_pad_0 = const()[name = tensor<string, []>("input_515_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            tensor<string, []> input_515_mode_0 = const()[name = tensor<string, []>("input_515_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_107_to_fp16 = const()[name = tensor<string, []>("const_107_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_515_cast_fp16 = pad(constant_val = const_107_to_fp16, mode = input_515_mode_0, pad = input_515_pad_0, x = input_513_cast_fp16)[name = tensor<string, []>("input_515_cast_fp16")];
            tensor<string, []> input_517_pad_type_0 = const()[name = tensor<string, []>("input_517_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, []> input_517_groups_0 = const()[name = tensor<string, []>("input_517_groups_0"), val = tensor<int32, []>(1024)];
            tensor<int32, [1]> input_517_strides_0 = const()[name = tensor<string, []>("input_517_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_517_pad_0 = const()[name = tensor<string, []>("input_517_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_517_dilations_0 = const()[name = tensor<string, []>("input_517_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_346_to_fp16 = const()[name = tensor<string, []>("const_346_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(480600000)))];
            tensor<fp16, [1024]> const_347_to_fp16 = const()[name = tensor<string, []>("const_347_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(480618496)))];
            tensor<fp16, [1, 1024, 188]> input_519_cast_fp16 = conv(bias = const_347_to_fp16, dilations = input_517_dilations_0, groups = input_517_groups_0, pad = input_517_pad_0, pad_type = input_517_pad_type_0, strides = input_517_strides_0, weight = const_346_to_fp16, x = input_515_cast_fp16)[name = tensor<string, []>("input_519_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_521_cast_fp16 = silu(x = input_519_cast_fp16)[name = tensor<string, []>("input_521_cast_fp16")];
            tensor<string, []> x_219_pad_type_0 = const()[name = tensor<string, []>("x_219_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> x_219_strides_0 = const()[name = tensor<string, []>("x_219_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_219_pad_0 = const()[name = tensor<string, []>("x_219_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_219_dilations_0 = const()[name = tensor<string, []>("x_219_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> x_219_groups_0 = const()[name = tensor<string, []>("x_219_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1024, 1024, 1]> encoder_layers_9_conv_pointwise_conv2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_9_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(480620608)))];
            tensor<fp16, [1024]> encoder_layers_9_conv_pointwise_conv2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_9_conv_pointwise_conv2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(482717824)))];
            tensor<fp16, [1, 1024, 188]> x_219_cast_fp16 = conv(bias = encoder_layers_9_conv_pointwise_conv2_bias_to_fp16, dilations = x_219_dilations_0, groups = x_219_groups_0, pad = x_219_pad_0, pad_type = x_219_pad_type_0, strides = x_219_strides_0, weight = encoder_layers_9_conv_pointwise_conv2_weight_to_fp16, x = input_521_cast_fp16)[name = tensor<string, []>("x_219_cast_fp16")];
            tensor<int32, [3]> input_523_perm_0 = const()[name = tensor<string, []>("input_523_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_523_cast_fp16 = transpose(perm = input_523_perm_0, x = x_219_cast_fp16)[name = tensor<string, []>("transpose_314")];
            tensor<fp16, [1, 188, 1024]> input_525_cast_fp16 = add(x = input_507_cast_fp16, y = input_523_cast_fp16)[name = tensor<string, []>("input_525_cast_fp16")];
            tensor<int32, [1]> input_527_axes_0 = const()[name = tensor<string, []>("input_527_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_9_norm_feed_forward2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_9_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(482719936)))];
            tensor<fp16, [1024]> encoder_layers_9_norm_feed_forward2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_9_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(482722048)))];
            tensor<fp16, [1, 188, 1024]> input_527_cast_fp16 = layer_norm(axes = input_527_axes_0, beta = encoder_layers_9_norm_feed_forward2_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_9_norm_feed_forward2_weight_to_fp16, x = input_525_cast_fp16)[name = tensor<string, []>("input_527_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_9_feed_forward2_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_9_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(482724160)))];
            tensor<fp16, [4096]> encoder_layers_9_feed_forward2_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_9_feed_forward2_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(491112832)))];
            tensor<fp16, [1, 188, 4096]> linear_89_cast_fp16 = linear(bias = encoder_layers_9_feed_forward2_linear1_bias_to_fp16, weight = encoder_layers_9_feed_forward2_linear1_weight_to_fp16, x = input_527_cast_fp16)[name = tensor<string, []>("linear_89_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_531_cast_fp16 = silu(x = linear_89_cast_fp16)[name = tensor<string, []>("input_531_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_9_feed_forward2_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_9_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(491121088)))];
            tensor<fp16, [1024]> encoder_layers_9_feed_forward2_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_9_feed_forward2_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(499509760)))];
            tensor<fp16, [1, 188, 1024]> linear_90_cast_fp16 = linear(bias = encoder_layers_9_feed_forward2_linear2_bias_to_fp16, weight = encoder_layers_9_feed_forward2_linear2_weight_to_fp16, x = input_531_cast_fp16)[name = tensor<string, []>("linear_90_cast_fp16")];
            tensor<fp16, []> var_1959_to_fp16 = const()[name = tensor<string, []>("op_1959_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_1960_cast_fp16 = mul(x = linear_90_cast_fp16, y = var_1959_to_fp16)[name = tensor<string, []>("op_1960_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_537_cast_fp16 = add(x = input_525_cast_fp16, y = var_1960_cast_fp16)[name = tensor<string, []>("input_537_cast_fp16")];
            tensor<int32, [1]> input_539_axes_0 = const()[name = tensor<string, []>("input_539_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_9_norm_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_9_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(499511872)))];
            tensor<fp16, [1024]> encoder_layers_9_norm_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_9_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(499513984)))];
            tensor<fp16, [1, 188, 1024]> input_539_cast_fp16 = layer_norm(axes = input_539_axes_0, beta = encoder_layers_9_norm_out_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_9_norm_out_weight_to_fp16, x = input_537_cast_fp16)[name = tensor<string, []>("input_539_cast_fp16")];
            tensor<int32, [1]> input_541_axes_0 = const()[name = tensor<string, []>("input_541_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_10_norm_feed_forward1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_10_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(499516096)))];
            tensor<fp16, [1024]> encoder_layers_10_norm_feed_forward1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_10_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(499518208)))];
            tensor<fp16, [1, 188, 1024]> input_541_cast_fp16 = layer_norm(axes = input_541_axes_0, beta = encoder_layers_10_norm_feed_forward1_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_10_norm_feed_forward1_weight_to_fp16, x = input_539_cast_fp16)[name = tensor<string, []>("input_541_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_10_feed_forward1_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_10_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(499520320)))];
            tensor<fp16, [4096]> encoder_layers_10_feed_forward1_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_10_feed_forward1_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(507908992)))];
            tensor<fp16, [1, 188, 4096]> linear_91_cast_fp16 = linear(bias = encoder_layers_10_feed_forward1_linear1_bias_to_fp16, weight = encoder_layers_10_feed_forward1_linear1_weight_to_fp16, x = input_541_cast_fp16)[name = tensor<string, []>("linear_91_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_545_cast_fp16 = silu(x = linear_91_cast_fp16)[name = tensor<string, []>("input_545_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_10_feed_forward1_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_10_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(507917248)))];
            tensor<fp16, [1024]> encoder_layers_10_feed_forward1_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_10_feed_forward1_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(516305920)))];
            tensor<fp16, [1, 188, 1024]> linear_92_cast_fp16 = linear(bias = encoder_layers_10_feed_forward1_linear2_bias_to_fp16, weight = encoder_layers_10_feed_forward1_linear2_weight_to_fp16, x = input_545_cast_fp16)[name = tensor<string, []>("linear_92_cast_fp16")];
            tensor<fp16, []> var_1990_to_fp16 = const()[name = tensor<string, []>("op_1990_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_1991_cast_fp16 = mul(x = linear_92_cast_fp16, y = var_1990_to_fp16)[name = tensor<string, []>("op_1991_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_551_cast_fp16 = add(x = input_539_cast_fp16, y = var_1991_cast_fp16)[name = tensor<string, []>("input_551_cast_fp16")];
            tensor<int32, [1]> query_21_axes_0 = const()[name = tensor<string, []>("query_21_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_10_norm_self_att_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_10_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(516308032)))];
            tensor<fp16, [1024]> encoder_layers_10_norm_self_att_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_10_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(516310144)))];
            tensor<fp16, [1, 188, 1024]> query_21_cast_fp16 = layer_norm(axes = query_21_axes_0, beta = encoder_layers_10_norm_self_att_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_10_norm_self_att_weight_to_fp16, x = input_551_cast_fp16)[name = tensor<string, []>("query_21_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_10_self_attn_linear_q_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_10_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(516312256)))];
            tensor<fp16, [1024]> encoder_layers_10_self_attn_linear_q_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_10_self_attn_linear_q_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(518409472)))];
            tensor<fp16, [1, 188, 1024]> linear_93_cast_fp16 = linear(bias = encoder_layers_10_self_attn_linear_q_bias_to_fp16, weight = encoder_layers_10_self_attn_linear_q_weight_to_fp16, x = query_21_cast_fp16)[name = tensor<string, []>("linear_93_cast_fp16")];
            tensor<int32, [4]> var_2008 = const()[name = tensor<string, []>("op_2008"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_61_cast_fp16 = reshape(shape = var_2008, x = linear_93_cast_fp16)[name = tensor<string, []>("q_61_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_10_self_attn_linear_k_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_10_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(518411584)))];
            tensor<fp16, [1024]> encoder_layers_10_self_attn_linear_k_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_10_self_attn_linear_k_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(520508800)))];
            tensor<fp16, [1, 188, 1024]> linear_94_cast_fp16 = linear(bias = encoder_layers_10_self_attn_linear_k_bias_to_fp16, weight = encoder_layers_10_self_attn_linear_k_weight_to_fp16, x = query_21_cast_fp16)[name = tensor<string, []>("linear_94_cast_fp16")];
            tensor<int32, [4]> var_2013 = const()[name = tensor<string, []>("op_2013"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_41_cast_fp16 = reshape(shape = var_2013, x = linear_94_cast_fp16)[name = tensor<string, []>("k_41_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_10_self_attn_linear_v_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_10_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(520510912)))];
            tensor<fp16, [1024]> encoder_layers_10_self_attn_linear_v_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_10_self_attn_linear_v_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(522608128)))];
            tensor<fp16, [1, 188, 1024]> linear_95_cast_fp16 = linear(bias = encoder_layers_10_self_attn_linear_v_bias_to_fp16, weight = encoder_layers_10_self_attn_linear_v_weight_to_fp16, x = query_21_cast_fp16)[name = tensor<string, []>("linear_95_cast_fp16")];
            tensor<int32, [4]> var_2018 = const()[name = tensor<string, []>("op_2018"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_21_cast_fp16 = reshape(shape = var_2018, x = linear_95_cast_fp16)[name = tensor<string, []>("v_21_cast_fp16")];
            tensor<int32, [4]> value_23_perm_0 = const()[name = tensor<string, []>("value_23_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> encoder_layers_10_self_attn_pos_bias_u_to_fp16 = const()[name = tensor<string, []>("encoder_layers_10_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(522610240)))];
            tensor<fp16, [1, 188, 8, 128]> var_2030_cast_fp16 = add(x = q_61_cast_fp16, y = encoder_layers_10_self_attn_pos_bias_u_to_fp16)[name = tensor<string, []>("op_2030_cast_fp16")];
            tensor<fp16, [8, 128]> encoder_layers_10_self_attn_pos_bias_v_to_fp16 = const()[name = tensor<string, []>("encoder_layers_10_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(522612352)))];
            tensor<fp16, [1, 188, 8, 128]> var_2032_cast_fp16 = add(x = q_61_cast_fp16, y = encoder_layers_10_self_attn_pos_bias_v_to_fp16)[name = tensor<string, []>("op_2032_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_21_perm_0 = const()[name = tensor<string, []>("q_with_bias_v_21_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<bool, []> x_227_transpose_x_0 = const()[name = tensor<string, []>("x_227_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_227_transpose_y_0 = const()[name = tensor<string, []>("x_227_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 128, 375]> var_2034_to_fp16 = const()[name = tensor<string, []>("op_2034_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(522614464)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_21_cast_fp16 = transpose(perm = q_with_bias_v_21_perm_0, x = var_2032_cast_fp16)[name = tensor<string, []>("transpose_312")];
            tensor<fp16, [1, 8, 188, 375]> x_227_cast_fp16 = matmul(transpose_x = x_227_transpose_x_0, transpose_y = x_227_transpose_y_0, x = q_with_bias_v_21_cast_fp16, y = var_2034_to_fp16)[name = tensor<string, []>("x_227_cast_fp16")];
            tensor<int32, [8]> x_229_pad_0 = const()[name = tensor<string, []>("x_229_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            tensor<string, []> x_229_mode_0 = const()[name = tensor<string, []>("x_229_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_114_to_fp16 = const()[name = tensor<string, []>("const_114_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_229_cast_fp16 = pad(constant_val = const_114_to_fp16, mode = x_229_mode_0, pad = x_229_pad_0, x = x_227_cast_fp16)[name = tensor<string, []>("x_229_cast_fp16")];
            tensor<int32, [4]> var_2042 = const()[name = tensor<string, []>("op_2042"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_231_cast_fp16 = reshape(shape = var_2042, x = x_229_cast_fp16)[name = tensor<string, []>("x_231_cast_fp16")];
            tensor<int32, [4]> var_2046_begin_0 = const()[name = tensor<string, []>("op_2046_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_2046_end_0 = const()[name = tensor<string, []>("op_2046_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_2046_end_mask_0 = const()[name = tensor<string, []>("op_2046_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_2046_cast_fp16 = slice_by_index(begin = var_2046_begin_0, end = var_2046_end_0, end_mask = var_2046_end_mask_0, x = x_231_cast_fp16)[name = tensor<string, []>("op_2046_cast_fp16")];
            tensor<int32, [4]> var_2047 = const()[name = tensor<string, []>("op_2047"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_41_cast_fp16 = reshape(shape = var_2047, x = var_2046_cast_fp16)[name = tensor<string, []>("matrix_bd_41_cast_fp16")];
            tensor<bool, []> matrix_ac_21_transpose_x_0 = const()[name = tensor<string, []>("matrix_ac_21_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> matrix_ac_21_transpose_y_0 = const()[name = tensor<string, []>("matrix_ac_21_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<int32, [4]> transpose_116_perm_0 = const()[name = tensor<string, []>("transpose_116_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_117_perm_0 = const()[name = tensor<string, []>("transpose_117_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_117 = transpose(perm = transpose_117_perm_0, x = k_41_cast_fp16)[name = tensor<string, []>("transpose_310")];
            tensor<fp16, [1, 8, 188, 128]> transpose_116 = transpose(perm = transpose_116_perm_0, x = var_2030_cast_fp16)[name = tensor<string, []>("transpose_311")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_21_cast_fp16 = matmul(transpose_x = matrix_ac_21_transpose_x_0, transpose_y = matrix_ac_21_transpose_y_0, x = transpose_116, y = transpose_117)[name = tensor<string, []>("matrix_ac_21_cast_fp16")];
            tensor<int32, [4]> matrix_bd_43_begin_0 = const()[name = tensor<string, []>("matrix_bd_43_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_43_end_0 = const()[name = tensor<string, []>("matrix_bd_43_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_43_end_mask_0 = const()[name = tensor<string, []>("matrix_bd_43_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_43_cast_fp16 = slice_by_index(begin = matrix_bd_43_begin_0, end = matrix_bd_43_end_0, end_mask = matrix_bd_43_end_mask_0, x = matrix_bd_41_cast_fp16)[name = tensor<string, []>("matrix_bd_43_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_2056_cast_fp16 = add(x = matrix_ac_21_cast_fp16, y = matrix_bd_43_cast_fp16)[name = tensor<string, []>("op_2056_cast_fp16")];
            tensor<fp16, []> _inversed_scores_41_y_0_to_fp16 = const()[name = tensor<string, []>("_inversed_scores_41_y_0_to_fp16"), val = tensor<fp16, []>(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_41_cast_fp16 = mul(x = var_2056_cast_fp16, y = _inversed_scores_41_y_0_to_fp16)[name = tensor<string, []>("_inversed_scores_41_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_43_cast_fp16 = select(a = var_12_to_fp16, b = _inversed_scores_41_cast_fp16, cond = mask_3)[name = tensor<string, []>("scores_43_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_2062_cast_fp16 = softmax(axis = var_30, x = scores_43_cast_fp16)[name = tensor<string, []>("op_2062_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_553_cast_fp16 = select(a = var_11_to_fp16, b = var_2062_cast_fp16, cond = mask_3)[name = tensor<string, []>("input_553_cast_fp16")];
            tensor<bool, []> x_233_transpose_x_0 = const()[name = tensor<string, []>("x_233_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_233_transpose_y_0 = const()[name = tensor<string, []>("x_233_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 188, 128]> value_23_cast_fp16 = transpose(perm = value_23_perm_0, x = v_21_cast_fp16)[name = tensor<string, []>("transpose_313")];
            tensor<fp16, [1, 8, 188, 128]> x_233_cast_fp16 = matmul(transpose_x = x_233_transpose_x_0, transpose_y = x_233_transpose_y_0, x = input_553_cast_fp16, y = value_23_cast_fp16)[name = tensor<string, []>("x_233_cast_fp16")];
            tensor<int32, [4]> var_2066_perm_0 = const()[name = tensor<string, []>("op_2066_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2067 = const()[name = tensor<string, []>("op_2067"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_2066_cast_fp16 = transpose(perm = var_2066_perm_0, x = x_233_cast_fp16)[name = tensor<string, []>("transpose_309")];
            tensor<fp16, [1, 188, 1024]> input_555_cast_fp16 = reshape(shape = var_2067, x = var_2066_cast_fp16)[name = tensor<string, []>("input_555_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_10_self_attn_linear_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_10_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(523382528)))];
            tensor<fp16, [1024]> encoder_layers_10_self_attn_linear_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_10_self_attn_linear_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(525479744)))];
            tensor<fp16, [1, 188, 1024]> linear_97_cast_fp16 = linear(bias = encoder_layers_10_self_attn_linear_out_bias_to_fp16, weight = encoder_layers_10_self_attn_linear_out_weight_to_fp16, x = input_555_cast_fp16)[name = tensor<string, []>("linear_97_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_559_cast_fp16 = add(x = input_551_cast_fp16, y = linear_97_cast_fp16)[name = tensor<string, []>("input_559_cast_fp16")];
            tensor<int32, [1]> x_237_axes_0 = const()[name = tensor<string, []>("x_237_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_10_norm_conv_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_10_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(525481856)))];
            tensor<fp16, [1024]> encoder_layers_10_norm_conv_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_10_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(525483968)))];
            tensor<fp16, [1, 188, 1024]> x_237_cast_fp16 = layer_norm(axes = x_237_axes_0, beta = encoder_layers_10_norm_conv_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_10_norm_conv_weight_to_fp16, x = input_559_cast_fp16)[name = tensor<string, []>("x_237_cast_fp16")];
            tensor<int32, [3]> input_561_perm_0 = const()[name = tensor<string, []>("input_561_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> input_563_pad_type_0 = const()[name = tensor<string, []>("input_563_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_563_strides_0 = const()[name = tensor<string, []>("input_563_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_563_pad_0 = const()[name = tensor<string, []>("input_563_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_563_dilations_0 = const()[name = tensor<string, []>("input_563_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_563_groups_0 = const()[name = tensor<string, []>("input_563_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [2048, 1024, 1]> encoder_layers_10_conv_pointwise_conv1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_10_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(525486080)))];
            tensor<fp16, [2048]> encoder_layers_10_conv_pointwise_conv1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_10_conv_pointwise_conv1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(529680448)))];
            tensor<fp16, [1, 1024, 188]> input_561_cast_fp16 = transpose(perm = input_561_perm_0, x = x_237_cast_fp16)[name = tensor<string, []>("transpose_308")];
            tensor<fp16, [1, 2048, 188]> input_563_cast_fp16 = conv(bias = encoder_layers_10_conv_pointwise_conv1_bias_to_fp16, dilations = input_563_dilations_0, groups = input_563_groups_0, pad = input_563_pad_0, pad_type = input_563_pad_type_0, strides = input_563_strides_0, weight = encoder_layers_10_conv_pointwise_conv1_weight_to_fp16, x = input_561_cast_fp16)[name = tensor<string, []>("input_563_cast_fp16")];
            tensor<int32, []> x_239_split_num_splits_0 = const()[name = tensor<string, []>("x_239_split_num_splits_0"), val = tensor<int32, []>(2)];
            tensor<int32, []> x_239_split_axis_0 = const()[name = tensor<string, []>("x_239_split_axis_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1, 1024, 188]> x_239_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_239_split_cast_fp16_1 = split(axis = x_239_split_axis_0, num_splits = x_239_split_num_splits_0, x = input_563_cast_fp16)[name = tensor<string, []>("x_239_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_239_split_1_sigmoid_cast_fp16 = sigmoid(x = x_239_split_cast_fp16_1)[name = tensor<string, []>("x_239_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_239_cast_fp16 = mul(x = x_239_split_cast_fp16_0, y = x_239_split_1_sigmoid_cast_fp16)[name = tensor<string, []>("x_239_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_565_cast_fp16 = select(a = var_11_to_fp16, b = x_239_cast_fp16, cond = var_351)[name = tensor<string, []>("input_565_cast_fp16")];
            tensor<int32, [6]> input_567_pad_0 = const()[name = tensor<string, []>("input_567_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            tensor<string, []> input_567_mode_0 = const()[name = tensor<string, []>("input_567_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_117_to_fp16 = const()[name = tensor<string, []>("const_117_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_567_cast_fp16 = pad(constant_val = const_117_to_fp16, mode = input_567_mode_0, pad = input_567_pad_0, x = input_565_cast_fp16)[name = tensor<string, []>("input_567_cast_fp16")];
            tensor<string, []> input_569_pad_type_0 = const()[name = tensor<string, []>("input_569_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, []> input_569_groups_0 = const()[name = tensor<string, []>("input_569_groups_0"), val = tensor<int32, []>(1024)];
            tensor<int32, [1]> input_569_strides_0 = const()[name = tensor<string, []>("input_569_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_569_pad_0 = const()[name = tensor<string, []>("input_569_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_569_dilations_0 = const()[name = tensor<string, []>("input_569_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_348_to_fp16 = const()[name = tensor<string, []>("const_348_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(529684608)))];
            tensor<fp16, [1024]> const_349_to_fp16 = const()[name = tensor<string, []>("const_349_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(529703104)))];
            tensor<fp16, [1, 1024, 188]> input_571_cast_fp16 = conv(bias = const_349_to_fp16, dilations = input_569_dilations_0, groups = input_569_groups_0, pad = input_569_pad_0, pad_type = input_569_pad_type_0, strides = input_569_strides_0, weight = const_348_to_fp16, x = input_567_cast_fp16)[name = tensor<string, []>("input_571_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_573_cast_fp16 = silu(x = input_571_cast_fp16)[name = tensor<string, []>("input_573_cast_fp16")];
            tensor<string, []> x_241_pad_type_0 = const()[name = tensor<string, []>("x_241_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> x_241_strides_0 = const()[name = tensor<string, []>("x_241_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_241_pad_0 = const()[name = tensor<string, []>("x_241_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_241_dilations_0 = const()[name = tensor<string, []>("x_241_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> x_241_groups_0 = const()[name = tensor<string, []>("x_241_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1024, 1024, 1]> encoder_layers_10_conv_pointwise_conv2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_10_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(529705216)))];
            tensor<fp16, [1024]> encoder_layers_10_conv_pointwise_conv2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_10_conv_pointwise_conv2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(531802432)))];
            tensor<fp16, [1, 1024, 188]> x_241_cast_fp16 = conv(bias = encoder_layers_10_conv_pointwise_conv2_bias_to_fp16, dilations = x_241_dilations_0, groups = x_241_groups_0, pad = x_241_pad_0, pad_type = x_241_pad_type_0, strides = x_241_strides_0, weight = encoder_layers_10_conv_pointwise_conv2_weight_to_fp16, x = input_573_cast_fp16)[name = tensor<string, []>("x_241_cast_fp16")];
            tensor<int32, [3]> input_575_perm_0 = const()[name = tensor<string, []>("input_575_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_575_cast_fp16 = transpose(perm = input_575_perm_0, x = x_241_cast_fp16)[name = tensor<string, []>("transpose_307")];
            tensor<fp16, [1, 188, 1024]> input_577_cast_fp16 = add(x = input_559_cast_fp16, y = input_575_cast_fp16)[name = tensor<string, []>("input_577_cast_fp16")];
            tensor<int32, [1]> input_579_axes_0 = const()[name = tensor<string, []>("input_579_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_10_norm_feed_forward2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_10_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(531804544)))];
            tensor<fp16, [1024]> encoder_layers_10_norm_feed_forward2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_10_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(531806656)))];
            tensor<fp16, [1, 188, 1024]> input_579_cast_fp16 = layer_norm(axes = input_579_axes_0, beta = encoder_layers_10_norm_feed_forward2_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_10_norm_feed_forward2_weight_to_fp16, x = input_577_cast_fp16)[name = tensor<string, []>("input_579_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_10_feed_forward2_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_10_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(531808768)))];
            tensor<fp16, [4096]> encoder_layers_10_feed_forward2_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_10_feed_forward2_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(540197440)))];
            tensor<fp16, [1, 188, 4096]> linear_98_cast_fp16 = linear(bias = encoder_layers_10_feed_forward2_linear1_bias_to_fp16, weight = encoder_layers_10_feed_forward2_linear1_weight_to_fp16, x = input_579_cast_fp16)[name = tensor<string, []>("linear_98_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_583_cast_fp16 = silu(x = linear_98_cast_fp16)[name = tensor<string, []>("input_583_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_10_feed_forward2_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_10_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(540205696)))];
            tensor<fp16, [1024]> encoder_layers_10_feed_forward2_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_10_feed_forward2_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(548594368)))];
            tensor<fp16, [1, 188, 1024]> linear_99_cast_fp16 = linear(bias = encoder_layers_10_feed_forward2_linear2_bias_to_fp16, weight = encoder_layers_10_feed_forward2_linear2_weight_to_fp16, x = input_583_cast_fp16)[name = tensor<string, []>("linear_99_cast_fp16")];
            tensor<fp16, []> var_2133_to_fp16 = const()[name = tensor<string, []>("op_2133_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_2134_cast_fp16 = mul(x = linear_99_cast_fp16, y = var_2133_to_fp16)[name = tensor<string, []>("op_2134_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_589_cast_fp16 = add(x = input_577_cast_fp16, y = var_2134_cast_fp16)[name = tensor<string, []>("input_589_cast_fp16")];
            tensor<int32, [1]> input_591_axes_0 = const()[name = tensor<string, []>("input_591_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_10_norm_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_10_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(548596480)))];
            tensor<fp16, [1024]> encoder_layers_10_norm_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_10_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(548598592)))];
            tensor<fp16, [1, 188, 1024]> input_591_cast_fp16 = layer_norm(axes = input_591_axes_0, beta = encoder_layers_10_norm_out_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_10_norm_out_weight_to_fp16, x = input_589_cast_fp16)[name = tensor<string, []>("input_591_cast_fp16")];
            tensor<int32, [1]> input_593_axes_0 = const()[name = tensor<string, []>("input_593_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_11_norm_feed_forward1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_11_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(548600704)))];
            tensor<fp16, [1024]> encoder_layers_11_norm_feed_forward1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_11_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(548602816)))];
            tensor<fp16, [1, 188, 1024]> input_593_cast_fp16 = layer_norm(axes = input_593_axes_0, beta = encoder_layers_11_norm_feed_forward1_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_11_norm_feed_forward1_weight_to_fp16, x = input_591_cast_fp16)[name = tensor<string, []>("input_593_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_11_feed_forward1_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_11_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(548604928)))];
            tensor<fp16, [4096]> encoder_layers_11_feed_forward1_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_11_feed_forward1_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(556993600)))];
            tensor<fp16, [1, 188, 4096]> linear_100_cast_fp16 = linear(bias = encoder_layers_11_feed_forward1_linear1_bias_to_fp16, weight = encoder_layers_11_feed_forward1_linear1_weight_to_fp16, x = input_593_cast_fp16)[name = tensor<string, []>("linear_100_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_597_cast_fp16 = silu(x = linear_100_cast_fp16)[name = tensor<string, []>("input_597_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_11_feed_forward1_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_11_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(557001856)))];
            tensor<fp16, [1024]> encoder_layers_11_feed_forward1_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_11_feed_forward1_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(565390528)))];
            tensor<fp16, [1, 188, 1024]> linear_101_cast_fp16 = linear(bias = encoder_layers_11_feed_forward1_linear2_bias_to_fp16, weight = encoder_layers_11_feed_forward1_linear2_weight_to_fp16, x = input_597_cast_fp16)[name = tensor<string, []>("linear_101_cast_fp16")];
            tensor<fp16, []> var_2164_to_fp16 = const()[name = tensor<string, []>("op_2164_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_2165_cast_fp16 = mul(x = linear_101_cast_fp16, y = var_2164_to_fp16)[name = tensor<string, []>("op_2165_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_603_cast_fp16 = add(x = input_591_cast_fp16, y = var_2165_cast_fp16)[name = tensor<string, []>("input_603_cast_fp16")];
            tensor<int32, [1]> query_23_axes_0 = const()[name = tensor<string, []>("query_23_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_11_norm_self_att_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_11_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(565392640)))];
            tensor<fp16, [1024]> encoder_layers_11_norm_self_att_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_11_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(565394752)))];
            tensor<fp16, [1, 188, 1024]> query_23_cast_fp16 = layer_norm(axes = query_23_axes_0, beta = encoder_layers_11_norm_self_att_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_11_norm_self_att_weight_to_fp16, x = input_603_cast_fp16)[name = tensor<string, []>("query_23_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_11_self_attn_linear_q_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_11_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(565396864)))];
            tensor<fp16, [1024]> encoder_layers_11_self_attn_linear_q_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_11_self_attn_linear_q_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(567494080)))];
            tensor<fp16, [1, 188, 1024]> linear_102_cast_fp16 = linear(bias = encoder_layers_11_self_attn_linear_q_bias_to_fp16, weight = encoder_layers_11_self_attn_linear_q_weight_to_fp16, x = query_23_cast_fp16)[name = tensor<string, []>("linear_102_cast_fp16")];
            tensor<int32, [4]> var_2182 = const()[name = tensor<string, []>("op_2182"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_67_cast_fp16 = reshape(shape = var_2182, x = linear_102_cast_fp16)[name = tensor<string, []>("q_67_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_11_self_attn_linear_k_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_11_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(567496192)))];
            tensor<fp16, [1024]> encoder_layers_11_self_attn_linear_k_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_11_self_attn_linear_k_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(569593408)))];
            tensor<fp16, [1, 188, 1024]> linear_103_cast_fp16 = linear(bias = encoder_layers_11_self_attn_linear_k_bias_to_fp16, weight = encoder_layers_11_self_attn_linear_k_weight_to_fp16, x = query_23_cast_fp16)[name = tensor<string, []>("linear_103_cast_fp16")];
            tensor<int32, [4]> var_2187 = const()[name = tensor<string, []>("op_2187"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_45_cast_fp16 = reshape(shape = var_2187, x = linear_103_cast_fp16)[name = tensor<string, []>("k_45_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_11_self_attn_linear_v_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_11_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(569595520)))];
            tensor<fp16, [1024]> encoder_layers_11_self_attn_linear_v_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_11_self_attn_linear_v_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(571692736)))];
            tensor<fp16, [1, 188, 1024]> linear_104_cast_fp16 = linear(bias = encoder_layers_11_self_attn_linear_v_bias_to_fp16, weight = encoder_layers_11_self_attn_linear_v_weight_to_fp16, x = query_23_cast_fp16)[name = tensor<string, []>("linear_104_cast_fp16")];
            tensor<int32, [4]> var_2192 = const()[name = tensor<string, []>("op_2192"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_23_cast_fp16 = reshape(shape = var_2192, x = linear_104_cast_fp16)[name = tensor<string, []>("v_23_cast_fp16")];
            tensor<int32, [4]> value_25_perm_0 = const()[name = tensor<string, []>("value_25_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> encoder_layers_11_self_attn_pos_bias_u_to_fp16 = const()[name = tensor<string, []>("encoder_layers_11_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(571694848)))];
            tensor<fp16, [1, 188, 8, 128]> var_2204_cast_fp16 = add(x = q_67_cast_fp16, y = encoder_layers_11_self_attn_pos_bias_u_to_fp16)[name = tensor<string, []>("op_2204_cast_fp16")];
            tensor<fp16, [8, 128]> encoder_layers_11_self_attn_pos_bias_v_to_fp16 = const()[name = tensor<string, []>("encoder_layers_11_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(571696960)))];
            tensor<fp16, [1, 188, 8, 128]> var_2206_cast_fp16 = add(x = q_67_cast_fp16, y = encoder_layers_11_self_attn_pos_bias_v_to_fp16)[name = tensor<string, []>("op_2206_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_23_perm_0 = const()[name = tensor<string, []>("q_with_bias_v_23_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<bool, []> x_249_transpose_x_0 = const()[name = tensor<string, []>("x_249_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_249_transpose_y_0 = const()[name = tensor<string, []>("x_249_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 128, 375]> var_2208_to_fp16 = const()[name = tensor<string, []>("op_2208_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(571699072)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_23_cast_fp16 = transpose(perm = q_with_bias_v_23_perm_0, x = var_2206_cast_fp16)[name = tensor<string, []>("transpose_305")];
            tensor<fp16, [1, 8, 188, 375]> x_249_cast_fp16 = matmul(transpose_x = x_249_transpose_x_0, transpose_y = x_249_transpose_y_0, x = q_with_bias_v_23_cast_fp16, y = var_2208_to_fp16)[name = tensor<string, []>("x_249_cast_fp16")];
            tensor<int32, [8]> x_251_pad_0 = const()[name = tensor<string, []>("x_251_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            tensor<string, []> x_251_mode_0 = const()[name = tensor<string, []>("x_251_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_124_to_fp16 = const()[name = tensor<string, []>("const_124_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_251_cast_fp16 = pad(constant_val = const_124_to_fp16, mode = x_251_mode_0, pad = x_251_pad_0, x = x_249_cast_fp16)[name = tensor<string, []>("x_251_cast_fp16")];
            tensor<int32, [4]> var_2216 = const()[name = tensor<string, []>("op_2216"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_253_cast_fp16 = reshape(shape = var_2216, x = x_251_cast_fp16)[name = tensor<string, []>("x_253_cast_fp16")];
            tensor<int32, [4]> var_2220_begin_0 = const()[name = tensor<string, []>("op_2220_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_2220_end_0 = const()[name = tensor<string, []>("op_2220_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_2220_end_mask_0 = const()[name = tensor<string, []>("op_2220_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_2220_cast_fp16 = slice_by_index(begin = var_2220_begin_0, end = var_2220_end_0, end_mask = var_2220_end_mask_0, x = x_253_cast_fp16)[name = tensor<string, []>("op_2220_cast_fp16")];
            tensor<int32, [4]> var_2221 = const()[name = tensor<string, []>("op_2221"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_45_cast_fp16 = reshape(shape = var_2221, x = var_2220_cast_fp16)[name = tensor<string, []>("matrix_bd_45_cast_fp16")];
            tensor<bool, []> matrix_ac_23_transpose_x_0 = const()[name = tensor<string, []>("matrix_ac_23_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> matrix_ac_23_transpose_y_0 = const()[name = tensor<string, []>("matrix_ac_23_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<int32, [4]> transpose_118_perm_0 = const()[name = tensor<string, []>("transpose_118_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_119_perm_0 = const()[name = tensor<string, []>("transpose_119_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_119 = transpose(perm = transpose_119_perm_0, x = k_45_cast_fp16)[name = tensor<string, []>("transpose_303")];
            tensor<fp16, [1, 8, 188, 128]> transpose_118 = transpose(perm = transpose_118_perm_0, x = var_2204_cast_fp16)[name = tensor<string, []>("transpose_304")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_23_cast_fp16 = matmul(transpose_x = matrix_ac_23_transpose_x_0, transpose_y = matrix_ac_23_transpose_y_0, x = transpose_118, y = transpose_119)[name = tensor<string, []>("matrix_ac_23_cast_fp16")];
            tensor<int32, [4]> matrix_bd_47_begin_0 = const()[name = tensor<string, []>("matrix_bd_47_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_47_end_0 = const()[name = tensor<string, []>("matrix_bd_47_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_47_end_mask_0 = const()[name = tensor<string, []>("matrix_bd_47_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_47_cast_fp16 = slice_by_index(begin = matrix_bd_47_begin_0, end = matrix_bd_47_end_0, end_mask = matrix_bd_47_end_mask_0, x = matrix_bd_45_cast_fp16)[name = tensor<string, []>("matrix_bd_47_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_2230_cast_fp16 = add(x = matrix_ac_23_cast_fp16, y = matrix_bd_47_cast_fp16)[name = tensor<string, []>("op_2230_cast_fp16")];
            tensor<fp16, []> _inversed_scores_45_y_0_to_fp16 = const()[name = tensor<string, []>("_inversed_scores_45_y_0_to_fp16"), val = tensor<fp16, []>(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_45_cast_fp16 = mul(x = var_2230_cast_fp16, y = _inversed_scores_45_y_0_to_fp16)[name = tensor<string, []>("_inversed_scores_45_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_47_cast_fp16 = select(a = var_12_to_fp16, b = _inversed_scores_45_cast_fp16, cond = mask_3)[name = tensor<string, []>("scores_47_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_2236_cast_fp16 = softmax(axis = var_30, x = scores_47_cast_fp16)[name = tensor<string, []>("op_2236_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_605_cast_fp16 = select(a = var_11_to_fp16, b = var_2236_cast_fp16, cond = mask_3)[name = tensor<string, []>("input_605_cast_fp16")];
            tensor<bool, []> x_255_transpose_x_0 = const()[name = tensor<string, []>("x_255_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_255_transpose_y_0 = const()[name = tensor<string, []>("x_255_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 188, 128]> value_25_cast_fp16 = transpose(perm = value_25_perm_0, x = v_23_cast_fp16)[name = tensor<string, []>("transpose_306")];
            tensor<fp16, [1, 8, 188, 128]> x_255_cast_fp16 = matmul(transpose_x = x_255_transpose_x_0, transpose_y = x_255_transpose_y_0, x = input_605_cast_fp16, y = value_25_cast_fp16)[name = tensor<string, []>("x_255_cast_fp16")];
            tensor<int32, [4]> var_2240_perm_0 = const()[name = tensor<string, []>("op_2240_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2241 = const()[name = tensor<string, []>("op_2241"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_2240_cast_fp16 = transpose(perm = var_2240_perm_0, x = x_255_cast_fp16)[name = tensor<string, []>("transpose_302")];
            tensor<fp16, [1, 188, 1024]> input_607_cast_fp16 = reshape(shape = var_2241, x = var_2240_cast_fp16)[name = tensor<string, []>("input_607_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_11_self_attn_linear_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_11_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(572467136)))];
            tensor<fp16, [1024]> encoder_layers_11_self_attn_linear_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_11_self_attn_linear_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(574564352)))];
            tensor<fp16, [1, 188, 1024]> linear_106_cast_fp16 = linear(bias = encoder_layers_11_self_attn_linear_out_bias_to_fp16, weight = encoder_layers_11_self_attn_linear_out_weight_to_fp16, x = input_607_cast_fp16)[name = tensor<string, []>("linear_106_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_611_cast_fp16 = add(x = input_603_cast_fp16, y = linear_106_cast_fp16)[name = tensor<string, []>("input_611_cast_fp16")];
            tensor<int32, [1]> x_259_axes_0 = const()[name = tensor<string, []>("x_259_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_11_norm_conv_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_11_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(574566464)))];
            tensor<fp16, [1024]> encoder_layers_11_norm_conv_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_11_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(574568576)))];
            tensor<fp16, [1, 188, 1024]> x_259_cast_fp16 = layer_norm(axes = x_259_axes_0, beta = encoder_layers_11_norm_conv_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_11_norm_conv_weight_to_fp16, x = input_611_cast_fp16)[name = tensor<string, []>("x_259_cast_fp16")];
            tensor<int32, [3]> input_613_perm_0 = const()[name = tensor<string, []>("input_613_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> input_615_pad_type_0 = const()[name = tensor<string, []>("input_615_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_615_strides_0 = const()[name = tensor<string, []>("input_615_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_615_pad_0 = const()[name = tensor<string, []>("input_615_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_615_dilations_0 = const()[name = tensor<string, []>("input_615_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_615_groups_0 = const()[name = tensor<string, []>("input_615_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [2048, 1024, 1]> encoder_layers_11_conv_pointwise_conv1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_11_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(574570688)))];
            tensor<fp16, [2048]> encoder_layers_11_conv_pointwise_conv1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_11_conv_pointwise_conv1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(578765056)))];
            tensor<fp16, [1, 1024, 188]> input_613_cast_fp16 = transpose(perm = input_613_perm_0, x = x_259_cast_fp16)[name = tensor<string, []>("transpose_301")];
            tensor<fp16, [1, 2048, 188]> input_615_cast_fp16 = conv(bias = encoder_layers_11_conv_pointwise_conv1_bias_to_fp16, dilations = input_615_dilations_0, groups = input_615_groups_0, pad = input_615_pad_0, pad_type = input_615_pad_type_0, strides = input_615_strides_0, weight = encoder_layers_11_conv_pointwise_conv1_weight_to_fp16, x = input_613_cast_fp16)[name = tensor<string, []>("input_615_cast_fp16")];
            tensor<int32, []> x_261_split_num_splits_0 = const()[name = tensor<string, []>("x_261_split_num_splits_0"), val = tensor<int32, []>(2)];
            tensor<int32, []> x_261_split_axis_0 = const()[name = tensor<string, []>("x_261_split_axis_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1, 1024, 188]> x_261_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_261_split_cast_fp16_1 = split(axis = x_261_split_axis_0, num_splits = x_261_split_num_splits_0, x = input_615_cast_fp16)[name = tensor<string, []>("x_261_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_261_split_1_sigmoid_cast_fp16 = sigmoid(x = x_261_split_cast_fp16_1)[name = tensor<string, []>("x_261_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_261_cast_fp16 = mul(x = x_261_split_cast_fp16_0, y = x_261_split_1_sigmoid_cast_fp16)[name = tensor<string, []>("x_261_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_617_cast_fp16 = select(a = var_11_to_fp16, b = x_261_cast_fp16, cond = var_351)[name = tensor<string, []>("input_617_cast_fp16")];
            tensor<int32, [6]> input_619_pad_0 = const()[name = tensor<string, []>("input_619_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            tensor<string, []> input_619_mode_0 = const()[name = tensor<string, []>("input_619_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_127_to_fp16 = const()[name = tensor<string, []>("const_127_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_619_cast_fp16 = pad(constant_val = const_127_to_fp16, mode = input_619_mode_0, pad = input_619_pad_0, x = input_617_cast_fp16)[name = tensor<string, []>("input_619_cast_fp16")];
            tensor<string, []> input_621_pad_type_0 = const()[name = tensor<string, []>("input_621_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, []> input_621_groups_0 = const()[name = tensor<string, []>("input_621_groups_0"), val = tensor<int32, []>(1024)];
            tensor<int32, [1]> input_621_strides_0 = const()[name = tensor<string, []>("input_621_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_621_pad_0 = const()[name = tensor<string, []>("input_621_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_621_dilations_0 = const()[name = tensor<string, []>("input_621_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_350_to_fp16 = const()[name = tensor<string, []>("const_350_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(578769216)))];
            tensor<fp16, [1024]> const_351_to_fp16 = const()[name = tensor<string, []>("const_351_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(578787712)))];
            tensor<fp16, [1, 1024, 188]> input_623_cast_fp16 = conv(bias = const_351_to_fp16, dilations = input_621_dilations_0, groups = input_621_groups_0, pad = input_621_pad_0, pad_type = input_621_pad_type_0, strides = input_621_strides_0, weight = const_350_to_fp16, x = input_619_cast_fp16)[name = tensor<string, []>("input_623_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_625_cast_fp16 = silu(x = input_623_cast_fp16)[name = tensor<string, []>("input_625_cast_fp16")];
            tensor<string, []> x_263_pad_type_0 = const()[name = tensor<string, []>("x_263_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> x_263_strides_0 = const()[name = tensor<string, []>("x_263_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_263_pad_0 = const()[name = tensor<string, []>("x_263_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_263_dilations_0 = const()[name = tensor<string, []>("x_263_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> x_263_groups_0 = const()[name = tensor<string, []>("x_263_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1024, 1024, 1]> encoder_layers_11_conv_pointwise_conv2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_11_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(578789824)))];
            tensor<fp16, [1024]> encoder_layers_11_conv_pointwise_conv2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_11_conv_pointwise_conv2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(580887040)))];
            tensor<fp16, [1, 1024, 188]> x_263_cast_fp16 = conv(bias = encoder_layers_11_conv_pointwise_conv2_bias_to_fp16, dilations = x_263_dilations_0, groups = x_263_groups_0, pad = x_263_pad_0, pad_type = x_263_pad_type_0, strides = x_263_strides_0, weight = encoder_layers_11_conv_pointwise_conv2_weight_to_fp16, x = input_625_cast_fp16)[name = tensor<string, []>("x_263_cast_fp16")];
            tensor<int32, [3]> input_627_perm_0 = const()[name = tensor<string, []>("input_627_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_627_cast_fp16 = transpose(perm = input_627_perm_0, x = x_263_cast_fp16)[name = tensor<string, []>("transpose_300")];
            tensor<fp16, [1, 188, 1024]> input_629_cast_fp16 = add(x = input_611_cast_fp16, y = input_627_cast_fp16)[name = tensor<string, []>("input_629_cast_fp16")];
            tensor<int32, [1]> input_631_axes_0 = const()[name = tensor<string, []>("input_631_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_11_norm_feed_forward2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_11_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(580889152)))];
            tensor<fp16, [1024]> encoder_layers_11_norm_feed_forward2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_11_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(580891264)))];
            tensor<fp16, [1, 188, 1024]> input_631_cast_fp16 = layer_norm(axes = input_631_axes_0, beta = encoder_layers_11_norm_feed_forward2_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_11_norm_feed_forward2_weight_to_fp16, x = input_629_cast_fp16)[name = tensor<string, []>("input_631_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_11_feed_forward2_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_11_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(580893376)))];
            tensor<fp16, [4096]> encoder_layers_11_feed_forward2_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_11_feed_forward2_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(589282048)))];
            tensor<fp16, [1, 188, 4096]> linear_107_cast_fp16 = linear(bias = encoder_layers_11_feed_forward2_linear1_bias_to_fp16, weight = encoder_layers_11_feed_forward2_linear1_weight_to_fp16, x = input_631_cast_fp16)[name = tensor<string, []>("linear_107_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_635_cast_fp16 = silu(x = linear_107_cast_fp16)[name = tensor<string, []>("input_635_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_11_feed_forward2_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_11_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(589290304)))];
            tensor<fp16, [1024]> encoder_layers_11_feed_forward2_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_11_feed_forward2_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(597678976)))];
            tensor<fp16, [1, 188, 1024]> linear_108_cast_fp16 = linear(bias = encoder_layers_11_feed_forward2_linear2_bias_to_fp16, weight = encoder_layers_11_feed_forward2_linear2_weight_to_fp16, x = input_635_cast_fp16)[name = tensor<string, []>("linear_108_cast_fp16")];
            tensor<fp16, []> var_2307_to_fp16 = const()[name = tensor<string, []>("op_2307_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_2308_cast_fp16 = mul(x = linear_108_cast_fp16, y = var_2307_to_fp16)[name = tensor<string, []>("op_2308_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_641_cast_fp16 = add(x = input_629_cast_fp16, y = var_2308_cast_fp16)[name = tensor<string, []>("input_641_cast_fp16")];
            tensor<int32, [1]> input_643_axes_0 = const()[name = tensor<string, []>("input_643_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_11_norm_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_11_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(597681088)))];
            tensor<fp16, [1024]> encoder_layers_11_norm_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_11_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(597683200)))];
            tensor<fp16, [1, 188, 1024]> input_643_cast_fp16 = layer_norm(axes = input_643_axes_0, beta = encoder_layers_11_norm_out_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_11_norm_out_weight_to_fp16, x = input_641_cast_fp16)[name = tensor<string, []>("input_643_cast_fp16")];
            tensor<int32, [1]> input_645_axes_0 = const()[name = tensor<string, []>("input_645_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_12_norm_feed_forward1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_12_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(597685312)))];
            tensor<fp16, [1024]> encoder_layers_12_norm_feed_forward1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_12_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(597687424)))];
            tensor<fp16, [1, 188, 1024]> input_645_cast_fp16 = layer_norm(axes = input_645_axes_0, beta = encoder_layers_12_norm_feed_forward1_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_12_norm_feed_forward1_weight_to_fp16, x = input_643_cast_fp16)[name = tensor<string, []>("input_645_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_12_feed_forward1_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_12_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(597689536)))];
            tensor<fp16, [4096]> encoder_layers_12_feed_forward1_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_12_feed_forward1_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(606078208)))];
            tensor<fp16, [1, 188, 4096]> linear_109_cast_fp16 = linear(bias = encoder_layers_12_feed_forward1_linear1_bias_to_fp16, weight = encoder_layers_12_feed_forward1_linear1_weight_to_fp16, x = input_645_cast_fp16)[name = tensor<string, []>("linear_109_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_649_cast_fp16 = silu(x = linear_109_cast_fp16)[name = tensor<string, []>("input_649_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_12_feed_forward1_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_12_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(606086464)))];
            tensor<fp16, [1024]> encoder_layers_12_feed_forward1_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_12_feed_forward1_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(614475136)))];
            tensor<fp16, [1, 188, 1024]> linear_110_cast_fp16 = linear(bias = encoder_layers_12_feed_forward1_linear2_bias_to_fp16, weight = encoder_layers_12_feed_forward1_linear2_weight_to_fp16, x = input_649_cast_fp16)[name = tensor<string, []>("linear_110_cast_fp16")];
            tensor<fp16, []> var_2338_to_fp16 = const()[name = tensor<string, []>("op_2338_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_2339_cast_fp16 = mul(x = linear_110_cast_fp16, y = var_2338_to_fp16)[name = tensor<string, []>("op_2339_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_655_cast_fp16 = add(x = input_643_cast_fp16, y = var_2339_cast_fp16)[name = tensor<string, []>("input_655_cast_fp16")];
            tensor<int32, [1]> query_25_axes_0 = const()[name = tensor<string, []>("query_25_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_12_norm_self_att_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_12_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(614477248)))];
            tensor<fp16, [1024]> encoder_layers_12_norm_self_att_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_12_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(614479360)))];
            tensor<fp16, [1, 188, 1024]> query_25_cast_fp16 = layer_norm(axes = query_25_axes_0, beta = encoder_layers_12_norm_self_att_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_12_norm_self_att_weight_to_fp16, x = input_655_cast_fp16)[name = tensor<string, []>("query_25_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_12_self_attn_linear_q_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_12_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(614481472)))];
            tensor<fp16, [1024]> encoder_layers_12_self_attn_linear_q_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_12_self_attn_linear_q_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(616578688)))];
            tensor<fp16, [1, 188, 1024]> linear_111_cast_fp16 = linear(bias = encoder_layers_12_self_attn_linear_q_bias_to_fp16, weight = encoder_layers_12_self_attn_linear_q_weight_to_fp16, x = query_25_cast_fp16)[name = tensor<string, []>("linear_111_cast_fp16")];
            tensor<int32, [4]> var_2356 = const()[name = tensor<string, []>("op_2356"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_73_cast_fp16 = reshape(shape = var_2356, x = linear_111_cast_fp16)[name = tensor<string, []>("q_73_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_12_self_attn_linear_k_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_12_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(616580800)))];
            tensor<fp16, [1024]> encoder_layers_12_self_attn_linear_k_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_12_self_attn_linear_k_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(618678016)))];
            tensor<fp16, [1, 188, 1024]> linear_112_cast_fp16 = linear(bias = encoder_layers_12_self_attn_linear_k_bias_to_fp16, weight = encoder_layers_12_self_attn_linear_k_weight_to_fp16, x = query_25_cast_fp16)[name = tensor<string, []>("linear_112_cast_fp16")];
            tensor<int32, [4]> var_2361 = const()[name = tensor<string, []>("op_2361"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_49_cast_fp16 = reshape(shape = var_2361, x = linear_112_cast_fp16)[name = tensor<string, []>("k_49_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_12_self_attn_linear_v_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_12_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(618680128)))];
            tensor<fp16, [1024]> encoder_layers_12_self_attn_linear_v_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_12_self_attn_linear_v_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(620777344)))];
            tensor<fp16, [1, 188, 1024]> linear_113_cast_fp16 = linear(bias = encoder_layers_12_self_attn_linear_v_bias_to_fp16, weight = encoder_layers_12_self_attn_linear_v_weight_to_fp16, x = query_25_cast_fp16)[name = tensor<string, []>("linear_113_cast_fp16")];
            tensor<int32, [4]> var_2366 = const()[name = tensor<string, []>("op_2366"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_25_cast_fp16 = reshape(shape = var_2366, x = linear_113_cast_fp16)[name = tensor<string, []>("v_25_cast_fp16")];
            tensor<int32, [4]> value_27_perm_0 = const()[name = tensor<string, []>("value_27_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> encoder_layers_12_self_attn_pos_bias_u_to_fp16 = const()[name = tensor<string, []>("encoder_layers_12_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(620779456)))];
            tensor<fp16, [1, 188, 8, 128]> var_2378_cast_fp16 = add(x = q_73_cast_fp16, y = encoder_layers_12_self_attn_pos_bias_u_to_fp16)[name = tensor<string, []>("op_2378_cast_fp16")];
            tensor<fp16, [8, 128]> encoder_layers_12_self_attn_pos_bias_v_to_fp16 = const()[name = tensor<string, []>("encoder_layers_12_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(620781568)))];
            tensor<fp16, [1, 188, 8, 128]> var_2380_cast_fp16 = add(x = q_73_cast_fp16, y = encoder_layers_12_self_attn_pos_bias_v_to_fp16)[name = tensor<string, []>("op_2380_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_25_perm_0 = const()[name = tensor<string, []>("q_with_bias_v_25_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<bool, []> x_271_transpose_x_0 = const()[name = tensor<string, []>("x_271_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_271_transpose_y_0 = const()[name = tensor<string, []>("x_271_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 128, 375]> var_2382_to_fp16 = const()[name = tensor<string, []>("op_2382_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(620783680)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_25_cast_fp16 = transpose(perm = q_with_bias_v_25_perm_0, x = var_2380_cast_fp16)[name = tensor<string, []>("transpose_298")];
            tensor<fp16, [1, 8, 188, 375]> x_271_cast_fp16 = matmul(transpose_x = x_271_transpose_x_0, transpose_y = x_271_transpose_y_0, x = q_with_bias_v_25_cast_fp16, y = var_2382_to_fp16)[name = tensor<string, []>("x_271_cast_fp16")];
            tensor<int32, [8]> x_273_pad_0 = const()[name = tensor<string, []>("x_273_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            tensor<string, []> x_273_mode_0 = const()[name = tensor<string, []>("x_273_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_134_to_fp16 = const()[name = tensor<string, []>("const_134_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_273_cast_fp16 = pad(constant_val = const_134_to_fp16, mode = x_273_mode_0, pad = x_273_pad_0, x = x_271_cast_fp16)[name = tensor<string, []>("x_273_cast_fp16")];
            tensor<int32, [4]> var_2390 = const()[name = tensor<string, []>("op_2390"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_275_cast_fp16 = reshape(shape = var_2390, x = x_273_cast_fp16)[name = tensor<string, []>("x_275_cast_fp16")];
            tensor<int32, [4]> var_2394_begin_0 = const()[name = tensor<string, []>("op_2394_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_2394_end_0 = const()[name = tensor<string, []>("op_2394_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_2394_end_mask_0 = const()[name = tensor<string, []>("op_2394_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_2394_cast_fp16 = slice_by_index(begin = var_2394_begin_0, end = var_2394_end_0, end_mask = var_2394_end_mask_0, x = x_275_cast_fp16)[name = tensor<string, []>("op_2394_cast_fp16")];
            tensor<int32, [4]> var_2395 = const()[name = tensor<string, []>("op_2395"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_49_cast_fp16 = reshape(shape = var_2395, x = var_2394_cast_fp16)[name = tensor<string, []>("matrix_bd_49_cast_fp16")];
            tensor<bool, []> matrix_ac_25_transpose_x_0 = const()[name = tensor<string, []>("matrix_ac_25_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> matrix_ac_25_transpose_y_0 = const()[name = tensor<string, []>("matrix_ac_25_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<int32, [4]> transpose_120_perm_0 = const()[name = tensor<string, []>("transpose_120_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_121_perm_0 = const()[name = tensor<string, []>("transpose_121_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_121 = transpose(perm = transpose_121_perm_0, x = k_49_cast_fp16)[name = tensor<string, []>("transpose_296")];
            tensor<fp16, [1, 8, 188, 128]> transpose_120 = transpose(perm = transpose_120_perm_0, x = var_2378_cast_fp16)[name = tensor<string, []>("transpose_297")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_25_cast_fp16 = matmul(transpose_x = matrix_ac_25_transpose_x_0, transpose_y = matrix_ac_25_transpose_y_0, x = transpose_120, y = transpose_121)[name = tensor<string, []>("matrix_ac_25_cast_fp16")];
            tensor<int32, [4]> matrix_bd_51_begin_0 = const()[name = tensor<string, []>("matrix_bd_51_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_51_end_0 = const()[name = tensor<string, []>("matrix_bd_51_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_51_end_mask_0 = const()[name = tensor<string, []>("matrix_bd_51_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_51_cast_fp16 = slice_by_index(begin = matrix_bd_51_begin_0, end = matrix_bd_51_end_0, end_mask = matrix_bd_51_end_mask_0, x = matrix_bd_49_cast_fp16)[name = tensor<string, []>("matrix_bd_51_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_2404_cast_fp16 = add(x = matrix_ac_25_cast_fp16, y = matrix_bd_51_cast_fp16)[name = tensor<string, []>("op_2404_cast_fp16")];
            tensor<fp16, []> _inversed_scores_49_y_0_to_fp16 = const()[name = tensor<string, []>("_inversed_scores_49_y_0_to_fp16"), val = tensor<fp16, []>(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_49_cast_fp16 = mul(x = var_2404_cast_fp16, y = _inversed_scores_49_y_0_to_fp16)[name = tensor<string, []>("_inversed_scores_49_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_51_cast_fp16 = select(a = var_12_to_fp16, b = _inversed_scores_49_cast_fp16, cond = mask_3)[name = tensor<string, []>("scores_51_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_2410_cast_fp16 = softmax(axis = var_30, x = scores_51_cast_fp16)[name = tensor<string, []>("op_2410_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_657_cast_fp16 = select(a = var_11_to_fp16, b = var_2410_cast_fp16, cond = mask_3)[name = tensor<string, []>("input_657_cast_fp16")];
            tensor<bool, []> x_277_transpose_x_0 = const()[name = tensor<string, []>("x_277_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_277_transpose_y_0 = const()[name = tensor<string, []>("x_277_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 188, 128]> value_27_cast_fp16 = transpose(perm = value_27_perm_0, x = v_25_cast_fp16)[name = tensor<string, []>("transpose_299")];
            tensor<fp16, [1, 8, 188, 128]> x_277_cast_fp16 = matmul(transpose_x = x_277_transpose_x_0, transpose_y = x_277_transpose_y_0, x = input_657_cast_fp16, y = value_27_cast_fp16)[name = tensor<string, []>("x_277_cast_fp16")];
            tensor<int32, [4]> var_2414_perm_0 = const()[name = tensor<string, []>("op_2414_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2415 = const()[name = tensor<string, []>("op_2415"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_2414_cast_fp16 = transpose(perm = var_2414_perm_0, x = x_277_cast_fp16)[name = tensor<string, []>("transpose_295")];
            tensor<fp16, [1, 188, 1024]> input_659_cast_fp16 = reshape(shape = var_2415, x = var_2414_cast_fp16)[name = tensor<string, []>("input_659_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_12_self_attn_linear_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_12_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(621551744)))];
            tensor<fp16, [1024]> encoder_layers_12_self_attn_linear_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_12_self_attn_linear_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(623648960)))];
            tensor<fp16, [1, 188, 1024]> linear_115_cast_fp16 = linear(bias = encoder_layers_12_self_attn_linear_out_bias_to_fp16, weight = encoder_layers_12_self_attn_linear_out_weight_to_fp16, x = input_659_cast_fp16)[name = tensor<string, []>("linear_115_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_663_cast_fp16 = add(x = input_655_cast_fp16, y = linear_115_cast_fp16)[name = tensor<string, []>("input_663_cast_fp16")];
            tensor<int32, [1]> x_281_axes_0 = const()[name = tensor<string, []>("x_281_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_12_norm_conv_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_12_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(623651072)))];
            tensor<fp16, [1024]> encoder_layers_12_norm_conv_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_12_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(623653184)))];
            tensor<fp16, [1, 188, 1024]> x_281_cast_fp16 = layer_norm(axes = x_281_axes_0, beta = encoder_layers_12_norm_conv_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_12_norm_conv_weight_to_fp16, x = input_663_cast_fp16)[name = tensor<string, []>("x_281_cast_fp16")];
            tensor<int32, [3]> input_665_perm_0 = const()[name = tensor<string, []>("input_665_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> input_667_pad_type_0 = const()[name = tensor<string, []>("input_667_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_667_strides_0 = const()[name = tensor<string, []>("input_667_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_667_pad_0 = const()[name = tensor<string, []>("input_667_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_667_dilations_0 = const()[name = tensor<string, []>("input_667_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_667_groups_0 = const()[name = tensor<string, []>("input_667_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [2048, 1024, 1]> encoder_layers_12_conv_pointwise_conv1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_12_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(623655296)))];
            tensor<fp16, [2048]> encoder_layers_12_conv_pointwise_conv1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_12_conv_pointwise_conv1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(627849664)))];
            tensor<fp16, [1, 1024, 188]> input_665_cast_fp16 = transpose(perm = input_665_perm_0, x = x_281_cast_fp16)[name = tensor<string, []>("transpose_294")];
            tensor<fp16, [1, 2048, 188]> input_667_cast_fp16 = conv(bias = encoder_layers_12_conv_pointwise_conv1_bias_to_fp16, dilations = input_667_dilations_0, groups = input_667_groups_0, pad = input_667_pad_0, pad_type = input_667_pad_type_0, strides = input_667_strides_0, weight = encoder_layers_12_conv_pointwise_conv1_weight_to_fp16, x = input_665_cast_fp16)[name = tensor<string, []>("input_667_cast_fp16")];
            tensor<int32, []> x_283_split_num_splits_0 = const()[name = tensor<string, []>("x_283_split_num_splits_0"), val = tensor<int32, []>(2)];
            tensor<int32, []> x_283_split_axis_0 = const()[name = tensor<string, []>("x_283_split_axis_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1, 1024, 188]> x_283_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_283_split_cast_fp16_1 = split(axis = x_283_split_axis_0, num_splits = x_283_split_num_splits_0, x = input_667_cast_fp16)[name = tensor<string, []>("x_283_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_283_split_1_sigmoid_cast_fp16 = sigmoid(x = x_283_split_cast_fp16_1)[name = tensor<string, []>("x_283_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_283_cast_fp16 = mul(x = x_283_split_cast_fp16_0, y = x_283_split_1_sigmoid_cast_fp16)[name = tensor<string, []>("x_283_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_669_cast_fp16 = select(a = var_11_to_fp16, b = x_283_cast_fp16, cond = var_351)[name = tensor<string, []>("input_669_cast_fp16")];
            tensor<int32, [6]> input_671_pad_0 = const()[name = tensor<string, []>("input_671_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            tensor<string, []> input_671_mode_0 = const()[name = tensor<string, []>("input_671_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_137_to_fp16 = const()[name = tensor<string, []>("const_137_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_671_cast_fp16 = pad(constant_val = const_137_to_fp16, mode = input_671_mode_0, pad = input_671_pad_0, x = input_669_cast_fp16)[name = tensor<string, []>("input_671_cast_fp16")];
            tensor<string, []> input_673_pad_type_0 = const()[name = tensor<string, []>("input_673_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, []> input_673_groups_0 = const()[name = tensor<string, []>("input_673_groups_0"), val = tensor<int32, []>(1024)];
            tensor<int32, [1]> input_673_strides_0 = const()[name = tensor<string, []>("input_673_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_673_pad_0 = const()[name = tensor<string, []>("input_673_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_673_dilations_0 = const()[name = tensor<string, []>("input_673_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_352_to_fp16 = const()[name = tensor<string, []>("const_352_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(627853824)))];
            tensor<fp16, [1024]> const_353_to_fp16 = const()[name = tensor<string, []>("const_353_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(627872320)))];
            tensor<fp16, [1, 1024, 188]> input_675_cast_fp16 = conv(bias = const_353_to_fp16, dilations = input_673_dilations_0, groups = input_673_groups_0, pad = input_673_pad_0, pad_type = input_673_pad_type_0, strides = input_673_strides_0, weight = const_352_to_fp16, x = input_671_cast_fp16)[name = tensor<string, []>("input_675_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_677_cast_fp16 = silu(x = input_675_cast_fp16)[name = tensor<string, []>("input_677_cast_fp16")];
            tensor<string, []> x_285_pad_type_0 = const()[name = tensor<string, []>("x_285_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> x_285_strides_0 = const()[name = tensor<string, []>("x_285_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_285_pad_0 = const()[name = tensor<string, []>("x_285_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_285_dilations_0 = const()[name = tensor<string, []>("x_285_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> x_285_groups_0 = const()[name = tensor<string, []>("x_285_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1024, 1024, 1]> encoder_layers_12_conv_pointwise_conv2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_12_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(627874432)))];
            tensor<fp16, [1024]> encoder_layers_12_conv_pointwise_conv2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_12_conv_pointwise_conv2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(629971648)))];
            tensor<fp16, [1, 1024, 188]> x_285_cast_fp16 = conv(bias = encoder_layers_12_conv_pointwise_conv2_bias_to_fp16, dilations = x_285_dilations_0, groups = x_285_groups_0, pad = x_285_pad_0, pad_type = x_285_pad_type_0, strides = x_285_strides_0, weight = encoder_layers_12_conv_pointwise_conv2_weight_to_fp16, x = input_677_cast_fp16)[name = tensor<string, []>("x_285_cast_fp16")];
            tensor<int32, [3]> input_679_perm_0 = const()[name = tensor<string, []>("input_679_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_679_cast_fp16 = transpose(perm = input_679_perm_0, x = x_285_cast_fp16)[name = tensor<string, []>("transpose_293")];
            tensor<fp16, [1, 188, 1024]> input_681_cast_fp16 = add(x = input_663_cast_fp16, y = input_679_cast_fp16)[name = tensor<string, []>("input_681_cast_fp16")];
            tensor<int32, [1]> input_683_axes_0 = const()[name = tensor<string, []>("input_683_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_12_norm_feed_forward2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_12_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(629973760)))];
            tensor<fp16, [1024]> encoder_layers_12_norm_feed_forward2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_12_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(629975872)))];
            tensor<fp16, [1, 188, 1024]> input_683_cast_fp16 = layer_norm(axes = input_683_axes_0, beta = encoder_layers_12_norm_feed_forward2_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_12_norm_feed_forward2_weight_to_fp16, x = input_681_cast_fp16)[name = tensor<string, []>("input_683_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_12_feed_forward2_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_12_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(629977984)))];
            tensor<fp16, [4096]> encoder_layers_12_feed_forward2_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_12_feed_forward2_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(638366656)))];
            tensor<fp16, [1, 188, 4096]> linear_116_cast_fp16 = linear(bias = encoder_layers_12_feed_forward2_linear1_bias_to_fp16, weight = encoder_layers_12_feed_forward2_linear1_weight_to_fp16, x = input_683_cast_fp16)[name = tensor<string, []>("linear_116_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_687_cast_fp16 = silu(x = linear_116_cast_fp16)[name = tensor<string, []>("input_687_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_12_feed_forward2_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_12_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(638374912)))];
            tensor<fp16, [1024]> encoder_layers_12_feed_forward2_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_12_feed_forward2_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(646763584)))];
            tensor<fp16, [1, 188, 1024]> linear_117_cast_fp16 = linear(bias = encoder_layers_12_feed_forward2_linear2_bias_to_fp16, weight = encoder_layers_12_feed_forward2_linear2_weight_to_fp16, x = input_687_cast_fp16)[name = tensor<string, []>("linear_117_cast_fp16")];
            tensor<fp16, []> var_2481_to_fp16 = const()[name = tensor<string, []>("op_2481_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_2482_cast_fp16 = mul(x = linear_117_cast_fp16, y = var_2481_to_fp16)[name = tensor<string, []>("op_2482_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_693_cast_fp16 = add(x = input_681_cast_fp16, y = var_2482_cast_fp16)[name = tensor<string, []>("input_693_cast_fp16")];
            tensor<int32, [1]> input_695_axes_0 = const()[name = tensor<string, []>("input_695_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_12_norm_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_12_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(646765696)))];
            tensor<fp16, [1024]> encoder_layers_12_norm_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_12_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(646767808)))];
            tensor<fp16, [1, 188, 1024]> input_695_cast_fp16 = layer_norm(axes = input_695_axes_0, beta = encoder_layers_12_norm_out_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_12_norm_out_weight_to_fp16, x = input_693_cast_fp16)[name = tensor<string, []>("input_695_cast_fp16")];
            tensor<int32, [1]> input_697_axes_0 = const()[name = tensor<string, []>("input_697_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_13_norm_feed_forward1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_13_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(646769920)))];
            tensor<fp16, [1024]> encoder_layers_13_norm_feed_forward1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_13_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(646772032)))];
            tensor<fp16, [1, 188, 1024]> input_697_cast_fp16 = layer_norm(axes = input_697_axes_0, beta = encoder_layers_13_norm_feed_forward1_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_13_norm_feed_forward1_weight_to_fp16, x = input_695_cast_fp16)[name = tensor<string, []>("input_697_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_13_feed_forward1_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_13_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(646774144)))];
            tensor<fp16, [4096]> encoder_layers_13_feed_forward1_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_13_feed_forward1_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(655162816)))];
            tensor<fp16, [1, 188, 4096]> linear_118_cast_fp16 = linear(bias = encoder_layers_13_feed_forward1_linear1_bias_to_fp16, weight = encoder_layers_13_feed_forward1_linear1_weight_to_fp16, x = input_697_cast_fp16)[name = tensor<string, []>("linear_118_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_701_cast_fp16 = silu(x = linear_118_cast_fp16)[name = tensor<string, []>("input_701_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_13_feed_forward1_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_13_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(655171072)))];
            tensor<fp16, [1024]> encoder_layers_13_feed_forward1_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_13_feed_forward1_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(663559744)))];
            tensor<fp16, [1, 188, 1024]> linear_119_cast_fp16 = linear(bias = encoder_layers_13_feed_forward1_linear2_bias_to_fp16, weight = encoder_layers_13_feed_forward1_linear2_weight_to_fp16, x = input_701_cast_fp16)[name = tensor<string, []>("linear_119_cast_fp16")];
            tensor<fp16, []> var_2512_to_fp16 = const()[name = tensor<string, []>("op_2512_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_2513_cast_fp16 = mul(x = linear_119_cast_fp16, y = var_2512_to_fp16)[name = tensor<string, []>("op_2513_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_707_cast_fp16 = add(x = input_695_cast_fp16, y = var_2513_cast_fp16)[name = tensor<string, []>("input_707_cast_fp16")];
            tensor<int32, [1]> query_27_axes_0 = const()[name = tensor<string, []>("query_27_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_13_norm_self_att_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_13_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(663561856)))];
            tensor<fp16, [1024]> encoder_layers_13_norm_self_att_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_13_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(663563968)))];
            tensor<fp16, [1, 188, 1024]> query_27_cast_fp16 = layer_norm(axes = query_27_axes_0, beta = encoder_layers_13_norm_self_att_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_13_norm_self_att_weight_to_fp16, x = input_707_cast_fp16)[name = tensor<string, []>("query_27_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_13_self_attn_linear_q_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_13_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(663566080)))];
            tensor<fp16, [1024]> encoder_layers_13_self_attn_linear_q_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_13_self_attn_linear_q_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(665663296)))];
            tensor<fp16, [1, 188, 1024]> linear_120_cast_fp16 = linear(bias = encoder_layers_13_self_attn_linear_q_bias_to_fp16, weight = encoder_layers_13_self_attn_linear_q_weight_to_fp16, x = query_27_cast_fp16)[name = tensor<string, []>("linear_120_cast_fp16")];
            tensor<int32, [4]> var_2530 = const()[name = tensor<string, []>("op_2530"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_79_cast_fp16 = reshape(shape = var_2530, x = linear_120_cast_fp16)[name = tensor<string, []>("q_79_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_13_self_attn_linear_k_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_13_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(665665408)))];
            tensor<fp16, [1024]> encoder_layers_13_self_attn_linear_k_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_13_self_attn_linear_k_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(667762624)))];
            tensor<fp16, [1, 188, 1024]> linear_121_cast_fp16 = linear(bias = encoder_layers_13_self_attn_linear_k_bias_to_fp16, weight = encoder_layers_13_self_attn_linear_k_weight_to_fp16, x = query_27_cast_fp16)[name = tensor<string, []>("linear_121_cast_fp16")];
            tensor<int32, [4]> var_2535 = const()[name = tensor<string, []>("op_2535"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_53_cast_fp16 = reshape(shape = var_2535, x = linear_121_cast_fp16)[name = tensor<string, []>("k_53_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_13_self_attn_linear_v_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_13_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(667764736)))];
            tensor<fp16, [1024]> encoder_layers_13_self_attn_linear_v_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_13_self_attn_linear_v_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(669861952)))];
            tensor<fp16, [1, 188, 1024]> linear_122_cast_fp16 = linear(bias = encoder_layers_13_self_attn_linear_v_bias_to_fp16, weight = encoder_layers_13_self_attn_linear_v_weight_to_fp16, x = query_27_cast_fp16)[name = tensor<string, []>("linear_122_cast_fp16")];
            tensor<int32, [4]> var_2540 = const()[name = tensor<string, []>("op_2540"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_27_cast_fp16 = reshape(shape = var_2540, x = linear_122_cast_fp16)[name = tensor<string, []>("v_27_cast_fp16")];
            tensor<int32, [4]> value_29_perm_0 = const()[name = tensor<string, []>("value_29_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> encoder_layers_13_self_attn_pos_bias_u_to_fp16 = const()[name = tensor<string, []>("encoder_layers_13_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(669864064)))];
            tensor<fp16, [1, 188, 8, 128]> var_2552_cast_fp16 = add(x = q_79_cast_fp16, y = encoder_layers_13_self_attn_pos_bias_u_to_fp16)[name = tensor<string, []>("op_2552_cast_fp16")];
            tensor<fp16, [8, 128]> encoder_layers_13_self_attn_pos_bias_v_to_fp16 = const()[name = tensor<string, []>("encoder_layers_13_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(669866176)))];
            tensor<fp16, [1, 188, 8, 128]> var_2554_cast_fp16 = add(x = q_79_cast_fp16, y = encoder_layers_13_self_attn_pos_bias_v_to_fp16)[name = tensor<string, []>("op_2554_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_27_perm_0 = const()[name = tensor<string, []>("q_with_bias_v_27_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<bool, []> x_293_transpose_x_0 = const()[name = tensor<string, []>("x_293_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_293_transpose_y_0 = const()[name = tensor<string, []>("x_293_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 128, 375]> var_2556_to_fp16 = const()[name = tensor<string, []>("op_2556_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(669868288)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_27_cast_fp16 = transpose(perm = q_with_bias_v_27_perm_0, x = var_2554_cast_fp16)[name = tensor<string, []>("transpose_291")];
            tensor<fp16, [1, 8, 188, 375]> x_293_cast_fp16 = matmul(transpose_x = x_293_transpose_x_0, transpose_y = x_293_transpose_y_0, x = q_with_bias_v_27_cast_fp16, y = var_2556_to_fp16)[name = tensor<string, []>("x_293_cast_fp16")];
            tensor<int32, [8]> x_295_pad_0 = const()[name = tensor<string, []>("x_295_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            tensor<string, []> x_295_mode_0 = const()[name = tensor<string, []>("x_295_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_144_to_fp16 = const()[name = tensor<string, []>("const_144_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_295_cast_fp16 = pad(constant_val = const_144_to_fp16, mode = x_295_mode_0, pad = x_295_pad_0, x = x_293_cast_fp16)[name = tensor<string, []>("x_295_cast_fp16")];
            tensor<int32, [4]> var_2564 = const()[name = tensor<string, []>("op_2564"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_297_cast_fp16 = reshape(shape = var_2564, x = x_295_cast_fp16)[name = tensor<string, []>("x_297_cast_fp16")];
            tensor<int32, [4]> var_2568_begin_0 = const()[name = tensor<string, []>("op_2568_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_2568_end_0 = const()[name = tensor<string, []>("op_2568_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_2568_end_mask_0 = const()[name = tensor<string, []>("op_2568_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_2568_cast_fp16 = slice_by_index(begin = var_2568_begin_0, end = var_2568_end_0, end_mask = var_2568_end_mask_0, x = x_297_cast_fp16)[name = tensor<string, []>("op_2568_cast_fp16")];
            tensor<int32, [4]> var_2569 = const()[name = tensor<string, []>("op_2569"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_53_cast_fp16 = reshape(shape = var_2569, x = var_2568_cast_fp16)[name = tensor<string, []>("matrix_bd_53_cast_fp16")];
            tensor<bool, []> matrix_ac_27_transpose_x_0 = const()[name = tensor<string, []>("matrix_ac_27_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> matrix_ac_27_transpose_y_0 = const()[name = tensor<string, []>("matrix_ac_27_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<int32, [4]> transpose_122_perm_0 = const()[name = tensor<string, []>("transpose_122_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_123_perm_0 = const()[name = tensor<string, []>("transpose_123_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_123 = transpose(perm = transpose_123_perm_0, x = k_53_cast_fp16)[name = tensor<string, []>("transpose_289")];
            tensor<fp16, [1, 8, 188, 128]> transpose_122 = transpose(perm = transpose_122_perm_0, x = var_2552_cast_fp16)[name = tensor<string, []>("transpose_290")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_27_cast_fp16 = matmul(transpose_x = matrix_ac_27_transpose_x_0, transpose_y = matrix_ac_27_transpose_y_0, x = transpose_122, y = transpose_123)[name = tensor<string, []>("matrix_ac_27_cast_fp16")];
            tensor<int32, [4]> matrix_bd_55_begin_0 = const()[name = tensor<string, []>("matrix_bd_55_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_55_end_0 = const()[name = tensor<string, []>("matrix_bd_55_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_55_end_mask_0 = const()[name = tensor<string, []>("matrix_bd_55_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_55_cast_fp16 = slice_by_index(begin = matrix_bd_55_begin_0, end = matrix_bd_55_end_0, end_mask = matrix_bd_55_end_mask_0, x = matrix_bd_53_cast_fp16)[name = tensor<string, []>("matrix_bd_55_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_2578_cast_fp16 = add(x = matrix_ac_27_cast_fp16, y = matrix_bd_55_cast_fp16)[name = tensor<string, []>("op_2578_cast_fp16")];
            tensor<fp16, []> _inversed_scores_53_y_0_to_fp16 = const()[name = tensor<string, []>("_inversed_scores_53_y_0_to_fp16"), val = tensor<fp16, []>(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_53_cast_fp16 = mul(x = var_2578_cast_fp16, y = _inversed_scores_53_y_0_to_fp16)[name = tensor<string, []>("_inversed_scores_53_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_55_cast_fp16 = select(a = var_12_to_fp16, b = _inversed_scores_53_cast_fp16, cond = mask_3)[name = tensor<string, []>("scores_55_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_2584_cast_fp16 = softmax(axis = var_30, x = scores_55_cast_fp16)[name = tensor<string, []>("op_2584_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_709_cast_fp16 = select(a = var_11_to_fp16, b = var_2584_cast_fp16, cond = mask_3)[name = tensor<string, []>("input_709_cast_fp16")];
            tensor<bool, []> x_299_transpose_x_0 = const()[name = tensor<string, []>("x_299_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_299_transpose_y_0 = const()[name = tensor<string, []>("x_299_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 188, 128]> value_29_cast_fp16 = transpose(perm = value_29_perm_0, x = v_27_cast_fp16)[name = tensor<string, []>("transpose_292")];
            tensor<fp16, [1, 8, 188, 128]> x_299_cast_fp16 = matmul(transpose_x = x_299_transpose_x_0, transpose_y = x_299_transpose_y_0, x = input_709_cast_fp16, y = value_29_cast_fp16)[name = tensor<string, []>("x_299_cast_fp16")];
            tensor<int32, [4]> var_2588_perm_0 = const()[name = tensor<string, []>("op_2588_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2589 = const()[name = tensor<string, []>("op_2589"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_2588_cast_fp16 = transpose(perm = var_2588_perm_0, x = x_299_cast_fp16)[name = tensor<string, []>("transpose_288")];
            tensor<fp16, [1, 188, 1024]> input_711_cast_fp16 = reshape(shape = var_2589, x = var_2588_cast_fp16)[name = tensor<string, []>("input_711_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_13_self_attn_linear_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_13_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(670636352)))];
            tensor<fp16, [1024]> encoder_layers_13_self_attn_linear_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_13_self_attn_linear_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(672733568)))];
            tensor<fp16, [1, 188, 1024]> linear_124_cast_fp16 = linear(bias = encoder_layers_13_self_attn_linear_out_bias_to_fp16, weight = encoder_layers_13_self_attn_linear_out_weight_to_fp16, x = input_711_cast_fp16)[name = tensor<string, []>("linear_124_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_715_cast_fp16 = add(x = input_707_cast_fp16, y = linear_124_cast_fp16)[name = tensor<string, []>("input_715_cast_fp16")];
            tensor<int32, [1]> x_303_axes_0 = const()[name = tensor<string, []>("x_303_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_13_norm_conv_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_13_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(672735680)))];
            tensor<fp16, [1024]> encoder_layers_13_norm_conv_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_13_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(672737792)))];
            tensor<fp16, [1, 188, 1024]> x_303_cast_fp16 = layer_norm(axes = x_303_axes_0, beta = encoder_layers_13_norm_conv_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_13_norm_conv_weight_to_fp16, x = input_715_cast_fp16)[name = tensor<string, []>("x_303_cast_fp16")];
            tensor<int32, [3]> input_717_perm_0 = const()[name = tensor<string, []>("input_717_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> input_719_pad_type_0 = const()[name = tensor<string, []>("input_719_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_719_strides_0 = const()[name = tensor<string, []>("input_719_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_719_pad_0 = const()[name = tensor<string, []>("input_719_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_719_dilations_0 = const()[name = tensor<string, []>("input_719_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_719_groups_0 = const()[name = tensor<string, []>("input_719_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [2048, 1024, 1]> encoder_layers_13_conv_pointwise_conv1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_13_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(672739904)))];
            tensor<fp16, [2048]> encoder_layers_13_conv_pointwise_conv1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_13_conv_pointwise_conv1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(676934272)))];
            tensor<fp16, [1, 1024, 188]> input_717_cast_fp16 = transpose(perm = input_717_perm_0, x = x_303_cast_fp16)[name = tensor<string, []>("transpose_287")];
            tensor<fp16, [1, 2048, 188]> input_719_cast_fp16 = conv(bias = encoder_layers_13_conv_pointwise_conv1_bias_to_fp16, dilations = input_719_dilations_0, groups = input_719_groups_0, pad = input_719_pad_0, pad_type = input_719_pad_type_0, strides = input_719_strides_0, weight = encoder_layers_13_conv_pointwise_conv1_weight_to_fp16, x = input_717_cast_fp16)[name = tensor<string, []>("input_719_cast_fp16")];
            tensor<int32, []> x_305_split_num_splits_0 = const()[name = tensor<string, []>("x_305_split_num_splits_0"), val = tensor<int32, []>(2)];
            tensor<int32, []> x_305_split_axis_0 = const()[name = tensor<string, []>("x_305_split_axis_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1, 1024, 188]> x_305_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_305_split_cast_fp16_1 = split(axis = x_305_split_axis_0, num_splits = x_305_split_num_splits_0, x = input_719_cast_fp16)[name = tensor<string, []>("x_305_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_305_split_1_sigmoid_cast_fp16 = sigmoid(x = x_305_split_cast_fp16_1)[name = tensor<string, []>("x_305_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_305_cast_fp16 = mul(x = x_305_split_cast_fp16_0, y = x_305_split_1_sigmoid_cast_fp16)[name = tensor<string, []>("x_305_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_721_cast_fp16 = select(a = var_11_to_fp16, b = x_305_cast_fp16, cond = var_351)[name = tensor<string, []>("input_721_cast_fp16")];
            tensor<int32, [6]> input_723_pad_0 = const()[name = tensor<string, []>("input_723_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            tensor<string, []> input_723_mode_0 = const()[name = tensor<string, []>("input_723_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_147_to_fp16 = const()[name = tensor<string, []>("const_147_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_723_cast_fp16 = pad(constant_val = const_147_to_fp16, mode = input_723_mode_0, pad = input_723_pad_0, x = input_721_cast_fp16)[name = tensor<string, []>("input_723_cast_fp16")];
            tensor<string, []> input_725_pad_type_0 = const()[name = tensor<string, []>("input_725_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, []> input_725_groups_0 = const()[name = tensor<string, []>("input_725_groups_0"), val = tensor<int32, []>(1024)];
            tensor<int32, [1]> input_725_strides_0 = const()[name = tensor<string, []>("input_725_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_725_pad_0 = const()[name = tensor<string, []>("input_725_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_725_dilations_0 = const()[name = tensor<string, []>("input_725_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_354_to_fp16 = const()[name = tensor<string, []>("const_354_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(676938432)))];
            tensor<fp16, [1024]> const_355_to_fp16 = const()[name = tensor<string, []>("const_355_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(676956928)))];
            tensor<fp16, [1, 1024, 188]> input_727_cast_fp16 = conv(bias = const_355_to_fp16, dilations = input_725_dilations_0, groups = input_725_groups_0, pad = input_725_pad_0, pad_type = input_725_pad_type_0, strides = input_725_strides_0, weight = const_354_to_fp16, x = input_723_cast_fp16)[name = tensor<string, []>("input_727_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_729_cast_fp16 = silu(x = input_727_cast_fp16)[name = tensor<string, []>("input_729_cast_fp16")];
            tensor<string, []> x_307_pad_type_0 = const()[name = tensor<string, []>("x_307_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> x_307_strides_0 = const()[name = tensor<string, []>("x_307_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_307_pad_0 = const()[name = tensor<string, []>("x_307_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_307_dilations_0 = const()[name = tensor<string, []>("x_307_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> x_307_groups_0 = const()[name = tensor<string, []>("x_307_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1024, 1024, 1]> encoder_layers_13_conv_pointwise_conv2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_13_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(676959040)))];
            tensor<fp16, [1024]> encoder_layers_13_conv_pointwise_conv2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_13_conv_pointwise_conv2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(679056256)))];
            tensor<fp16, [1, 1024, 188]> x_307_cast_fp16 = conv(bias = encoder_layers_13_conv_pointwise_conv2_bias_to_fp16, dilations = x_307_dilations_0, groups = x_307_groups_0, pad = x_307_pad_0, pad_type = x_307_pad_type_0, strides = x_307_strides_0, weight = encoder_layers_13_conv_pointwise_conv2_weight_to_fp16, x = input_729_cast_fp16)[name = tensor<string, []>("x_307_cast_fp16")];
            tensor<int32, [3]> input_731_perm_0 = const()[name = tensor<string, []>("input_731_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_731_cast_fp16 = transpose(perm = input_731_perm_0, x = x_307_cast_fp16)[name = tensor<string, []>("transpose_286")];
            tensor<fp16, [1, 188, 1024]> input_733_cast_fp16 = add(x = input_715_cast_fp16, y = input_731_cast_fp16)[name = tensor<string, []>("input_733_cast_fp16")];
            tensor<int32, [1]> input_735_axes_0 = const()[name = tensor<string, []>("input_735_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_13_norm_feed_forward2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_13_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(679058368)))];
            tensor<fp16, [1024]> encoder_layers_13_norm_feed_forward2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_13_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(679060480)))];
            tensor<fp16, [1, 188, 1024]> input_735_cast_fp16 = layer_norm(axes = input_735_axes_0, beta = encoder_layers_13_norm_feed_forward2_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_13_norm_feed_forward2_weight_to_fp16, x = input_733_cast_fp16)[name = tensor<string, []>("input_735_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_13_feed_forward2_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_13_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(679062592)))];
            tensor<fp16, [4096]> encoder_layers_13_feed_forward2_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_13_feed_forward2_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(687451264)))];
            tensor<fp16, [1, 188, 4096]> linear_125_cast_fp16 = linear(bias = encoder_layers_13_feed_forward2_linear1_bias_to_fp16, weight = encoder_layers_13_feed_forward2_linear1_weight_to_fp16, x = input_735_cast_fp16)[name = tensor<string, []>("linear_125_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_739_cast_fp16 = silu(x = linear_125_cast_fp16)[name = tensor<string, []>("input_739_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_13_feed_forward2_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_13_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(687459520)))];
            tensor<fp16, [1024]> encoder_layers_13_feed_forward2_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_13_feed_forward2_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(695848192)))];
            tensor<fp16, [1, 188, 1024]> linear_126_cast_fp16 = linear(bias = encoder_layers_13_feed_forward2_linear2_bias_to_fp16, weight = encoder_layers_13_feed_forward2_linear2_weight_to_fp16, x = input_739_cast_fp16)[name = tensor<string, []>("linear_126_cast_fp16")];
            tensor<fp16, []> var_2655_to_fp16 = const()[name = tensor<string, []>("op_2655_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_2656_cast_fp16 = mul(x = linear_126_cast_fp16, y = var_2655_to_fp16)[name = tensor<string, []>("op_2656_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_745_cast_fp16 = add(x = input_733_cast_fp16, y = var_2656_cast_fp16)[name = tensor<string, []>("input_745_cast_fp16")];
            tensor<int32, [1]> input_747_axes_0 = const()[name = tensor<string, []>("input_747_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_13_norm_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_13_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(695850304)))];
            tensor<fp16, [1024]> encoder_layers_13_norm_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_13_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(695852416)))];
            tensor<fp16, [1, 188, 1024]> input_747_cast_fp16 = layer_norm(axes = input_747_axes_0, beta = encoder_layers_13_norm_out_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_13_norm_out_weight_to_fp16, x = input_745_cast_fp16)[name = tensor<string, []>("input_747_cast_fp16")];
            tensor<int32, [1]> input_749_axes_0 = const()[name = tensor<string, []>("input_749_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_14_norm_feed_forward1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_14_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(695854528)))];
            tensor<fp16, [1024]> encoder_layers_14_norm_feed_forward1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_14_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(695856640)))];
            tensor<fp16, [1, 188, 1024]> input_749_cast_fp16 = layer_norm(axes = input_749_axes_0, beta = encoder_layers_14_norm_feed_forward1_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_14_norm_feed_forward1_weight_to_fp16, x = input_747_cast_fp16)[name = tensor<string, []>("input_749_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_14_feed_forward1_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_14_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(695858752)))];
            tensor<fp16, [4096]> encoder_layers_14_feed_forward1_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_14_feed_forward1_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(704247424)))];
            tensor<fp16, [1, 188, 4096]> linear_127_cast_fp16 = linear(bias = encoder_layers_14_feed_forward1_linear1_bias_to_fp16, weight = encoder_layers_14_feed_forward1_linear1_weight_to_fp16, x = input_749_cast_fp16)[name = tensor<string, []>("linear_127_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_753_cast_fp16 = silu(x = linear_127_cast_fp16)[name = tensor<string, []>("input_753_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_14_feed_forward1_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_14_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(704255680)))];
            tensor<fp16, [1024]> encoder_layers_14_feed_forward1_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_14_feed_forward1_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(712644352)))];
            tensor<fp16, [1, 188, 1024]> linear_128_cast_fp16 = linear(bias = encoder_layers_14_feed_forward1_linear2_bias_to_fp16, weight = encoder_layers_14_feed_forward1_linear2_weight_to_fp16, x = input_753_cast_fp16)[name = tensor<string, []>("linear_128_cast_fp16")];
            tensor<fp16, []> var_2686_to_fp16 = const()[name = tensor<string, []>("op_2686_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_2687_cast_fp16 = mul(x = linear_128_cast_fp16, y = var_2686_to_fp16)[name = tensor<string, []>("op_2687_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_759_cast_fp16 = add(x = input_747_cast_fp16, y = var_2687_cast_fp16)[name = tensor<string, []>("input_759_cast_fp16")];
            tensor<int32, [1]> query_29_axes_0 = const()[name = tensor<string, []>("query_29_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_14_norm_self_att_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_14_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(712646464)))];
            tensor<fp16, [1024]> encoder_layers_14_norm_self_att_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_14_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(712648576)))];
            tensor<fp16, [1, 188, 1024]> query_29_cast_fp16 = layer_norm(axes = query_29_axes_0, beta = encoder_layers_14_norm_self_att_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_14_norm_self_att_weight_to_fp16, x = input_759_cast_fp16)[name = tensor<string, []>("query_29_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_14_self_attn_linear_q_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_14_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(712650688)))];
            tensor<fp16, [1024]> encoder_layers_14_self_attn_linear_q_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_14_self_attn_linear_q_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(714747904)))];
            tensor<fp16, [1, 188, 1024]> linear_129_cast_fp16 = linear(bias = encoder_layers_14_self_attn_linear_q_bias_to_fp16, weight = encoder_layers_14_self_attn_linear_q_weight_to_fp16, x = query_29_cast_fp16)[name = tensor<string, []>("linear_129_cast_fp16")];
            tensor<int32, [4]> var_2704 = const()[name = tensor<string, []>("op_2704"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_85_cast_fp16 = reshape(shape = var_2704, x = linear_129_cast_fp16)[name = tensor<string, []>("q_85_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_14_self_attn_linear_k_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_14_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(714750016)))];
            tensor<fp16, [1024]> encoder_layers_14_self_attn_linear_k_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_14_self_attn_linear_k_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(716847232)))];
            tensor<fp16, [1, 188, 1024]> linear_130_cast_fp16 = linear(bias = encoder_layers_14_self_attn_linear_k_bias_to_fp16, weight = encoder_layers_14_self_attn_linear_k_weight_to_fp16, x = query_29_cast_fp16)[name = tensor<string, []>("linear_130_cast_fp16")];
            tensor<int32, [4]> var_2709 = const()[name = tensor<string, []>("op_2709"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_57_cast_fp16 = reshape(shape = var_2709, x = linear_130_cast_fp16)[name = tensor<string, []>("k_57_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_14_self_attn_linear_v_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_14_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(716849344)))];
            tensor<fp16, [1024]> encoder_layers_14_self_attn_linear_v_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_14_self_attn_linear_v_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(718946560)))];
            tensor<fp16, [1, 188, 1024]> linear_131_cast_fp16 = linear(bias = encoder_layers_14_self_attn_linear_v_bias_to_fp16, weight = encoder_layers_14_self_attn_linear_v_weight_to_fp16, x = query_29_cast_fp16)[name = tensor<string, []>("linear_131_cast_fp16")];
            tensor<int32, [4]> var_2714 = const()[name = tensor<string, []>("op_2714"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_29_cast_fp16 = reshape(shape = var_2714, x = linear_131_cast_fp16)[name = tensor<string, []>("v_29_cast_fp16")];
            tensor<int32, [4]> value_31_perm_0 = const()[name = tensor<string, []>("value_31_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> encoder_layers_14_self_attn_pos_bias_u_to_fp16 = const()[name = tensor<string, []>("encoder_layers_14_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(718948672)))];
            tensor<fp16, [1, 188, 8, 128]> var_2726_cast_fp16 = add(x = q_85_cast_fp16, y = encoder_layers_14_self_attn_pos_bias_u_to_fp16)[name = tensor<string, []>("op_2726_cast_fp16")];
            tensor<fp16, [8, 128]> encoder_layers_14_self_attn_pos_bias_v_to_fp16 = const()[name = tensor<string, []>("encoder_layers_14_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(718950784)))];
            tensor<fp16, [1, 188, 8, 128]> var_2728_cast_fp16 = add(x = q_85_cast_fp16, y = encoder_layers_14_self_attn_pos_bias_v_to_fp16)[name = tensor<string, []>("op_2728_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_29_perm_0 = const()[name = tensor<string, []>("q_with_bias_v_29_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<bool, []> x_315_transpose_x_0 = const()[name = tensor<string, []>("x_315_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_315_transpose_y_0 = const()[name = tensor<string, []>("x_315_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 128, 375]> var_2730_to_fp16 = const()[name = tensor<string, []>("op_2730_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(718952896)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_29_cast_fp16 = transpose(perm = q_with_bias_v_29_perm_0, x = var_2728_cast_fp16)[name = tensor<string, []>("transpose_284")];
            tensor<fp16, [1, 8, 188, 375]> x_315_cast_fp16 = matmul(transpose_x = x_315_transpose_x_0, transpose_y = x_315_transpose_y_0, x = q_with_bias_v_29_cast_fp16, y = var_2730_to_fp16)[name = tensor<string, []>("x_315_cast_fp16")];
            tensor<int32, [8]> x_317_pad_0 = const()[name = tensor<string, []>("x_317_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            tensor<string, []> x_317_mode_0 = const()[name = tensor<string, []>("x_317_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_154_to_fp16 = const()[name = tensor<string, []>("const_154_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_317_cast_fp16 = pad(constant_val = const_154_to_fp16, mode = x_317_mode_0, pad = x_317_pad_0, x = x_315_cast_fp16)[name = tensor<string, []>("x_317_cast_fp16")];
            tensor<int32, [4]> var_2738 = const()[name = tensor<string, []>("op_2738"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_319_cast_fp16 = reshape(shape = var_2738, x = x_317_cast_fp16)[name = tensor<string, []>("x_319_cast_fp16")];
            tensor<int32, [4]> var_2742_begin_0 = const()[name = tensor<string, []>("op_2742_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_2742_end_0 = const()[name = tensor<string, []>("op_2742_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_2742_end_mask_0 = const()[name = tensor<string, []>("op_2742_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_2742_cast_fp16 = slice_by_index(begin = var_2742_begin_0, end = var_2742_end_0, end_mask = var_2742_end_mask_0, x = x_319_cast_fp16)[name = tensor<string, []>("op_2742_cast_fp16")];
            tensor<int32, [4]> var_2743 = const()[name = tensor<string, []>("op_2743"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_57_cast_fp16 = reshape(shape = var_2743, x = var_2742_cast_fp16)[name = tensor<string, []>("matrix_bd_57_cast_fp16")];
            tensor<bool, []> matrix_ac_29_transpose_x_0 = const()[name = tensor<string, []>("matrix_ac_29_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> matrix_ac_29_transpose_y_0 = const()[name = tensor<string, []>("matrix_ac_29_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<int32, [4]> transpose_124_perm_0 = const()[name = tensor<string, []>("transpose_124_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_125_perm_0 = const()[name = tensor<string, []>("transpose_125_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_125 = transpose(perm = transpose_125_perm_0, x = k_57_cast_fp16)[name = tensor<string, []>("transpose_282")];
            tensor<fp16, [1, 8, 188, 128]> transpose_124 = transpose(perm = transpose_124_perm_0, x = var_2726_cast_fp16)[name = tensor<string, []>("transpose_283")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_29_cast_fp16 = matmul(transpose_x = matrix_ac_29_transpose_x_0, transpose_y = matrix_ac_29_transpose_y_0, x = transpose_124, y = transpose_125)[name = tensor<string, []>("matrix_ac_29_cast_fp16")];
            tensor<int32, [4]> matrix_bd_59_begin_0 = const()[name = tensor<string, []>("matrix_bd_59_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_59_end_0 = const()[name = tensor<string, []>("matrix_bd_59_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_59_end_mask_0 = const()[name = tensor<string, []>("matrix_bd_59_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_59_cast_fp16 = slice_by_index(begin = matrix_bd_59_begin_0, end = matrix_bd_59_end_0, end_mask = matrix_bd_59_end_mask_0, x = matrix_bd_57_cast_fp16)[name = tensor<string, []>("matrix_bd_59_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_2752_cast_fp16 = add(x = matrix_ac_29_cast_fp16, y = matrix_bd_59_cast_fp16)[name = tensor<string, []>("op_2752_cast_fp16")];
            tensor<fp16, []> _inversed_scores_57_y_0_to_fp16 = const()[name = tensor<string, []>("_inversed_scores_57_y_0_to_fp16"), val = tensor<fp16, []>(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_57_cast_fp16 = mul(x = var_2752_cast_fp16, y = _inversed_scores_57_y_0_to_fp16)[name = tensor<string, []>("_inversed_scores_57_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_59_cast_fp16 = select(a = var_12_to_fp16, b = _inversed_scores_57_cast_fp16, cond = mask_3)[name = tensor<string, []>("scores_59_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_2758_cast_fp16 = softmax(axis = var_30, x = scores_59_cast_fp16)[name = tensor<string, []>("op_2758_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_761_cast_fp16 = select(a = var_11_to_fp16, b = var_2758_cast_fp16, cond = mask_3)[name = tensor<string, []>("input_761_cast_fp16")];
            tensor<bool, []> x_321_transpose_x_0 = const()[name = tensor<string, []>("x_321_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_321_transpose_y_0 = const()[name = tensor<string, []>("x_321_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 188, 128]> value_31_cast_fp16 = transpose(perm = value_31_perm_0, x = v_29_cast_fp16)[name = tensor<string, []>("transpose_285")];
            tensor<fp16, [1, 8, 188, 128]> x_321_cast_fp16 = matmul(transpose_x = x_321_transpose_x_0, transpose_y = x_321_transpose_y_0, x = input_761_cast_fp16, y = value_31_cast_fp16)[name = tensor<string, []>("x_321_cast_fp16")];
            tensor<int32, [4]> var_2762_perm_0 = const()[name = tensor<string, []>("op_2762_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2763 = const()[name = tensor<string, []>("op_2763"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_2762_cast_fp16 = transpose(perm = var_2762_perm_0, x = x_321_cast_fp16)[name = tensor<string, []>("transpose_281")];
            tensor<fp16, [1, 188, 1024]> input_763_cast_fp16 = reshape(shape = var_2763, x = var_2762_cast_fp16)[name = tensor<string, []>("input_763_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_14_self_attn_linear_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_14_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(719720960)))];
            tensor<fp16, [1024]> encoder_layers_14_self_attn_linear_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_14_self_attn_linear_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(721818176)))];
            tensor<fp16, [1, 188, 1024]> linear_133_cast_fp16 = linear(bias = encoder_layers_14_self_attn_linear_out_bias_to_fp16, weight = encoder_layers_14_self_attn_linear_out_weight_to_fp16, x = input_763_cast_fp16)[name = tensor<string, []>("linear_133_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_767_cast_fp16 = add(x = input_759_cast_fp16, y = linear_133_cast_fp16)[name = tensor<string, []>("input_767_cast_fp16")];
            tensor<int32, [1]> x_325_axes_0 = const()[name = tensor<string, []>("x_325_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_14_norm_conv_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_14_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(721820288)))];
            tensor<fp16, [1024]> encoder_layers_14_norm_conv_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_14_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(721822400)))];
            tensor<fp16, [1, 188, 1024]> x_325_cast_fp16 = layer_norm(axes = x_325_axes_0, beta = encoder_layers_14_norm_conv_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_14_norm_conv_weight_to_fp16, x = input_767_cast_fp16)[name = tensor<string, []>("x_325_cast_fp16")];
            tensor<int32, [3]> input_769_perm_0 = const()[name = tensor<string, []>("input_769_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> input_771_pad_type_0 = const()[name = tensor<string, []>("input_771_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_771_strides_0 = const()[name = tensor<string, []>("input_771_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_771_pad_0 = const()[name = tensor<string, []>("input_771_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_771_dilations_0 = const()[name = tensor<string, []>("input_771_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_771_groups_0 = const()[name = tensor<string, []>("input_771_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [2048, 1024, 1]> encoder_layers_14_conv_pointwise_conv1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_14_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(721824512)))];
            tensor<fp16, [2048]> encoder_layers_14_conv_pointwise_conv1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_14_conv_pointwise_conv1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(726018880)))];
            tensor<fp16, [1, 1024, 188]> input_769_cast_fp16 = transpose(perm = input_769_perm_0, x = x_325_cast_fp16)[name = tensor<string, []>("transpose_280")];
            tensor<fp16, [1, 2048, 188]> input_771_cast_fp16 = conv(bias = encoder_layers_14_conv_pointwise_conv1_bias_to_fp16, dilations = input_771_dilations_0, groups = input_771_groups_0, pad = input_771_pad_0, pad_type = input_771_pad_type_0, strides = input_771_strides_0, weight = encoder_layers_14_conv_pointwise_conv1_weight_to_fp16, x = input_769_cast_fp16)[name = tensor<string, []>("input_771_cast_fp16")];
            tensor<int32, []> x_327_split_num_splits_0 = const()[name = tensor<string, []>("x_327_split_num_splits_0"), val = tensor<int32, []>(2)];
            tensor<int32, []> x_327_split_axis_0 = const()[name = tensor<string, []>("x_327_split_axis_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1, 1024, 188]> x_327_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_327_split_cast_fp16_1 = split(axis = x_327_split_axis_0, num_splits = x_327_split_num_splits_0, x = input_771_cast_fp16)[name = tensor<string, []>("x_327_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_327_split_1_sigmoid_cast_fp16 = sigmoid(x = x_327_split_cast_fp16_1)[name = tensor<string, []>("x_327_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_327_cast_fp16 = mul(x = x_327_split_cast_fp16_0, y = x_327_split_1_sigmoid_cast_fp16)[name = tensor<string, []>("x_327_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_773_cast_fp16 = select(a = var_11_to_fp16, b = x_327_cast_fp16, cond = var_351)[name = tensor<string, []>("input_773_cast_fp16")];
            tensor<int32, [6]> input_775_pad_0 = const()[name = tensor<string, []>("input_775_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            tensor<string, []> input_775_mode_0 = const()[name = tensor<string, []>("input_775_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_157_to_fp16 = const()[name = tensor<string, []>("const_157_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_775_cast_fp16 = pad(constant_val = const_157_to_fp16, mode = input_775_mode_0, pad = input_775_pad_0, x = input_773_cast_fp16)[name = tensor<string, []>("input_775_cast_fp16")];
            tensor<string, []> input_777_pad_type_0 = const()[name = tensor<string, []>("input_777_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, []> input_777_groups_0 = const()[name = tensor<string, []>("input_777_groups_0"), val = tensor<int32, []>(1024)];
            tensor<int32, [1]> input_777_strides_0 = const()[name = tensor<string, []>("input_777_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_777_pad_0 = const()[name = tensor<string, []>("input_777_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_777_dilations_0 = const()[name = tensor<string, []>("input_777_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_356_to_fp16 = const()[name = tensor<string, []>("const_356_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(726023040)))];
            tensor<fp16, [1024]> const_357_to_fp16 = const()[name = tensor<string, []>("const_357_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(726041536)))];
            tensor<fp16, [1, 1024, 188]> input_779_cast_fp16 = conv(bias = const_357_to_fp16, dilations = input_777_dilations_0, groups = input_777_groups_0, pad = input_777_pad_0, pad_type = input_777_pad_type_0, strides = input_777_strides_0, weight = const_356_to_fp16, x = input_775_cast_fp16)[name = tensor<string, []>("input_779_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_781_cast_fp16 = silu(x = input_779_cast_fp16)[name = tensor<string, []>("input_781_cast_fp16")];
            tensor<string, []> x_329_pad_type_0 = const()[name = tensor<string, []>("x_329_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> x_329_strides_0 = const()[name = tensor<string, []>("x_329_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_329_pad_0 = const()[name = tensor<string, []>("x_329_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_329_dilations_0 = const()[name = tensor<string, []>("x_329_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> x_329_groups_0 = const()[name = tensor<string, []>("x_329_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1024, 1024, 1]> encoder_layers_14_conv_pointwise_conv2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_14_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(726043648)))];
            tensor<fp16, [1024]> encoder_layers_14_conv_pointwise_conv2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_14_conv_pointwise_conv2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(728140864)))];
            tensor<fp16, [1, 1024, 188]> x_329_cast_fp16 = conv(bias = encoder_layers_14_conv_pointwise_conv2_bias_to_fp16, dilations = x_329_dilations_0, groups = x_329_groups_0, pad = x_329_pad_0, pad_type = x_329_pad_type_0, strides = x_329_strides_0, weight = encoder_layers_14_conv_pointwise_conv2_weight_to_fp16, x = input_781_cast_fp16)[name = tensor<string, []>("x_329_cast_fp16")];
            tensor<int32, [3]> input_783_perm_0 = const()[name = tensor<string, []>("input_783_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_783_cast_fp16 = transpose(perm = input_783_perm_0, x = x_329_cast_fp16)[name = tensor<string, []>("transpose_279")];
            tensor<fp16, [1, 188, 1024]> input_785_cast_fp16 = add(x = input_767_cast_fp16, y = input_783_cast_fp16)[name = tensor<string, []>("input_785_cast_fp16")];
            tensor<int32, [1]> input_787_axes_0 = const()[name = tensor<string, []>("input_787_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_14_norm_feed_forward2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_14_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(728142976)))];
            tensor<fp16, [1024]> encoder_layers_14_norm_feed_forward2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_14_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(728145088)))];
            tensor<fp16, [1, 188, 1024]> input_787_cast_fp16 = layer_norm(axes = input_787_axes_0, beta = encoder_layers_14_norm_feed_forward2_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_14_norm_feed_forward2_weight_to_fp16, x = input_785_cast_fp16)[name = tensor<string, []>("input_787_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_14_feed_forward2_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_14_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(728147200)))];
            tensor<fp16, [4096]> encoder_layers_14_feed_forward2_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_14_feed_forward2_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(736535872)))];
            tensor<fp16, [1, 188, 4096]> linear_134_cast_fp16 = linear(bias = encoder_layers_14_feed_forward2_linear1_bias_to_fp16, weight = encoder_layers_14_feed_forward2_linear1_weight_to_fp16, x = input_787_cast_fp16)[name = tensor<string, []>("linear_134_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_791_cast_fp16 = silu(x = linear_134_cast_fp16)[name = tensor<string, []>("input_791_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_14_feed_forward2_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_14_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(736544128)))];
            tensor<fp16, [1024]> encoder_layers_14_feed_forward2_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_14_feed_forward2_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(744932800)))];
            tensor<fp16, [1, 188, 1024]> linear_135_cast_fp16 = linear(bias = encoder_layers_14_feed_forward2_linear2_bias_to_fp16, weight = encoder_layers_14_feed_forward2_linear2_weight_to_fp16, x = input_791_cast_fp16)[name = tensor<string, []>("linear_135_cast_fp16")];
            tensor<fp16, []> var_2829_to_fp16 = const()[name = tensor<string, []>("op_2829_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_2830_cast_fp16 = mul(x = linear_135_cast_fp16, y = var_2829_to_fp16)[name = tensor<string, []>("op_2830_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_797_cast_fp16 = add(x = input_785_cast_fp16, y = var_2830_cast_fp16)[name = tensor<string, []>("input_797_cast_fp16")];
            tensor<int32, [1]> input_799_axes_0 = const()[name = tensor<string, []>("input_799_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_14_norm_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_14_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(744934912)))];
            tensor<fp16, [1024]> encoder_layers_14_norm_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_14_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(744937024)))];
            tensor<fp16, [1, 188, 1024]> input_799_cast_fp16 = layer_norm(axes = input_799_axes_0, beta = encoder_layers_14_norm_out_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_14_norm_out_weight_to_fp16, x = input_797_cast_fp16)[name = tensor<string, []>("input_799_cast_fp16")];
            tensor<int32, [1]> input_801_axes_0 = const()[name = tensor<string, []>("input_801_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_15_norm_feed_forward1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_15_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(744939136)))];
            tensor<fp16, [1024]> encoder_layers_15_norm_feed_forward1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_15_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(744941248)))];
            tensor<fp16, [1, 188, 1024]> input_801_cast_fp16 = layer_norm(axes = input_801_axes_0, beta = encoder_layers_15_norm_feed_forward1_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_15_norm_feed_forward1_weight_to_fp16, x = input_799_cast_fp16)[name = tensor<string, []>("input_801_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_15_feed_forward1_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_15_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(744943360)))];
            tensor<fp16, [4096]> encoder_layers_15_feed_forward1_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_15_feed_forward1_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(753332032)))];
            tensor<fp16, [1, 188, 4096]> linear_136_cast_fp16 = linear(bias = encoder_layers_15_feed_forward1_linear1_bias_to_fp16, weight = encoder_layers_15_feed_forward1_linear1_weight_to_fp16, x = input_801_cast_fp16)[name = tensor<string, []>("linear_136_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_805_cast_fp16 = silu(x = linear_136_cast_fp16)[name = tensor<string, []>("input_805_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_15_feed_forward1_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_15_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(753340288)))];
            tensor<fp16, [1024]> encoder_layers_15_feed_forward1_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_15_feed_forward1_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(761728960)))];
            tensor<fp16, [1, 188, 1024]> linear_137_cast_fp16 = linear(bias = encoder_layers_15_feed_forward1_linear2_bias_to_fp16, weight = encoder_layers_15_feed_forward1_linear2_weight_to_fp16, x = input_805_cast_fp16)[name = tensor<string, []>("linear_137_cast_fp16")];
            tensor<fp16, []> var_2860_to_fp16 = const()[name = tensor<string, []>("op_2860_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_2861_cast_fp16 = mul(x = linear_137_cast_fp16, y = var_2860_to_fp16)[name = tensor<string, []>("op_2861_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_811_cast_fp16 = add(x = input_799_cast_fp16, y = var_2861_cast_fp16)[name = tensor<string, []>("input_811_cast_fp16")];
            tensor<int32, [1]> query_31_axes_0 = const()[name = tensor<string, []>("query_31_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_15_norm_self_att_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_15_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(761731072)))];
            tensor<fp16, [1024]> encoder_layers_15_norm_self_att_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_15_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(761733184)))];
            tensor<fp16, [1, 188, 1024]> query_31_cast_fp16 = layer_norm(axes = query_31_axes_0, beta = encoder_layers_15_norm_self_att_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_15_norm_self_att_weight_to_fp16, x = input_811_cast_fp16)[name = tensor<string, []>("query_31_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_15_self_attn_linear_q_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_15_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(761735296)))];
            tensor<fp16, [1024]> encoder_layers_15_self_attn_linear_q_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_15_self_attn_linear_q_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(763832512)))];
            tensor<fp16, [1, 188, 1024]> linear_138_cast_fp16 = linear(bias = encoder_layers_15_self_attn_linear_q_bias_to_fp16, weight = encoder_layers_15_self_attn_linear_q_weight_to_fp16, x = query_31_cast_fp16)[name = tensor<string, []>("linear_138_cast_fp16")];
            tensor<int32, [4]> var_2878 = const()[name = tensor<string, []>("op_2878"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_91_cast_fp16 = reshape(shape = var_2878, x = linear_138_cast_fp16)[name = tensor<string, []>("q_91_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_15_self_attn_linear_k_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_15_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(763834624)))];
            tensor<fp16, [1024]> encoder_layers_15_self_attn_linear_k_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_15_self_attn_linear_k_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(765931840)))];
            tensor<fp16, [1, 188, 1024]> linear_139_cast_fp16 = linear(bias = encoder_layers_15_self_attn_linear_k_bias_to_fp16, weight = encoder_layers_15_self_attn_linear_k_weight_to_fp16, x = query_31_cast_fp16)[name = tensor<string, []>("linear_139_cast_fp16")];
            tensor<int32, [4]> var_2883 = const()[name = tensor<string, []>("op_2883"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_61_cast_fp16 = reshape(shape = var_2883, x = linear_139_cast_fp16)[name = tensor<string, []>("k_61_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_15_self_attn_linear_v_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_15_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(765933952)))];
            tensor<fp16, [1024]> encoder_layers_15_self_attn_linear_v_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_15_self_attn_linear_v_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(768031168)))];
            tensor<fp16, [1, 188, 1024]> linear_140_cast_fp16 = linear(bias = encoder_layers_15_self_attn_linear_v_bias_to_fp16, weight = encoder_layers_15_self_attn_linear_v_weight_to_fp16, x = query_31_cast_fp16)[name = tensor<string, []>("linear_140_cast_fp16")];
            tensor<int32, [4]> var_2888 = const()[name = tensor<string, []>("op_2888"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_31_cast_fp16 = reshape(shape = var_2888, x = linear_140_cast_fp16)[name = tensor<string, []>("v_31_cast_fp16")];
            tensor<int32, [4]> value_33_perm_0 = const()[name = tensor<string, []>("value_33_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> encoder_layers_15_self_attn_pos_bias_u_to_fp16 = const()[name = tensor<string, []>("encoder_layers_15_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(768033280)))];
            tensor<fp16, [1, 188, 8, 128]> var_2900_cast_fp16 = add(x = q_91_cast_fp16, y = encoder_layers_15_self_attn_pos_bias_u_to_fp16)[name = tensor<string, []>("op_2900_cast_fp16")];
            tensor<fp16, [8, 128]> encoder_layers_15_self_attn_pos_bias_v_to_fp16 = const()[name = tensor<string, []>("encoder_layers_15_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(768035392)))];
            tensor<fp16, [1, 188, 8, 128]> var_2902_cast_fp16 = add(x = q_91_cast_fp16, y = encoder_layers_15_self_attn_pos_bias_v_to_fp16)[name = tensor<string, []>("op_2902_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_31_perm_0 = const()[name = tensor<string, []>("q_with_bias_v_31_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<bool, []> x_337_transpose_x_0 = const()[name = tensor<string, []>("x_337_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_337_transpose_y_0 = const()[name = tensor<string, []>("x_337_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 128, 375]> var_2904_to_fp16 = const()[name = tensor<string, []>("op_2904_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(768037504)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_31_cast_fp16 = transpose(perm = q_with_bias_v_31_perm_0, x = var_2902_cast_fp16)[name = tensor<string, []>("transpose_277")];
            tensor<fp16, [1, 8, 188, 375]> x_337_cast_fp16 = matmul(transpose_x = x_337_transpose_x_0, transpose_y = x_337_transpose_y_0, x = q_with_bias_v_31_cast_fp16, y = var_2904_to_fp16)[name = tensor<string, []>("x_337_cast_fp16")];
            tensor<int32, [8]> x_339_pad_0 = const()[name = tensor<string, []>("x_339_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            tensor<string, []> x_339_mode_0 = const()[name = tensor<string, []>("x_339_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_164_to_fp16 = const()[name = tensor<string, []>("const_164_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_339_cast_fp16 = pad(constant_val = const_164_to_fp16, mode = x_339_mode_0, pad = x_339_pad_0, x = x_337_cast_fp16)[name = tensor<string, []>("x_339_cast_fp16")];
            tensor<int32, [4]> var_2912 = const()[name = tensor<string, []>("op_2912"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_341_cast_fp16 = reshape(shape = var_2912, x = x_339_cast_fp16)[name = tensor<string, []>("x_341_cast_fp16")];
            tensor<int32, [4]> var_2916_begin_0 = const()[name = tensor<string, []>("op_2916_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_2916_end_0 = const()[name = tensor<string, []>("op_2916_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_2916_end_mask_0 = const()[name = tensor<string, []>("op_2916_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_2916_cast_fp16 = slice_by_index(begin = var_2916_begin_0, end = var_2916_end_0, end_mask = var_2916_end_mask_0, x = x_341_cast_fp16)[name = tensor<string, []>("op_2916_cast_fp16")];
            tensor<int32, [4]> var_2917 = const()[name = tensor<string, []>("op_2917"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_61_cast_fp16 = reshape(shape = var_2917, x = var_2916_cast_fp16)[name = tensor<string, []>("matrix_bd_61_cast_fp16")];
            tensor<bool, []> matrix_ac_31_transpose_x_0 = const()[name = tensor<string, []>("matrix_ac_31_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> matrix_ac_31_transpose_y_0 = const()[name = tensor<string, []>("matrix_ac_31_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<int32, [4]> transpose_126_perm_0 = const()[name = tensor<string, []>("transpose_126_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_127_perm_0 = const()[name = tensor<string, []>("transpose_127_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_127 = transpose(perm = transpose_127_perm_0, x = k_61_cast_fp16)[name = tensor<string, []>("transpose_275")];
            tensor<fp16, [1, 8, 188, 128]> transpose_126 = transpose(perm = transpose_126_perm_0, x = var_2900_cast_fp16)[name = tensor<string, []>("transpose_276")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_31_cast_fp16 = matmul(transpose_x = matrix_ac_31_transpose_x_0, transpose_y = matrix_ac_31_transpose_y_0, x = transpose_126, y = transpose_127)[name = tensor<string, []>("matrix_ac_31_cast_fp16")];
            tensor<int32, [4]> matrix_bd_63_begin_0 = const()[name = tensor<string, []>("matrix_bd_63_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_63_end_0 = const()[name = tensor<string, []>("matrix_bd_63_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_63_end_mask_0 = const()[name = tensor<string, []>("matrix_bd_63_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_63_cast_fp16 = slice_by_index(begin = matrix_bd_63_begin_0, end = matrix_bd_63_end_0, end_mask = matrix_bd_63_end_mask_0, x = matrix_bd_61_cast_fp16)[name = tensor<string, []>("matrix_bd_63_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_2926_cast_fp16 = add(x = matrix_ac_31_cast_fp16, y = matrix_bd_63_cast_fp16)[name = tensor<string, []>("op_2926_cast_fp16")];
            tensor<fp16, []> _inversed_scores_61_y_0_to_fp16 = const()[name = tensor<string, []>("_inversed_scores_61_y_0_to_fp16"), val = tensor<fp16, []>(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_61_cast_fp16 = mul(x = var_2926_cast_fp16, y = _inversed_scores_61_y_0_to_fp16)[name = tensor<string, []>("_inversed_scores_61_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_63_cast_fp16 = select(a = var_12_to_fp16, b = _inversed_scores_61_cast_fp16, cond = mask_3)[name = tensor<string, []>("scores_63_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_2932_cast_fp16 = softmax(axis = var_30, x = scores_63_cast_fp16)[name = tensor<string, []>("op_2932_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_813_cast_fp16 = select(a = var_11_to_fp16, b = var_2932_cast_fp16, cond = mask_3)[name = tensor<string, []>("input_813_cast_fp16")];
            tensor<bool, []> x_343_transpose_x_0 = const()[name = tensor<string, []>("x_343_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_343_transpose_y_0 = const()[name = tensor<string, []>("x_343_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 188, 128]> value_33_cast_fp16 = transpose(perm = value_33_perm_0, x = v_31_cast_fp16)[name = tensor<string, []>("transpose_278")];
            tensor<fp16, [1, 8, 188, 128]> x_343_cast_fp16 = matmul(transpose_x = x_343_transpose_x_0, transpose_y = x_343_transpose_y_0, x = input_813_cast_fp16, y = value_33_cast_fp16)[name = tensor<string, []>("x_343_cast_fp16")];
            tensor<int32, [4]> var_2936_perm_0 = const()[name = tensor<string, []>("op_2936_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2937 = const()[name = tensor<string, []>("op_2937"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_2936_cast_fp16 = transpose(perm = var_2936_perm_0, x = x_343_cast_fp16)[name = tensor<string, []>("transpose_274")];
            tensor<fp16, [1, 188, 1024]> input_815_cast_fp16 = reshape(shape = var_2937, x = var_2936_cast_fp16)[name = tensor<string, []>("input_815_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_15_self_attn_linear_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_15_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(768805568)))];
            tensor<fp16, [1024]> encoder_layers_15_self_attn_linear_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_15_self_attn_linear_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(770902784)))];
            tensor<fp16, [1, 188, 1024]> linear_142_cast_fp16 = linear(bias = encoder_layers_15_self_attn_linear_out_bias_to_fp16, weight = encoder_layers_15_self_attn_linear_out_weight_to_fp16, x = input_815_cast_fp16)[name = tensor<string, []>("linear_142_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_819_cast_fp16 = add(x = input_811_cast_fp16, y = linear_142_cast_fp16)[name = tensor<string, []>("input_819_cast_fp16")];
            tensor<int32, [1]> x_347_axes_0 = const()[name = tensor<string, []>("x_347_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_15_norm_conv_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_15_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(770904896)))];
            tensor<fp16, [1024]> encoder_layers_15_norm_conv_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_15_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(770907008)))];
            tensor<fp16, [1, 188, 1024]> x_347_cast_fp16 = layer_norm(axes = x_347_axes_0, beta = encoder_layers_15_norm_conv_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_15_norm_conv_weight_to_fp16, x = input_819_cast_fp16)[name = tensor<string, []>("x_347_cast_fp16")];
            tensor<int32, [3]> input_821_perm_0 = const()[name = tensor<string, []>("input_821_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> input_823_pad_type_0 = const()[name = tensor<string, []>("input_823_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_823_strides_0 = const()[name = tensor<string, []>("input_823_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_823_pad_0 = const()[name = tensor<string, []>("input_823_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_823_dilations_0 = const()[name = tensor<string, []>("input_823_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_823_groups_0 = const()[name = tensor<string, []>("input_823_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [2048, 1024, 1]> encoder_layers_15_conv_pointwise_conv1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_15_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(770909120)))];
            tensor<fp16, [2048]> encoder_layers_15_conv_pointwise_conv1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_15_conv_pointwise_conv1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(775103488)))];
            tensor<fp16, [1, 1024, 188]> input_821_cast_fp16 = transpose(perm = input_821_perm_0, x = x_347_cast_fp16)[name = tensor<string, []>("transpose_273")];
            tensor<fp16, [1, 2048, 188]> input_823_cast_fp16 = conv(bias = encoder_layers_15_conv_pointwise_conv1_bias_to_fp16, dilations = input_823_dilations_0, groups = input_823_groups_0, pad = input_823_pad_0, pad_type = input_823_pad_type_0, strides = input_823_strides_0, weight = encoder_layers_15_conv_pointwise_conv1_weight_to_fp16, x = input_821_cast_fp16)[name = tensor<string, []>("input_823_cast_fp16")];
            tensor<int32, []> x_349_split_num_splits_0 = const()[name = tensor<string, []>("x_349_split_num_splits_0"), val = tensor<int32, []>(2)];
            tensor<int32, []> x_349_split_axis_0 = const()[name = tensor<string, []>("x_349_split_axis_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1, 1024, 188]> x_349_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_349_split_cast_fp16_1 = split(axis = x_349_split_axis_0, num_splits = x_349_split_num_splits_0, x = input_823_cast_fp16)[name = tensor<string, []>("x_349_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_349_split_1_sigmoid_cast_fp16 = sigmoid(x = x_349_split_cast_fp16_1)[name = tensor<string, []>("x_349_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_349_cast_fp16 = mul(x = x_349_split_cast_fp16_0, y = x_349_split_1_sigmoid_cast_fp16)[name = tensor<string, []>("x_349_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_825_cast_fp16 = select(a = var_11_to_fp16, b = x_349_cast_fp16, cond = var_351)[name = tensor<string, []>("input_825_cast_fp16")];
            tensor<int32, [6]> input_827_pad_0 = const()[name = tensor<string, []>("input_827_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            tensor<string, []> input_827_mode_0 = const()[name = tensor<string, []>("input_827_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_167_to_fp16 = const()[name = tensor<string, []>("const_167_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_827_cast_fp16 = pad(constant_val = const_167_to_fp16, mode = input_827_mode_0, pad = input_827_pad_0, x = input_825_cast_fp16)[name = tensor<string, []>("input_827_cast_fp16")];
            tensor<string, []> input_829_pad_type_0 = const()[name = tensor<string, []>("input_829_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, []> input_829_groups_0 = const()[name = tensor<string, []>("input_829_groups_0"), val = tensor<int32, []>(1024)];
            tensor<int32, [1]> input_829_strides_0 = const()[name = tensor<string, []>("input_829_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_829_pad_0 = const()[name = tensor<string, []>("input_829_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_829_dilations_0 = const()[name = tensor<string, []>("input_829_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_358_to_fp16 = const()[name = tensor<string, []>("const_358_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(775107648)))];
            tensor<fp16, [1024]> const_359_to_fp16 = const()[name = tensor<string, []>("const_359_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(775126144)))];
            tensor<fp16, [1, 1024, 188]> input_831_cast_fp16 = conv(bias = const_359_to_fp16, dilations = input_829_dilations_0, groups = input_829_groups_0, pad = input_829_pad_0, pad_type = input_829_pad_type_0, strides = input_829_strides_0, weight = const_358_to_fp16, x = input_827_cast_fp16)[name = tensor<string, []>("input_831_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_833_cast_fp16 = silu(x = input_831_cast_fp16)[name = tensor<string, []>("input_833_cast_fp16")];
            tensor<string, []> x_351_pad_type_0 = const()[name = tensor<string, []>("x_351_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> x_351_strides_0 = const()[name = tensor<string, []>("x_351_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_351_pad_0 = const()[name = tensor<string, []>("x_351_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_351_dilations_0 = const()[name = tensor<string, []>("x_351_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> x_351_groups_0 = const()[name = tensor<string, []>("x_351_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1024, 1024, 1]> encoder_layers_15_conv_pointwise_conv2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_15_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(775128256)))];
            tensor<fp16, [1024]> encoder_layers_15_conv_pointwise_conv2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_15_conv_pointwise_conv2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(777225472)))];
            tensor<fp16, [1, 1024, 188]> x_351_cast_fp16 = conv(bias = encoder_layers_15_conv_pointwise_conv2_bias_to_fp16, dilations = x_351_dilations_0, groups = x_351_groups_0, pad = x_351_pad_0, pad_type = x_351_pad_type_0, strides = x_351_strides_0, weight = encoder_layers_15_conv_pointwise_conv2_weight_to_fp16, x = input_833_cast_fp16)[name = tensor<string, []>("x_351_cast_fp16")];
            tensor<int32, [3]> input_835_perm_0 = const()[name = tensor<string, []>("input_835_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_835_cast_fp16 = transpose(perm = input_835_perm_0, x = x_351_cast_fp16)[name = tensor<string, []>("transpose_272")];
            tensor<fp16, [1, 188, 1024]> input_837_cast_fp16 = add(x = input_819_cast_fp16, y = input_835_cast_fp16)[name = tensor<string, []>("input_837_cast_fp16")];
            tensor<int32, [1]> input_839_axes_0 = const()[name = tensor<string, []>("input_839_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_15_norm_feed_forward2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_15_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(777227584)))];
            tensor<fp16, [1024]> encoder_layers_15_norm_feed_forward2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_15_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(777229696)))];
            tensor<fp16, [1, 188, 1024]> input_839_cast_fp16 = layer_norm(axes = input_839_axes_0, beta = encoder_layers_15_norm_feed_forward2_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_15_norm_feed_forward2_weight_to_fp16, x = input_837_cast_fp16)[name = tensor<string, []>("input_839_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_15_feed_forward2_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_15_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(777231808)))];
            tensor<fp16, [4096]> encoder_layers_15_feed_forward2_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_15_feed_forward2_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(785620480)))];
            tensor<fp16, [1, 188, 4096]> linear_143_cast_fp16 = linear(bias = encoder_layers_15_feed_forward2_linear1_bias_to_fp16, weight = encoder_layers_15_feed_forward2_linear1_weight_to_fp16, x = input_839_cast_fp16)[name = tensor<string, []>("linear_143_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_843_cast_fp16 = silu(x = linear_143_cast_fp16)[name = tensor<string, []>("input_843_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_15_feed_forward2_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_15_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(785628736)))];
            tensor<fp16, [1024]> encoder_layers_15_feed_forward2_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_15_feed_forward2_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(794017408)))];
            tensor<fp16, [1, 188, 1024]> linear_144_cast_fp16 = linear(bias = encoder_layers_15_feed_forward2_linear2_bias_to_fp16, weight = encoder_layers_15_feed_forward2_linear2_weight_to_fp16, x = input_843_cast_fp16)[name = tensor<string, []>("linear_144_cast_fp16")];
            tensor<fp16, []> var_3003_to_fp16 = const()[name = tensor<string, []>("op_3003_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_3004_cast_fp16 = mul(x = linear_144_cast_fp16, y = var_3003_to_fp16)[name = tensor<string, []>("op_3004_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_849_cast_fp16 = add(x = input_837_cast_fp16, y = var_3004_cast_fp16)[name = tensor<string, []>("input_849_cast_fp16")];
            tensor<int32, [1]> input_851_axes_0 = const()[name = tensor<string, []>("input_851_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_15_norm_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_15_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(794019520)))];
            tensor<fp16, [1024]> encoder_layers_15_norm_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_15_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(794021632)))];
            tensor<fp16, [1, 188, 1024]> input_851_cast_fp16 = layer_norm(axes = input_851_axes_0, beta = encoder_layers_15_norm_out_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_15_norm_out_weight_to_fp16, x = input_849_cast_fp16)[name = tensor<string, []>("input_851_cast_fp16")];
            tensor<int32, [1]> input_853_axes_0 = const()[name = tensor<string, []>("input_853_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_16_norm_feed_forward1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_16_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(794023744)))];
            tensor<fp16, [1024]> encoder_layers_16_norm_feed_forward1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_16_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(794025856)))];
            tensor<fp16, [1, 188, 1024]> input_853_cast_fp16 = layer_norm(axes = input_853_axes_0, beta = encoder_layers_16_norm_feed_forward1_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_16_norm_feed_forward1_weight_to_fp16, x = input_851_cast_fp16)[name = tensor<string, []>("input_853_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_16_feed_forward1_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_16_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(794027968)))];
            tensor<fp16, [4096]> encoder_layers_16_feed_forward1_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_16_feed_forward1_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(802416640)))];
            tensor<fp16, [1, 188, 4096]> linear_145_cast_fp16 = linear(bias = encoder_layers_16_feed_forward1_linear1_bias_to_fp16, weight = encoder_layers_16_feed_forward1_linear1_weight_to_fp16, x = input_853_cast_fp16)[name = tensor<string, []>("linear_145_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_857_cast_fp16 = silu(x = linear_145_cast_fp16)[name = tensor<string, []>("input_857_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_16_feed_forward1_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_16_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(802424896)))];
            tensor<fp16, [1024]> encoder_layers_16_feed_forward1_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_16_feed_forward1_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(810813568)))];
            tensor<fp16, [1, 188, 1024]> linear_146_cast_fp16 = linear(bias = encoder_layers_16_feed_forward1_linear2_bias_to_fp16, weight = encoder_layers_16_feed_forward1_linear2_weight_to_fp16, x = input_857_cast_fp16)[name = tensor<string, []>("linear_146_cast_fp16")];
            tensor<fp16, []> var_3034_to_fp16 = const()[name = tensor<string, []>("op_3034_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_3035_cast_fp16 = mul(x = linear_146_cast_fp16, y = var_3034_to_fp16)[name = tensor<string, []>("op_3035_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_863_cast_fp16 = add(x = input_851_cast_fp16, y = var_3035_cast_fp16)[name = tensor<string, []>("input_863_cast_fp16")];
            tensor<int32, [1]> query_33_axes_0 = const()[name = tensor<string, []>("query_33_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_16_norm_self_att_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_16_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(810815680)))];
            tensor<fp16, [1024]> encoder_layers_16_norm_self_att_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_16_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(810817792)))];
            tensor<fp16, [1, 188, 1024]> query_33_cast_fp16 = layer_norm(axes = query_33_axes_0, beta = encoder_layers_16_norm_self_att_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_16_norm_self_att_weight_to_fp16, x = input_863_cast_fp16)[name = tensor<string, []>("query_33_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_16_self_attn_linear_q_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_16_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(810819904)))];
            tensor<fp16, [1024]> encoder_layers_16_self_attn_linear_q_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_16_self_attn_linear_q_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(812917120)))];
            tensor<fp16, [1, 188, 1024]> linear_147_cast_fp16 = linear(bias = encoder_layers_16_self_attn_linear_q_bias_to_fp16, weight = encoder_layers_16_self_attn_linear_q_weight_to_fp16, x = query_33_cast_fp16)[name = tensor<string, []>("linear_147_cast_fp16")];
            tensor<int32, [4]> var_3052 = const()[name = tensor<string, []>("op_3052"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_97_cast_fp16 = reshape(shape = var_3052, x = linear_147_cast_fp16)[name = tensor<string, []>("q_97_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_16_self_attn_linear_k_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_16_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(812919232)))];
            tensor<fp16, [1024]> encoder_layers_16_self_attn_linear_k_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_16_self_attn_linear_k_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(815016448)))];
            tensor<fp16, [1, 188, 1024]> linear_148_cast_fp16 = linear(bias = encoder_layers_16_self_attn_linear_k_bias_to_fp16, weight = encoder_layers_16_self_attn_linear_k_weight_to_fp16, x = query_33_cast_fp16)[name = tensor<string, []>("linear_148_cast_fp16")];
            tensor<int32, [4]> var_3057 = const()[name = tensor<string, []>("op_3057"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_65_cast_fp16 = reshape(shape = var_3057, x = linear_148_cast_fp16)[name = tensor<string, []>("k_65_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_16_self_attn_linear_v_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_16_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(815018560)))];
            tensor<fp16, [1024]> encoder_layers_16_self_attn_linear_v_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_16_self_attn_linear_v_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(817115776)))];
            tensor<fp16, [1, 188, 1024]> linear_149_cast_fp16 = linear(bias = encoder_layers_16_self_attn_linear_v_bias_to_fp16, weight = encoder_layers_16_self_attn_linear_v_weight_to_fp16, x = query_33_cast_fp16)[name = tensor<string, []>("linear_149_cast_fp16")];
            tensor<int32, [4]> var_3062 = const()[name = tensor<string, []>("op_3062"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_33_cast_fp16 = reshape(shape = var_3062, x = linear_149_cast_fp16)[name = tensor<string, []>("v_33_cast_fp16")];
            tensor<int32, [4]> value_35_perm_0 = const()[name = tensor<string, []>("value_35_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> encoder_layers_16_self_attn_pos_bias_u_to_fp16 = const()[name = tensor<string, []>("encoder_layers_16_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(817117888)))];
            tensor<fp16, [1, 188, 8, 128]> var_3074_cast_fp16 = add(x = q_97_cast_fp16, y = encoder_layers_16_self_attn_pos_bias_u_to_fp16)[name = tensor<string, []>("op_3074_cast_fp16")];
            tensor<fp16, [8, 128]> encoder_layers_16_self_attn_pos_bias_v_to_fp16 = const()[name = tensor<string, []>("encoder_layers_16_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(817120000)))];
            tensor<fp16, [1, 188, 8, 128]> var_3076_cast_fp16 = add(x = q_97_cast_fp16, y = encoder_layers_16_self_attn_pos_bias_v_to_fp16)[name = tensor<string, []>("op_3076_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_33_perm_0 = const()[name = tensor<string, []>("q_with_bias_v_33_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<bool, []> x_359_transpose_x_0 = const()[name = tensor<string, []>("x_359_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_359_transpose_y_0 = const()[name = tensor<string, []>("x_359_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 128, 375]> var_3078_to_fp16 = const()[name = tensor<string, []>("op_3078_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(817122112)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_33_cast_fp16 = transpose(perm = q_with_bias_v_33_perm_0, x = var_3076_cast_fp16)[name = tensor<string, []>("transpose_270")];
            tensor<fp16, [1, 8, 188, 375]> x_359_cast_fp16 = matmul(transpose_x = x_359_transpose_x_0, transpose_y = x_359_transpose_y_0, x = q_with_bias_v_33_cast_fp16, y = var_3078_to_fp16)[name = tensor<string, []>("x_359_cast_fp16")];
            tensor<int32, [8]> x_361_pad_0 = const()[name = tensor<string, []>("x_361_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            tensor<string, []> x_361_mode_0 = const()[name = tensor<string, []>("x_361_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_174_to_fp16 = const()[name = tensor<string, []>("const_174_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_361_cast_fp16 = pad(constant_val = const_174_to_fp16, mode = x_361_mode_0, pad = x_361_pad_0, x = x_359_cast_fp16)[name = tensor<string, []>("x_361_cast_fp16")];
            tensor<int32, [4]> var_3086 = const()[name = tensor<string, []>("op_3086"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_363_cast_fp16 = reshape(shape = var_3086, x = x_361_cast_fp16)[name = tensor<string, []>("x_363_cast_fp16")];
            tensor<int32, [4]> var_3090_begin_0 = const()[name = tensor<string, []>("op_3090_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_3090_end_0 = const()[name = tensor<string, []>("op_3090_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_3090_end_mask_0 = const()[name = tensor<string, []>("op_3090_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_3090_cast_fp16 = slice_by_index(begin = var_3090_begin_0, end = var_3090_end_0, end_mask = var_3090_end_mask_0, x = x_363_cast_fp16)[name = tensor<string, []>("op_3090_cast_fp16")];
            tensor<int32, [4]> var_3091 = const()[name = tensor<string, []>("op_3091"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_65_cast_fp16 = reshape(shape = var_3091, x = var_3090_cast_fp16)[name = tensor<string, []>("matrix_bd_65_cast_fp16")];
            tensor<bool, []> matrix_ac_33_transpose_x_0 = const()[name = tensor<string, []>("matrix_ac_33_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> matrix_ac_33_transpose_y_0 = const()[name = tensor<string, []>("matrix_ac_33_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<int32, [4]> transpose_128_perm_0 = const()[name = tensor<string, []>("transpose_128_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_129_perm_0 = const()[name = tensor<string, []>("transpose_129_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_129 = transpose(perm = transpose_129_perm_0, x = k_65_cast_fp16)[name = tensor<string, []>("transpose_268")];
            tensor<fp16, [1, 8, 188, 128]> transpose_128 = transpose(perm = transpose_128_perm_0, x = var_3074_cast_fp16)[name = tensor<string, []>("transpose_269")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_33_cast_fp16 = matmul(transpose_x = matrix_ac_33_transpose_x_0, transpose_y = matrix_ac_33_transpose_y_0, x = transpose_128, y = transpose_129)[name = tensor<string, []>("matrix_ac_33_cast_fp16")];
            tensor<int32, [4]> matrix_bd_67_begin_0 = const()[name = tensor<string, []>("matrix_bd_67_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_67_end_0 = const()[name = tensor<string, []>("matrix_bd_67_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_67_end_mask_0 = const()[name = tensor<string, []>("matrix_bd_67_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_67_cast_fp16 = slice_by_index(begin = matrix_bd_67_begin_0, end = matrix_bd_67_end_0, end_mask = matrix_bd_67_end_mask_0, x = matrix_bd_65_cast_fp16)[name = tensor<string, []>("matrix_bd_67_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_3100_cast_fp16 = add(x = matrix_ac_33_cast_fp16, y = matrix_bd_67_cast_fp16)[name = tensor<string, []>("op_3100_cast_fp16")];
            tensor<fp16, []> _inversed_scores_65_y_0_to_fp16 = const()[name = tensor<string, []>("_inversed_scores_65_y_0_to_fp16"), val = tensor<fp16, []>(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_65_cast_fp16 = mul(x = var_3100_cast_fp16, y = _inversed_scores_65_y_0_to_fp16)[name = tensor<string, []>("_inversed_scores_65_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_67_cast_fp16 = select(a = var_12_to_fp16, b = _inversed_scores_65_cast_fp16, cond = mask_3)[name = tensor<string, []>("scores_67_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_3106_cast_fp16 = softmax(axis = var_30, x = scores_67_cast_fp16)[name = tensor<string, []>("op_3106_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_865_cast_fp16 = select(a = var_11_to_fp16, b = var_3106_cast_fp16, cond = mask_3)[name = tensor<string, []>("input_865_cast_fp16")];
            tensor<bool, []> x_365_transpose_x_0 = const()[name = tensor<string, []>("x_365_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_365_transpose_y_0 = const()[name = tensor<string, []>("x_365_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 188, 128]> value_35_cast_fp16 = transpose(perm = value_35_perm_0, x = v_33_cast_fp16)[name = tensor<string, []>("transpose_271")];
            tensor<fp16, [1, 8, 188, 128]> x_365_cast_fp16 = matmul(transpose_x = x_365_transpose_x_0, transpose_y = x_365_transpose_y_0, x = input_865_cast_fp16, y = value_35_cast_fp16)[name = tensor<string, []>("x_365_cast_fp16")];
            tensor<int32, [4]> var_3110_perm_0 = const()[name = tensor<string, []>("op_3110_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_3111 = const()[name = tensor<string, []>("op_3111"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_3110_cast_fp16 = transpose(perm = var_3110_perm_0, x = x_365_cast_fp16)[name = tensor<string, []>("transpose_267")];
            tensor<fp16, [1, 188, 1024]> input_867_cast_fp16 = reshape(shape = var_3111, x = var_3110_cast_fp16)[name = tensor<string, []>("input_867_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_16_self_attn_linear_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_16_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(817890176)))];
            tensor<fp16, [1024]> encoder_layers_16_self_attn_linear_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_16_self_attn_linear_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(819987392)))];
            tensor<fp16, [1, 188, 1024]> linear_151_cast_fp16 = linear(bias = encoder_layers_16_self_attn_linear_out_bias_to_fp16, weight = encoder_layers_16_self_attn_linear_out_weight_to_fp16, x = input_867_cast_fp16)[name = tensor<string, []>("linear_151_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_871_cast_fp16 = add(x = input_863_cast_fp16, y = linear_151_cast_fp16)[name = tensor<string, []>("input_871_cast_fp16")];
            tensor<int32, [1]> x_369_axes_0 = const()[name = tensor<string, []>("x_369_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_16_norm_conv_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_16_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(819989504)))];
            tensor<fp16, [1024]> encoder_layers_16_norm_conv_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_16_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(819991616)))];
            tensor<fp16, [1, 188, 1024]> x_369_cast_fp16 = layer_norm(axes = x_369_axes_0, beta = encoder_layers_16_norm_conv_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_16_norm_conv_weight_to_fp16, x = input_871_cast_fp16)[name = tensor<string, []>("x_369_cast_fp16")];
            tensor<int32, [3]> input_873_perm_0 = const()[name = tensor<string, []>("input_873_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> input_875_pad_type_0 = const()[name = tensor<string, []>("input_875_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_875_strides_0 = const()[name = tensor<string, []>("input_875_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_875_pad_0 = const()[name = tensor<string, []>("input_875_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_875_dilations_0 = const()[name = tensor<string, []>("input_875_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_875_groups_0 = const()[name = tensor<string, []>("input_875_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [2048, 1024, 1]> encoder_layers_16_conv_pointwise_conv1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_16_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(819993728)))];
            tensor<fp16, [2048]> encoder_layers_16_conv_pointwise_conv1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_16_conv_pointwise_conv1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(824188096)))];
            tensor<fp16, [1, 1024, 188]> input_873_cast_fp16 = transpose(perm = input_873_perm_0, x = x_369_cast_fp16)[name = tensor<string, []>("transpose_266")];
            tensor<fp16, [1, 2048, 188]> input_875_cast_fp16 = conv(bias = encoder_layers_16_conv_pointwise_conv1_bias_to_fp16, dilations = input_875_dilations_0, groups = input_875_groups_0, pad = input_875_pad_0, pad_type = input_875_pad_type_0, strides = input_875_strides_0, weight = encoder_layers_16_conv_pointwise_conv1_weight_to_fp16, x = input_873_cast_fp16)[name = tensor<string, []>("input_875_cast_fp16")];
            tensor<int32, []> x_371_split_num_splits_0 = const()[name = tensor<string, []>("x_371_split_num_splits_0"), val = tensor<int32, []>(2)];
            tensor<int32, []> x_371_split_axis_0 = const()[name = tensor<string, []>("x_371_split_axis_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1, 1024, 188]> x_371_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_371_split_cast_fp16_1 = split(axis = x_371_split_axis_0, num_splits = x_371_split_num_splits_0, x = input_875_cast_fp16)[name = tensor<string, []>("x_371_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_371_split_1_sigmoid_cast_fp16 = sigmoid(x = x_371_split_cast_fp16_1)[name = tensor<string, []>("x_371_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_371_cast_fp16 = mul(x = x_371_split_cast_fp16_0, y = x_371_split_1_sigmoid_cast_fp16)[name = tensor<string, []>("x_371_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_877_cast_fp16 = select(a = var_11_to_fp16, b = x_371_cast_fp16, cond = var_351)[name = tensor<string, []>("input_877_cast_fp16")];
            tensor<int32, [6]> input_879_pad_0 = const()[name = tensor<string, []>("input_879_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            tensor<string, []> input_879_mode_0 = const()[name = tensor<string, []>("input_879_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_177_to_fp16 = const()[name = tensor<string, []>("const_177_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_879_cast_fp16 = pad(constant_val = const_177_to_fp16, mode = input_879_mode_0, pad = input_879_pad_0, x = input_877_cast_fp16)[name = tensor<string, []>("input_879_cast_fp16")];
            tensor<string, []> input_881_pad_type_0 = const()[name = tensor<string, []>("input_881_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, []> input_881_groups_0 = const()[name = tensor<string, []>("input_881_groups_0"), val = tensor<int32, []>(1024)];
            tensor<int32, [1]> input_881_strides_0 = const()[name = tensor<string, []>("input_881_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_881_pad_0 = const()[name = tensor<string, []>("input_881_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_881_dilations_0 = const()[name = tensor<string, []>("input_881_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_360_to_fp16 = const()[name = tensor<string, []>("const_360_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(824192256)))];
            tensor<fp16, [1024]> const_361_to_fp16 = const()[name = tensor<string, []>("const_361_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(824210752)))];
            tensor<fp16, [1, 1024, 188]> input_883_cast_fp16 = conv(bias = const_361_to_fp16, dilations = input_881_dilations_0, groups = input_881_groups_0, pad = input_881_pad_0, pad_type = input_881_pad_type_0, strides = input_881_strides_0, weight = const_360_to_fp16, x = input_879_cast_fp16)[name = tensor<string, []>("input_883_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_885_cast_fp16 = silu(x = input_883_cast_fp16)[name = tensor<string, []>("input_885_cast_fp16")];
            tensor<string, []> x_373_pad_type_0 = const()[name = tensor<string, []>("x_373_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> x_373_strides_0 = const()[name = tensor<string, []>("x_373_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_373_pad_0 = const()[name = tensor<string, []>("x_373_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_373_dilations_0 = const()[name = tensor<string, []>("x_373_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> x_373_groups_0 = const()[name = tensor<string, []>("x_373_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1024, 1024, 1]> encoder_layers_16_conv_pointwise_conv2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_16_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(824212864)))];
            tensor<fp16, [1024]> encoder_layers_16_conv_pointwise_conv2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_16_conv_pointwise_conv2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(826310080)))];
            tensor<fp16, [1, 1024, 188]> x_373_cast_fp16 = conv(bias = encoder_layers_16_conv_pointwise_conv2_bias_to_fp16, dilations = x_373_dilations_0, groups = x_373_groups_0, pad = x_373_pad_0, pad_type = x_373_pad_type_0, strides = x_373_strides_0, weight = encoder_layers_16_conv_pointwise_conv2_weight_to_fp16, x = input_885_cast_fp16)[name = tensor<string, []>("x_373_cast_fp16")];
            tensor<int32, [3]> input_887_perm_0 = const()[name = tensor<string, []>("input_887_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_887_cast_fp16 = transpose(perm = input_887_perm_0, x = x_373_cast_fp16)[name = tensor<string, []>("transpose_265")];
            tensor<fp16, [1, 188, 1024]> input_889_cast_fp16 = add(x = input_871_cast_fp16, y = input_887_cast_fp16)[name = tensor<string, []>("input_889_cast_fp16")];
            tensor<int32, [1]> input_891_axes_0 = const()[name = tensor<string, []>("input_891_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_16_norm_feed_forward2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_16_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(826312192)))];
            tensor<fp16, [1024]> encoder_layers_16_norm_feed_forward2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_16_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(826314304)))];
            tensor<fp16, [1, 188, 1024]> input_891_cast_fp16 = layer_norm(axes = input_891_axes_0, beta = encoder_layers_16_norm_feed_forward2_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_16_norm_feed_forward2_weight_to_fp16, x = input_889_cast_fp16)[name = tensor<string, []>("input_891_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_16_feed_forward2_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_16_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(826316416)))];
            tensor<fp16, [4096]> encoder_layers_16_feed_forward2_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_16_feed_forward2_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(834705088)))];
            tensor<fp16, [1, 188, 4096]> linear_152_cast_fp16 = linear(bias = encoder_layers_16_feed_forward2_linear1_bias_to_fp16, weight = encoder_layers_16_feed_forward2_linear1_weight_to_fp16, x = input_891_cast_fp16)[name = tensor<string, []>("linear_152_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_895_cast_fp16 = silu(x = linear_152_cast_fp16)[name = tensor<string, []>("input_895_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_16_feed_forward2_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_16_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(834713344)))];
            tensor<fp16, [1024]> encoder_layers_16_feed_forward2_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_16_feed_forward2_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(843102016)))];
            tensor<fp16, [1, 188, 1024]> linear_153_cast_fp16 = linear(bias = encoder_layers_16_feed_forward2_linear2_bias_to_fp16, weight = encoder_layers_16_feed_forward2_linear2_weight_to_fp16, x = input_895_cast_fp16)[name = tensor<string, []>("linear_153_cast_fp16")];
            tensor<fp16, []> var_3177_to_fp16 = const()[name = tensor<string, []>("op_3177_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_3178_cast_fp16 = mul(x = linear_153_cast_fp16, y = var_3177_to_fp16)[name = tensor<string, []>("op_3178_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_901_cast_fp16 = add(x = input_889_cast_fp16, y = var_3178_cast_fp16)[name = tensor<string, []>("input_901_cast_fp16")];
            tensor<int32, [1]> input_903_axes_0 = const()[name = tensor<string, []>("input_903_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_16_norm_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_16_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(843104128)))];
            tensor<fp16, [1024]> encoder_layers_16_norm_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_16_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(843106240)))];
            tensor<fp16, [1, 188, 1024]> input_903_cast_fp16 = layer_norm(axes = input_903_axes_0, beta = encoder_layers_16_norm_out_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_16_norm_out_weight_to_fp16, x = input_901_cast_fp16)[name = tensor<string, []>("input_903_cast_fp16")];
            tensor<int32, [1]> input_905_axes_0 = const()[name = tensor<string, []>("input_905_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_17_norm_feed_forward1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_17_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(843108352)))];
            tensor<fp16, [1024]> encoder_layers_17_norm_feed_forward1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_17_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(843110464)))];
            tensor<fp16, [1, 188, 1024]> input_905_cast_fp16 = layer_norm(axes = input_905_axes_0, beta = encoder_layers_17_norm_feed_forward1_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_17_norm_feed_forward1_weight_to_fp16, x = input_903_cast_fp16)[name = tensor<string, []>("input_905_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_17_feed_forward1_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_17_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(843112576)))];
            tensor<fp16, [4096]> encoder_layers_17_feed_forward1_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_17_feed_forward1_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(851501248)))];
            tensor<fp16, [1, 188, 4096]> linear_154_cast_fp16 = linear(bias = encoder_layers_17_feed_forward1_linear1_bias_to_fp16, weight = encoder_layers_17_feed_forward1_linear1_weight_to_fp16, x = input_905_cast_fp16)[name = tensor<string, []>("linear_154_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_909_cast_fp16 = silu(x = linear_154_cast_fp16)[name = tensor<string, []>("input_909_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_17_feed_forward1_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_17_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(851509504)))];
            tensor<fp16, [1024]> encoder_layers_17_feed_forward1_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_17_feed_forward1_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(859898176)))];
            tensor<fp16, [1, 188, 1024]> linear_155_cast_fp16 = linear(bias = encoder_layers_17_feed_forward1_linear2_bias_to_fp16, weight = encoder_layers_17_feed_forward1_linear2_weight_to_fp16, x = input_909_cast_fp16)[name = tensor<string, []>("linear_155_cast_fp16")];
            tensor<fp16, []> var_3208_to_fp16 = const()[name = tensor<string, []>("op_3208_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_3209_cast_fp16 = mul(x = linear_155_cast_fp16, y = var_3208_to_fp16)[name = tensor<string, []>("op_3209_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_915_cast_fp16 = add(x = input_903_cast_fp16, y = var_3209_cast_fp16)[name = tensor<string, []>("input_915_cast_fp16")];
            tensor<int32, [1]> query_35_axes_0 = const()[name = tensor<string, []>("query_35_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_17_norm_self_att_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_17_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(859900288)))];
            tensor<fp16, [1024]> encoder_layers_17_norm_self_att_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_17_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(859902400)))];
            tensor<fp16, [1, 188, 1024]> query_35_cast_fp16 = layer_norm(axes = query_35_axes_0, beta = encoder_layers_17_norm_self_att_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_17_norm_self_att_weight_to_fp16, x = input_915_cast_fp16)[name = tensor<string, []>("query_35_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_17_self_attn_linear_q_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_17_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(859904512)))];
            tensor<fp16, [1024]> encoder_layers_17_self_attn_linear_q_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_17_self_attn_linear_q_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(862001728)))];
            tensor<fp16, [1, 188, 1024]> linear_156_cast_fp16 = linear(bias = encoder_layers_17_self_attn_linear_q_bias_to_fp16, weight = encoder_layers_17_self_attn_linear_q_weight_to_fp16, x = query_35_cast_fp16)[name = tensor<string, []>("linear_156_cast_fp16")];
            tensor<int32, [4]> var_3226 = const()[name = tensor<string, []>("op_3226"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_103_cast_fp16 = reshape(shape = var_3226, x = linear_156_cast_fp16)[name = tensor<string, []>("q_103_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_17_self_attn_linear_k_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_17_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(862003840)))];
            tensor<fp16, [1024]> encoder_layers_17_self_attn_linear_k_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_17_self_attn_linear_k_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(864101056)))];
            tensor<fp16, [1, 188, 1024]> linear_157_cast_fp16 = linear(bias = encoder_layers_17_self_attn_linear_k_bias_to_fp16, weight = encoder_layers_17_self_attn_linear_k_weight_to_fp16, x = query_35_cast_fp16)[name = tensor<string, []>("linear_157_cast_fp16")];
            tensor<int32, [4]> var_3231 = const()[name = tensor<string, []>("op_3231"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_69_cast_fp16 = reshape(shape = var_3231, x = linear_157_cast_fp16)[name = tensor<string, []>("k_69_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_17_self_attn_linear_v_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_17_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(864103168)))];
            tensor<fp16, [1024]> encoder_layers_17_self_attn_linear_v_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_17_self_attn_linear_v_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(866200384)))];
            tensor<fp16, [1, 188, 1024]> linear_158_cast_fp16 = linear(bias = encoder_layers_17_self_attn_linear_v_bias_to_fp16, weight = encoder_layers_17_self_attn_linear_v_weight_to_fp16, x = query_35_cast_fp16)[name = tensor<string, []>("linear_158_cast_fp16")];
            tensor<int32, [4]> var_3236 = const()[name = tensor<string, []>("op_3236"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_35_cast_fp16 = reshape(shape = var_3236, x = linear_158_cast_fp16)[name = tensor<string, []>("v_35_cast_fp16")];
            tensor<int32, [4]> value_37_perm_0 = const()[name = tensor<string, []>("value_37_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> encoder_layers_17_self_attn_pos_bias_u_to_fp16 = const()[name = tensor<string, []>("encoder_layers_17_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(866202496)))];
            tensor<fp16, [1, 188, 8, 128]> var_3248_cast_fp16 = add(x = q_103_cast_fp16, y = encoder_layers_17_self_attn_pos_bias_u_to_fp16)[name = tensor<string, []>("op_3248_cast_fp16")];
            tensor<fp16, [8, 128]> encoder_layers_17_self_attn_pos_bias_v_to_fp16 = const()[name = tensor<string, []>("encoder_layers_17_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(866204608)))];
            tensor<fp16, [1, 188, 8, 128]> var_3250_cast_fp16 = add(x = q_103_cast_fp16, y = encoder_layers_17_self_attn_pos_bias_v_to_fp16)[name = tensor<string, []>("op_3250_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_35_perm_0 = const()[name = tensor<string, []>("q_with_bias_v_35_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<bool, []> x_381_transpose_x_0 = const()[name = tensor<string, []>("x_381_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_381_transpose_y_0 = const()[name = tensor<string, []>("x_381_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 128, 375]> var_3252_to_fp16 = const()[name = tensor<string, []>("op_3252_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(866206720)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_35_cast_fp16 = transpose(perm = q_with_bias_v_35_perm_0, x = var_3250_cast_fp16)[name = tensor<string, []>("transpose_263")];
            tensor<fp16, [1, 8, 188, 375]> x_381_cast_fp16 = matmul(transpose_x = x_381_transpose_x_0, transpose_y = x_381_transpose_y_0, x = q_with_bias_v_35_cast_fp16, y = var_3252_to_fp16)[name = tensor<string, []>("x_381_cast_fp16")];
            tensor<int32, [8]> x_383_pad_0 = const()[name = tensor<string, []>("x_383_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            tensor<string, []> x_383_mode_0 = const()[name = tensor<string, []>("x_383_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_184_to_fp16 = const()[name = tensor<string, []>("const_184_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_383_cast_fp16 = pad(constant_val = const_184_to_fp16, mode = x_383_mode_0, pad = x_383_pad_0, x = x_381_cast_fp16)[name = tensor<string, []>("x_383_cast_fp16")];
            tensor<int32, [4]> var_3260 = const()[name = tensor<string, []>("op_3260"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_385_cast_fp16 = reshape(shape = var_3260, x = x_383_cast_fp16)[name = tensor<string, []>("x_385_cast_fp16")];
            tensor<int32, [4]> var_3264_begin_0 = const()[name = tensor<string, []>("op_3264_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_3264_end_0 = const()[name = tensor<string, []>("op_3264_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_3264_end_mask_0 = const()[name = tensor<string, []>("op_3264_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_3264_cast_fp16 = slice_by_index(begin = var_3264_begin_0, end = var_3264_end_0, end_mask = var_3264_end_mask_0, x = x_385_cast_fp16)[name = tensor<string, []>("op_3264_cast_fp16")];
            tensor<int32, [4]> var_3265 = const()[name = tensor<string, []>("op_3265"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_69_cast_fp16 = reshape(shape = var_3265, x = var_3264_cast_fp16)[name = tensor<string, []>("matrix_bd_69_cast_fp16")];
            tensor<bool, []> matrix_ac_35_transpose_x_0 = const()[name = tensor<string, []>("matrix_ac_35_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> matrix_ac_35_transpose_y_0 = const()[name = tensor<string, []>("matrix_ac_35_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<int32, [4]> transpose_130_perm_0 = const()[name = tensor<string, []>("transpose_130_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_131_perm_0 = const()[name = tensor<string, []>("transpose_131_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_131 = transpose(perm = transpose_131_perm_0, x = k_69_cast_fp16)[name = tensor<string, []>("transpose_261")];
            tensor<fp16, [1, 8, 188, 128]> transpose_130 = transpose(perm = transpose_130_perm_0, x = var_3248_cast_fp16)[name = tensor<string, []>("transpose_262")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_35_cast_fp16 = matmul(transpose_x = matrix_ac_35_transpose_x_0, transpose_y = matrix_ac_35_transpose_y_0, x = transpose_130, y = transpose_131)[name = tensor<string, []>("matrix_ac_35_cast_fp16")];
            tensor<int32, [4]> matrix_bd_71_begin_0 = const()[name = tensor<string, []>("matrix_bd_71_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_71_end_0 = const()[name = tensor<string, []>("matrix_bd_71_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_71_end_mask_0 = const()[name = tensor<string, []>("matrix_bd_71_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_71_cast_fp16 = slice_by_index(begin = matrix_bd_71_begin_0, end = matrix_bd_71_end_0, end_mask = matrix_bd_71_end_mask_0, x = matrix_bd_69_cast_fp16)[name = tensor<string, []>("matrix_bd_71_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_3274_cast_fp16 = add(x = matrix_ac_35_cast_fp16, y = matrix_bd_71_cast_fp16)[name = tensor<string, []>("op_3274_cast_fp16")];
            tensor<fp16, []> _inversed_scores_69_y_0_to_fp16 = const()[name = tensor<string, []>("_inversed_scores_69_y_0_to_fp16"), val = tensor<fp16, []>(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_69_cast_fp16 = mul(x = var_3274_cast_fp16, y = _inversed_scores_69_y_0_to_fp16)[name = tensor<string, []>("_inversed_scores_69_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_71_cast_fp16 = select(a = var_12_to_fp16, b = _inversed_scores_69_cast_fp16, cond = mask_3)[name = tensor<string, []>("scores_71_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_3280_cast_fp16 = softmax(axis = var_30, x = scores_71_cast_fp16)[name = tensor<string, []>("op_3280_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_917_cast_fp16 = select(a = var_11_to_fp16, b = var_3280_cast_fp16, cond = mask_3)[name = tensor<string, []>("input_917_cast_fp16")];
            tensor<bool, []> x_387_transpose_x_0 = const()[name = tensor<string, []>("x_387_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_387_transpose_y_0 = const()[name = tensor<string, []>("x_387_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 188, 128]> value_37_cast_fp16 = transpose(perm = value_37_perm_0, x = v_35_cast_fp16)[name = tensor<string, []>("transpose_264")];
            tensor<fp16, [1, 8, 188, 128]> x_387_cast_fp16 = matmul(transpose_x = x_387_transpose_x_0, transpose_y = x_387_transpose_y_0, x = input_917_cast_fp16, y = value_37_cast_fp16)[name = tensor<string, []>("x_387_cast_fp16")];
            tensor<int32, [4]> var_3284_perm_0 = const()[name = tensor<string, []>("op_3284_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_3285 = const()[name = tensor<string, []>("op_3285"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_3284_cast_fp16 = transpose(perm = var_3284_perm_0, x = x_387_cast_fp16)[name = tensor<string, []>("transpose_260")];
            tensor<fp16, [1, 188, 1024]> input_919_cast_fp16 = reshape(shape = var_3285, x = var_3284_cast_fp16)[name = tensor<string, []>("input_919_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_17_self_attn_linear_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_17_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(866974784)))];
            tensor<fp16, [1024]> encoder_layers_17_self_attn_linear_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_17_self_attn_linear_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(869072000)))];
            tensor<fp16, [1, 188, 1024]> linear_160_cast_fp16 = linear(bias = encoder_layers_17_self_attn_linear_out_bias_to_fp16, weight = encoder_layers_17_self_attn_linear_out_weight_to_fp16, x = input_919_cast_fp16)[name = tensor<string, []>("linear_160_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_923_cast_fp16 = add(x = input_915_cast_fp16, y = linear_160_cast_fp16)[name = tensor<string, []>("input_923_cast_fp16")];
            tensor<int32, [1]> x_391_axes_0 = const()[name = tensor<string, []>("x_391_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_17_norm_conv_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_17_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(869074112)))];
            tensor<fp16, [1024]> encoder_layers_17_norm_conv_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_17_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(869076224)))];
            tensor<fp16, [1, 188, 1024]> x_391_cast_fp16 = layer_norm(axes = x_391_axes_0, beta = encoder_layers_17_norm_conv_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_17_norm_conv_weight_to_fp16, x = input_923_cast_fp16)[name = tensor<string, []>("x_391_cast_fp16")];
            tensor<int32, [3]> input_925_perm_0 = const()[name = tensor<string, []>("input_925_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> input_927_pad_type_0 = const()[name = tensor<string, []>("input_927_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_927_strides_0 = const()[name = tensor<string, []>("input_927_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_927_pad_0 = const()[name = tensor<string, []>("input_927_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_927_dilations_0 = const()[name = tensor<string, []>("input_927_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_927_groups_0 = const()[name = tensor<string, []>("input_927_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [2048, 1024, 1]> encoder_layers_17_conv_pointwise_conv1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_17_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(869078336)))];
            tensor<fp16, [2048]> encoder_layers_17_conv_pointwise_conv1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_17_conv_pointwise_conv1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(873272704)))];
            tensor<fp16, [1, 1024, 188]> input_925_cast_fp16 = transpose(perm = input_925_perm_0, x = x_391_cast_fp16)[name = tensor<string, []>("transpose_259")];
            tensor<fp16, [1, 2048, 188]> input_927_cast_fp16 = conv(bias = encoder_layers_17_conv_pointwise_conv1_bias_to_fp16, dilations = input_927_dilations_0, groups = input_927_groups_0, pad = input_927_pad_0, pad_type = input_927_pad_type_0, strides = input_927_strides_0, weight = encoder_layers_17_conv_pointwise_conv1_weight_to_fp16, x = input_925_cast_fp16)[name = tensor<string, []>("input_927_cast_fp16")];
            tensor<int32, []> x_393_split_num_splits_0 = const()[name = tensor<string, []>("x_393_split_num_splits_0"), val = tensor<int32, []>(2)];
            tensor<int32, []> x_393_split_axis_0 = const()[name = tensor<string, []>("x_393_split_axis_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1, 1024, 188]> x_393_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_393_split_cast_fp16_1 = split(axis = x_393_split_axis_0, num_splits = x_393_split_num_splits_0, x = input_927_cast_fp16)[name = tensor<string, []>("x_393_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_393_split_1_sigmoid_cast_fp16 = sigmoid(x = x_393_split_cast_fp16_1)[name = tensor<string, []>("x_393_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_393_cast_fp16 = mul(x = x_393_split_cast_fp16_0, y = x_393_split_1_sigmoid_cast_fp16)[name = tensor<string, []>("x_393_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_929_cast_fp16 = select(a = var_11_to_fp16, b = x_393_cast_fp16, cond = var_351)[name = tensor<string, []>("input_929_cast_fp16")];
            tensor<int32, [6]> input_931_pad_0 = const()[name = tensor<string, []>("input_931_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            tensor<string, []> input_931_mode_0 = const()[name = tensor<string, []>("input_931_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_187_to_fp16 = const()[name = tensor<string, []>("const_187_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_931_cast_fp16 = pad(constant_val = const_187_to_fp16, mode = input_931_mode_0, pad = input_931_pad_0, x = input_929_cast_fp16)[name = tensor<string, []>("input_931_cast_fp16")];
            tensor<string, []> input_933_pad_type_0 = const()[name = tensor<string, []>("input_933_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, []> input_933_groups_0 = const()[name = tensor<string, []>("input_933_groups_0"), val = tensor<int32, []>(1024)];
            tensor<int32, [1]> input_933_strides_0 = const()[name = tensor<string, []>("input_933_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_933_pad_0 = const()[name = tensor<string, []>("input_933_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_933_dilations_0 = const()[name = tensor<string, []>("input_933_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_362_to_fp16 = const()[name = tensor<string, []>("const_362_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(873276864)))];
            tensor<fp16, [1024]> const_363_to_fp16 = const()[name = tensor<string, []>("const_363_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(873295360)))];
            tensor<fp16, [1, 1024, 188]> input_935_cast_fp16 = conv(bias = const_363_to_fp16, dilations = input_933_dilations_0, groups = input_933_groups_0, pad = input_933_pad_0, pad_type = input_933_pad_type_0, strides = input_933_strides_0, weight = const_362_to_fp16, x = input_931_cast_fp16)[name = tensor<string, []>("input_935_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_937_cast_fp16 = silu(x = input_935_cast_fp16)[name = tensor<string, []>("input_937_cast_fp16")];
            tensor<string, []> x_395_pad_type_0 = const()[name = tensor<string, []>("x_395_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> x_395_strides_0 = const()[name = tensor<string, []>("x_395_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_395_pad_0 = const()[name = tensor<string, []>("x_395_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_395_dilations_0 = const()[name = tensor<string, []>("x_395_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> x_395_groups_0 = const()[name = tensor<string, []>("x_395_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1024, 1024, 1]> encoder_layers_17_conv_pointwise_conv2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_17_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(873297472)))];
            tensor<fp16, [1024]> encoder_layers_17_conv_pointwise_conv2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_17_conv_pointwise_conv2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(875394688)))];
            tensor<fp16, [1, 1024, 188]> x_395_cast_fp16 = conv(bias = encoder_layers_17_conv_pointwise_conv2_bias_to_fp16, dilations = x_395_dilations_0, groups = x_395_groups_0, pad = x_395_pad_0, pad_type = x_395_pad_type_0, strides = x_395_strides_0, weight = encoder_layers_17_conv_pointwise_conv2_weight_to_fp16, x = input_937_cast_fp16)[name = tensor<string, []>("x_395_cast_fp16")];
            tensor<int32, [3]> input_939_perm_0 = const()[name = tensor<string, []>("input_939_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_939_cast_fp16 = transpose(perm = input_939_perm_0, x = x_395_cast_fp16)[name = tensor<string, []>("transpose_258")];
            tensor<fp16, [1, 188, 1024]> input_941_cast_fp16 = add(x = input_923_cast_fp16, y = input_939_cast_fp16)[name = tensor<string, []>("input_941_cast_fp16")];
            tensor<int32, [1]> input_943_axes_0 = const()[name = tensor<string, []>("input_943_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_17_norm_feed_forward2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_17_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(875396800)))];
            tensor<fp16, [1024]> encoder_layers_17_norm_feed_forward2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_17_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(875398912)))];
            tensor<fp16, [1, 188, 1024]> input_943_cast_fp16 = layer_norm(axes = input_943_axes_0, beta = encoder_layers_17_norm_feed_forward2_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_17_norm_feed_forward2_weight_to_fp16, x = input_941_cast_fp16)[name = tensor<string, []>("input_943_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_17_feed_forward2_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_17_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(875401024)))];
            tensor<fp16, [4096]> encoder_layers_17_feed_forward2_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_17_feed_forward2_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(883789696)))];
            tensor<fp16, [1, 188, 4096]> linear_161_cast_fp16 = linear(bias = encoder_layers_17_feed_forward2_linear1_bias_to_fp16, weight = encoder_layers_17_feed_forward2_linear1_weight_to_fp16, x = input_943_cast_fp16)[name = tensor<string, []>("linear_161_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_947_cast_fp16 = silu(x = linear_161_cast_fp16)[name = tensor<string, []>("input_947_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_17_feed_forward2_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_17_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(883797952)))];
            tensor<fp16, [1024]> encoder_layers_17_feed_forward2_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_17_feed_forward2_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(892186624)))];
            tensor<fp16, [1, 188, 1024]> linear_162_cast_fp16 = linear(bias = encoder_layers_17_feed_forward2_linear2_bias_to_fp16, weight = encoder_layers_17_feed_forward2_linear2_weight_to_fp16, x = input_947_cast_fp16)[name = tensor<string, []>("linear_162_cast_fp16")];
            tensor<fp16, []> var_3351_to_fp16 = const()[name = tensor<string, []>("op_3351_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_3352_cast_fp16 = mul(x = linear_162_cast_fp16, y = var_3351_to_fp16)[name = tensor<string, []>("op_3352_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_953_cast_fp16 = add(x = input_941_cast_fp16, y = var_3352_cast_fp16)[name = tensor<string, []>("input_953_cast_fp16")];
            tensor<int32, [1]> input_955_axes_0 = const()[name = tensor<string, []>("input_955_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_17_norm_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_17_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(892188736)))];
            tensor<fp16, [1024]> encoder_layers_17_norm_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_17_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(892190848)))];
            tensor<fp16, [1, 188, 1024]> input_955_cast_fp16 = layer_norm(axes = input_955_axes_0, beta = encoder_layers_17_norm_out_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_17_norm_out_weight_to_fp16, x = input_953_cast_fp16)[name = tensor<string, []>("input_955_cast_fp16")];
            tensor<int32, [1]> input_957_axes_0 = const()[name = tensor<string, []>("input_957_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_18_norm_feed_forward1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_18_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(892192960)))];
            tensor<fp16, [1024]> encoder_layers_18_norm_feed_forward1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_18_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(892195072)))];
            tensor<fp16, [1, 188, 1024]> input_957_cast_fp16 = layer_norm(axes = input_957_axes_0, beta = encoder_layers_18_norm_feed_forward1_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_18_norm_feed_forward1_weight_to_fp16, x = input_955_cast_fp16)[name = tensor<string, []>("input_957_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_18_feed_forward1_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_18_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(892197184)))];
            tensor<fp16, [4096]> encoder_layers_18_feed_forward1_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_18_feed_forward1_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(900585856)))];
            tensor<fp16, [1, 188, 4096]> linear_163_cast_fp16 = linear(bias = encoder_layers_18_feed_forward1_linear1_bias_to_fp16, weight = encoder_layers_18_feed_forward1_linear1_weight_to_fp16, x = input_957_cast_fp16)[name = tensor<string, []>("linear_163_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_961_cast_fp16 = silu(x = linear_163_cast_fp16)[name = tensor<string, []>("input_961_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_18_feed_forward1_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_18_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(900594112)))];
            tensor<fp16, [1024]> encoder_layers_18_feed_forward1_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_18_feed_forward1_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(908982784)))];
            tensor<fp16, [1, 188, 1024]> linear_164_cast_fp16 = linear(bias = encoder_layers_18_feed_forward1_linear2_bias_to_fp16, weight = encoder_layers_18_feed_forward1_linear2_weight_to_fp16, x = input_961_cast_fp16)[name = tensor<string, []>("linear_164_cast_fp16")];
            tensor<fp16, []> var_3382_to_fp16 = const()[name = tensor<string, []>("op_3382_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_3383_cast_fp16 = mul(x = linear_164_cast_fp16, y = var_3382_to_fp16)[name = tensor<string, []>("op_3383_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_967_cast_fp16 = add(x = input_955_cast_fp16, y = var_3383_cast_fp16)[name = tensor<string, []>("input_967_cast_fp16")];
            tensor<int32, [1]> query_37_axes_0 = const()[name = tensor<string, []>("query_37_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_18_norm_self_att_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_18_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(908984896)))];
            tensor<fp16, [1024]> encoder_layers_18_norm_self_att_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_18_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(908987008)))];
            tensor<fp16, [1, 188, 1024]> query_37_cast_fp16 = layer_norm(axes = query_37_axes_0, beta = encoder_layers_18_norm_self_att_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_18_norm_self_att_weight_to_fp16, x = input_967_cast_fp16)[name = tensor<string, []>("query_37_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_18_self_attn_linear_q_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_18_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(908989120)))];
            tensor<fp16, [1024]> encoder_layers_18_self_attn_linear_q_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_18_self_attn_linear_q_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(911086336)))];
            tensor<fp16, [1, 188, 1024]> linear_165_cast_fp16 = linear(bias = encoder_layers_18_self_attn_linear_q_bias_to_fp16, weight = encoder_layers_18_self_attn_linear_q_weight_to_fp16, x = query_37_cast_fp16)[name = tensor<string, []>("linear_165_cast_fp16")];
            tensor<int32, [4]> var_3400 = const()[name = tensor<string, []>("op_3400"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_109_cast_fp16 = reshape(shape = var_3400, x = linear_165_cast_fp16)[name = tensor<string, []>("q_109_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_18_self_attn_linear_k_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_18_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(911088448)))];
            tensor<fp16, [1024]> encoder_layers_18_self_attn_linear_k_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_18_self_attn_linear_k_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(913185664)))];
            tensor<fp16, [1, 188, 1024]> linear_166_cast_fp16 = linear(bias = encoder_layers_18_self_attn_linear_k_bias_to_fp16, weight = encoder_layers_18_self_attn_linear_k_weight_to_fp16, x = query_37_cast_fp16)[name = tensor<string, []>("linear_166_cast_fp16")];
            tensor<int32, [4]> var_3405 = const()[name = tensor<string, []>("op_3405"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_73_cast_fp16 = reshape(shape = var_3405, x = linear_166_cast_fp16)[name = tensor<string, []>("k_73_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_18_self_attn_linear_v_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_18_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(913187776)))];
            tensor<fp16, [1024]> encoder_layers_18_self_attn_linear_v_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_18_self_attn_linear_v_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(915284992)))];
            tensor<fp16, [1, 188, 1024]> linear_167_cast_fp16 = linear(bias = encoder_layers_18_self_attn_linear_v_bias_to_fp16, weight = encoder_layers_18_self_attn_linear_v_weight_to_fp16, x = query_37_cast_fp16)[name = tensor<string, []>("linear_167_cast_fp16")];
            tensor<int32, [4]> var_3410 = const()[name = tensor<string, []>("op_3410"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_37_cast_fp16 = reshape(shape = var_3410, x = linear_167_cast_fp16)[name = tensor<string, []>("v_37_cast_fp16")];
            tensor<int32, [4]> value_39_perm_0 = const()[name = tensor<string, []>("value_39_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> encoder_layers_18_self_attn_pos_bias_u_to_fp16 = const()[name = tensor<string, []>("encoder_layers_18_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(915287104)))];
            tensor<fp16, [1, 188, 8, 128]> var_3422_cast_fp16 = add(x = q_109_cast_fp16, y = encoder_layers_18_self_attn_pos_bias_u_to_fp16)[name = tensor<string, []>("op_3422_cast_fp16")];
            tensor<fp16, [8, 128]> encoder_layers_18_self_attn_pos_bias_v_to_fp16 = const()[name = tensor<string, []>("encoder_layers_18_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(915289216)))];
            tensor<fp16, [1, 188, 8, 128]> var_3424_cast_fp16 = add(x = q_109_cast_fp16, y = encoder_layers_18_self_attn_pos_bias_v_to_fp16)[name = tensor<string, []>("op_3424_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_37_perm_0 = const()[name = tensor<string, []>("q_with_bias_v_37_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<bool, []> x_403_transpose_x_0 = const()[name = tensor<string, []>("x_403_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_403_transpose_y_0 = const()[name = tensor<string, []>("x_403_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 128, 375]> var_3426_to_fp16 = const()[name = tensor<string, []>("op_3426_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(915291328)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_37_cast_fp16 = transpose(perm = q_with_bias_v_37_perm_0, x = var_3424_cast_fp16)[name = tensor<string, []>("transpose_256")];
            tensor<fp16, [1, 8, 188, 375]> x_403_cast_fp16 = matmul(transpose_x = x_403_transpose_x_0, transpose_y = x_403_transpose_y_0, x = q_with_bias_v_37_cast_fp16, y = var_3426_to_fp16)[name = tensor<string, []>("x_403_cast_fp16")];
            tensor<int32, [8]> x_405_pad_0 = const()[name = tensor<string, []>("x_405_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            tensor<string, []> x_405_mode_0 = const()[name = tensor<string, []>("x_405_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_194_to_fp16 = const()[name = tensor<string, []>("const_194_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_405_cast_fp16 = pad(constant_val = const_194_to_fp16, mode = x_405_mode_0, pad = x_405_pad_0, x = x_403_cast_fp16)[name = tensor<string, []>("x_405_cast_fp16")];
            tensor<int32, [4]> var_3434 = const()[name = tensor<string, []>("op_3434"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_407_cast_fp16 = reshape(shape = var_3434, x = x_405_cast_fp16)[name = tensor<string, []>("x_407_cast_fp16")];
            tensor<int32, [4]> var_3438_begin_0 = const()[name = tensor<string, []>("op_3438_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_3438_end_0 = const()[name = tensor<string, []>("op_3438_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_3438_end_mask_0 = const()[name = tensor<string, []>("op_3438_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_3438_cast_fp16 = slice_by_index(begin = var_3438_begin_0, end = var_3438_end_0, end_mask = var_3438_end_mask_0, x = x_407_cast_fp16)[name = tensor<string, []>("op_3438_cast_fp16")];
            tensor<int32, [4]> var_3439 = const()[name = tensor<string, []>("op_3439"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_73_cast_fp16 = reshape(shape = var_3439, x = var_3438_cast_fp16)[name = tensor<string, []>("matrix_bd_73_cast_fp16")];
            tensor<bool, []> matrix_ac_37_transpose_x_0 = const()[name = tensor<string, []>("matrix_ac_37_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> matrix_ac_37_transpose_y_0 = const()[name = tensor<string, []>("matrix_ac_37_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<int32, [4]> transpose_132_perm_0 = const()[name = tensor<string, []>("transpose_132_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_133_perm_0 = const()[name = tensor<string, []>("transpose_133_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_133 = transpose(perm = transpose_133_perm_0, x = k_73_cast_fp16)[name = tensor<string, []>("transpose_254")];
            tensor<fp16, [1, 8, 188, 128]> transpose_132 = transpose(perm = transpose_132_perm_0, x = var_3422_cast_fp16)[name = tensor<string, []>("transpose_255")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_37_cast_fp16 = matmul(transpose_x = matrix_ac_37_transpose_x_0, transpose_y = matrix_ac_37_transpose_y_0, x = transpose_132, y = transpose_133)[name = tensor<string, []>("matrix_ac_37_cast_fp16")];
            tensor<int32, [4]> matrix_bd_75_begin_0 = const()[name = tensor<string, []>("matrix_bd_75_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_75_end_0 = const()[name = tensor<string, []>("matrix_bd_75_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_75_end_mask_0 = const()[name = tensor<string, []>("matrix_bd_75_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_75_cast_fp16 = slice_by_index(begin = matrix_bd_75_begin_0, end = matrix_bd_75_end_0, end_mask = matrix_bd_75_end_mask_0, x = matrix_bd_73_cast_fp16)[name = tensor<string, []>("matrix_bd_75_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_3448_cast_fp16 = add(x = matrix_ac_37_cast_fp16, y = matrix_bd_75_cast_fp16)[name = tensor<string, []>("op_3448_cast_fp16")];
            tensor<fp16, []> _inversed_scores_73_y_0_to_fp16 = const()[name = tensor<string, []>("_inversed_scores_73_y_0_to_fp16"), val = tensor<fp16, []>(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_73_cast_fp16 = mul(x = var_3448_cast_fp16, y = _inversed_scores_73_y_0_to_fp16)[name = tensor<string, []>("_inversed_scores_73_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_75_cast_fp16 = select(a = var_12_to_fp16, b = _inversed_scores_73_cast_fp16, cond = mask_3)[name = tensor<string, []>("scores_75_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_3454_cast_fp16 = softmax(axis = var_30, x = scores_75_cast_fp16)[name = tensor<string, []>("op_3454_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_969_cast_fp16 = select(a = var_11_to_fp16, b = var_3454_cast_fp16, cond = mask_3)[name = tensor<string, []>("input_969_cast_fp16")];
            tensor<bool, []> x_409_transpose_x_0 = const()[name = tensor<string, []>("x_409_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_409_transpose_y_0 = const()[name = tensor<string, []>("x_409_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 188, 128]> value_39_cast_fp16 = transpose(perm = value_39_perm_0, x = v_37_cast_fp16)[name = tensor<string, []>("transpose_257")];
            tensor<fp16, [1, 8, 188, 128]> x_409_cast_fp16 = matmul(transpose_x = x_409_transpose_x_0, transpose_y = x_409_transpose_y_0, x = input_969_cast_fp16, y = value_39_cast_fp16)[name = tensor<string, []>("x_409_cast_fp16")];
            tensor<int32, [4]> var_3458_perm_0 = const()[name = tensor<string, []>("op_3458_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_3459 = const()[name = tensor<string, []>("op_3459"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_3458_cast_fp16 = transpose(perm = var_3458_perm_0, x = x_409_cast_fp16)[name = tensor<string, []>("transpose_253")];
            tensor<fp16, [1, 188, 1024]> input_971_cast_fp16 = reshape(shape = var_3459, x = var_3458_cast_fp16)[name = tensor<string, []>("input_971_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_18_self_attn_linear_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_18_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(916059392)))];
            tensor<fp16, [1024]> encoder_layers_18_self_attn_linear_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_18_self_attn_linear_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(918156608)))];
            tensor<fp16, [1, 188, 1024]> linear_169_cast_fp16 = linear(bias = encoder_layers_18_self_attn_linear_out_bias_to_fp16, weight = encoder_layers_18_self_attn_linear_out_weight_to_fp16, x = input_971_cast_fp16)[name = tensor<string, []>("linear_169_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_975_cast_fp16 = add(x = input_967_cast_fp16, y = linear_169_cast_fp16)[name = tensor<string, []>("input_975_cast_fp16")];
            tensor<int32, [1]> x_413_axes_0 = const()[name = tensor<string, []>("x_413_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_18_norm_conv_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_18_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(918158720)))];
            tensor<fp16, [1024]> encoder_layers_18_norm_conv_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_18_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(918160832)))];
            tensor<fp16, [1, 188, 1024]> x_413_cast_fp16 = layer_norm(axes = x_413_axes_0, beta = encoder_layers_18_norm_conv_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_18_norm_conv_weight_to_fp16, x = input_975_cast_fp16)[name = tensor<string, []>("x_413_cast_fp16")];
            tensor<int32, [3]> input_977_perm_0 = const()[name = tensor<string, []>("input_977_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> input_979_pad_type_0 = const()[name = tensor<string, []>("input_979_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_979_strides_0 = const()[name = tensor<string, []>("input_979_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_979_pad_0 = const()[name = tensor<string, []>("input_979_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_979_dilations_0 = const()[name = tensor<string, []>("input_979_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_979_groups_0 = const()[name = tensor<string, []>("input_979_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [2048, 1024, 1]> encoder_layers_18_conv_pointwise_conv1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_18_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(918162944)))];
            tensor<fp16, [2048]> encoder_layers_18_conv_pointwise_conv1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_18_conv_pointwise_conv1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(922357312)))];
            tensor<fp16, [1, 1024, 188]> input_977_cast_fp16 = transpose(perm = input_977_perm_0, x = x_413_cast_fp16)[name = tensor<string, []>("transpose_252")];
            tensor<fp16, [1, 2048, 188]> input_979_cast_fp16 = conv(bias = encoder_layers_18_conv_pointwise_conv1_bias_to_fp16, dilations = input_979_dilations_0, groups = input_979_groups_0, pad = input_979_pad_0, pad_type = input_979_pad_type_0, strides = input_979_strides_0, weight = encoder_layers_18_conv_pointwise_conv1_weight_to_fp16, x = input_977_cast_fp16)[name = tensor<string, []>("input_979_cast_fp16")];
            tensor<int32, []> x_415_split_num_splits_0 = const()[name = tensor<string, []>("x_415_split_num_splits_0"), val = tensor<int32, []>(2)];
            tensor<int32, []> x_415_split_axis_0 = const()[name = tensor<string, []>("x_415_split_axis_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1, 1024, 188]> x_415_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_415_split_cast_fp16_1 = split(axis = x_415_split_axis_0, num_splits = x_415_split_num_splits_0, x = input_979_cast_fp16)[name = tensor<string, []>("x_415_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_415_split_1_sigmoid_cast_fp16 = sigmoid(x = x_415_split_cast_fp16_1)[name = tensor<string, []>("x_415_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_415_cast_fp16 = mul(x = x_415_split_cast_fp16_0, y = x_415_split_1_sigmoid_cast_fp16)[name = tensor<string, []>("x_415_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_981_cast_fp16 = select(a = var_11_to_fp16, b = x_415_cast_fp16, cond = var_351)[name = tensor<string, []>("input_981_cast_fp16")];
            tensor<int32, [6]> input_983_pad_0 = const()[name = tensor<string, []>("input_983_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            tensor<string, []> input_983_mode_0 = const()[name = tensor<string, []>("input_983_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_197_to_fp16 = const()[name = tensor<string, []>("const_197_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_983_cast_fp16 = pad(constant_val = const_197_to_fp16, mode = input_983_mode_0, pad = input_983_pad_0, x = input_981_cast_fp16)[name = tensor<string, []>("input_983_cast_fp16")];
            tensor<string, []> input_985_pad_type_0 = const()[name = tensor<string, []>("input_985_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, []> input_985_groups_0 = const()[name = tensor<string, []>("input_985_groups_0"), val = tensor<int32, []>(1024)];
            tensor<int32, [1]> input_985_strides_0 = const()[name = tensor<string, []>("input_985_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_985_pad_0 = const()[name = tensor<string, []>("input_985_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_985_dilations_0 = const()[name = tensor<string, []>("input_985_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_364_to_fp16 = const()[name = tensor<string, []>("const_364_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(922361472)))];
            tensor<fp16, [1024]> const_365_to_fp16 = const()[name = tensor<string, []>("const_365_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(922379968)))];
            tensor<fp16, [1, 1024, 188]> input_987_cast_fp16 = conv(bias = const_365_to_fp16, dilations = input_985_dilations_0, groups = input_985_groups_0, pad = input_985_pad_0, pad_type = input_985_pad_type_0, strides = input_985_strides_0, weight = const_364_to_fp16, x = input_983_cast_fp16)[name = tensor<string, []>("input_987_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_989_cast_fp16 = silu(x = input_987_cast_fp16)[name = tensor<string, []>("input_989_cast_fp16")];
            tensor<string, []> x_417_pad_type_0 = const()[name = tensor<string, []>("x_417_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> x_417_strides_0 = const()[name = tensor<string, []>("x_417_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_417_pad_0 = const()[name = tensor<string, []>("x_417_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_417_dilations_0 = const()[name = tensor<string, []>("x_417_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> x_417_groups_0 = const()[name = tensor<string, []>("x_417_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1024, 1024, 1]> encoder_layers_18_conv_pointwise_conv2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_18_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(922382080)))];
            tensor<fp16, [1024]> encoder_layers_18_conv_pointwise_conv2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_18_conv_pointwise_conv2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(924479296)))];
            tensor<fp16, [1, 1024, 188]> x_417_cast_fp16 = conv(bias = encoder_layers_18_conv_pointwise_conv2_bias_to_fp16, dilations = x_417_dilations_0, groups = x_417_groups_0, pad = x_417_pad_0, pad_type = x_417_pad_type_0, strides = x_417_strides_0, weight = encoder_layers_18_conv_pointwise_conv2_weight_to_fp16, x = input_989_cast_fp16)[name = tensor<string, []>("x_417_cast_fp16")];
            tensor<int32, [3]> input_991_perm_0 = const()[name = tensor<string, []>("input_991_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_991_cast_fp16 = transpose(perm = input_991_perm_0, x = x_417_cast_fp16)[name = tensor<string, []>("transpose_251")];
            tensor<fp16, [1, 188, 1024]> input_993_cast_fp16 = add(x = input_975_cast_fp16, y = input_991_cast_fp16)[name = tensor<string, []>("input_993_cast_fp16")];
            tensor<int32, [1]> input_995_axes_0 = const()[name = tensor<string, []>("input_995_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_18_norm_feed_forward2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_18_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(924481408)))];
            tensor<fp16, [1024]> encoder_layers_18_norm_feed_forward2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_18_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(924483520)))];
            tensor<fp16, [1, 188, 1024]> input_995_cast_fp16 = layer_norm(axes = input_995_axes_0, beta = encoder_layers_18_norm_feed_forward2_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_18_norm_feed_forward2_weight_to_fp16, x = input_993_cast_fp16)[name = tensor<string, []>("input_995_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_18_feed_forward2_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_18_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(924485632)))];
            tensor<fp16, [4096]> encoder_layers_18_feed_forward2_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_18_feed_forward2_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(932874304)))];
            tensor<fp16, [1, 188, 4096]> linear_170_cast_fp16 = linear(bias = encoder_layers_18_feed_forward2_linear1_bias_to_fp16, weight = encoder_layers_18_feed_forward2_linear1_weight_to_fp16, x = input_995_cast_fp16)[name = tensor<string, []>("linear_170_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_999_cast_fp16 = silu(x = linear_170_cast_fp16)[name = tensor<string, []>("input_999_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_18_feed_forward2_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_18_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(932882560)))];
            tensor<fp16, [1024]> encoder_layers_18_feed_forward2_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_18_feed_forward2_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(941271232)))];
            tensor<fp16, [1, 188, 1024]> linear_171_cast_fp16 = linear(bias = encoder_layers_18_feed_forward2_linear2_bias_to_fp16, weight = encoder_layers_18_feed_forward2_linear2_weight_to_fp16, x = input_999_cast_fp16)[name = tensor<string, []>("linear_171_cast_fp16")];
            tensor<fp16, []> var_3525_to_fp16 = const()[name = tensor<string, []>("op_3525_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_3526_cast_fp16 = mul(x = linear_171_cast_fp16, y = var_3525_to_fp16)[name = tensor<string, []>("op_3526_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1005_cast_fp16 = add(x = input_993_cast_fp16, y = var_3526_cast_fp16)[name = tensor<string, []>("input_1005_cast_fp16")];
            tensor<int32, [1]> input_1007_axes_0 = const()[name = tensor<string, []>("input_1007_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_18_norm_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_18_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(941273344)))];
            tensor<fp16, [1024]> encoder_layers_18_norm_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_18_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(941275456)))];
            tensor<fp16, [1, 188, 1024]> input_1007_cast_fp16 = layer_norm(axes = input_1007_axes_0, beta = encoder_layers_18_norm_out_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_18_norm_out_weight_to_fp16, x = input_1005_cast_fp16)[name = tensor<string, []>("input_1007_cast_fp16")];
            tensor<int32, [1]> input_1009_axes_0 = const()[name = tensor<string, []>("input_1009_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_19_norm_feed_forward1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_19_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(941277568)))];
            tensor<fp16, [1024]> encoder_layers_19_norm_feed_forward1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_19_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(941279680)))];
            tensor<fp16, [1, 188, 1024]> input_1009_cast_fp16 = layer_norm(axes = input_1009_axes_0, beta = encoder_layers_19_norm_feed_forward1_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_19_norm_feed_forward1_weight_to_fp16, x = input_1007_cast_fp16)[name = tensor<string, []>("input_1009_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_19_feed_forward1_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_19_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(941281792)))];
            tensor<fp16, [4096]> encoder_layers_19_feed_forward1_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_19_feed_forward1_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(949670464)))];
            tensor<fp16, [1, 188, 4096]> linear_172_cast_fp16 = linear(bias = encoder_layers_19_feed_forward1_linear1_bias_to_fp16, weight = encoder_layers_19_feed_forward1_linear1_weight_to_fp16, x = input_1009_cast_fp16)[name = tensor<string, []>("linear_172_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_1013_cast_fp16 = silu(x = linear_172_cast_fp16)[name = tensor<string, []>("input_1013_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_19_feed_forward1_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_19_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(949678720)))];
            tensor<fp16, [1024]> encoder_layers_19_feed_forward1_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_19_feed_forward1_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(958067392)))];
            tensor<fp16, [1, 188, 1024]> linear_173_cast_fp16 = linear(bias = encoder_layers_19_feed_forward1_linear2_bias_to_fp16, weight = encoder_layers_19_feed_forward1_linear2_weight_to_fp16, x = input_1013_cast_fp16)[name = tensor<string, []>("linear_173_cast_fp16")];
            tensor<fp16, []> var_3556_to_fp16 = const()[name = tensor<string, []>("op_3556_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_3557_cast_fp16 = mul(x = linear_173_cast_fp16, y = var_3556_to_fp16)[name = tensor<string, []>("op_3557_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1019_cast_fp16 = add(x = input_1007_cast_fp16, y = var_3557_cast_fp16)[name = tensor<string, []>("input_1019_cast_fp16")];
            tensor<int32, [1]> query_39_axes_0 = const()[name = tensor<string, []>("query_39_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_19_norm_self_att_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_19_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(958069504)))];
            tensor<fp16, [1024]> encoder_layers_19_norm_self_att_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_19_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(958071616)))];
            tensor<fp16, [1, 188, 1024]> query_39_cast_fp16 = layer_norm(axes = query_39_axes_0, beta = encoder_layers_19_norm_self_att_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_19_norm_self_att_weight_to_fp16, x = input_1019_cast_fp16)[name = tensor<string, []>("query_39_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_19_self_attn_linear_q_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_19_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(958073728)))];
            tensor<fp16, [1024]> encoder_layers_19_self_attn_linear_q_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_19_self_attn_linear_q_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(960170944)))];
            tensor<fp16, [1, 188, 1024]> linear_174_cast_fp16 = linear(bias = encoder_layers_19_self_attn_linear_q_bias_to_fp16, weight = encoder_layers_19_self_attn_linear_q_weight_to_fp16, x = query_39_cast_fp16)[name = tensor<string, []>("linear_174_cast_fp16")];
            tensor<int32, [4]> var_3574 = const()[name = tensor<string, []>("op_3574"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_115_cast_fp16 = reshape(shape = var_3574, x = linear_174_cast_fp16)[name = tensor<string, []>("q_115_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_19_self_attn_linear_k_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_19_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(960173056)))];
            tensor<fp16, [1024]> encoder_layers_19_self_attn_linear_k_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_19_self_attn_linear_k_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(962270272)))];
            tensor<fp16, [1, 188, 1024]> linear_175_cast_fp16 = linear(bias = encoder_layers_19_self_attn_linear_k_bias_to_fp16, weight = encoder_layers_19_self_attn_linear_k_weight_to_fp16, x = query_39_cast_fp16)[name = tensor<string, []>("linear_175_cast_fp16")];
            tensor<int32, [4]> var_3579 = const()[name = tensor<string, []>("op_3579"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_77_cast_fp16 = reshape(shape = var_3579, x = linear_175_cast_fp16)[name = tensor<string, []>("k_77_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_19_self_attn_linear_v_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_19_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(962272384)))];
            tensor<fp16, [1024]> encoder_layers_19_self_attn_linear_v_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_19_self_attn_linear_v_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(964369600)))];
            tensor<fp16, [1, 188, 1024]> linear_176_cast_fp16 = linear(bias = encoder_layers_19_self_attn_linear_v_bias_to_fp16, weight = encoder_layers_19_self_attn_linear_v_weight_to_fp16, x = query_39_cast_fp16)[name = tensor<string, []>("linear_176_cast_fp16")];
            tensor<int32, [4]> var_3584 = const()[name = tensor<string, []>("op_3584"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_39_cast_fp16 = reshape(shape = var_3584, x = linear_176_cast_fp16)[name = tensor<string, []>("v_39_cast_fp16")];
            tensor<int32, [4]> value_41_perm_0 = const()[name = tensor<string, []>("value_41_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> encoder_layers_19_self_attn_pos_bias_u_to_fp16 = const()[name = tensor<string, []>("encoder_layers_19_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(964371712)))];
            tensor<fp16, [1, 188, 8, 128]> var_3596_cast_fp16 = add(x = q_115_cast_fp16, y = encoder_layers_19_self_attn_pos_bias_u_to_fp16)[name = tensor<string, []>("op_3596_cast_fp16")];
            tensor<fp16, [8, 128]> encoder_layers_19_self_attn_pos_bias_v_to_fp16 = const()[name = tensor<string, []>("encoder_layers_19_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(964373824)))];
            tensor<fp16, [1, 188, 8, 128]> var_3598_cast_fp16 = add(x = q_115_cast_fp16, y = encoder_layers_19_self_attn_pos_bias_v_to_fp16)[name = tensor<string, []>("op_3598_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_39_perm_0 = const()[name = tensor<string, []>("q_with_bias_v_39_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<bool, []> x_425_transpose_x_0 = const()[name = tensor<string, []>("x_425_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_425_transpose_y_0 = const()[name = tensor<string, []>("x_425_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 128, 375]> var_3600_to_fp16 = const()[name = tensor<string, []>("op_3600_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(964375936)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_39_cast_fp16 = transpose(perm = q_with_bias_v_39_perm_0, x = var_3598_cast_fp16)[name = tensor<string, []>("transpose_249")];
            tensor<fp16, [1, 8, 188, 375]> x_425_cast_fp16 = matmul(transpose_x = x_425_transpose_x_0, transpose_y = x_425_transpose_y_0, x = q_with_bias_v_39_cast_fp16, y = var_3600_to_fp16)[name = tensor<string, []>("x_425_cast_fp16")];
            tensor<int32, [8]> x_427_pad_0 = const()[name = tensor<string, []>("x_427_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            tensor<string, []> x_427_mode_0 = const()[name = tensor<string, []>("x_427_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_204_to_fp16 = const()[name = tensor<string, []>("const_204_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_427_cast_fp16 = pad(constant_val = const_204_to_fp16, mode = x_427_mode_0, pad = x_427_pad_0, x = x_425_cast_fp16)[name = tensor<string, []>("x_427_cast_fp16")];
            tensor<int32, [4]> var_3608 = const()[name = tensor<string, []>("op_3608"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_429_cast_fp16 = reshape(shape = var_3608, x = x_427_cast_fp16)[name = tensor<string, []>("x_429_cast_fp16")];
            tensor<int32, [4]> var_3612_begin_0 = const()[name = tensor<string, []>("op_3612_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_3612_end_0 = const()[name = tensor<string, []>("op_3612_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_3612_end_mask_0 = const()[name = tensor<string, []>("op_3612_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_3612_cast_fp16 = slice_by_index(begin = var_3612_begin_0, end = var_3612_end_0, end_mask = var_3612_end_mask_0, x = x_429_cast_fp16)[name = tensor<string, []>("op_3612_cast_fp16")];
            tensor<int32, [4]> var_3613 = const()[name = tensor<string, []>("op_3613"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_77_cast_fp16 = reshape(shape = var_3613, x = var_3612_cast_fp16)[name = tensor<string, []>("matrix_bd_77_cast_fp16")];
            tensor<bool, []> matrix_ac_39_transpose_x_0 = const()[name = tensor<string, []>("matrix_ac_39_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> matrix_ac_39_transpose_y_0 = const()[name = tensor<string, []>("matrix_ac_39_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<int32, [4]> transpose_134_perm_0 = const()[name = tensor<string, []>("transpose_134_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_135_perm_0 = const()[name = tensor<string, []>("transpose_135_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_135 = transpose(perm = transpose_135_perm_0, x = k_77_cast_fp16)[name = tensor<string, []>("transpose_247")];
            tensor<fp16, [1, 8, 188, 128]> transpose_134 = transpose(perm = transpose_134_perm_0, x = var_3596_cast_fp16)[name = tensor<string, []>("transpose_248")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_39_cast_fp16 = matmul(transpose_x = matrix_ac_39_transpose_x_0, transpose_y = matrix_ac_39_transpose_y_0, x = transpose_134, y = transpose_135)[name = tensor<string, []>("matrix_ac_39_cast_fp16")];
            tensor<int32, [4]> matrix_bd_79_begin_0 = const()[name = tensor<string, []>("matrix_bd_79_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_79_end_0 = const()[name = tensor<string, []>("matrix_bd_79_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_79_end_mask_0 = const()[name = tensor<string, []>("matrix_bd_79_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_79_cast_fp16 = slice_by_index(begin = matrix_bd_79_begin_0, end = matrix_bd_79_end_0, end_mask = matrix_bd_79_end_mask_0, x = matrix_bd_77_cast_fp16)[name = tensor<string, []>("matrix_bd_79_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_3622_cast_fp16 = add(x = matrix_ac_39_cast_fp16, y = matrix_bd_79_cast_fp16)[name = tensor<string, []>("op_3622_cast_fp16")];
            tensor<fp16, []> _inversed_scores_77_y_0_to_fp16 = const()[name = tensor<string, []>("_inversed_scores_77_y_0_to_fp16"), val = tensor<fp16, []>(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_77_cast_fp16 = mul(x = var_3622_cast_fp16, y = _inversed_scores_77_y_0_to_fp16)[name = tensor<string, []>("_inversed_scores_77_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_79_cast_fp16 = select(a = var_12_to_fp16, b = _inversed_scores_77_cast_fp16, cond = mask_3)[name = tensor<string, []>("scores_79_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_3628_cast_fp16 = softmax(axis = var_30, x = scores_79_cast_fp16)[name = tensor<string, []>("op_3628_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_1021_cast_fp16 = select(a = var_11_to_fp16, b = var_3628_cast_fp16, cond = mask_3)[name = tensor<string, []>("input_1021_cast_fp16")];
            tensor<bool, []> x_431_transpose_x_0 = const()[name = tensor<string, []>("x_431_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_431_transpose_y_0 = const()[name = tensor<string, []>("x_431_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 188, 128]> value_41_cast_fp16 = transpose(perm = value_41_perm_0, x = v_39_cast_fp16)[name = tensor<string, []>("transpose_250")];
            tensor<fp16, [1, 8, 188, 128]> x_431_cast_fp16 = matmul(transpose_x = x_431_transpose_x_0, transpose_y = x_431_transpose_y_0, x = input_1021_cast_fp16, y = value_41_cast_fp16)[name = tensor<string, []>("x_431_cast_fp16")];
            tensor<int32, [4]> var_3632_perm_0 = const()[name = tensor<string, []>("op_3632_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_3633 = const()[name = tensor<string, []>("op_3633"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_3632_cast_fp16 = transpose(perm = var_3632_perm_0, x = x_431_cast_fp16)[name = tensor<string, []>("transpose_246")];
            tensor<fp16, [1, 188, 1024]> input_1023_cast_fp16 = reshape(shape = var_3633, x = var_3632_cast_fp16)[name = tensor<string, []>("input_1023_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_19_self_attn_linear_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_19_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(965144000)))];
            tensor<fp16, [1024]> encoder_layers_19_self_attn_linear_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_19_self_attn_linear_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(967241216)))];
            tensor<fp16, [1, 188, 1024]> linear_178_cast_fp16 = linear(bias = encoder_layers_19_self_attn_linear_out_bias_to_fp16, weight = encoder_layers_19_self_attn_linear_out_weight_to_fp16, x = input_1023_cast_fp16)[name = tensor<string, []>("linear_178_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1027_cast_fp16 = add(x = input_1019_cast_fp16, y = linear_178_cast_fp16)[name = tensor<string, []>("input_1027_cast_fp16")];
            tensor<int32, [1]> x_435_axes_0 = const()[name = tensor<string, []>("x_435_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_19_norm_conv_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_19_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(967243328)))];
            tensor<fp16, [1024]> encoder_layers_19_norm_conv_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_19_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(967245440)))];
            tensor<fp16, [1, 188, 1024]> x_435_cast_fp16 = layer_norm(axes = x_435_axes_0, beta = encoder_layers_19_norm_conv_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_19_norm_conv_weight_to_fp16, x = input_1027_cast_fp16)[name = tensor<string, []>("x_435_cast_fp16")];
            tensor<int32, [3]> input_1029_perm_0 = const()[name = tensor<string, []>("input_1029_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> input_1031_pad_type_0 = const()[name = tensor<string, []>("input_1031_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_1031_strides_0 = const()[name = tensor<string, []>("input_1031_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1031_pad_0 = const()[name = tensor<string, []>("input_1031_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1031_dilations_0 = const()[name = tensor<string, []>("input_1031_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_1031_groups_0 = const()[name = tensor<string, []>("input_1031_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [2048, 1024, 1]> encoder_layers_19_conv_pointwise_conv1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_19_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(967247552)))];
            tensor<fp16, [2048]> encoder_layers_19_conv_pointwise_conv1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_19_conv_pointwise_conv1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(971441920)))];
            tensor<fp16, [1, 1024, 188]> input_1029_cast_fp16 = transpose(perm = input_1029_perm_0, x = x_435_cast_fp16)[name = tensor<string, []>("transpose_245")];
            tensor<fp16, [1, 2048, 188]> input_1031_cast_fp16 = conv(bias = encoder_layers_19_conv_pointwise_conv1_bias_to_fp16, dilations = input_1031_dilations_0, groups = input_1031_groups_0, pad = input_1031_pad_0, pad_type = input_1031_pad_type_0, strides = input_1031_strides_0, weight = encoder_layers_19_conv_pointwise_conv1_weight_to_fp16, x = input_1029_cast_fp16)[name = tensor<string, []>("input_1031_cast_fp16")];
            tensor<int32, []> x_437_split_num_splits_0 = const()[name = tensor<string, []>("x_437_split_num_splits_0"), val = tensor<int32, []>(2)];
            tensor<int32, []> x_437_split_axis_0 = const()[name = tensor<string, []>("x_437_split_axis_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1, 1024, 188]> x_437_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_437_split_cast_fp16_1 = split(axis = x_437_split_axis_0, num_splits = x_437_split_num_splits_0, x = input_1031_cast_fp16)[name = tensor<string, []>("x_437_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_437_split_1_sigmoid_cast_fp16 = sigmoid(x = x_437_split_cast_fp16_1)[name = tensor<string, []>("x_437_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_437_cast_fp16 = mul(x = x_437_split_cast_fp16_0, y = x_437_split_1_sigmoid_cast_fp16)[name = tensor<string, []>("x_437_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_1033_cast_fp16 = select(a = var_11_to_fp16, b = x_437_cast_fp16, cond = var_351)[name = tensor<string, []>("input_1033_cast_fp16")];
            tensor<int32, [6]> input_1035_pad_0 = const()[name = tensor<string, []>("input_1035_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            tensor<string, []> input_1035_mode_0 = const()[name = tensor<string, []>("input_1035_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_207_to_fp16 = const()[name = tensor<string, []>("const_207_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_1035_cast_fp16 = pad(constant_val = const_207_to_fp16, mode = input_1035_mode_0, pad = input_1035_pad_0, x = input_1033_cast_fp16)[name = tensor<string, []>("input_1035_cast_fp16")];
            tensor<string, []> input_1037_pad_type_0 = const()[name = tensor<string, []>("input_1037_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, []> input_1037_groups_0 = const()[name = tensor<string, []>("input_1037_groups_0"), val = tensor<int32, []>(1024)];
            tensor<int32, [1]> input_1037_strides_0 = const()[name = tensor<string, []>("input_1037_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1037_pad_0 = const()[name = tensor<string, []>("input_1037_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1037_dilations_0 = const()[name = tensor<string, []>("input_1037_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_366_to_fp16 = const()[name = tensor<string, []>("const_366_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(971446080)))];
            tensor<fp16, [1024]> const_367_to_fp16 = const()[name = tensor<string, []>("const_367_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(971464576)))];
            tensor<fp16, [1, 1024, 188]> input_1039_cast_fp16 = conv(bias = const_367_to_fp16, dilations = input_1037_dilations_0, groups = input_1037_groups_0, pad = input_1037_pad_0, pad_type = input_1037_pad_type_0, strides = input_1037_strides_0, weight = const_366_to_fp16, x = input_1035_cast_fp16)[name = tensor<string, []>("input_1039_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_1041_cast_fp16 = silu(x = input_1039_cast_fp16)[name = tensor<string, []>("input_1041_cast_fp16")];
            tensor<string, []> x_439_pad_type_0 = const()[name = tensor<string, []>("x_439_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> x_439_strides_0 = const()[name = tensor<string, []>("x_439_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_439_pad_0 = const()[name = tensor<string, []>("x_439_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_439_dilations_0 = const()[name = tensor<string, []>("x_439_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> x_439_groups_0 = const()[name = tensor<string, []>("x_439_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1024, 1024, 1]> encoder_layers_19_conv_pointwise_conv2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_19_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(971466688)))];
            tensor<fp16, [1024]> encoder_layers_19_conv_pointwise_conv2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_19_conv_pointwise_conv2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(973563904)))];
            tensor<fp16, [1, 1024, 188]> x_439_cast_fp16 = conv(bias = encoder_layers_19_conv_pointwise_conv2_bias_to_fp16, dilations = x_439_dilations_0, groups = x_439_groups_0, pad = x_439_pad_0, pad_type = x_439_pad_type_0, strides = x_439_strides_0, weight = encoder_layers_19_conv_pointwise_conv2_weight_to_fp16, x = input_1041_cast_fp16)[name = tensor<string, []>("x_439_cast_fp16")];
            tensor<int32, [3]> input_1043_perm_0 = const()[name = tensor<string, []>("input_1043_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_1043_cast_fp16 = transpose(perm = input_1043_perm_0, x = x_439_cast_fp16)[name = tensor<string, []>("transpose_244")];
            tensor<fp16, [1, 188, 1024]> input_1045_cast_fp16 = add(x = input_1027_cast_fp16, y = input_1043_cast_fp16)[name = tensor<string, []>("input_1045_cast_fp16")];
            tensor<int32, [1]> input_1047_axes_0 = const()[name = tensor<string, []>("input_1047_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_19_norm_feed_forward2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_19_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(973566016)))];
            tensor<fp16, [1024]> encoder_layers_19_norm_feed_forward2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_19_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(973568128)))];
            tensor<fp16, [1, 188, 1024]> input_1047_cast_fp16 = layer_norm(axes = input_1047_axes_0, beta = encoder_layers_19_norm_feed_forward2_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_19_norm_feed_forward2_weight_to_fp16, x = input_1045_cast_fp16)[name = tensor<string, []>("input_1047_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_19_feed_forward2_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_19_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(973570240)))];
            tensor<fp16, [4096]> encoder_layers_19_feed_forward2_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_19_feed_forward2_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(981958912)))];
            tensor<fp16, [1, 188, 4096]> linear_179_cast_fp16 = linear(bias = encoder_layers_19_feed_forward2_linear1_bias_to_fp16, weight = encoder_layers_19_feed_forward2_linear1_weight_to_fp16, x = input_1047_cast_fp16)[name = tensor<string, []>("linear_179_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_1051_cast_fp16 = silu(x = linear_179_cast_fp16)[name = tensor<string, []>("input_1051_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_19_feed_forward2_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_19_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(981967168)))];
            tensor<fp16, [1024]> encoder_layers_19_feed_forward2_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_19_feed_forward2_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(990355840)))];
            tensor<fp16, [1, 188, 1024]> linear_180_cast_fp16 = linear(bias = encoder_layers_19_feed_forward2_linear2_bias_to_fp16, weight = encoder_layers_19_feed_forward2_linear2_weight_to_fp16, x = input_1051_cast_fp16)[name = tensor<string, []>("linear_180_cast_fp16")];
            tensor<fp16, []> var_3699_to_fp16 = const()[name = tensor<string, []>("op_3699_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_3700_cast_fp16 = mul(x = linear_180_cast_fp16, y = var_3699_to_fp16)[name = tensor<string, []>("op_3700_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1057_cast_fp16 = add(x = input_1045_cast_fp16, y = var_3700_cast_fp16)[name = tensor<string, []>("input_1057_cast_fp16")];
            tensor<int32, [1]> input_1059_axes_0 = const()[name = tensor<string, []>("input_1059_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_19_norm_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_19_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(990357952)))];
            tensor<fp16, [1024]> encoder_layers_19_norm_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_19_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(990360064)))];
            tensor<fp16, [1, 188, 1024]> input_1059_cast_fp16 = layer_norm(axes = input_1059_axes_0, beta = encoder_layers_19_norm_out_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_19_norm_out_weight_to_fp16, x = input_1057_cast_fp16)[name = tensor<string, []>("input_1059_cast_fp16")];
            tensor<int32, [1]> input_1061_axes_0 = const()[name = tensor<string, []>("input_1061_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_20_norm_feed_forward1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_20_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(990362176)))];
            tensor<fp16, [1024]> encoder_layers_20_norm_feed_forward1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_20_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(990364288)))];
            tensor<fp16, [1, 188, 1024]> input_1061_cast_fp16 = layer_norm(axes = input_1061_axes_0, beta = encoder_layers_20_norm_feed_forward1_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_20_norm_feed_forward1_weight_to_fp16, x = input_1059_cast_fp16)[name = tensor<string, []>("input_1061_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_20_feed_forward1_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_20_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(990366400)))];
            tensor<fp16, [4096]> encoder_layers_20_feed_forward1_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_20_feed_forward1_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(998755072)))];
            tensor<fp16, [1, 188, 4096]> linear_181_cast_fp16 = linear(bias = encoder_layers_20_feed_forward1_linear1_bias_to_fp16, weight = encoder_layers_20_feed_forward1_linear1_weight_to_fp16, x = input_1061_cast_fp16)[name = tensor<string, []>("linear_181_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_1065_cast_fp16 = silu(x = linear_181_cast_fp16)[name = tensor<string, []>("input_1065_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_20_feed_forward1_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_20_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(998763328)))];
            tensor<fp16, [1024]> encoder_layers_20_feed_forward1_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_20_feed_forward1_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1007152000)))];
            tensor<fp16, [1, 188, 1024]> linear_182_cast_fp16 = linear(bias = encoder_layers_20_feed_forward1_linear2_bias_to_fp16, weight = encoder_layers_20_feed_forward1_linear2_weight_to_fp16, x = input_1065_cast_fp16)[name = tensor<string, []>("linear_182_cast_fp16")];
            tensor<fp16, []> var_3730_to_fp16 = const()[name = tensor<string, []>("op_3730_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_3731_cast_fp16 = mul(x = linear_182_cast_fp16, y = var_3730_to_fp16)[name = tensor<string, []>("op_3731_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1071_cast_fp16 = add(x = input_1059_cast_fp16, y = var_3731_cast_fp16)[name = tensor<string, []>("input_1071_cast_fp16")];
            tensor<int32, [1]> query_41_axes_0 = const()[name = tensor<string, []>("query_41_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_20_norm_self_att_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_20_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1007154112)))];
            tensor<fp16, [1024]> encoder_layers_20_norm_self_att_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_20_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1007156224)))];
            tensor<fp16, [1, 188, 1024]> query_41_cast_fp16 = layer_norm(axes = query_41_axes_0, beta = encoder_layers_20_norm_self_att_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_20_norm_self_att_weight_to_fp16, x = input_1071_cast_fp16)[name = tensor<string, []>("query_41_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_20_self_attn_linear_q_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_20_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1007158336)))];
            tensor<fp16, [1024]> encoder_layers_20_self_attn_linear_q_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_20_self_attn_linear_q_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1009255552)))];
            tensor<fp16, [1, 188, 1024]> linear_183_cast_fp16 = linear(bias = encoder_layers_20_self_attn_linear_q_bias_to_fp16, weight = encoder_layers_20_self_attn_linear_q_weight_to_fp16, x = query_41_cast_fp16)[name = tensor<string, []>("linear_183_cast_fp16")];
            tensor<int32, [4]> var_3748 = const()[name = tensor<string, []>("op_3748"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_121_cast_fp16 = reshape(shape = var_3748, x = linear_183_cast_fp16)[name = tensor<string, []>("q_121_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_20_self_attn_linear_k_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_20_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1009257664)))];
            tensor<fp16, [1024]> encoder_layers_20_self_attn_linear_k_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_20_self_attn_linear_k_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1011354880)))];
            tensor<fp16, [1, 188, 1024]> linear_184_cast_fp16 = linear(bias = encoder_layers_20_self_attn_linear_k_bias_to_fp16, weight = encoder_layers_20_self_attn_linear_k_weight_to_fp16, x = query_41_cast_fp16)[name = tensor<string, []>("linear_184_cast_fp16")];
            tensor<int32, [4]> var_3753 = const()[name = tensor<string, []>("op_3753"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_81_cast_fp16 = reshape(shape = var_3753, x = linear_184_cast_fp16)[name = tensor<string, []>("k_81_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_20_self_attn_linear_v_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_20_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1011356992)))];
            tensor<fp16, [1024]> encoder_layers_20_self_attn_linear_v_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_20_self_attn_linear_v_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1013454208)))];
            tensor<fp16, [1, 188, 1024]> linear_185_cast_fp16 = linear(bias = encoder_layers_20_self_attn_linear_v_bias_to_fp16, weight = encoder_layers_20_self_attn_linear_v_weight_to_fp16, x = query_41_cast_fp16)[name = tensor<string, []>("linear_185_cast_fp16")];
            tensor<int32, [4]> var_3758 = const()[name = tensor<string, []>("op_3758"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_41_cast_fp16 = reshape(shape = var_3758, x = linear_185_cast_fp16)[name = tensor<string, []>("v_41_cast_fp16")];
            tensor<int32, [4]> value_43_perm_0 = const()[name = tensor<string, []>("value_43_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> encoder_layers_20_self_attn_pos_bias_u_to_fp16 = const()[name = tensor<string, []>("encoder_layers_20_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1013456320)))];
            tensor<fp16, [1, 188, 8, 128]> var_3770_cast_fp16 = add(x = q_121_cast_fp16, y = encoder_layers_20_self_attn_pos_bias_u_to_fp16)[name = tensor<string, []>("op_3770_cast_fp16")];
            tensor<fp16, [8, 128]> encoder_layers_20_self_attn_pos_bias_v_to_fp16 = const()[name = tensor<string, []>("encoder_layers_20_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1013458432)))];
            tensor<fp16, [1, 188, 8, 128]> var_3772_cast_fp16 = add(x = q_121_cast_fp16, y = encoder_layers_20_self_attn_pos_bias_v_to_fp16)[name = tensor<string, []>("op_3772_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_41_perm_0 = const()[name = tensor<string, []>("q_with_bias_v_41_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<bool, []> x_447_transpose_x_0 = const()[name = tensor<string, []>("x_447_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_447_transpose_y_0 = const()[name = tensor<string, []>("x_447_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 128, 375]> var_3774_to_fp16 = const()[name = tensor<string, []>("op_3774_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1013460544)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_41_cast_fp16 = transpose(perm = q_with_bias_v_41_perm_0, x = var_3772_cast_fp16)[name = tensor<string, []>("transpose_242")];
            tensor<fp16, [1, 8, 188, 375]> x_447_cast_fp16 = matmul(transpose_x = x_447_transpose_x_0, transpose_y = x_447_transpose_y_0, x = q_with_bias_v_41_cast_fp16, y = var_3774_to_fp16)[name = tensor<string, []>("x_447_cast_fp16")];
            tensor<int32, [8]> x_449_pad_0 = const()[name = tensor<string, []>("x_449_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            tensor<string, []> x_449_mode_0 = const()[name = tensor<string, []>("x_449_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_214_to_fp16 = const()[name = tensor<string, []>("const_214_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_449_cast_fp16 = pad(constant_val = const_214_to_fp16, mode = x_449_mode_0, pad = x_449_pad_0, x = x_447_cast_fp16)[name = tensor<string, []>("x_449_cast_fp16")];
            tensor<int32, [4]> var_3782 = const()[name = tensor<string, []>("op_3782"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_451_cast_fp16 = reshape(shape = var_3782, x = x_449_cast_fp16)[name = tensor<string, []>("x_451_cast_fp16")];
            tensor<int32, [4]> var_3786_begin_0 = const()[name = tensor<string, []>("op_3786_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_3786_end_0 = const()[name = tensor<string, []>("op_3786_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_3786_end_mask_0 = const()[name = tensor<string, []>("op_3786_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_3786_cast_fp16 = slice_by_index(begin = var_3786_begin_0, end = var_3786_end_0, end_mask = var_3786_end_mask_0, x = x_451_cast_fp16)[name = tensor<string, []>("op_3786_cast_fp16")];
            tensor<int32, [4]> var_3787 = const()[name = tensor<string, []>("op_3787"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_81_cast_fp16 = reshape(shape = var_3787, x = var_3786_cast_fp16)[name = tensor<string, []>("matrix_bd_81_cast_fp16")];
            tensor<bool, []> matrix_ac_41_transpose_x_0 = const()[name = tensor<string, []>("matrix_ac_41_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> matrix_ac_41_transpose_y_0 = const()[name = tensor<string, []>("matrix_ac_41_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<int32, [4]> transpose_136_perm_0 = const()[name = tensor<string, []>("transpose_136_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_137_perm_0 = const()[name = tensor<string, []>("transpose_137_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_137 = transpose(perm = transpose_137_perm_0, x = k_81_cast_fp16)[name = tensor<string, []>("transpose_240")];
            tensor<fp16, [1, 8, 188, 128]> transpose_136 = transpose(perm = transpose_136_perm_0, x = var_3770_cast_fp16)[name = tensor<string, []>("transpose_241")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_41_cast_fp16 = matmul(transpose_x = matrix_ac_41_transpose_x_0, transpose_y = matrix_ac_41_transpose_y_0, x = transpose_136, y = transpose_137)[name = tensor<string, []>("matrix_ac_41_cast_fp16")];
            tensor<int32, [4]> matrix_bd_83_begin_0 = const()[name = tensor<string, []>("matrix_bd_83_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_83_end_0 = const()[name = tensor<string, []>("matrix_bd_83_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_83_end_mask_0 = const()[name = tensor<string, []>("matrix_bd_83_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_83_cast_fp16 = slice_by_index(begin = matrix_bd_83_begin_0, end = matrix_bd_83_end_0, end_mask = matrix_bd_83_end_mask_0, x = matrix_bd_81_cast_fp16)[name = tensor<string, []>("matrix_bd_83_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_3796_cast_fp16 = add(x = matrix_ac_41_cast_fp16, y = matrix_bd_83_cast_fp16)[name = tensor<string, []>("op_3796_cast_fp16")];
            tensor<fp16, []> _inversed_scores_81_y_0_to_fp16 = const()[name = tensor<string, []>("_inversed_scores_81_y_0_to_fp16"), val = tensor<fp16, []>(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_81_cast_fp16 = mul(x = var_3796_cast_fp16, y = _inversed_scores_81_y_0_to_fp16)[name = tensor<string, []>("_inversed_scores_81_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_83_cast_fp16 = select(a = var_12_to_fp16, b = _inversed_scores_81_cast_fp16, cond = mask_3)[name = tensor<string, []>("scores_83_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_3802_cast_fp16 = softmax(axis = var_30, x = scores_83_cast_fp16)[name = tensor<string, []>("op_3802_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_1073_cast_fp16 = select(a = var_11_to_fp16, b = var_3802_cast_fp16, cond = mask_3)[name = tensor<string, []>("input_1073_cast_fp16")];
            tensor<bool, []> x_453_transpose_x_0 = const()[name = tensor<string, []>("x_453_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_453_transpose_y_0 = const()[name = tensor<string, []>("x_453_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 188, 128]> value_43_cast_fp16 = transpose(perm = value_43_perm_0, x = v_41_cast_fp16)[name = tensor<string, []>("transpose_243")];
            tensor<fp16, [1, 8, 188, 128]> x_453_cast_fp16 = matmul(transpose_x = x_453_transpose_x_0, transpose_y = x_453_transpose_y_0, x = input_1073_cast_fp16, y = value_43_cast_fp16)[name = tensor<string, []>("x_453_cast_fp16")];
            tensor<int32, [4]> var_3806_perm_0 = const()[name = tensor<string, []>("op_3806_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_3807 = const()[name = tensor<string, []>("op_3807"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_3806_cast_fp16 = transpose(perm = var_3806_perm_0, x = x_453_cast_fp16)[name = tensor<string, []>("transpose_239")];
            tensor<fp16, [1, 188, 1024]> input_1075_cast_fp16 = reshape(shape = var_3807, x = var_3806_cast_fp16)[name = tensor<string, []>("input_1075_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_20_self_attn_linear_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_20_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1014228608)))];
            tensor<fp16, [1024]> encoder_layers_20_self_attn_linear_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_20_self_attn_linear_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1016325824)))];
            tensor<fp16, [1, 188, 1024]> linear_187_cast_fp16 = linear(bias = encoder_layers_20_self_attn_linear_out_bias_to_fp16, weight = encoder_layers_20_self_attn_linear_out_weight_to_fp16, x = input_1075_cast_fp16)[name = tensor<string, []>("linear_187_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1079_cast_fp16 = add(x = input_1071_cast_fp16, y = linear_187_cast_fp16)[name = tensor<string, []>("input_1079_cast_fp16")];
            tensor<int32, [1]> x_457_axes_0 = const()[name = tensor<string, []>("x_457_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_20_norm_conv_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_20_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1016327936)))];
            tensor<fp16, [1024]> encoder_layers_20_norm_conv_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_20_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1016330048)))];
            tensor<fp16, [1, 188, 1024]> x_457_cast_fp16 = layer_norm(axes = x_457_axes_0, beta = encoder_layers_20_norm_conv_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_20_norm_conv_weight_to_fp16, x = input_1079_cast_fp16)[name = tensor<string, []>("x_457_cast_fp16")];
            tensor<int32, [3]> input_1081_perm_0 = const()[name = tensor<string, []>("input_1081_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> input_1083_pad_type_0 = const()[name = tensor<string, []>("input_1083_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_1083_strides_0 = const()[name = tensor<string, []>("input_1083_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1083_pad_0 = const()[name = tensor<string, []>("input_1083_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1083_dilations_0 = const()[name = tensor<string, []>("input_1083_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_1083_groups_0 = const()[name = tensor<string, []>("input_1083_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [2048, 1024, 1]> encoder_layers_20_conv_pointwise_conv1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_20_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1016332160)))];
            tensor<fp16, [2048]> encoder_layers_20_conv_pointwise_conv1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_20_conv_pointwise_conv1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1020526528)))];
            tensor<fp16, [1, 1024, 188]> input_1081_cast_fp16 = transpose(perm = input_1081_perm_0, x = x_457_cast_fp16)[name = tensor<string, []>("transpose_238")];
            tensor<fp16, [1, 2048, 188]> input_1083_cast_fp16 = conv(bias = encoder_layers_20_conv_pointwise_conv1_bias_to_fp16, dilations = input_1083_dilations_0, groups = input_1083_groups_0, pad = input_1083_pad_0, pad_type = input_1083_pad_type_0, strides = input_1083_strides_0, weight = encoder_layers_20_conv_pointwise_conv1_weight_to_fp16, x = input_1081_cast_fp16)[name = tensor<string, []>("input_1083_cast_fp16")];
            tensor<int32, []> x_459_split_num_splits_0 = const()[name = tensor<string, []>("x_459_split_num_splits_0"), val = tensor<int32, []>(2)];
            tensor<int32, []> x_459_split_axis_0 = const()[name = tensor<string, []>("x_459_split_axis_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1, 1024, 188]> x_459_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_459_split_cast_fp16_1 = split(axis = x_459_split_axis_0, num_splits = x_459_split_num_splits_0, x = input_1083_cast_fp16)[name = tensor<string, []>("x_459_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_459_split_1_sigmoid_cast_fp16 = sigmoid(x = x_459_split_cast_fp16_1)[name = tensor<string, []>("x_459_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_459_cast_fp16 = mul(x = x_459_split_cast_fp16_0, y = x_459_split_1_sigmoid_cast_fp16)[name = tensor<string, []>("x_459_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_1085_cast_fp16 = select(a = var_11_to_fp16, b = x_459_cast_fp16, cond = var_351)[name = tensor<string, []>("input_1085_cast_fp16")];
            tensor<int32, [6]> input_1087_pad_0 = const()[name = tensor<string, []>("input_1087_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            tensor<string, []> input_1087_mode_0 = const()[name = tensor<string, []>("input_1087_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_217_to_fp16 = const()[name = tensor<string, []>("const_217_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_1087_cast_fp16 = pad(constant_val = const_217_to_fp16, mode = input_1087_mode_0, pad = input_1087_pad_0, x = input_1085_cast_fp16)[name = tensor<string, []>("input_1087_cast_fp16")];
            tensor<string, []> input_1089_pad_type_0 = const()[name = tensor<string, []>("input_1089_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, []> input_1089_groups_0 = const()[name = tensor<string, []>("input_1089_groups_0"), val = tensor<int32, []>(1024)];
            tensor<int32, [1]> input_1089_strides_0 = const()[name = tensor<string, []>("input_1089_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1089_pad_0 = const()[name = tensor<string, []>("input_1089_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1089_dilations_0 = const()[name = tensor<string, []>("input_1089_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_368_to_fp16 = const()[name = tensor<string, []>("const_368_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1020530688)))];
            tensor<fp16, [1024]> const_369_to_fp16 = const()[name = tensor<string, []>("const_369_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1020549184)))];
            tensor<fp16, [1, 1024, 188]> input_1091_cast_fp16 = conv(bias = const_369_to_fp16, dilations = input_1089_dilations_0, groups = input_1089_groups_0, pad = input_1089_pad_0, pad_type = input_1089_pad_type_0, strides = input_1089_strides_0, weight = const_368_to_fp16, x = input_1087_cast_fp16)[name = tensor<string, []>("input_1091_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_1093_cast_fp16 = silu(x = input_1091_cast_fp16)[name = tensor<string, []>("input_1093_cast_fp16")];
            tensor<string, []> x_461_pad_type_0 = const()[name = tensor<string, []>("x_461_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> x_461_strides_0 = const()[name = tensor<string, []>("x_461_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_461_pad_0 = const()[name = tensor<string, []>("x_461_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_461_dilations_0 = const()[name = tensor<string, []>("x_461_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> x_461_groups_0 = const()[name = tensor<string, []>("x_461_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1024, 1024, 1]> encoder_layers_20_conv_pointwise_conv2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_20_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1020551296)))];
            tensor<fp16, [1024]> encoder_layers_20_conv_pointwise_conv2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_20_conv_pointwise_conv2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1022648512)))];
            tensor<fp16, [1, 1024, 188]> x_461_cast_fp16 = conv(bias = encoder_layers_20_conv_pointwise_conv2_bias_to_fp16, dilations = x_461_dilations_0, groups = x_461_groups_0, pad = x_461_pad_0, pad_type = x_461_pad_type_0, strides = x_461_strides_0, weight = encoder_layers_20_conv_pointwise_conv2_weight_to_fp16, x = input_1093_cast_fp16)[name = tensor<string, []>("x_461_cast_fp16")];
            tensor<int32, [3]> input_1095_perm_0 = const()[name = tensor<string, []>("input_1095_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_1095_cast_fp16 = transpose(perm = input_1095_perm_0, x = x_461_cast_fp16)[name = tensor<string, []>("transpose_237")];
            tensor<fp16, [1, 188, 1024]> input_1097_cast_fp16 = add(x = input_1079_cast_fp16, y = input_1095_cast_fp16)[name = tensor<string, []>("input_1097_cast_fp16")];
            tensor<int32, [1]> input_1099_axes_0 = const()[name = tensor<string, []>("input_1099_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_20_norm_feed_forward2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_20_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1022650624)))];
            tensor<fp16, [1024]> encoder_layers_20_norm_feed_forward2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_20_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1022652736)))];
            tensor<fp16, [1, 188, 1024]> input_1099_cast_fp16 = layer_norm(axes = input_1099_axes_0, beta = encoder_layers_20_norm_feed_forward2_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_20_norm_feed_forward2_weight_to_fp16, x = input_1097_cast_fp16)[name = tensor<string, []>("input_1099_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_20_feed_forward2_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_20_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1022654848)))];
            tensor<fp16, [4096]> encoder_layers_20_feed_forward2_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_20_feed_forward2_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1031043520)))];
            tensor<fp16, [1, 188, 4096]> linear_188_cast_fp16 = linear(bias = encoder_layers_20_feed_forward2_linear1_bias_to_fp16, weight = encoder_layers_20_feed_forward2_linear1_weight_to_fp16, x = input_1099_cast_fp16)[name = tensor<string, []>("linear_188_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_1103_cast_fp16 = silu(x = linear_188_cast_fp16)[name = tensor<string, []>("input_1103_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_20_feed_forward2_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_20_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1031051776)))];
            tensor<fp16, [1024]> encoder_layers_20_feed_forward2_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_20_feed_forward2_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1039440448)))];
            tensor<fp16, [1, 188, 1024]> linear_189_cast_fp16 = linear(bias = encoder_layers_20_feed_forward2_linear2_bias_to_fp16, weight = encoder_layers_20_feed_forward2_linear2_weight_to_fp16, x = input_1103_cast_fp16)[name = tensor<string, []>("linear_189_cast_fp16")];
            tensor<fp16, []> var_3873_to_fp16 = const()[name = tensor<string, []>("op_3873_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_3874_cast_fp16 = mul(x = linear_189_cast_fp16, y = var_3873_to_fp16)[name = tensor<string, []>("op_3874_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1109_cast_fp16 = add(x = input_1097_cast_fp16, y = var_3874_cast_fp16)[name = tensor<string, []>("input_1109_cast_fp16")];
            tensor<int32, [1]> input_1111_axes_0 = const()[name = tensor<string, []>("input_1111_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_20_norm_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_20_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1039442560)))];
            tensor<fp16, [1024]> encoder_layers_20_norm_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_20_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1039444672)))];
            tensor<fp16, [1, 188, 1024]> input_1111_cast_fp16 = layer_norm(axes = input_1111_axes_0, beta = encoder_layers_20_norm_out_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_20_norm_out_weight_to_fp16, x = input_1109_cast_fp16)[name = tensor<string, []>("input_1111_cast_fp16")];
            tensor<int32, [1]> input_1113_axes_0 = const()[name = tensor<string, []>("input_1113_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_21_norm_feed_forward1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_21_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1039446784)))];
            tensor<fp16, [1024]> encoder_layers_21_norm_feed_forward1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_21_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1039448896)))];
            tensor<fp16, [1, 188, 1024]> input_1113_cast_fp16 = layer_norm(axes = input_1113_axes_0, beta = encoder_layers_21_norm_feed_forward1_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_21_norm_feed_forward1_weight_to_fp16, x = input_1111_cast_fp16)[name = tensor<string, []>("input_1113_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_21_feed_forward1_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_21_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1039451008)))];
            tensor<fp16, [4096]> encoder_layers_21_feed_forward1_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_21_feed_forward1_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1047839680)))];
            tensor<fp16, [1, 188, 4096]> linear_190_cast_fp16 = linear(bias = encoder_layers_21_feed_forward1_linear1_bias_to_fp16, weight = encoder_layers_21_feed_forward1_linear1_weight_to_fp16, x = input_1113_cast_fp16)[name = tensor<string, []>("linear_190_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_1117_cast_fp16 = silu(x = linear_190_cast_fp16)[name = tensor<string, []>("input_1117_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_21_feed_forward1_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_21_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1047847936)))];
            tensor<fp16, [1024]> encoder_layers_21_feed_forward1_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_21_feed_forward1_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1056236608)))];
            tensor<fp16, [1, 188, 1024]> linear_191_cast_fp16 = linear(bias = encoder_layers_21_feed_forward1_linear2_bias_to_fp16, weight = encoder_layers_21_feed_forward1_linear2_weight_to_fp16, x = input_1117_cast_fp16)[name = tensor<string, []>("linear_191_cast_fp16")];
            tensor<fp16, []> var_3904_to_fp16 = const()[name = tensor<string, []>("op_3904_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_3905_cast_fp16 = mul(x = linear_191_cast_fp16, y = var_3904_to_fp16)[name = tensor<string, []>("op_3905_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1123_cast_fp16 = add(x = input_1111_cast_fp16, y = var_3905_cast_fp16)[name = tensor<string, []>("input_1123_cast_fp16")];
            tensor<int32, [1]> query_43_axes_0 = const()[name = tensor<string, []>("query_43_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_21_norm_self_att_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_21_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1056238720)))];
            tensor<fp16, [1024]> encoder_layers_21_norm_self_att_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_21_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1056240832)))];
            tensor<fp16, [1, 188, 1024]> query_43_cast_fp16 = layer_norm(axes = query_43_axes_0, beta = encoder_layers_21_norm_self_att_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_21_norm_self_att_weight_to_fp16, x = input_1123_cast_fp16)[name = tensor<string, []>("query_43_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_21_self_attn_linear_q_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_21_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1056242944)))];
            tensor<fp16, [1024]> encoder_layers_21_self_attn_linear_q_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_21_self_attn_linear_q_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1058340160)))];
            tensor<fp16, [1, 188, 1024]> linear_192_cast_fp16 = linear(bias = encoder_layers_21_self_attn_linear_q_bias_to_fp16, weight = encoder_layers_21_self_attn_linear_q_weight_to_fp16, x = query_43_cast_fp16)[name = tensor<string, []>("linear_192_cast_fp16")];
            tensor<int32, [4]> var_3922 = const()[name = tensor<string, []>("op_3922"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_127_cast_fp16 = reshape(shape = var_3922, x = linear_192_cast_fp16)[name = tensor<string, []>("q_127_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_21_self_attn_linear_k_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_21_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1058342272)))];
            tensor<fp16, [1024]> encoder_layers_21_self_attn_linear_k_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_21_self_attn_linear_k_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1060439488)))];
            tensor<fp16, [1, 188, 1024]> linear_193_cast_fp16 = linear(bias = encoder_layers_21_self_attn_linear_k_bias_to_fp16, weight = encoder_layers_21_self_attn_linear_k_weight_to_fp16, x = query_43_cast_fp16)[name = tensor<string, []>("linear_193_cast_fp16")];
            tensor<int32, [4]> var_3927 = const()[name = tensor<string, []>("op_3927"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_85_cast_fp16 = reshape(shape = var_3927, x = linear_193_cast_fp16)[name = tensor<string, []>("k_85_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_21_self_attn_linear_v_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_21_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1060441600)))];
            tensor<fp16, [1024]> encoder_layers_21_self_attn_linear_v_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_21_self_attn_linear_v_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1062538816)))];
            tensor<fp16, [1, 188, 1024]> linear_194_cast_fp16 = linear(bias = encoder_layers_21_self_attn_linear_v_bias_to_fp16, weight = encoder_layers_21_self_attn_linear_v_weight_to_fp16, x = query_43_cast_fp16)[name = tensor<string, []>("linear_194_cast_fp16")];
            tensor<int32, [4]> var_3932 = const()[name = tensor<string, []>("op_3932"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_43_cast_fp16 = reshape(shape = var_3932, x = linear_194_cast_fp16)[name = tensor<string, []>("v_43_cast_fp16")];
            tensor<int32, [4]> value_45_perm_0 = const()[name = tensor<string, []>("value_45_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> encoder_layers_21_self_attn_pos_bias_u_to_fp16 = const()[name = tensor<string, []>("encoder_layers_21_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1062540928)))];
            tensor<fp16, [1, 188, 8, 128]> var_3944_cast_fp16 = add(x = q_127_cast_fp16, y = encoder_layers_21_self_attn_pos_bias_u_to_fp16)[name = tensor<string, []>("op_3944_cast_fp16")];
            tensor<fp16, [8, 128]> encoder_layers_21_self_attn_pos_bias_v_to_fp16 = const()[name = tensor<string, []>("encoder_layers_21_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1062543040)))];
            tensor<fp16, [1, 188, 8, 128]> var_3946_cast_fp16 = add(x = q_127_cast_fp16, y = encoder_layers_21_self_attn_pos_bias_v_to_fp16)[name = tensor<string, []>("op_3946_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_43_perm_0 = const()[name = tensor<string, []>("q_with_bias_v_43_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<bool, []> x_469_transpose_x_0 = const()[name = tensor<string, []>("x_469_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_469_transpose_y_0 = const()[name = tensor<string, []>("x_469_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 128, 375]> var_3948_to_fp16 = const()[name = tensor<string, []>("op_3948_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1062545152)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_43_cast_fp16 = transpose(perm = q_with_bias_v_43_perm_0, x = var_3946_cast_fp16)[name = tensor<string, []>("transpose_235")];
            tensor<fp16, [1, 8, 188, 375]> x_469_cast_fp16 = matmul(transpose_x = x_469_transpose_x_0, transpose_y = x_469_transpose_y_0, x = q_with_bias_v_43_cast_fp16, y = var_3948_to_fp16)[name = tensor<string, []>("x_469_cast_fp16")];
            tensor<int32, [8]> x_471_pad_0 = const()[name = tensor<string, []>("x_471_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            tensor<string, []> x_471_mode_0 = const()[name = tensor<string, []>("x_471_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_224_to_fp16 = const()[name = tensor<string, []>("const_224_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_471_cast_fp16 = pad(constant_val = const_224_to_fp16, mode = x_471_mode_0, pad = x_471_pad_0, x = x_469_cast_fp16)[name = tensor<string, []>("x_471_cast_fp16")];
            tensor<int32, [4]> var_3956 = const()[name = tensor<string, []>("op_3956"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_473_cast_fp16 = reshape(shape = var_3956, x = x_471_cast_fp16)[name = tensor<string, []>("x_473_cast_fp16")];
            tensor<int32, [4]> var_3960_begin_0 = const()[name = tensor<string, []>("op_3960_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_3960_end_0 = const()[name = tensor<string, []>("op_3960_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_3960_end_mask_0 = const()[name = tensor<string, []>("op_3960_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_3960_cast_fp16 = slice_by_index(begin = var_3960_begin_0, end = var_3960_end_0, end_mask = var_3960_end_mask_0, x = x_473_cast_fp16)[name = tensor<string, []>("op_3960_cast_fp16")];
            tensor<int32, [4]> var_3961 = const()[name = tensor<string, []>("op_3961"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_85_cast_fp16 = reshape(shape = var_3961, x = var_3960_cast_fp16)[name = tensor<string, []>("matrix_bd_85_cast_fp16")];
            tensor<bool, []> matrix_ac_43_transpose_x_0 = const()[name = tensor<string, []>("matrix_ac_43_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> matrix_ac_43_transpose_y_0 = const()[name = tensor<string, []>("matrix_ac_43_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<int32, [4]> transpose_138_perm_0 = const()[name = tensor<string, []>("transpose_138_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_139_perm_0 = const()[name = tensor<string, []>("transpose_139_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_139 = transpose(perm = transpose_139_perm_0, x = k_85_cast_fp16)[name = tensor<string, []>("transpose_233")];
            tensor<fp16, [1, 8, 188, 128]> transpose_138 = transpose(perm = transpose_138_perm_0, x = var_3944_cast_fp16)[name = tensor<string, []>("transpose_234")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_43_cast_fp16 = matmul(transpose_x = matrix_ac_43_transpose_x_0, transpose_y = matrix_ac_43_transpose_y_0, x = transpose_138, y = transpose_139)[name = tensor<string, []>("matrix_ac_43_cast_fp16")];
            tensor<int32, [4]> matrix_bd_87_begin_0 = const()[name = tensor<string, []>("matrix_bd_87_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_87_end_0 = const()[name = tensor<string, []>("matrix_bd_87_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_87_end_mask_0 = const()[name = tensor<string, []>("matrix_bd_87_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_87_cast_fp16 = slice_by_index(begin = matrix_bd_87_begin_0, end = matrix_bd_87_end_0, end_mask = matrix_bd_87_end_mask_0, x = matrix_bd_85_cast_fp16)[name = tensor<string, []>("matrix_bd_87_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_3970_cast_fp16 = add(x = matrix_ac_43_cast_fp16, y = matrix_bd_87_cast_fp16)[name = tensor<string, []>("op_3970_cast_fp16")];
            tensor<fp16, []> _inversed_scores_85_y_0_to_fp16 = const()[name = tensor<string, []>("_inversed_scores_85_y_0_to_fp16"), val = tensor<fp16, []>(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_85_cast_fp16 = mul(x = var_3970_cast_fp16, y = _inversed_scores_85_y_0_to_fp16)[name = tensor<string, []>("_inversed_scores_85_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_87_cast_fp16 = select(a = var_12_to_fp16, b = _inversed_scores_85_cast_fp16, cond = mask_3)[name = tensor<string, []>("scores_87_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_3976_cast_fp16 = softmax(axis = var_30, x = scores_87_cast_fp16)[name = tensor<string, []>("op_3976_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_1125_cast_fp16 = select(a = var_11_to_fp16, b = var_3976_cast_fp16, cond = mask_3)[name = tensor<string, []>("input_1125_cast_fp16")];
            tensor<bool, []> x_475_transpose_x_0 = const()[name = tensor<string, []>("x_475_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_475_transpose_y_0 = const()[name = tensor<string, []>("x_475_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 188, 128]> value_45_cast_fp16 = transpose(perm = value_45_perm_0, x = v_43_cast_fp16)[name = tensor<string, []>("transpose_236")];
            tensor<fp16, [1, 8, 188, 128]> x_475_cast_fp16 = matmul(transpose_x = x_475_transpose_x_0, transpose_y = x_475_transpose_y_0, x = input_1125_cast_fp16, y = value_45_cast_fp16)[name = tensor<string, []>("x_475_cast_fp16")];
            tensor<int32, [4]> var_3980_perm_0 = const()[name = tensor<string, []>("op_3980_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_3981 = const()[name = tensor<string, []>("op_3981"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_3980_cast_fp16 = transpose(perm = var_3980_perm_0, x = x_475_cast_fp16)[name = tensor<string, []>("transpose_232")];
            tensor<fp16, [1, 188, 1024]> input_1127_cast_fp16 = reshape(shape = var_3981, x = var_3980_cast_fp16)[name = tensor<string, []>("input_1127_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_21_self_attn_linear_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_21_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1063313216)))];
            tensor<fp16, [1024]> encoder_layers_21_self_attn_linear_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_21_self_attn_linear_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1065410432)))];
            tensor<fp16, [1, 188, 1024]> linear_196_cast_fp16 = linear(bias = encoder_layers_21_self_attn_linear_out_bias_to_fp16, weight = encoder_layers_21_self_attn_linear_out_weight_to_fp16, x = input_1127_cast_fp16)[name = tensor<string, []>("linear_196_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1131_cast_fp16 = add(x = input_1123_cast_fp16, y = linear_196_cast_fp16)[name = tensor<string, []>("input_1131_cast_fp16")];
            tensor<int32, [1]> x_479_axes_0 = const()[name = tensor<string, []>("x_479_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_21_norm_conv_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_21_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1065412544)))];
            tensor<fp16, [1024]> encoder_layers_21_norm_conv_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_21_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1065414656)))];
            tensor<fp16, [1, 188, 1024]> x_479_cast_fp16 = layer_norm(axes = x_479_axes_0, beta = encoder_layers_21_norm_conv_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_21_norm_conv_weight_to_fp16, x = input_1131_cast_fp16)[name = tensor<string, []>("x_479_cast_fp16")];
            tensor<int32, [3]> input_1133_perm_0 = const()[name = tensor<string, []>("input_1133_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> input_1135_pad_type_0 = const()[name = tensor<string, []>("input_1135_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_1135_strides_0 = const()[name = tensor<string, []>("input_1135_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1135_pad_0 = const()[name = tensor<string, []>("input_1135_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1135_dilations_0 = const()[name = tensor<string, []>("input_1135_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_1135_groups_0 = const()[name = tensor<string, []>("input_1135_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [2048, 1024, 1]> encoder_layers_21_conv_pointwise_conv1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_21_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1065416768)))];
            tensor<fp16, [2048]> encoder_layers_21_conv_pointwise_conv1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_21_conv_pointwise_conv1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1069611136)))];
            tensor<fp16, [1, 1024, 188]> input_1133_cast_fp16 = transpose(perm = input_1133_perm_0, x = x_479_cast_fp16)[name = tensor<string, []>("transpose_231")];
            tensor<fp16, [1, 2048, 188]> input_1135_cast_fp16 = conv(bias = encoder_layers_21_conv_pointwise_conv1_bias_to_fp16, dilations = input_1135_dilations_0, groups = input_1135_groups_0, pad = input_1135_pad_0, pad_type = input_1135_pad_type_0, strides = input_1135_strides_0, weight = encoder_layers_21_conv_pointwise_conv1_weight_to_fp16, x = input_1133_cast_fp16)[name = tensor<string, []>("input_1135_cast_fp16")];
            tensor<int32, []> x_481_split_num_splits_0 = const()[name = tensor<string, []>("x_481_split_num_splits_0"), val = tensor<int32, []>(2)];
            tensor<int32, []> x_481_split_axis_0 = const()[name = tensor<string, []>("x_481_split_axis_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1, 1024, 188]> x_481_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_481_split_cast_fp16_1 = split(axis = x_481_split_axis_0, num_splits = x_481_split_num_splits_0, x = input_1135_cast_fp16)[name = tensor<string, []>("x_481_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_481_split_1_sigmoid_cast_fp16 = sigmoid(x = x_481_split_cast_fp16_1)[name = tensor<string, []>("x_481_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_481_cast_fp16 = mul(x = x_481_split_cast_fp16_0, y = x_481_split_1_sigmoid_cast_fp16)[name = tensor<string, []>("x_481_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_1137_cast_fp16 = select(a = var_11_to_fp16, b = x_481_cast_fp16, cond = var_351)[name = tensor<string, []>("input_1137_cast_fp16")];
            tensor<int32, [6]> input_1139_pad_0 = const()[name = tensor<string, []>("input_1139_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            tensor<string, []> input_1139_mode_0 = const()[name = tensor<string, []>("input_1139_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_227_to_fp16 = const()[name = tensor<string, []>("const_227_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_1139_cast_fp16 = pad(constant_val = const_227_to_fp16, mode = input_1139_mode_0, pad = input_1139_pad_0, x = input_1137_cast_fp16)[name = tensor<string, []>("input_1139_cast_fp16")];
            tensor<string, []> input_1141_pad_type_0 = const()[name = tensor<string, []>("input_1141_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, []> input_1141_groups_0 = const()[name = tensor<string, []>("input_1141_groups_0"), val = tensor<int32, []>(1024)];
            tensor<int32, [1]> input_1141_strides_0 = const()[name = tensor<string, []>("input_1141_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1141_pad_0 = const()[name = tensor<string, []>("input_1141_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1141_dilations_0 = const()[name = tensor<string, []>("input_1141_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_370_to_fp16 = const()[name = tensor<string, []>("const_370_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1069615296)))];
            tensor<fp16, [1024]> const_371_to_fp16 = const()[name = tensor<string, []>("const_371_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1069633792)))];
            tensor<fp16, [1, 1024, 188]> input_1143_cast_fp16 = conv(bias = const_371_to_fp16, dilations = input_1141_dilations_0, groups = input_1141_groups_0, pad = input_1141_pad_0, pad_type = input_1141_pad_type_0, strides = input_1141_strides_0, weight = const_370_to_fp16, x = input_1139_cast_fp16)[name = tensor<string, []>("input_1143_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_1145_cast_fp16 = silu(x = input_1143_cast_fp16)[name = tensor<string, []>("input_1145_cast_fp16")];
            tensor<string, []> x_483_pad_type_0 = const()[name = tensor<string, []>("x_483_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> x_483_strides_0 = const()[name = tensor<string, []>("x_483_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_483_pad_0 = const()[name = tensor<string, []>("x_483_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_483_dilations_0 = const()[name = tensor<string, []>("x_483_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> x_483_groups_0 = const()[name = tensor<string, []>("x_483_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1024, 1024, 1]> encoder_layers_21_conv_pointwise_conv2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_21_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1069635904)))];
            tensor<fp16, [1024]> encoder_layers_21_conv_pointwise_conv2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_21_conv_pointwise_conv2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1071733120)))];
            tensor<fp16, [1, 1024, 188]> x_483_cast_fp16 = conv(bias = encoder_layers_21_conv_pointwise_conv2_bias_to_fp16, dilations = x_483_dilations_0, groups = x_483_groups_0, pad = x_483_pad_0, pad_type = x_483_pad_type_0, strides = x_483_strides_0, weight = encoder_layers_21_conv_pointwise_conv2_weight_to_fp16, x = input_1145_cast_fp16)[name = tensor<string, []>("x_483_cast_fp16")];
            tensor<int32, [3]> input_1147_perm_0 = const()[name = tensor<string, []>("input_1147_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_1147_cast_fp16 = transpose(perm = input_1147_perm_0, x = x_483_cast_fp16)[name = tensor<string, []>("transpose_230")];
            tensor<fp16, [1, 188, 1024]> input_1149_cast_fp16 = add(x = input_1131_cast_fp16, y = input_1147_cast_fp16)[name = tensor<string, []>("input_1149_cast_fp16")];
            tensor<int32, [1]> input_1151_axes_0 = const()[name = tensor<string, []>("input_1151_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_21_norm_feed_forward2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_21_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1071735232)))];
            tensor<fp16, [1024]> encoder_layers_21_norm_feed_forward2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_21_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1071737344)))];
            tensor<fp16, [1, 188, 1024]> input_1151_cast_fp16 = layer_norm(axes = input_1151_axes_0, beta = encoder_layers_21_norm_feed_forward2_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_21_norm_feed_forward2_weight_to_fp16, x = input_1149_cast_fp16)[name = tensor<string, []>("input_1151_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_21_feed_forward2_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_21_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1071739456)))];
            tensor<fp16, [4096]> encoder_layers_21_feed_forward2_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_21_feed_forward2_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1080128128)))];
            tensor<fp16, [1, 188, 4096]> linear_197_cast_fp16 = linear(bias = encoder_layers_21_feed_forward2_linear1_bias_to_fp16, weight = encoder_layers_21_feed_forward2_linear1_weight_to_fp16, x = input_1151_cast_fp16)[name = tensor<string, []>("linear_197_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_1155_cast_fp16 = silu(x = linear_197_cast_fp16)[name = tensor<string, []>("input_1155_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_21_feed_forward2_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_21_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1080136384)))];
            tensor<fp16, [1024]> encoder_layers_21_feed_forward2_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_21_feed_forward2_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1088525056)))];
            tensor<fp16, [1, 188, 1024]> linear_198_cast_fp16 = linear(bias = encoder_layers_21_feed_forward2_linear2_bias_to_fp16, weight = encoder_layers_21_feed_forward2_linear2_weight_to_fp16, x = input_1155_cast_fp16)[name = tensor<string, []>("linear_198_cast_fp16")];
            tensor<fp16, []> var_4047_to_fp16 = const()[name = tensor<string, []>("op_4047_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_4048_cast_fp16 = mul(x = linear_198_cast_fp16, y = var_4047_to_fp16)[name = tensor<string, []>("op_4048_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1161_cast_fp16 = add(x = input_1149_cast_fp16, y = var_4048_cast_fp16)[name = tensor<string, []>("input_1161_cast_fp16")];
            tensor<int32, [1]> input_1163_axes_0 = const()[name = tensor<string, []>("input_1163_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_21_norm_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_21_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1088527168)))];
            tensor<fp16, [1024]> encoder_layers_21_norm_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_21_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1088529280)))];
            tensor<fp16, [1, 188, 1024]> input_1163_cast_fp16 = layer_norm(axes = input_1163_axes_0, beta = encoder_layers_21_norm_out_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_21_norm_out_weight_to_fp16, x = input_1161_cast_fp16)[name = tensor<string, []>("input_1163_cast_fp16")];
            tensor<int32, [1]> input_1165_axes_0 = const()[name = tensor<string, []>("input_1165_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_22_norm_feed_forward1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_22_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1088531392)))];
            tensor<fp16, [1024]> encoder_layers_22_norm_feed_forward1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_22_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1088533504)))];
            tensor<fp16, [1, 188, 1024]> input_1165_cast_fp16 = layer_norm(axes = input_1165_axes_0, beta = encoder_layers_22_norm_feed_forward1_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_22_norm_feed_forward1_weight_to_fp16, x = input_1163_cast_fp16)[name = tensor<string, []>("input_1165_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_22_feed_forward1_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_22_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1088535616)))];
            tensor<fp16, [4096]> encoder_layers_22_feed_forward1_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_22_feed_forward1_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1096924288)))];
            tensor<fp16, [1, 188, 4096]> linear_199_cast_fp16 = linear(bias = encoder_layers_22_feed_forward1_linear1_bias_to_fp16, weight = encoder_layers_22_feed_forward1_linear1_weight_to_fp16, x = input_1165_cast_fp16)[name = tensor<string, []>("linear_199_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_1169_cast_fp16 = silu(x = linear_199_cast_fp16)[name = tensor<string, []>("input_1169_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_22_feed_forward1_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_22_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1096932544)))];
            tensor<fp16, [1024]> encoder_layers_22_feed_forward1_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_22_feed_forward1_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1105321216)))];
            tensor<fp16, [1, 188, 1024]> linear_200_cast_fp16 = linear(bias = encoder_layers_22_feed_forward1_linear2_bias_to_fp16, weight = encoder_layers_22_feed_forward1_linear2_weight_to_fp16, x = input_1169_cast_fp16)[name = tensor<string, []>("linear_200_cast_fp16")];
            tensor<fp16, []> var_4078_to_fp16 = const()[name = tensor<string, []>("op_4078_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_4079_cast_fp16 = mul(x = linear_200_cast_fp16, y = var_4078_to_fp16)[name = tensor<string, []>("op_4079_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1175_cast_fp16 = add(x = input_1163_cast_fp16, y = var_4079_cast_fp16)[name = tensor<string, []>("input_1175_cast_fp16")];
            tensor<int32, [1]> query_45_axes_0 = const()[name = tensor<string, []>("query_45_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_22_norm_self_att_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_22_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1105323328)))];
            tensor<fp16, [1024]> encoder_layers_22_norm_self_att_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_22_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1105325440)))];
            tensor<fp16, [1, 188, 1024]> query_45_cast_fp16 = layer_norm(axes = query_45_axes_0, beta = encoder_layers_22_norm_self_att_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_22_norm_self_att_weight_to_fp16, x = input_1175_cast_fp16)[name = tensor<string, []>("query_45_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_22_self_attn_linear_q_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_22_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1105327552)))];
            tensor<fp16, [1024]> encoder_layers_22_self_attn_linear_q_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_22_self_attn_linear_q_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1107424768)))];
            tensor<fp16, [1, 188, 1024]> linear_201_cast_fp16 = linear(bias = encoder_layers_22_self_attn_linear_q_bias_to_fp16, weight = encoder_layers_22_self_attn_linear_q_weight_to_fp16, x = query_45_cast_fp16)[name = tensor<string, []>("linear_201_cast_fp16")];
            tensor<int32, [4]> var_4096 = const()[name = tensor<string, []>("op_4096"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_133_cast_fp16 = reshape(shape = var_4096, x = linear_201_cast_fp16)[name = tensor<string, []>("q_133_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_22_self_attn_linear_k_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_22_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1107426880)))];
            tensor<fp16, [1024]> encoder_layers_22_self_attn_linear_k_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_22_self_attn_linear_k_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1109524096)))];
            tensor<fp16, [1, 188, 1024]> linear_202_cast_fp16 = linear(bias = encoder_layers_22_self_attn_linear_k_bias_to_fp16, weight = encoder_layers_22_self_attn_linear_k_weight_to_fp16, x = query_45_cast_fp16)[name = tensor<string, []>("linear_202_cast_fp16")];
            tensor<int32, [4]> var_4101 = const()[name = tensor<string, []>("op_4101"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_89_cast_fp16 = reshape(shape = var_4101, x = linear_202_cast_fp16)[name = tensor<string, []>("k_89_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_22_self_attn_linear_v_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_22_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1109526208)))];
            tensor<fp16, [1024]> encoder_layers_22_self_attn_linear_v_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_22_self_attn_linear_v_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1111623424)))];
            tensor<fp16, [1, 188, 1024]> linear_203_cast_fp16 = linear(bias = encoder_layers_22_self_attn_linear_v_bias_to_fp16, weight = encoder_layers_22_self_attn_linear_v_weight_to_fp16, x = query_45_cast_fp16)[name = tensor<string, []>("linear_203_cast_fp16")];
            tensor<int32, [4]> var_4106 = const()[name = tensor<string, []>("op_4106"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_45_cast_fp16 = reshape(shape = var_4106, x = linear_203_cast_fp16)[name = tensor<string, []>("v_45_cast_fp16")];
            tensor<int32, [4]> value_47_perm_0 = const()[name = tensor<string, []>("value_47_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> encoder_layers_22_self_attn_pos_bias_u_to_fp16 = const()[name = tensor<string, []>("encoder_layers_22_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1111625536)))];
            tensor<fp16, [1, 188, 8, 128]> var_4118_cast_fp16 = add(x = q_133_cast_fp16, y = encoder_layers_22_self_attn_pos_bias_u_to_fp16)[name = tensor<string, []>("op_4118_cast_fp16")];
            tensor<fp16, [8, 128]> encoder_layers_22_self_attn_pos_bias_v_to_fp16 = const()[name = tensor<string, []>("encoder_layers_22_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1111627648)))];
            tensor<fp16, [1, 188, 8, 128]> var_4120_cast_fp16 = add(x = q_133_cast_fp16, y = encoder_layers_22_self_attn_pos_bias_v_to_fp16)[name = tensor<string, []>("op_4120_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_45_perm_0 = const()[name = tensor<string, []>("q_with_bias_v_45_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<bool, []> x_491_transpose_x_0 = const()[name = tensor<string, []>("x_491_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_491_transpose_y_0 = const()[name = tensor<string, []>("x_491_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 128, 375]> var_4122_to_fp16 = const()[name = tensor<string, []>("op_4122_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1111629760)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_45_cast_fp16 = transpose(perm = q_with_bias_v_45_perm_0, x = var_4120_cast_fp16)[name = tensor<string, []>("transpose_228")];
            tensor<fp16, [1, 8, 188, 375]> x_491_cast_fp16 = matmul(transpose_x = x_491_transpose_x_0, transpose_y = x_491_transpose_y_0, x = q_with_bias_v_45_cast_fp16, y = var_4122_to_fp16)[name = tensor<string, []>("x_491_cast_fp16")];
            tensor<int32, [8]> x_493_pad_0 = const()[name = tensor<string, []>("x_493_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            tensor<string, []> x_493_mode_0 = const()[name = tensor<string, []>("x_493_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_234_to_fp16 = const()[name = tensor<string, []>("const_234_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_493_cast_fp16 = pad(constant_val = const_234_to_fp16, mode = x_493_mode_0, pad = x_493_pad_0, x = x_491_cast_fp16)[name = tensor<string, []>("x_493_cast_fp16")];
            tensor<int32, [4]> var_4130 = const()[name = tensor<string, []>("op_4130"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_495_cast_fp16 = reshape(shape = var_4130, x = x_493_cast_fp16)[name = tensor<string, []>("x_495_cast_fp16")];
            tensor<int32, [4]> var_4134_begin_0 = const()[name = tensor<string, []>("op_4134_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_4134_end_0 = const()[name = tensor<string, []>("op_4134_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_4134_end_mask_0 = const()[name = tensor<string, []>("op_4134_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_4134_cast_fp16 = slice_by_index(begin = var_4134_begin_0, end = var_4134_end_0, end_mask = var_4134_end_mask_0, x = x_495_cast_fp16)[name = tensor<string, []>("op_4134_cast_fp16")];
            tensor<int32, [4]> var_4135 = const()[name = tensor<string, []>("op_4135"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_89_cast_fp16 = reshape(shape = var_4135, x = var_4134_cast_fp16)[name = tensor<string, []>("matrix_bd_89_cast_fp16")];
            tensor<bool, []> matrix_ac_45_transpose_x_0 = const()[name = tensor<string, []>("matrix_ac_45_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> matrix_ac_45_transpose_y_0 = const()[name = tensor<string, []>("matrix_ac_45_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<int32, [4]> transpose_140_perm_0 = const()[name = tensor<string, []>("transpose_140_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_141_perm_0 = const()[name = tensor<string, []>("transpose_141_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_141 = transpose(perm = transpose_141_perm_0, x = k_89_cast_fp16)[name = tensor<string, []>("transpose_226")];
            tensor<fp16, [1, 8, 188, 128]> transpose_140 = transpose(perm = transpose_140_perm_0, x = var_4118_cast_fp16)[name = tensor<string, []>("transpose_227")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_45_cast_fp16 = matmul(transpose_x = matrix_ac_45_transpose_x_0, transpose_y = matrix_ac_45_transpose_y_0, x = transpose_140, y = transpose_141)[name = tensor<string, []>("matrix_ac_45_cast_fp16")];
            tensor<int32, [4]> matrix_bd_91_begin_0 = const()[name = tensor<string, []>("matrix_bd_91_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_91_end_0 = const()[name = tensor<string, []>("matrix_bd_91_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_91_end_mask_0 = const()[name = tensor<string, []>("matrix_bd_91_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_91_cast_fp16 = slice_by_index(begin = matrix_bd_91_begin_0, end = matrix_bd_91_end_0, end_mask = matrix_bd_91_end_mask_0, x = matrix_bd_89_cast_fp16)[name = tensor<string, []>("matrix_bd_91_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_4144_cast_fp16 = add(x = matrix_ac_45_cast_fp16, y = matrix_bd_91_cast_fp16)[name = tensor<string, []>("op_4144_cast_fp16")];
            tensor<fp16, []> _inversed_scores_89_y_0_to_fp16 = const()[name = tensor<string, []>("_inversed_scores_89_y_0_to_fp16"), val = tensor<fp16, []>(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_89_cast_fp16 = mul(x = var_4144_cast_fp16, y = _inversed_scores_89_y_0_to_fp16)[name = tensor<string, []>("_inversed_scores_89_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_91_cast_fp16 = select(a = var_12_to_fp16, b = _inversed_scores_89_cast_fp16, cond = mask_3)[name = tensor<string, []>("scores_91_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_4150_cast_fp16 = softmax(axis = var_30, x = scores_91_cast_fp16)[name = tensor<string, []>("op_4150_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_1177_cast_fp16 = select(a = var_11_to_fp16, b = var_4150_cast_fp16, cond = mask_3)[name = tensor<string, []>("input_1177_cast_fp16")];
            tensor<bool, []> x_497_transpose_x_0 = const()[name = tensor<string, []>("x_497_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_497_transpose_y_0 = const()[name = tensor<string, []>("x_497_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 188, 128]> value_47_cast_fp16 = transpose(perm = value_47_perm_0, x = v_45_cast_fp16)[name = tensor<string, []>("transpose_229")];
            tensor<fp16, [1, 8, 188, 128]> x_497_cast_fp16 = matmul(transpose_x = x_497_transpose_x_0, transpose_y = x_497_transpose_y_0, x = input_1177_cast_fp16, y = value_47_cast_fp16)[name = tensor<string, []>("x_497_cast_fp16")];
            tensor<int32, [4]> var_4154_perm_0 = const()[name = tensor<string, []>("op_4154_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_4155 = const()[name = tensor<string, []>("op_4155"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_4154_cast_fp16 = transpose(perm = var_4154_perm_0, x = x_497_cast_fp16)[name = tensor<string, []>("transpose_225")];
            tensor<fp16, [1, 188, 1024]> input_1179_cast_fp16 = reshape(shape = var_4155, x = var_4154_cast_fp16)[name = tensor<string, []>("input_1179_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_22_self_attn_linear_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_22_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1112397824)))];
            tensor<fp16, [1024]> encoder_layers_22_self_attn_linear_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_22_self_attn_linear_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1114495040)))];
            tensor<fp16, [1, 188, 1024]> linear_205_cast_fp16 = linear(bias = encoder_layers_22_self_attn_linear_out_bias_to_fp16, weight = encoder_layers_22_self_attn_linear_out_weight_to_fp16, x = input_1179_cast_fp16)[name = tensor<string, []>("linear_205_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1183_cast_fp16 = add(x = input_1175_cast_fp16, y = linear_205_cast_fp16)[name = tensor<string, []>("input_1183_cast_fp16")];
            tensor<int32, [1]> x_501_axes_0 = const()[name = tensor<string, []>("x_501_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_22_norm_conv_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_22_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1114497152)))];
            tensor<fp16, [1024]> encoder_layers_22_norm_conv_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_22_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1114499264)))];
            tensor<fp16, [1, 188, 1024]> x_501_cast_fp16 = layer_norm(axes = x_501_axes_0, beta = encoder_layers_22_norm_conv_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_22_norm_conv_weight_to_fp16, x = input_1183_cast_fp16)[name = tensor<string, []>("x_501_cast_fp16")];
            tensor<int32, [3]> input_1185_perm_0 = const()[name = tensor<string, []>("input_1185_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> input_1187_pad_type_0 = const()[name = tensor<string, []>("input_1187_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_1187_strides_0 = const()[name = tensor<string, []>("input_1187_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1187_pad_0 = const()[name = tensor<string, []>("input_1187_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1187_dilations_0 = const()[name = tensor<string, []>("input_1187_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_1187_groups_0 = const()[name = tensor<string, []>("input_1187_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [2048, 1024, 1]> encoder_layers_22_conv_pointwise_conv1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_22_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1114501376)))];
            tensor<fp16, [2048]> encoder_layers_22_conv_pointwise_conv1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_22_conv_pointwise_conv1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1118695744)))];
            tensor<fp16, [1, 1024, 188]> input_1185_cast_fp16 = transpose(perm = input_1185_perm_0, x = x_501_cast_fp16)[name = tensor<string, []>("transpose_224")];
            tensor<fp16, [1, 2048, 188]> input_1187_cast_fp16 = conv(bias = encoder_layers_22_conv_pointwise_conv1_bias_to_fp16, dilations = input_1187_dilations_0, groups = input_1187_groups_0, pad = input_1187_pad_0, pad_type = input_1187_pad_type_0, strides = input_1187_strides_0, weight = encoder_layers_22_conv_pointwise_conv1_weight_to_fp16, x = input_1185_cast_fp16)[name = tensor<string, []>("input_1187_cast_fp16")];
            tensor<int32, []> x_503_split_num_splits_0 = const()[name = tensor<string, []>("x_503_split_num_splits_0"), val = tensor<int32, []>(2)];
            tensor<int32, []> x_503_split_axis_0 = const()[name = tensor<string, []>("x_503_split_axis_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1, 1024, 188]> x_503_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_503_split_cast_fp16_1 = split(axis = x_503_split_axis_0, num_splits = x_503_split_num_splits_0, x = input_1187_cast_fp16)[name = tensor<string, []>("x_503_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_503_split_1_sigmoid_cast_fp16 = sigmoid(x = x_503_split_cast_fp16_1)[name = tensor<string, []>("x_503_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_503_cast_fp16 = mul(x = x_503_split_cast_fp16_0, y = x_503_split_1_sigmoid_cast_fp16)[name = tensor<string, []>("x_503_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_1189_cast_fp16 = select(a = var_11_to_fp16, b = x_503_cast_fp16, cond = var_351)[name = tensor<string, []>("input_1189_cast_fp16")];
            tensor<int32, [6]> input_1191_pad_0 = const()[name = tensor<string, []>("input_1191_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            tensor<string, []> input_1191_mode_0 = const()[name = tensor<string, []>("input_1191_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_237_to_fp16 = const()[name = tensor<string, []>("const_237_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_1191_cast_fp16 = pad(constant_val = const_237_to_fp16, mode = input_1191_mode_0, pad = input_1191_pad_0, x = input_1189_cast_fp16)[name = tensor<string, []>("input_1191_cast_fp16")];
            tensor<string, []> input_1193_pad_type_0 = const()[name = tensor<string, []>("input_1193_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, []> input_1193_groups_0 = const()[name = tensor<string, []>("input_1193_groups_0"), val = tensor<int32, []>(1024)];
            tensor<int32, [1]> input_1193_strides_0 = const()[name = tensor<string, []>("input_1193_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1193_pad_0 = const()[name = tensor<string, []>("input_1193_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1193_dilations_0 = const()[name = tensor<string, []>("input_1193_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_372_to_fp16 = const()[name = tensor<string, []>("const_372_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1118699904)))];
            tensor<fp16, [1024]> const_373_to_fp16 = const()[name = tensor<string, []>("const_373_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1118718400)))];
            tensor<fp16, [1, 1024, 188]> input_1195_cast_fp16 = conv(bias = const_373_to_fp16, dilations = input_1193_dilations_0, groups = input_1193_groups_0, pad = input_1193_pad_0, pad_type = input_1193_pad_type_0, strides = input_1193_strides_0, weight = const_372_to_fp16, x = input_1191_cast_fp16)[name = tensor<string, []>("input_1195_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_1197_cast_fp16 = silu(x = input_1195_cast_fp16)[name = tensor<string, []>("input_1197_cast_fp16")];
            tensor<string, []> x_505_pad_type_0 = const()[name = tensor<string, []>("x_505_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> x_505_strides_0 = const()[name = tensor<string, []>("x_505_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_505_pad_0 = const()[name = tensor<string, []>("x_505_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_505_dilations_0 = const()[name = tensor<string, []>("x_505_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> x_505_groups_0 = const()[name = tensor<string, []>("x_505_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1024, 1024, 1]> encoder_layers_22_conv_pointwise_conv2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_22_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1118720512)))];
            tensor<fp16, [1024]> encoder_layers_22_conv_pointwise_conv2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_22_conv_pointwise_conv2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1120817728)))];
            tensor<fp16, [1, 1024, 188]> x_505_cast_fp16 = conv(bias = encoder_layers_22_conv_pointwise_conv2_bias_to_fp16, dilations = x_505_dilations_0, groups = x_505_groups_0, pad = x_505_pad_0, pad_type = x_505_pad_type_0, strides = x_505_strides_0, weight = encoder_layers_22_conv_pointwise_conv2_weight_to_fp16, x = input_1197_cast_fp16)[name = tensor<string, []>("x_505_cast_fp16")];
            tensor<int32, [3]> input_1199_perm_0 = const()[name = tensor<string, []>("input_1199_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_1199_cast_fp16 = transpose(perm = input_1199_perm_0, x = x_505_cast_fp16)[name = tensor<string, []>("transpose_223")];
            tensor<fp16, [1, 188, 1024]> input_1201_cast_fp16 = add(x = input_1183_cast_fp16, y = input_1199_cast_fp16)[name = tensor<string, []>("input_1201_cast_fp16")];
            tensor<int32, [1]> input_1203_axes_0 = const()[name = tensor<string, []>("input_1203_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_22_norm_feed_forward2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_22_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1120819840)))];
            tensor<fp16, [1024]> encoder_layers_22_norm_feed_forward2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_22_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1120821952)))];
            tensor<fp16, [1, 188, 1024]> input_1203_cast_fp16 = layer_norm(axes = input_1203_axes_0, beta = encoder_layers_22_norm_feed_forward2_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_22_norm_feed_forward2_weight_to_fp16, x = input_1201_cast_fp16)[name = tensor<string, []>("input_1203_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_22_feed_forward2_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_22_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1120824064)))];
            tensor<fp16, [4096]> encoder_layers_22_feed_forward2_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_22_feed_forward2_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1129212736)))];
            tensor<fp16, [1, 188, 4096]> linear_206_cast_fp16 = linear(bias = encoder_layers_22_feed_forward2_linear1_bias_to_fp16, weight = encoder_layers_22_feed_forward2_linear1_weight_to_fp16, x = input_1203_cast_fp16)[name = tensor<string, []>("linear_206_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_1207_cast_fp16 = silu(x = linear_206_cast_fp16)[name = tensor<string, []>("input_1207_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_22_feed_forward2_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_22_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1129220992)))];
            tensor<fp16, [1024]> encoder_layers_22_feed_forward2_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_22_feed_forward2_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1137609664)))];
            tensor<fp16, [1, 188, 1024]> linear_207_cast_fp16 = linear(bias = encoder_layers_22_feed_forward2_linear2_bias_to_fp16, weight = encoder_layers_22_feed_forward2_linear2_weight_to_fp16, x = input_1207_cast_fp16)[name = tensor<string, []>("linear_207_cast_fp16")];
            tensor<fp16, []> var_4221_to_fp16 = const()[name = tensor<string, []>("op_4221_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_4222_cast_fp16 = mul(x = linear_207_cast_fp16, y = var_4221_to_fp16)[name = tensor<string, []>("op_4222_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1213_cast_fp16 = add(x = input_1201_cast_fp16, y = var_4222_cast_fp16)[name = tensor<string, []>("input_1213_cast_fp16")];
            tensor<int32, [1]> input_1215_axes_0 = const()[name = tensor<string, []>("input_1215_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_22_norm_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_22_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1137611776)))];
            tensor<fp16, [1024]> encoder_layers_22_norm_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_22_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1137613888)))];
            tensor<fp16, [1, 188, 1024]> input_1215_cast_fp16 = layer_norm(axes = input_1215_axes_0, beta = encoder_layers_22_norm_out_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_22_norm_out_weight_to_fp16, x = input_1213_cast_fp16)[name = tensor<string, []>("input_1215_cast_fp16")];
            tensor<int32, [1]> input_1217_axes_0 = const()[name = tensor<string, []>("input_1217_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_23_norm_feed_forward1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_23_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1137616000)))];
            tensor<fp16, [1024]> encoder_layers_23_norm_feed_forward1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_23_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1137618112)))];
            tensor<fp16, [1, 188, 1024]> input_1217_cast_fp16 = layer_norm(axes = input_1217_axes_0, beta = encoder_layers_23_norm_feed_forward1_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_23_norm_feed_forward1_weight_to_fp16, x = input_1215_cast_fp16)[name = tensor<string, []>("input_1217_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_23_feed_forward1_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_23_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1137620224)))];
            tensor<fp16, [4096]> encoder_layers_23_feed_forward1_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_23_feed_forward1_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1146008896)))];
            tensor<fp16, [1, 188, 4096]> linear_208_cast_fp16 = linear(bias = encoder_layers_23_feed_forward1_linear1_bias_to_fp16, weight = encoder_layers_23_feed_forward1_linear1_weight_to_fp16, x = input_1217_cast_fp16)[name = tensor<string, []>("linear_208_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_1221_cast_fp16 = silu(x = linear_208_cast_fp16)[name = tensor<string, []>("input_1221_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_23_feed_forward1_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_23_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1146017152)))];
            tensor<fp16, [1024]> encoder_layers_23_feed_forward1_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_23_feed_forward1_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1154405824)))];
            tensor<fp16, [1, 188, 1024]> linear_209_cast_fp16 = linear(bias = encoder_layers_23_feed_forward1_linear2_bias_to_fp16, weight = encoder_layers_23_feed_forward1_linear2_weight_to_fp16, x = input_1221_cast_fp16)[name = tensor<string, []>("linear_209_cast_fp16")];
            tensor<fp16, []> var_4252_to_fp16 = const()[name = tensor<string, []>("op_4252_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_4253_cast_fp16 = mul(x = linear_209_cast_fp16, y = var_4252_to_fp16)[name = tensor<string, []>("op_4253_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1227_cast_fp16 = add(x = input_1215_cast_fp16, y = var_4253_cast_fp16)[name = tensor<string, []>("input_1227_cast_fp16")];
            tensor<int32, [1]> query_47_axes_0 = const()[name = tensor<string, []>("query_47_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_23_norm_self_att_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_23_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1154407936)))];
            tensor<fp16, [1024]> encoder_layers_23_norm_self_att_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_23_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1154410048)))];
            tensor<fp16, [1, 188, 1024]> query_47_cast_fp16 = layer_norm(axes = query_47_axes_0, beta = encoder_layers_23_norm_self_att_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_23_norm_self_att_weight_to_fp16, x = input_1227_cast_fp16)[name = tensor<string, []>("query_47_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_23_self_attn_linear_q_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_23_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1154412160)))];
            tensor<fp16, [1024]> encoder_layers_23_self_attn_linear_q_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_23_self_attn_linear_q_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1156509376)))];
            tensor<fp16, [1, 188, 1024]> linear_210_cast_fp16 = linear(bias = encoder_layers_23_self_attn_linear_q_bias_to_fp16, weight = encoder_layers_23_self_attn_linear_q_weight_to_fp16, x = query_47_cast_fp16)[name = tensor<string, []>("linear_210_cast_fp16")];
            tensor<int32, [4]> var_4270 = const()[name = tensor<string, []>("op_4270"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_139_cast_fp16 = reshape(shape = var_4270, x = linear_210_cast_fp16)[name = tensor<string, []>("q_139_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_23_self_attn_linear_k_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_23_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1156511488)))];
            tensor<fp16, [1024]> encoder_layers_23_self_attn_linear_k_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_23_self_attn_linear_k_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1158608704)))];
            tensor<fp16, [1, 188, 1024]> linear_211_cast_fp16 = linear(bias = encoder_layers_23_self_attn_linear_k_bias_to_fp16, weight = encoder_layers_23_self_attn_linear_k_weight_to_fp16, x = query_47_cast_fp16)[name = tensor<string, []>("linear_211_cast_fp16")];
            tensor<int32, [4]> var_4275 = const()[name = tensor<string, []>("op_4275"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_93_cast_fp16 = reshape(shape = var_4275, x = linear_211_cast_fp16)[name = tensor<string, []>("k_93_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_23_self_attn_linear_v_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_23_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1158610816)))];
            tensor<fp16, [1024]> encoder_layers_23_self_attn_linear_v_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_23_self_attn_linear_v_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1160708032)))];
            tensor<fp16, [1, 188, 1024]> linear_212_cast_fp16 = linear(bias = encoder_layers_23_self_attn_linear_v_bias_to_fp16, weight = encoder_layers_23_self_attn_linear_v_weight_to_fp16, x = query_47_cast_fp16)[name = tensor<string, []>("linear_212_cast_fp16")];
            tensor<int32, [4]> var_4280 = const()[name = tensor<string, []>("op_4280"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_47_cast_fp16 = reshape(shape = var_4280, x = linear_212_cast_fp16)[name = tensor<string, []>("v_47_cast_fp16")];
            tensor<int32, [4]> value_49_perm_0 = const()[name = tensor<string, []>("value_49_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> encoder_layers_23_self_attn_pos_bias_u_to_fp16 = const()[name = tensor<string, []>("encoder_layers_23_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1160710144)))];
            tensor<fp16, [1, 188, 8, 128]> var_4292_cast_fp16 = add(x = q_139_cast_fp16, y = encoder_layers_23_self_attn_pos_bias_u_to_fp16)[name = tensor<string, []>("op_4292_cast_fp16")];
            tensor<fp16, [8, 128]> encoder_layers_23_self_attn_pos_bias_v_to_fp16 = const()[name = tensor<string, []>("encoder_layers_23_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1160712256)))];
            tensor<fp16, [1, 188, 8, 128]> var_4294_cast_fp16 = add(x = q_139_cast_fp16, y = encoder_layers_23_self_attn_pos_bias_v_to_fp16)[name = tensor<string, []>("op_4294_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_47_perm_0 = const()[name = tensor<string, []>("q_with_bias_v_47_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<bool, []> x_513_transpose_x_0 = const()[name = tensor<string, []>("x_513_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_513_transpose_y_0 = const()[name = tensor<string, []>("x_513_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 128, 375]> var_4296_to_fp16 = const()[name = tensor<string, []>("op_4296_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1160714368)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_47_cast_fp16 = transpose(perm = q_with_bias_v_47_perm_0, x = var_4294_cast_fp16)[name = tensor<string, []>("transpose_221")];
            tensor<fp16, [1, 8, 188, 375]> x_513_cast_fp16 = matmul(transpose_x = x_513_transpose_x_0, transpose_y = x_513_transpose_y_0, x = q_with_bias_v_47_cast_fp16, y = var_4296_to_fp16)[name = tensor<string, []>("x_513_cast_fp16")];
            tensor<int32, [8]> x_515_pad_0 = const()[name = tensor<string, []>("x_515_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            tensor<string, []> x_515_mode_0 = const()[name = tensor<string, []>("x_515_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_244_to_fp16 = const()[name = tensor<string, []>("const_244_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_515_cast_fp16 = pad(constant_val = const_244_to_fp16, mode = x_515_mode_0, pad = x_515_pad_0, x = x_513_cast_fp16)[name = tensor<string, []>("x_515_cast_fp16")];
            tensor<int32, [4]> var_4304 = const()[name = tensor<string, []>("op_4304"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_517_cast_fp16 = reshape(shape = var_4304, x = x_515_cast_fp16)[name = tensor<string, []>("x_517_cast_fp16")];
            tensor<int32, [4]> var_4308_begin_0 = const()[name = tensor<string, []>("op_4308_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_4308_end_0 = const()[name = tensor<string, []>("op_4308_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_4308_end_mask_0 = const()[name = tensor<string, []>("op_4308_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_4308_cast_fp16 = slice_by_index(begin = var_4308_begin_0, end = var_4308_end_0, end_mask = var_4308_end_mask_0, x = x_517_cast_fp16)[name = tensor<string, []>("op_4308_cast_fp16")];
            tensor<int32, [4]> var_4309 = const()[name = tensor<string, []>("op_4309"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_93_cast_fp16 = reshape(shape = var_4309, x = var_4308_cast_fp16)[name = tensor<string, []>("matrix_bd_93_cast_fp16")];
            tensor<bool, []> matrix_ac_47_transpose_x_0 = const()[name = tensor<string, []>("matrix_ac_47_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> matrix_ac_47_transpose_y_0 = const()[name = tensor<string, []>("matrix_ac_47_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<int32, [4]> transpose_142_perm_0 = const()[name = tensor<string, []>("transpose_142_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_143_perm_0 = const()[name = tensor<string, []>("transpose_143_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_143 = transpose(perm = transpose_143_perm_0, x = k_93_cast_fp16)[name = tensor<string, []>("transpose_219")];
            tensor<fp16, [1, 8, 188, 128]> transpose_142 = transpose(perm = transpose_142_perm_0, x = var_4292_cast_fp16)[name = tensor<string, []>("transpose_220")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_47_cast_fp16 = matmul(transpose_x = matrix_ac_47_transpose_x_0, transpose_y = matrix_ac_47_transpose_y_0, x = transpose_142, y = transpose_143)[name = tensor<string, []>("matrix_ac_47_cast_fp16")];
            tensor<int32, [4]> matrix_bd_95_begin_0 = const()[name = tensor<string, []>("matrix_bd_95_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_95_end_0 = const()[name = tensor<string, []>("matrix_bd_95_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_95_end_mask_0 = const()[name = tensor<string, []>("matrix_bd_95_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_95_cast_fp16 = slice_by_index(begin = matrix_bd_95_begin_0, end = matrix_bd_95_end_0, end_mask = matrix_bd_95_end_mask_0, x = matrix_bd_93_cast_fp16)[name = tensor<string, []>("matrix_bd_95_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_4318_cast_fp16 = add(x = matrix_ac_47_cast_fp16, y = matrix_bd_95_cast_fp16)[name = tensor<string, []>("op_4318_cast_fp16")];
            tensor<fp16, []> _inversed_scores_93_y_0_to_fp16 = const()[name = tensor<string, []>("_inversed_scores_93_y_0_to_fp16"), val = tensor<fp16, []>(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_93_cast_fp16 = mul(x = var_4318_cast_fp16, y = _inversed_scores_93_y_0_to_fp16)[name = tensor<string, []>("_inversed_scores_93_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_95_cast_fp16 = select(a = var_12_to_fp16, b = _inversed_scores_93_cast_fp16, cond = mask_3)[name = tensor<string, []>("scores_95_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_4324_cast_fp16 = softmax(axis = var_30, x = scores_95_cast_fp16)[name = tensor<string, []>("op_4324_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_1229_cast_fp16 = select(a = var_11_to_fp16, b = var_4324_cast_fp16, cond = mask_3)[name = tensor<string, []>("input_1229_cast_fp16")];
            tensor<bool, []> x_519_transpose_x_0 = const()[name = tensor<string, []>("x_519_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_519_transpose_y_0 = const()[name = tensor<string, []>("x_519_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 188, 128]> value_49_cast_fp16 = transpose(perm = value_49_perm_0, x = v_47_cast_fp16)[name = tensor<string, []>("transpose_222")];
            tensor<fp16, [1, 8, 188, 128]> x_519_cast_fp16 = matmul(transpose_x = x_519_transpose_x_0, transpose_y = x_519_transpose_y_0, x = input_1229_cast_fp16, y = value_49_cast_fp16)[name = tensor<string, []>("x_519_cast_fp16")];
            tensor<int32, [4]> var_4328_perm_0 = const()[name = tensor<string, []>("op_4328_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_4329 = const()[name = tensor<string, []>("op_4329"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_4328_cast_fp16 = transpose(perm = var_4328_perm_0, x = x_519_cast_fp16)[name = tensor<string, []>("transpose_218")];
            tensor<fp16, [1, 188, 1024]> input_1231_cast_fp16 = reshape(shape = var_4329, x = var_4328_cast_fp16)[name = tensor<string, []>("input_1231_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_23_self_attn_linear_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_23_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1161482432)))];
            tensor<fp16, [1024]> encoder_layers_23_self_attn_linear_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_23_self_attn_linear_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1163579648)))];
            tensor<fp16, [1, 188, 1024]> linear_214_cast_fp16 = linear(bias = encoder_layers_23_self_attn_linear_out_bias_to_fp16, weight = encoder_layers_23_self_attn_linear_out_weight_to_fp16, x = input_1231_cast_fp16)[name = tensor<string, []>("linear_214_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1235_cast_fp16 = add(x = input_1227_cast_fp16, y = linear_214_cast_fp16)[name = tensor<string, []>("input_1235_cast_fp16")];
            tensor<int32, [1]> x_523_axes_0 = const()[name = tensor<string, []>("x_523_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_23_norm_conv_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_23_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1163581760)))];
            tensor<fp16, [1024]> encoder_layers_23_norm_conv_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_23_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1163583872)))];
            tensor<fp16, [1, 188, 1024]> x_523_cast_fp16 = layer_norm(axes = x_523_axes_0, beta = encoder_layers_23_norm_conv_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_23_norm_conv_weight_to_fp16, x = input_1235_cast_fp16)[name = tensor<string, []>("x_523_cast_fp16")];
            tensor<int32, [3]> input_1237_perm_0 = const()[name = tensor<string, []>("input_1237_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> input_1239_pad_type_0 = const()[name = tensor<string, []>("input_1239_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_1239_strides_0 = const()[name = tensor<string, []>("input_1239_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1239_pad_0 = const()[name = tensor<string, []>("input_1239_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1239_dilations_0 = const()[name = tensor<string, []>("input_1239_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_1239_groups_0 = const()[name = tensor<string, []>("input_1239_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [2048, 1024, 1]> encoder_layers_23_conv_pointwise_conv1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_23_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1163585984)))];
            tensor<fp16, [2048]> encoder_layers_23_conv_pointwise_conv1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_23_conv_pointwise_conv1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1167780352)))];
            tensor<fp16, [1, 1024, 188]> input_1237_cast_fp16 = transpose(perm = input_1237_perm_0, x = x_523_cast_fp16)[name = tensor<string, []>("transpose_217")];
            tensor<fp16, [1, 2048, 188]> input_1239_cast_fp16 = conv(bias = encoder_layers_23_conv_pointwise_conv1_bias_to_fp16, dilations = input_1239_dilations_0, groups = input_1239_groups_0, pad = input_1239_pad_0, pad_type = input_1239_pad_type_0, strides = input_1239_strides_0, weight = encoder_layers_23_conv_pointwise_conv1_weight_to_fp16, x = input_1237_cast_fp16)[name = tensor<string, []>("input_1239_cast_fp16")];
            tensor<int32, []> x_525_split_num_splits_0 = const()[name = tensor<string, []>("x_525_split_num_splits_0"), val = tensor<int32, []>(2)];
            tensor<int32, []> x_525_split_axis_0 = const()[name = tensor<string, []>("x_525_split_axis_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1, 1024, 188]> x_525_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_525_split_cast_fp16_1 = split(axis = x_525_split_axis_0, num_splits = x_525_split_num_splits_0, x = input_1239_cast_fp16)[name = tensor<string, []>("x_525_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_525_split_1_sigmoid_cast_fp16 = sigmoid(x = x_525_split_cast_fp16_1)[name = tensor<string, []>("x_525_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_525_cast_fp16 = mul(x = x_525_split_cast_fp16_0, y = x_525_split_1_sigmoid_cast_fp16)[name = tensor<string, []>("x_525_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_1241_cast_fp16 = select(a = var_11_to_fp16, b = x_525_cast_fp16, cond = var_351)[name = tensor<string, []>("input_1241_cast_fp16")];
            tensor<int32, [6]> input_1243_pad_0 = const()[name = tensor<string, []>("input_1243_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            tensor<string, []> input_1243_mode_0 = const()[name = tensor<string, []>("input_1243_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_247_to_fp16 = const()[name = tensor<string, []>("const_247_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_1243_cast_fp16 = pad(constant_val = const_247_to_fp16, mode = input_1243_mode_0, pad = input_1243_pad_0, x = input_1241_cast_fp16)[name = tensor<string, []>("input_1243_cast_fp16")];
            tensor<string, []> input_1245_pad_type_0 = const()[name = tensor<string, []>("input_1245_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, []> input_1245_groups_0 = const()[name = tensor<string, []>("input_1245_groups_0"), val = tensor<int32, []>(1024)];
            tensor<int32, [1]> input_1245_strides_0 = const()[name = tensor<string, []>("input_1245_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1245_pad_0 = const()[name = tensor<string, []>("input_1245_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1245_dilations_0 = const()[name = tensor<string, []>("input_1245_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_374_to_fp16 = const()[name = tensor<string, []>("const_374_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1167784512)))];
            tensor<fp16, [1024]> const_375_to_fp16 = const()[name = tensor<string, []>("const_375_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1167803008)))];
            tensor<fp16, [1, 1024, 188]> input_1247_cast_fp16 = conv(bias = const_375_to_fp16, dilations = input_1245_dilations_0, groups = input_1245_groups_0, pad = input_1245_pad_0, pad_type = input_1245_pad_type_0, strides = input_1245_strides_0, weight = const_374_to_fp16, x = input_1243_cast_fp16)[name = tensor<string, []>("input_1247_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_1249_cast_fp16 = silu(x = input_1247_cast_fp16)[name = tensor<string, []>("input_1249_cast_fp16")];
            tensor<string, []> x_527_pad_type_0 = const()[name = tensor<string, []>("x_527_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> x_527_strides_0 = const()[name = tensor<string, []>("x_527_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_527_pad_0 = const()[name = tensor<string, []>("x_527_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_527_dilations_0 = const()[name = tensor<string, []>("x_527_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> x_527_groups_0 = const()[name = tensor<string, []>("x_527_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1024, 1024, 1]> encoder_layers_23_conv_pointwise_conv2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_23_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1167805120)))];
            tensor<fp16, [1024]> encoder_layers_23_conv_pointwise_conv2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_23_conv_pointwise_conv2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1169902336)))];
            tensor<fp16, [1, 1024, 188]> x_527_cast_fp16 = conv(bias = encoder_layers_23_conv_pointwise_conv2_bias_to_fp16, dilations = x_527_dilations_0, groups = x_527_groups_0, pad = x_527_pad_0, pad_type = x_527_pad_type_0, strides = x_527_strides_0, weight = encoder_layers_23_conv_pointwise_conv2_weight_to_fp16, x = input_1249_cast_fp16)[name = tensor<string, []>("x_527_cast_fp16")];
            tensor<int32, [3]> input_1251_perm_0 = const()[name = tensor<string, []>("input_1251_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_1251_cast_fp16 = transpose(perm = input_1251_perm_0, x = x_527_cast_fp16)[name = tensor<string, []>("transpose_216")];
            tensor<fp16, [1, 188, 1024]> input_1253_cast_fp16 = add(x = input_1235_cast_fp16, y = input_1251_cast_fp16)[name = tensor<string, []>("input_1253_cast_fp16")];
            tensor<int32, [1]> input_1255_axes_0 = const()[name = tensor<string, []>("input_1255_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_23_norm_feed_forward2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_23_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1169904448)))];
            tensor<fp16, [1024]> encoder_layers_23_norm_feed_forward2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_23_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1169906560)))];
            tensor<fp16, [1, 188, 1024]> input_1255_cast_fp16 = layer_norm(axes = input_1255_axes_0, beta = encoder_layers_23_norm_feed_forward2_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_23_norm_feed_forward2_weight_to_fp16, x = input_1253_cast_fp16)[name = tensor<string, []>("input_1255_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_23_feed_forward2_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_23_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1169908672)))];
            tensor<fp16, [4096]> encoder_layers_23_feed_forward2_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_23_feed_forward2_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1178297344)))];
            tensor<fp16, [1, 188, 4096]> linear_215_cast_fp16 = linear(bias = encoder_layers_23_feed_forward2_linear1_bias_to_fp16, weight = encoder_layers_23_feed_forward2_linear1_weight_to_fp16, x = input_1255_cast_fp16)[name = tensor<string, []>("linear_215_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_1259_cast_fp16 = silu(x = linear_215_cast_fp16)[name = tensor<string, []>("input_1259_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_23_feed_forward2_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_23_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1178305600)))];
            tensor<fp16, [1024]> encoder_layers_23_feed_forward2_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_23_feed_forward2_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1186694272)))];
            tensor<fp16, [1, 188, 1024]> linear_216_cast_fp16 = linear(bias = encoder_layers_23_feed_forward2_linear2_bias_to_fp16, weight = encoder_layers_23_feed_forward2_linear2_weight_to_fp16, x = input_1259_cast_fp16)[name = tensor<string, []>("linear_216_cast_fp16")];
            tensor<fp16, []> var_4395_to_fp16 = const()[name = tensor<string, []>("op_4395_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_4396_cast_fp16 = mul(x = linear_216_cast_fp16, y = var_4395_to_fp16)[name = tensor<string, []>("op_4396_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1265_cast_fp16 = add(x = input_1253_cast_fp16, y = var_4396_cast_fp16)[name = tensor<string, []>("input_1265_cast_fp16")];
            tensor<int32, [1]> input_1267_axes_0 = const()[name = tensor<string, []>("input_1267_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_23_norm_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_23_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1186696384)))];
            tensor<fp16, [1024]> encoder_layers_23_norm_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_23_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1186698496)))];
            tensor<fp16, [1, 188, 1024]> input_1267_cast_fp16 = layer_norm(axes = input_1267_axes_0, beta = encoder_layers_23_norm_out_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_23_norm_out_weight_to_fp16, x = input_1265_cast_fp16)[name = tensor<string, []>("input_1267_cast_fp16")];
            tensor<int32, [1]> input_1269_axes_0 = const()[name = tensor<string, []>("input_1269_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_24_norm_feed_forward1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_24_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1186700608)))];
            tensor<fp16, [1024]> encoder_layers_24_norm_feed_forward1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_24_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1186702720)))];
            tensor<fp16, [1, 188, 1024]> input_1269_cast_fp16 = layer_norm(axes = input_1269_axes_0, beta = encoder_layers_24_norm_feed_forward1_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_24_norm_feed_forward1_weight_to_fp16, x = input_1267_cast_fp16)[name = tensor<string, []>("input_1269_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_24_feed_forward1_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_24_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1186704832)))];
            tensor<fp16, [4096]> encoder_layers_24_feed_forward1_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_24_feed_forward1_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1195093504)))];
            tensor<fp16, [1, 188, 4096]> linear_217_cast_fp16 = linear(bias = encoder_layers_24_feed_forward1_linear1_bias_to_fp16, weight = encoder_layers_24_feed_forward1_linear1_weight_to_fp16, x = input_1269_cast_fp16)[name = tensor<string, []>("linear_217_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_1273_cast_fp16 = silu(x = linear_217_cast_fp16)[name = tensor<string, []>("input_1273_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_24_feed_forward1_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_24_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1195101760)))];
            tensor<fp16, [1024]> encoder_layers_24_feed_forward1_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_24_feed_forward1_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1203490432)))];
            tensor<fp16, [1, 188, 1024]> linear_218_cast_fp16 = linear(bias = encoder_layers_24_feed_forward1_linear2_bias_to_fp16, weight = encoder_layers_24_feed_forward1_linear2_weight_to_fp16, x = input_1273_cast_fp16)[name = tensor<string, []>("linear_218_cast_fp16")];
            tensor<fp16, []> var_4426_to_fp16 = const()[name = tensor<string, []>("op_4426_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_4427_cast_fp16 = mul(x = linear_218_cast_fp16, y = var_4426_to_fp16)[name = tensor<string, []>("op_4427_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1279_cast_fp16 = add(x = input_1267_cast_fp16, y = var_4427_cast_fp16)[name = tensor<string, []>("input_1279_cast_fp16")];
            tensor<int32, [1]> query_49_axes_0 = const()[name = tensor<string, []>("query_49_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_24_norm_self_att_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_24_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1203492544)))];
            tensor<fp16, [1024]> encoder_layers_24_norm_self_att_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_24_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1203494656)))];
            tensor<fp16, [1, 188, 1024]> query_49_cast_fp16 = layer_norm(axes = query_49_axes_0, beta = encoder_layers_24_norm_self_att_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_24_norm_self_att_weight_to_fp16, x = input_1279_cast_fp16)[name = tensor<string, []>("query_49_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_24_self_attn_linear_q_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_24_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1203496768)))];
            tensor<fp16, [1024]> encoder_layers_24_self_attn_linear_q_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_24_self_attn_linear_q_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1205593984)))];
            tensor<fp16, [1, 188, 1024]> linear_219_cast_fp16 = linear(bias = encoder_layers_24_self_attn_linear_q_bias_to_fp16, weight = encoder_layers_24_self_attn_linear_q_weight_to_fp16, x = query_49_cast_fp16)[name = tensor<string, []>("linear_219_cast_fp16")];
            tensor<int32, [4]> var_4444 = const()[name = tensor<string, []>("op_4444"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_145_cast_fp16 = reshape(shape = var_4444, x = linear_219_cast_fp16)[name = tensor<string, []>("q_145_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_24_self_attn_linear_k_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_24_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1205596096)))];
            tensor<fp16, [1024]> encoder_layers_24_self_attn_linear_k_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_24_self_attn_linear_k_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1207693312)))];
            tensor<fp16, [1, 188, 1024]> linear_220_cast_fp16 = linear(bias = encoder_layers_24_self_attn_linear_k_bias_to_fp16, weight = encoder_layers_24_self_attn_linear_k_weight_to_fp16, x = query_49_cast_fp16)[name = tensor<string, []>("linear_220_cast_fp16")];
            tensor<int32, [4]> var_4449 = const()[name = tensor<string, []>("op_4449"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_97_cast_fp16 = reshape(shape = var_4449, x = linear_220_cast_fp16)[name = tensor<string, []>("k_97_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_24_self_attn_linear_v_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_24_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1207695424)))];
            tensor<fp16, [1024]> encoder_layers_24_self_attn_linear_v_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_24_self_attn_linear_v_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1209792640)))];
            tensor<fp16, [1, 188, 1024]> linear_221_cast_fp16 = linear(bias = encoder_layers_24_self_attn_linear_v_bias_to_fp16, weight = encoder_layers_24_self_attn_linear_v_weight_to_fp16, x = query_49_cast_fp16)[name = tensor<string, []>("linear_221_cast_fp16")];
            tensor<int32, [4]> var_4454 = const()[name = tensor<string, []>("op_4454"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_49_cast_fp16 = reshape(shape = var_4454, x = linear_221_cast_fp16)[name = tensor<string, []>("v_49_cast_fp16")];
            tensor<int32, [4]> value_51_perm_0 = const()[name = tensor<string, []>("value_51_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> encoder_layers_24_self_attn_pos_bias_u_to_fp16 = const()[name = tensor<string, []>("encoder_layers_24_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1209794752)))];
            tensor<fp16, [1, 188, 8, 128]> var_4466_cast_fp16 = add(x = q_145_cast_fp16, y = encoder_layers_24_self_attn_pos_bias_u_to_fp16)[name = tensor<string, []>("op_4466_cast_fp16")];
            tensor<fp16, [8, 128]> encoder_layers_24_self_attn_pos_bias_v_to_fp16 = const()[name = tensor<string, []>("encoder_layers_24_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1209796864)))];
            tensor<fp16, [1, 188, 8, 128]> var_4468_cast_fp16 = add(x = q_145_cast_fp16, y = encoder_layers_24_self_attn_pos_bias_v_to_fp16)[name = tensor<string, []>("op_4468_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_49_perm_0 = const()[name = tensor<string, []>("q_with_bias_v_49_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<bool, []> x_535_transpose_x_0 = const()[name = tensor<string, []>("x_535_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_535_transpose_y_0 = const()[name = tensor<string, []>("x_535_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 128, 375]> var_4470_to_fp16 = const()[name = tensor<string, []>("op_4470_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1209798976)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_49_cast_fp16 = transpose(perm = q_with_bias_v_49_perm_0, x = var_4468_cast_fp16)[name = tensor<string, []>("transpose_214")];
            tensor<fp16, [1, 8, 188, 375]> x_535_cast_fp16 = matmul(transpose_x = x_535_transpose_x_0, transpose_y = x_535_transpose_y_0, x = q_with_bias_v_49_cast_fp16, y = var_4470_to_fp16)[name = tensor<string, []>("x_535_cast_fp16")];
            tensor<int32, [8]> x_537_pad_0 = const()[name = tensor<string, []>("x_537_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            tensor<string, []> x_537_mode_0 = const()[name = tensor<string, []>("x_537_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_254_to_fp16 = const()[name = tensor<string, []>("const_254_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_537_cast_fp16 = pad(constant_val = const_254_to_fp16, mode = x_537_mode_0, pad = x_537_pad_0, x = x_535_cast_fp16)[name = tensor<string, []>("x_537_cast_fp16")];
            tensor<int32, [4]> var_4478 = const()[name = tensor<string, []>("op_4478"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_539_cast_fp16 = reshape(shape = var_4478, x = x_537_cast_fp16)[name = tensor<string, []>("x_539_cast_fp16")];
            tensor<int32, [4]> var_4482_begin_0 = const()[name = tensor<string, []>("op_4482_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_4482_end_0 = const()[name = tensor<string, []>("op_4482_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_4482_end_mask_0 = const()[name = tensor<string, []>("op_4482_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_4482_cast_fp16 = slice_by_index(begin = var_4482_begin_0, end = var_4482_end_0, end_mask = var_4482_end_mask_0, x = x_539_cast_fp16)[name = tensor<string, []>("op_4482_cast_fp16")];
            tensor<int32, [4]> var_4483 = const()[name = tensor<string, []>("op_4483"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_97_cast_fp16 = reshape(shape = var_4483, x = var_4482_cast_fp16)[name = tensor<string, []>("matrix_bd_97_cast_fp16")];
            tensor<bool, []> matrix_ac_49_transpose_x_0 = const()[name = tensor<string, []>("matrix_ac_49_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> matrix_ac_49_transpose_y_0 = const()[name = tensor<string, []>("matrix_ac_49_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<int32, [4]> transpose_144_perm_0 = const()[name = tensor<string, []>("transpose_144_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_145_perm_0 = const()[name = tensor<string, []>("transpose_145_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_145 = transpose(perm = transpose_145_perm_0, x = k_97_cast_fp16)[name = tensor<string, []>("transpose_212")];
            tensor<fp16, [1, 8, 188, 128]> transpose_144 = transpose(perm = transpose_144_perm_0, x = var_4466_cast_fp16)[name = tensor<string, []>("transpose_213")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_49_cast_fp16 = matmul(transpose_x = matrix_ac_49_transpose_x_0, transpose_y = matrix_ac_49_transpose_y_0, x = transpose_144, y = transpose_145)[name = tensor<string, []>("matrix_ac_49_cast_fp16")];
            tensor<int32, [4]> matrix_bd_99_begin_0 = const()[name = tensor<string, []>("matrix_bd_99_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_99_end_0 = const()[name = tensor<string, []>("matrix_bd_99_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_99_end_mask_0 = const()[name = tensor<string, []>("matrix_bd_99_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_99_cast_fp16 = slice_by_index(begin = matrix_bd_99_begin_0, end = matrix_bd_99_end_0, end_mask = matrix_bd_99_end_mask_0, x = matrix_bd_97_cast_fp16)[name = tensor<string, []>("matrix_bd_99_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_4492_cast_fp16 = add(x = matrix_ac_49_cast_fp16, y = matrix_bd_99_cast_fp16)[name = tensor<string, []>("op_4492_cast_fp16")];
            tensor<fp16, []> _inversed_scores_97_y_0_to_fp16 = const()[name = tensor<string, []>("_inversed_scores_97_y_0_to_fp16"), val = tensor<fp16, []>(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_97_cast_fp16 = mul(x = var_4492_cast_fp16, y = _inversed_scores_97_y_0_to_fp16)[name = tensor<string, []>("_inversed_scores_97_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_99_cast_fp16 = select(a = var_12_to_fp16, b = _inversed_scores_97_cast_fp16, cond = mask_3)[name = tensor<string, []>("scores_99_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_4498_cast_fp16 = softmax(axis = var_30, x = scores_99_cast_fp16)[name = tensor<string, []>("op_4498_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_1281_cast_fp16 = select(a = var_11_to_fp16, b = var_4498_cast_fp16, cond = mask_3)[name = tensor<string, []>("input_1281_cast_fp16")];
            tensor<bool, []> x_541_transpose_x_0 = const()[name = tensor<string, []>("x_541_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_541_transpose_y_0 = const()[name = tensor<string, []>("x_541_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 188, 128]> value_51_cast_fp16 = transpose(perm = value_51_perm_0, x = v_49_cast_fp16)[name = tensor<string, []>("transpose_215")];
            tensor<fp16, [1, 8, 188, 128]> x_541_cast_fp16 = matmul(transpose_x = x_541_transpose_x_0, transpose_y = x_541_transpose_y_0, x = input_1281_cast_fp16, y = value_51_cast_fp16)[name = tensor<string, []>("x_541_cast_fp16")];
            tensor<int32, [4]> var_4502_perm_0 = const()[name = tensor<string, []>("op_4502_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_4503 = const()[name = tensor<string, []>("op_4503"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_4502_cast_fp16 = transpose(perm = var_4502_perm_0, x = x_541_cast_fp16)[name = tensor<string, []>("transpose_211")];
            tensor<fp16, [1, 188, 1024]> input_1283_cast_fp16 = reshape(shape = var_4503, x = var_4502_cast_fp16)[name = tensor<string, []>("input_1283_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_24_self_attn_linear_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_24_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1210567040)))];
            tensor<fp16, [1024]> encoder_layers_24_self_attn_linear_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_24_self_attn_linear_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1212664256)))];
            tensor<fp16, [1, 188, 1024]> linear_223_cast_fp16 = linear(bias = encoder_layers_24_self_attn_linear_out_bias_to_fp16, weight = encoder_layers_24_self_attn_linear_out_weight_to_fp16, x = input_1283_cast_fp16)[name = tensor<string, []>("linear_223_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1287_cast_fp16 = add(x = input_1279_cast_fp16, y = linear_223_cast_fp16)[name = tensor<string, []>("input_1287_cast_fp16")];
            tensor<int32, [1]> x_545_axes_0 = const()[name = tensor<string, []>("x_545_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_24_norm_conv_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_24_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1212666368)))];
            tensor<fp16, [1024]> encoder_layers_24_norm_conv_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_24_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1212668480)))];
            tensor<fp16, [1, 188, 1024]> x_545_cast_fp16 = layer_norm(axes = x_545_axes_0, beta = encoder_layers_24_norm_conv_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_24_norm_conv_weight_to_fp16, x = input_1287_cast_fp16)[name = tensor<string, []>("x_545_cast_fp16")];
            tensor<int32, [3]> input_1289_perm_0 = const()[name = tensor<string, []>("input_1289_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> input_1291_pad_type_0 = const()[name = tensor<string, []>("input_1291_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_1291_strides_0 = const()[name = tensor<string, []>("input_1291_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1291_pad_0 = const()[name = tensor<string, []>("input_1291_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1291_dilations_0 = const()[name = tensor<string, []>("input_1291_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_1291_groups_0 = const()[name = tensor<string, []>("input_1291_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [2048, 1024, 1]> encoder_layers_24_conv_pointwise_conv1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_24_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1212670592)))];
            tensor<fp16, [2048]> encoder_layers_24_conv_pointwise_conv1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_24_conv_pointwise_conv1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1216864960)))];
            tensor<fp16, [1, 1024, 188]> input_1289_cast_fp16 = transpose(perm = input_1289_perm_0, x = x_545_cast_fp16)[name = tensor<string, []>("transpose_210")];
            tensor<fp16, [1, 2048, 188]> input_1291_cast_fp16 = conv(bias = encoder_layers_24_conv_pointwise_conv1_bias_to_fp16, dilations = input_1291_dilations_0, groups = input_1291_groups_0, pad = input_1291_pad_0, pad_type = input_1291_pad_type_0, strides = input_1291_strides_0, weight = encoder_layers_24_conv_pointwise_conv1_weight_to_fp16, x = input_1289_cast_fp16)[name = tensor<string, []>("input_1291_cast_fp16")];
            tensor<int32, []> x_547_split_num_splits_0 = const()[name = tensor<string, []>("x_547_split_num_splits_0"), val = tensor<int32, []>(2)];
            tensor<int32, []> x_547_split_axis_0 = const()[name = tensor<string, []>("x_547_split_axis_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1, 1024, 188]> x_547_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_547_split_cast_fp16_1 = split(axis = x_547_split_axis_0, num_splits = x_547_split_num_splits_0, x = input_1291_cast_fp16)[name = tensor<string, []>("x_547_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_547_split_1_sigmoid_cast_fp16 = sigmoid(x = x_547_split_cast_fp16_1)[name = tensor<string, []>("x_547_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_547_cast_fp16 = mul(x = x_547_split_cast_fp16_0, y = x_547_split_1_sigmoid_cast_fp16)[name = tensor<string, []>("x_547_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_1293_cast_fp16 = select(a = var_11_to_fp16, b = x_547_cast_fp16, cond = var_351)[name = tensor<string, []>("input_1293_cast_fp16")];
            tensor<int32, [6]> input_1295_pad_0 = const()[name = tensor<string, []>("input_1295_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            tensor<string, []> input_1295_mode_0 = const()[name = tensor<string, []>("input_1295_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_257_to_fp16 = const()[name = tensor<string, []>("const_257_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_1295_cast_fp16 = pad(constant_val = const_257_to_fp16, mode = input_1295_mode_0, pad = input_1295_pad_0, x = input_1293_cast_fp16)[name = tensor<string, []>("input_1295_cast_fp16")];
            tensor<string, []> input_1297_pad_type_0 = const()[name = tensor<string, []>("input_1297_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, []> input_1297_groups_0 = const()[name = tensor<string, []>("input_1297_groups_0"), val = tensor<int32, []>(1024)];
            tensor<int32, [1]> input_1297_strides_0 = const()[name = tensor<string, []>("input_1297_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1297_pad_0 = const()[name = tensor<string, []>("input_1297_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1297_dilations_0 = const()[name = tensor<string, []>("input_1297_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_376_to_fp16 = const()[name = tensor<string, []>("const_376_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1216869120)))];
            tensor<fp16, [1024]> const_377_to_fp16 = const()[name = tensor<string, []>("const_377_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1216887616)))];
            tensor<fp16, [1, 1024, 188]> input_1299_cast_fp16 = conv(bias = const_377_to_fp16, dilations = input_1297_dilations_0, groups = input_1297_groups_0, pad = input_1297_pad_0, pad_type = input_1297_pad_type_0, strides = input_1297_strides_0, weight = const_376_to_fp16, x = input_1295_cast_fp16)[name = tensor<string, []>("input_1299_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_1301_cast_fp16 = silu(x = input_1299_cast_fp16)[name = tensor<string, []>("input_1301_cast_fp16")];
            tensor<string, []> x_549_pad_type_0 = const()[name = tensor<string, []>("x_549_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> x_549_strides_0 = const()[name = tensor<string, []>("x_549_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_549_pad_0 = const()[name = tensor<string, []>("x_549_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_549_dilations_0 = const()[name = tensor<string, []>("x_549_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> x_549_groups_0 = const()[name = tensor<string, []>("x_549_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1024, 1024, 1]> encoder_layers_24_conv_pointwise_conv2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_24_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1216889728)))];
            tensor<fp16, [1024]> encoder_layers_24_conv_pointwise_conv2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_24_conv_pointwise_conv2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1218986944)))];
            tensor<fp16, [1, 1024, 188]> x_549_cast_fp16 = conv(bias = encoder_layers_24_conv_pointwise_conv2_bias_to_fp16, dilations = x_549_dilations_0, groups = x_549_groups_0, pad = x_549_pad_0, pad_type = x_549_pad_type_0, strides = x_549_strides_0, weight = encoder_layers_24_conv_pointwise_conv2_weight_to_fp16, x = input_1301_cast_fp16)[name = tensor<string, []>("x_549_cast_fp16")];
            tensor<int32, [3]> input_1303_perm_0 = const()[name = tensor<string, []>("input_1303_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_1303_cast_fp16 = transpose(perm = input_1303_perm_0, x = x_549_cast_fp16)[name = tensor<string, []>("transpose_209")];
            tensor<fp16, [1, 188, 1024]> input_1305_cast_fp16 = add(x = input_1287_cast_fp16, y = input_1303_cast_fp16)[name = tensor<string, []>("input_1305_cast_fp16")];
            tensor<int32, [1]> input_1307_axes_0 = const()[name = tensor<string, []>("input_1307_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_24_norm_feed_forward2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_24_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1218989056)))];
            tensor<fp16, [1024]> encoder_layers_24_norm_feed_forward2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_24_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1218991168)))];
            tensor<fp16, [1, 188, 1024]> input_1307_cast_fp16 = layer_norm(axes = input_1307_axes_0, beta = encoder_layers_24_norm_feed_forward2_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_24_norm_feed_forward2_weight_to_fp16, x = input_1305_cast_fp16)[name = tensor<string, []>("input_1307_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_24_feed_forward2_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_24_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1218993280)))];
            tensor<fp16, [4096]> encoder_layers_24_feed_forward2_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_24_feed_forward2_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1227381952)))];
            tensor<fp16, [1, 188, 4096]> linear_224_cast_fp16 = linear(bias = encoder_layers_24_feed_forward2_linear1_bias_to_fp16, weight = encoder_layers_24_feed_forward2_linear1_weight_to_fp16, x = input_1307_cast_fp16)[name = tensor<string, []>("linear_224_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_1311_cast_fp16 = silu(x = linear_224_cast_fp16)[name = tensor<string, []>("input_1311_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_24_feed_forward2_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_24_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1227390208)))];
            tensor<fp16, [1024]> encoder_layers_24_feed_forward2_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_24_feed_forward2_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1235778880)))];
            tensor<fp16, [1, 188, 1024]> linear_225_cast_fp16 = linear(bias = encoder_layers_24_feed_forward2_linear2_bias_to_fp16, weight = encoder_layers_24_feed_forward2_linear2_weight_to_fp16, x = input_1311_cast_fp16)[name = tensor<string, []>("linear_225_cast_fp16")];
            tensor<fp16, []> var_4569_to_fp16 = const()[name = tensor<string, []>("op_4569_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_4570_cast_fp16 = mul(x = linear_225_cast_fp16, y = var_4569_to_fp16)[name = tensor<string, []>("op_4570_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1317_cast_fp16 = add(x = input_1305_cast_fp16, y = var_4570_cast_fp16)[name = tensor<string, []>("input_1317_cast_fp16")];
            tensor<int32, [1]> input_1319_axes_0 = const()[name = tensor<string, []>("input_1319_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_24_norm_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_24_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1235780992)))];
            tensor<fp16, [1024]> encoder_layers_24_norm_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_24_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1235783104)))];
            tensor<fp16, [1, 188, 1024]> input_1319_cast_fp16 = layer_norm(axes = input_1319_axes_0, beta = encoder_layers_24_norm_out_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_24_norm_out_weight_to_fp16, x = input_1317_cast_fp16)[name = tensor<string, []>("input_1319_cast_fp16")];
            tensor<int32, [1]> input_1321_axes_0 = const()[name = tensor<string, []>("input_1321_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_25_norm_feed_forward1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_25_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1235785216)))];
            tensor<fp16, [1024]> encoder_layers_25_norm_feed_forward1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_25_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1235787328)))];
            tensor<fp16, [1, 188, 1024]> input_1321_cast_fp16 = layer_norm(axes = input_1321_axes_0, beta = encoder_layers_25_norm_feed_forward1_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_25_norm_feed_forward1_weight_to_fp16, x = input_1319_cast_fp16)[name = tensor<string, []>("input_1321_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_25_feed_forward1_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_25_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1235789440)))];
            tensor<fp16, [4096]> encoder_layers_25_feed_forward1_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_25_feed_forward1_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1244178112)))];
            tensor<fp16, [1, 188, 4096]> linear_226_cast_fp16 = linear(bias = encoder_layers_25_feed_forward1_linear1_bias_to_fp16, weight = encoder_layers_25_feed_forward1_linear1_weight_to_fp16, x = input_1321_cast_fp16)[name = tensor<string, []>("linear_226_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_1325_cast_fp16 = silu(x = linear_226_cast_fp16)[name = tensor<string, []>("input_1325_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_25_feed_forward1_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_25_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1244186368)))];
            tensor<fp16, [1024]> encoder_layers_25_feed_forward1_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_25_feed_forward1_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1252575040)))];
            tensor<fp16, [1, 188, 1024]> linear_227_cast_fp16 = linear(bias = encoder_layers_25_feed_forward1_linear2_bias_to_fp16, weight = encoder_layers_25_feed_forward1_linear2_weight_to_fp16, x = input_1325_cast_fp16)[name = tensor<string, []>("linear_227_cast_fp16")];
            tensor<fp16, []> var_4600_to_fp16 = const()[name = tensor<string, []>("op_4600_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_4601_cast_fp16 = mul(x = linear_227_cast_fp16, y = var_4600_to_fp16)[name = tensor<string, []>("op_4601_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1331_cast_fp16 = add(x = input_1319_cast_fp16, y = var_4601_cast_fp16)[name = tensor<string, []>("input_1331_cast_fp16")];
            tensor<int32, [1]> query_51_axes_0 = const()[name = tensor<string, []>("query_51_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_25_norm_self_att_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_25_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1252577152)))];
            tensor<fp16, [1024]> encoder_layers_25_norm_self_att_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_25_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1252579264)))];
            tensor<fp16, [1, 188, 1024]> query_51_cast_fp16 = layer_norm(axes = query_51_axes_0, beta = encoder_layers_25_norm_self_att_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_25_norm_self_att_weight_to_fp16, x = input_1331_cast_fp16)[name = tensor<string, []>("query_51_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_25_self_attn_linear_q_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_25_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1252581376)))];
            tensor<fp16, [1024]> encoder_layers_25_self_attn_linear_q_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_25_self_attn_linear_q_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1254678592)))];
            tensor<fp16, [1, 188, 1024]> linear_228_cast_fp16 = linear(bias = encoder_layers_25_self_attn_linear_q_bias_to_fp16, weight = encoder_layers_25_self_attn_linear_q_weight_to_fp16, x = query_51_cast_fp16)[name = tensor<string, []>("linear_228_cast_fp16")];
            tensor<int32, [4]> var_4618 = const()[name = tensor<string, []>("op_4618"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_151_cast_fp16 = reshape(shape = var_4618, x = linear_228_cast_fp16)[name = tensor<string, []>("q_151_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_25_self_attn_linear_k_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_25_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1254680704)))];
            tensor<fp16, [1024]> encoder_layers_25_self_attn_linear_k_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_25_self_attn_linear_k_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1256777920)))];
            tensor<fp16, [1, 188, 1024]> linear_229_cast_fp16 = linear(bias = encoder_layers_25_self_attn_linear_k_bias_to_fp16, weight = encoder_layers_25_self_attn_linear_k_weight_to_fp16, x = query_51_cast_fp16)[name = tensor<string, []>("linear_229_cast_fp16")];
            tensor<int32, [4]> var_4623 = const()[name = tensor<string, []>("op_4623"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_101_cast_fp16 = reshape(shape = var_4623, x = linear_229_cast_fp16)[name = tensor<string, []>("k_101_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_25_self_attn_linear_v_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_25_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1256780032)))];
            tensor<fp16, [1024]> encoder_layers_25_self_attn_linear_v_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_25_self_attn_linear_v_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1258877248)))];
            tensor<fp16, [1, 188, 1024]> linear_230_cast_fp16 = linear(bias = encoder_layers_25_self_attn_linear_v_bias_to_fp16, weight = encoder_layers_25_self_attn_linear_v_weight_to_fp16, x = query_51_cast_fp16)[name = tensor<string, []>("linear_230_cast_fp16")];
            tensor<int32, [4]> var_4628 = const()[name = tensor<string, []>("op_4628"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_51_cast_fp16 = reshape(shape = var_4628, x = linear_230_cast_fp16)[name = tensor<string, []>("v_51_cast_fp16")];
            tensor<int32, [4]> value_53_perm_0 = const()[name = tensor<string, []>("value_53_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> encoder_layers_25_self_attn_pos_bias_u_to_fp16 = const()[name = tensor<string, []>("encoder_layers_25_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1258879360)))];
            tensor<fp16, [1, 188, 8, 128]> var_4640_cast_fp16 = add(x = q_151_cast_fp16, y = encoder_layers_25_self_attn_pos_bias_u_to_fp16)[name = tensor<string, []>("op_4640_cast_fp16")];
            tensor<fp16, [8, 128]> encoder_layers_25_self_attn_pos_bias_v_to_fp16 = const()[name = tensor<string, []>("encoder_layers_25_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1258881472)))];
            tensor<fp16, [1, 188, 8, 128]> var_4642_cast_fp16 = add(x = q_151_cast_fp16, y = encoder_layers_25_self_attn_pos_bias_v_to_fp16)[name = tensor<string, []>("op_4642_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_51_perm_0 = const()[name = tensor<string, []>("q_with_bias_v_51_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<bool, []> x_557_transpose_x_0 = const()[name = tensor<string, []>("x_557_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_557_transpose_y_0 = const()[name = tensor<string, []>("x_557_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 128, 375]> var_4644_to_fp16 = const()[name = tensor<string, []>("op_4644_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1258883584)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_51_cast_fp16 = transpose(perm = q_with_bias_v_51_perm_0, x = var_4642_cast_fp16)[name = tensor<string, []>("transpose_207")];
            tensor<fp16, [1, 8, 188, 375]> x_557_cast_fp16 = matmul(transpose_x = x_557_transpose_x_0, transpose_y = x_557_transpose_y_0, x = q_with_bias_v_51_cast_fp16, y = var_4644_to_fp16)[name = tensor<string, []>("x_557_cast_fp16")];
            tensor<int32, [8]> x_559_pad_0 = const()[name = tensor<string, []>("x_559_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            tensor<string, []> x_559_mode_0 = const()[name = tensor<string, []>("x_559_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_264_to_fp16 = const()[name = tensor<string, []>("const_264_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_559_cast_fp16 = pad(constant_val = const_264_to_fp16, mode = x_559_mode_0, pad = x_559_pad_0, x = x_557_cast_fp16)[name = tensor<string, []>("x_559_cast_fp16")];
            tensor<int32, [4]> var_4652 = const()[name = tensor<string, []>("op_4652"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_561_cast_fp16 = reshape(shape = var_4652, x = x_559_cast_fp16)[name = tensor<string, []>("x_561_cast_fp16")];
            tensor<int32, [4]> var_4656_begin_0 = const()[name = tensor<string, []>("op_4656_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_4656_end_0 = const()[name = tensor<string, []>("op_4656_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_4656_end_mask_0 = const()[name = tensor<string, []>("op_4656_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_4656_cast_fp16 = slice_by_index(begin = var_4656_begin_0, end = var_4656_end_0, end_mask = var_4656_end_mask_0, x = x_561_cast_fp16)[name = tensor<string, []>("op_4656_cast_fp16")];
            tensor<int32, [4]> var_4657 = const()[name = tensor<string, []>("op_4657"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_101_cast_fp16 = reshape(shape = var_4657, x = var_4656_cast_fp16)[name = tensor<string, []>("matrix_bd_101_cast_fp16")];
            tensor<bool, []> matrix_ac_51_transpose_x_0 = const()[name = tensor<string, []>("matrix_ac_51_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> matrix_ac_51_transpose_y_0 = const()[name = tensor<string, []>("matrix_ac_51_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<int32, [4]> transpose_146_perm_0 = const()[name = tensor<string, []>("transpose_146_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_147_perm_0 = const()[name = tensor<string, []>("transpose_147_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_147 = transpose(perm = transpose_147_perm_0, x = k_101_cast_fp16)[name = tensor<string, []>("transpose_205")];
            tensor<fp16, [1, 8, 188, 128]> transpose_146 = transpose(perm = transpose_146_perm_0, x = var_4640_cast_fp16)[name = tensor<string, []>("transpose_206")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_51_cast_fp16 = matmul(transpose_x = matrix_ac_51_transpose_x_0, transpose_y = matrix_ac_51_transpose_y_0, x = transpose_146, y = transpose_147)[name = tensor<string, []>("matrix_ac_51_cast_fp16")];
            tensor<int32, [4]> matrix_bd_103_begin_0 = const()[name = tensor<string, []>("matrix_bd_103_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_103_end_0 = const()[name = tensor<string, []>("matrix_bd_103_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_103_end_mask_0 = const()[name = tensor<string, []>("matrix_bd_103_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_103_cast_fp16 = slice_by_index(begin = matrix_bd_103_begin_0, end = matrix_bd_103_end_0, end_mask = matrix_bd_103_end_mask_0, x = matrix_bd_101_cast_fp16)[name = tensor<string, []>("matrix_bd_103_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_4666_cast_fp16 = add(x = matrix_ac_51_cast_fp16, y = matrix_bd_103_cast_fp16)[name = tensor<string, []>("op_4666_cast_fp16")];
            tensor<fp16, []> _inversed_scores_101_y_0_to_fp16 = const()[name = tensor<string, []>("_inversed_scores_101_y_0_to_fp16"), val = tensor<fp16, []>(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_101_cast_fp16 = mul(x = var_4666_cast_fp16, y = _inversed_scores_101_y_0_to_fp16)[name = tensor<string, []>("_inversed_scores_101_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_103_cast_fp16 = select(a = var_12_to_fp16, b = _inversed_scores_101_cast_fp16, cond = mask_3)[name = tensor<string, []>("scores_103_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_4672_cast_fp16 = softmax(axis = var_30, x = scores_103_cast_fp16)[name = tensor<string, []>("op_4672_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_1333_cast_fp16 = select(a = var_11_to_fp16, b = var_4672_cast_fp16, cond = mask_3)[name = tensor<string, []>("input_1333_cast_fp16")];
            tensor<bool, []> x_563_transpose_x_0 = const()[name = tensor<string, []>("x_563_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_563_transpose_y_0 = const()[name = tensor<string, []>("x_563_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 188, 128]> value_53_cast_fp16 = transpose(perm = value_53_perm_0, x = v_51_cast_fp16)[name = tensor<string, []>("transpose_208")];
            tensor<fp16, [1, 8, 188, 128]> x_563_cast_fp16 = matmul(transpose_x = x_563_transpose_x_0, transpose_y = x_563_transpose_y_0, x = input_1333_cast_fp16, y = value_53_cast_fp16)[name = tensor<string, []>("x_563_cast_fp16")];
            tensor<int32, [4]> var_4676_perm_0 = const()[name = tensor<string, []>("op_4676_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_4677 = const()[name = tensor<string, []>("op_4677"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_4676_cast_fp16 = transpose(perm = var_4676_perm_0, x = x_563_cast_fp16)[name = tensor<string, []>("transpose_204")];
            tensor<fp16, [1, 188, 1024]> input_1335_cast_fp16 = reshape(shape = var_4677, x = var_4676_cast_fp16)[name = tensor<string, []>("input_1335_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_25_self_attn_linear_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_25_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1259651648)))];
            tensor<fp16, [1024]> encoder_layers_25_self_attn_linear_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_25_self_attn_linear_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1261748864)))];
            tensor<fp16, [1, 188, 1024]> linear_232_cast_fp16 = linear(bias = encoder_layers_25_self_attn_linear_out_bias_to_fp16, weight = encoder_layers_25_self_attn_linear_out_weight_to_fp16, x = input_1335_cast_fp16)[name = tensor<string, []>("linear_232_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1339_cast_fp16 = add(x = input_1331_cast_fp16, y = linear_232_cast_fp16)[name = tensor<string, []>("input_1339_cast_fp16")];
            tensor<int32, [1]> x_567_axes_0 = const()[name = tensor<string, []>("x_567_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_25_norm_conv_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_25_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1261750976)))];
            tensor<fp16, [1024]> encoder_layers_25_norm_conv_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_25_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1261753088)))];
            tensor<fp16, [1, 188, 1024]> x_567_cast_fp16 = layer_norm(axes = x_567_axes_0, beta = encoder_layers_25_norm_conv_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_25_norm_conv_weight_to_fp16, x = input_1339_cast_fp16)[name = tensor<string, []>("x_567_cast_fp16")];
            tensor<int32, [3]> input_1341_perm_0 = const()[name = tensor<string, []>("input_1341_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> input_1343_pad_type_0 = const()[name = tensor<string, []>("input_1343_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_1343_strides_0 = const()[name = tensor<string, []>("input_1343_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1343_pad_0 = const()[name = tensor<string, []>("input_1343_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1343_dilations_0 = const()[name = tensor<string, []>("input_1343_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_1343_groups_0 = const()[name = tensor<string, []>("input_1343_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [2048, 1024, 1]> encoder_layers_25_conv_pointwise_conv1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_25_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1261755200)))];
            tensor<fp16, [2048]> encoder_layers_25_conv_pointwise_conv1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_25_conv_pointwise_conv1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1265949568)))];
            tensor<fp16, [1, 1024, 188]> input_1341_cast_fp16 = transpose(perm = input_1341_perm_0, x = x_567_cast_fp16)[name = tensor<string, []>("transpose_203")];
            tensor<fp16, [1, 2048, 188]> input_1343_cast_fp16 = conv(bias = encoder_layers_25_conv_pointwise_conv1_bias_to_fp16, dilations = input_1343_dilations_0, groups = input_1343_groups_0, pad = input_1343_pad_0, pad_type = input_1343_pad_type_0, strides = input_1343_strides_0, weight = encoder_layers_25_conv_pointwise_conv1_weight_to_fp16, x = input_1341_cast_fp16)[name = tensor<string, []>("input_1343_cast_fp16")];
            tensor<int32, []> x_569_split_num_splits_0 = const()[name = tensor<string, []>("x_569_split_num_splits_0"), val = tensor<int32, []>(2)];
            tensor<int32, []> x_569_split_axis_0 = const()[name = tensor<string, []>("x_569_split_axis_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1, 1024, 188]> x_569_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_569_split_cast_fp16_1 = split(axis = x_569_split_axis_0, num_splits = x_569_split_num_splits_0, x = input_1343_cast_fp16)[name = tensor<string, []>("x_569_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_569_split_1_sigmoid_cast_fp16 = sigmoid(x = x_569_split_cast_fp16_1)[name = tensor<string, []>("x_569_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_569_cast_fp16 = mul(x = x_569_split_cast_fp16_0, y = x_569_split_1_sigmoid_cast_fp16)[name = tensor<string, []>("x_569_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_1345_cast_fp16 = select(a = var_11_to_fp16, b = x_569_cast_fp16, cond = var_351)[name = tensor<string, []>("input_1345_cast_fp16")];
            tensor<int32, [6]> input_1347_pad_0 = const()[name = tensor<string, []>("input_1347_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            tensor<string, []> input_1347_mode_0 = const()[name = tensor<string, []>("input_1347_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_267_to_fp16 = const()[name = tensor<string, []>("const_267_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_1347_cast_fp16 = pad(constant_val = const_267_to_fp16, mode = input_1347_mode_0, pad = input_1347_pad_0, x = input_1345_cast_fp16)[name = tensor<string, []>("input_1347_cast_fp16")];
            tensor<string, []> input_1349_pad_type_0 = const()[name = tensor<string, []>("input_1349_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, []> input_1349_groups_0 = const()[name = tensor<string, []>("input_1349_groups_0"), val = tensor<int32, []>(1024)];
            tensor<int32, [1]> input_1349_strides_0 = const()[name = tensor<string, []>("input_1349_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1349_pad_0 = const()[name = tensor<string, []>("input_1349_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1349_dilations_0 = const()[name = tensor<string, []>("input_1349_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_378_to_fp16 = const()[name = tensor<string, []>("const_378_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1265953728)))];
            tensor<fp16, [1024]> const_379_to_fp16 = const()[name = tensor<string, []>("const_379_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1265972224)))];
            tensor<fp16, [1, 1024, 188]> input_1351_cast_fp16 = conv(bias = const_379_to_fp16, dilations = input_1349_dilations_0, groups = input_1349_groups_0, pad = input_1349_pad_0, pad_type = input_1349_pad_type_0, strides = input_1349_strides_0, weight = const_378_to_fp16, x = input_1347_cast_fp16)[name = tensor<string, []>("input_1351_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_1353_cast_fp16 = silu(x = input_1351_cast_fp16)[name = tensor<string, []>("input_1353_cast_fp16")];
            tensor<string, []> x_571_pad_type_0 = const()[name = tensor<string, []>("x_571_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> x_571_strides_0 = const()[name = tensor<string, []>("x_571_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_571_pad_0 = const()[name = tensor<string, []>("x_571_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_571_dilations_0 = const()[name = tensor<string, []>("x_571_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> x_571_groups_0 = const()[name = tensor<string, []>("x_571_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1024, 1024, 1]> encoder_layers_25_conv_pointwise_conv2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_25_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1265974336)))];
            tensor<fp16, [1024]> encoder_layers_25_conv_pointwise_conv2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_25_conv_pointwise_conv2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1268071552)))];
            tensor<fp16, [1, 1024, 188]> x_571_cast_fp16 = conv(bias = encoder_layers_25_conv_pointwise_conv2_bias_to_fp16, dilations = x_571_dilations_0, groups = x_571_groups_0, pad = x_571_pad_0, pad_type = x_571_pad_type_0, strides = x_571_strides_0, weight = encoder_layers_25_conv_pointwise_conv2_weight_to_fp16, x = input_1353_cast_fp16)[name = tensor<string, []>("x_571_cast_fp16")];
            tensor<int32, [3]> input_1355_perm_0 = const()[name = tensor<string, []>("input_1355_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_1355_cast_fp16 = transpose(perm = input_1355_perm_0, x = x_571_cast_fp16)[name = tensor<string, []>("transpose_202")];
            tensor<fp16, [1, 188, 1024]> input_1357_cast_fp16 = add(x = input_1339_cast_fp16, y = input_1355_cast_fp16)[name = tensor<string, []>("input_1357_cast_fp16")];
            tensor<int32, [1]> input_1359_axes_0 = const()[name = tensor<string, []>("input_1359_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_25_norm_feed_forward2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_25_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1268073664)))];
            tensor<fp16, [1024]> encoder_layers_25_norm_feed_forward2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_25_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1268075776)))];
            tensor<fp16, [1, 188, 1024]> input_1359_cast_fp16 = layer_norm(axes = input_1359_axes_0, beta = encoder_layers_25_norm_feed_forward2_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_25_norm_feed_forward2_weight_to_fp16, x = input_1357_cast_fp16)[name = tensor<string, []>("input_1359_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_25_feed_forward2_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_25_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1268077888)))];
            tensor<fp16, [4096]> encoder_layers_25_feed_forward2_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_25_feed_forward2_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1276466560)))];
            tensor<fp16, [1, 188, 4096]> linear_233_cast_fp16 = linear(bias = encoder_layers_25_feed_forward2_linear1_bias_to_fp16, weight = encoder_layers_25_feed_forward2_linear1_weight_to_fp16, x = input_1359_cast_fp16)[name = tensor<string, []>("linear_233_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_1363_cast_fp16 = silu(x = linear_233_cast_fp16)[name = tensor<string, []>("input_1363_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_25_feed_forward2_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_25_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1276474816)))];
            tensor<fp16, [1024]> encoder_layers_25_feed_forward2_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_25_feed_forward2_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1284863488)))];
            tensor<fp16, [1, 188, 1024]> linear_234_cast_fp16 = linear(bias = encoder_layers_25_feed_forward2_linear2_bias_to_fp16, weight = encoder_layers_25_feed_forward2_linear2_weight_to_fp16, x = input_1363_cast_fp16)[name = tensor<string, []>("linear_234_cast_fp16")];
            tensor<fp16, []> var_4743_to_fp16 = const()[name = tensor<string, []>("op_4743_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_4744_cast_fp16 = mul(x = linear_234_cast_fp16, y = var_4743_to_fp16)[name = tensor<string, []>("op_4744_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1369_cast_fp16 = add(x = input_1357_cast_fp16, y = var_4744_cast_fp16)[name = tensor<string, []>("input_1369_cast_fp16")];
            tensor<int32, [1]> input_1371_axes_0 = const()[name = tensor<string, []>("input_1371_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_25_norm_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_25_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1284865600)))];
            tensor<fp16, [1024]> encoder_layers_25_norm_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_25_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1284867712)))];
            tensor<fp16, [1, 188, 1024]> input_1371_cast_fp16 = layer_norm(axes = input_1371_axes_0, beta = encoder_layers_25_norm_out_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_25_norm_out_weight_to_fp16, x = input_1369_cast_fp16)[name = tensor<string, []>("input_1371_cast_fp16")];
            tensor<int32, [1]> input_1373_axes_0 = const()[name = tensor<string, []>("input_1373_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_26_norm_feed_forward1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_26_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1284869824)))];
            tensor<fp16, [1024]> encoder_layers_26_norm_feed_forward1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_26_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1284871936)))];
            tensor<fp16, [1, 188, 1024]> input_1373_cast_fp16 = layer_norm(axes = input_1373_axes_0, beta = encoder_layers_26_norm_feed_forward1_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_26_norm_feed_forward1_weight_to_fp16, x = input_1371_cast_fp16)[name = tensor<string, []>("input_1373_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_26_feed_forward1_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_26_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1284874048)))];
            tensor<fp16, [4096]> encoder_layers_26_feed_forward1_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_26_feed_forward1_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1293262720)))];
            tensor<fp16, [1, 188, 4096]> linear_235_cast_fp16 = linear(bias = encoder_layers_26_feed_forward1_linear1_bias_to_fp16, weight = encoder_layers_26_feed_forward1_linear1_weight_to_fp16, x = input_1373_cast_fp16)[name = tensor<string, []>("linear_235_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_1377_cast_fp16 = silu(x = linear_235_cast_fp16)[name = tensor<string, []>("input_1377_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_26_feed_forward1_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_26_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1293270976)))];
            tensor<fp16, [1024]> encoder_layers_26_feed_forward1_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_26_feed_forward1_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1301659648)))];
            tensor<fp16, [1, 188, 1024]> linear_236_cast_fp16 = linear(bias = encoder_layers_26_feed_forward1_linear2_bias_to_fp16, weight = encoder_layers_26_feed_forward1_linear2_weight_to_fp16, x = input_1377_cast_fp16)[name = tensor<string, []>("linear_236_cast_fp16")];
            tensor<fp16, []> var_4774_to_fp16 = const()[name = tensor<string, []>("op_4774_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_4775_cast_fp16 = mul(x = linear_236_cast_fp16, y = var_4774_to_fp16)[name = tensor<string, []>("op_4775_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1383_cast_fp16 = add(x = input_1371_cast_fp16, y = var_4775_cast_fp16)[name = tensor<string, []>("input_1383_cast_fp16")];
            tensor<int32, [1]> query_53_axes_0 = const()[name = tensor<string, []>("query_53_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_26_norm_self_att_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_26_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1301661760)))];
            tensor<fp16, [1024]> encoder_layers_26_norm_self_att_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_26_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1301663872)))];
            tensor<fp16, [1, 188, 1024]> query_53_cast_fp16 = layer_norm(axes = query_53_axes_0, beta = encoder_layers_26_norm_self_att_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_26_norm_self_att_weight_to_fp16, x = input_1383_cast_fp16)[name = tensor<string, []>("query_53_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_26_self_attn_linear_q_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_26_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1301665984)))];
            tensor<fp16, [1024]> encoder_layers_26_self_attn_linear_q_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_26_self_attn_linear_q_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1303763200)))];
            tensor<fp16, [1, 188, 1024]> linear_237_cast_fp16 = linear(bias = encoder_layers_26_self_attn_linear_q_bias_to_fp16, weight = encoder_layers_26_self_attn_linear_q_weight_to_fp16, x = query_53_cast_fp16)[name = tensor<string, []>("linear_237_cast_fp16")];
            tensor<int32, [4]> var_4792 = const()[name = tensor<string, []>("op_4792"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_157_cast_fp16 = reshape(shape = var_4792, x = linear_237_cast_fp16)[name = tensor<string, []>("q_157_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_26_self_attn_linear_k_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_26_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1303765312)))];
            tensor<fp16, [1024]> encoder_layers_26_self_attn_linear_k_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_26_self_attn_linear_k_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1305862528)))];
            tensor<fp16, [1, 188, 1024]> linear_238_cast_fp16 = linear(bias = encoder_layers_26_self_attn_linear_k_bias_to_fp16, weight = encoder_layers_26_self_attn_linear_k_weight_to_fp16, x = query_53_cast_fp16)[name = tensor<string, []>("linear_238_cast_fp16")];
            tensor<int32, [4]> var_4797 = const()[name = tensor<string, []>("op_4797"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_105_cast_fp16 = reshape(shape = var_4797, x = linear_238_cast_fp16)[name = tensor<string, []>("k_105_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_26_self_attn_linear_v_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_26_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1305864640)))];
            tensor<fp16, [1024]> encoder_layers_26_self_attn_linear_v_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_26_self_attn_linear_v_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1307961856)))];
            tensor<fp16, [1, 188, 1024]> linear_239_cast_fp16 = linear(bias = encoder_layers_26_self_attn_linear_v_bias_to_fp16, weight = encoder_layers_26_self_attn_linear_v_weight_to_fp16, x = query_53_cast_fp16)[name = tensor<string, []>("linear_239_cast_fp16")];
            tensor<int32, [4]> var_4802 = const()[name = tensor<string, []>("op_4802"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_53_cast_fp16 = reshape(shape = var_4802, x = linear_239_cast_fp16)[name = tensor<string, []>("v_53_cast_fp16")];
            tensor<int32, [4]> value_55_perm_0 = const()[name = tensor<string, []>("value_55_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> encoder_layers_26_self_attn_pos_bias_u_to_fp16 = const()[name = tensor<string, []>("encoder_layers_26_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1307963968)))];
            tensor<fp16, [1, 188, 8, 128]> var_4814_cast_fp16 = add(x = q_157_cast_fp16, y = encoder_layers_26_self_attn_pos_bias_u_to_fp16)[name = tensor<string, []>("op_4814_cast_fp16")];
            tensor<fp16, [8, 128]> encoder_layers_26_self_attn_pos_bias_v_to_fp16 = const()[name = tensor<string, []>("encoder_layers_26_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1307966080)))];
            tensor<fp16, [1, 188, 8, 128]> var_4816_cast_fp16 = add(x = q_157_cast_fp16, y = encoder_layers_26_self_attn_pos_bias_v_to_fp16)[name = tensor<string, []>("op_4816_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_53_perm_0 = const()[name = tensor<string, []>("q_with_bias_v_53_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<bool, []> x_579_transpose_x_0 = const()[name = tensor<string, []>("x_579_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_579_transpose_y_0 = const()[name = tensor<string, []>("x_579_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 128, 375]> var_4818_to_fp16 = const()[name = tensor<string, []>("op_4818_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1307968192)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_53_cast_fp16 = transpose(perm = q_with_bias_v_53_perm_0, x = var_4816_cast_fp16)[name = tensor<string, []>("transpose_200")];
            tensor<fp16, [1, 8, 188, 375]> x_579_cast_fp16 = matmul(transpose_x = x_579_transpose_x_0, transpose_y = x_579_transpose_y_0, x = q_with_bias_v_53_cast_fp16, y = var_4818_to_fp16)[name = tensor<string, []>("x_579_cast_fp16")];
            tensor<int32, [8]> x_581_pad_0 = const()[name = tensor<string, []>("x_581_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            tensor<string, []> x_581_mode_0 = const()[name = tensor<string, []>("x_581_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_274_to_fp16 = const()[name = tensor<string, []>("const_274_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_581_cast_fp16 = pad(constant_val = const_274_to_fp16, mode = x_581_mode_0, pad = x_581_pad_0, x = x_579_cast_fp16)[name = tensor<string, []>("x_581_cast_fp16")];
            tensor<int32, [4]> var_4826 = const()[name = tensor<string, []>("op_4826"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_583_cast_fp16 = reshape(shape = var_4826, x = x_581_cast_fp16)[name = tensor<string, []>("x_583_cast_fp16")];
            tensor<int32, [4]> var_4830_begin_0 = const()[name = tensor<string, []>("op_4830_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_4830_end_0 = const()[name = tensor<string, []>("op_4830_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_4830_end_mask_0 = const()[name = tensor<string, []>("op_4830_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_4830_cast_fp16 = slice_by_index(begin = var_4830_begin_0, end = var_4830_end_0, end_mask = var_4830_end_mask_0, x = x_583_cast_fp16)[name = tensor<string, []>("op_4830_cast_fp16")];
            tensor<int32, [4]> var_4831 = const()[name = tensor<string, []>("op_4831"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_105_cast_fp16 = reshape(shape = var_4831, x = var_4830_cast_fp16)[name = tensor<string, []>("matrix_bd_105_cast_fp16")];
            tensor<bool, []> matrix_ac_53_transpose_x_0 = const()[name = tensor<string, []>("matrix_ac_53_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> matrix_ac_53_transpose_y_0 = const()[name = tensor<string, []>("matrix_ac_53_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<int32, [4]> transpose_148_perm_0 = const()[name = tensor<string, []>("transpose_148_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_149_perm_0 = const()[name = tensor<string, []>("transpose_149_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_149 = transpose(perm = transpose_149_perm_0, x = k_105_cast_fp16)[name = tensor<string, []>("transpose_198")];
            tensor<fp16, [1, 8, 188, 128]> transpose_148 = transpose(perm = transpose_148_perm_0, x = var_4814_cast_fp16)[name = tensor<string, []>("transpose_199")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_53_cast_fp16 = matmul(transpose_x = matrix_ac_53_transpose_x_0, transpose_y = matrix_ac_53_transpose_y_0, x = transpose_148, y = transpose_149)[name = tensor<string, []>("matrix_ac_53_cast_fp16")];
            tensor<int32, [4]> matrix_bd_107_begin_0 = const()[name = tensor<string, []>("matrix_bd_107_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_107_end_0 = const()[name = tensor<string, []>("matrix_bd_107_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_107_end_mask_0 = const()[name = tensor<string, []>("matrix_bd_107_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_107_cast_fp16 = slice_by_index(begin = matrix_bd_107_begin_0, end = matrix_bd_107_end_0, end_mask = matrix_bd_107_end_mask_0, x = matrix_bd_105_cast_fp16)[name = tensor<string, []>("matrix_bd_107_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_4840_cast_fp16 = add(x = matrix_ac_53_cast_fp16, y = matrix_bd_107_cast_fp16)[name = tensor<string, []>("op_4840_cast_fp16")];
            tensor<fp16, []> _inversed_scores_105_y_0_to_fp16 = const()[name = tensor<string, []>("_inversed_scores_105_y_0_to_fp16"), val = tensor<fp16, []>(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_105_cast_fp16 = mul(x = var_4840_cast_fp16, y = _inversed_scores_105_y_0_to_fp16)[name = tensor<string, []>("_inversed_scores_105_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_107_cast_fp16 = select(a = var_12_to_fp16, b = _inversed_scores_105_cast_fp16, cond = mask_3)[name = tensor<string, []>("scores_107_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_4846_cast_fp16 = softmax(axis = var_30, x = scores_107_cast_fp16)[name = tensor<string, []>("op_4846_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_1385_cast_fp16 = select(a = var_11_to_fp16, b = var_4846_cast_fp16, cond = mask_3)[name = tensor<string, []>("input_1385_cast_fp16")];
            tensor<bool, []> x_585_transpose_x_0 = const()[name = tensor<string, []>("x_585_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_585_transpose_y_0 = const()[name = tensor<string, []>("x_585_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 188, 128]> value_55_cast_fp16 = transpose(perm = value_55_perm_0, x = v_53_cast_fp16)[name = tensor<string, []>("transpose_201")];
            tensor<fp16, [1, 8, 188, 128]> x_585_cast_fp16 = matmul(transpose_x = x_585_transpose_x_0, transpose_y = x_585_transpose_y_0, x = input_1385_cast_fp16, y = value_55_cast_fp16)[name = tensor<string, []>("x_585_cast_fp16")];
            tensor<int32, [4]> var_4850_perm_0 = const()[name = tensor<string, []>("op_4850_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_4851 = const()[name = tensor<string, []>("op_4851"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_4850_cast_fp16 = transpose(perm = var_4850_perm_0, x = x_585_cast_fp16)[name = tensor<string, []>("transpose_197")];
            tensor<fp16, [1, 188, 1024]> input_1387_cast_fp16 = reshape(shape = var_4851, x = var_4850_cast_fp16)[name = tensor<string, []>("input_1387_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_26_self_attn_linear_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_26_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1308736256)))];
            tensor<fp16, [1024]> encoder_layers_26_self_attn_linear_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_26_self_attn_linear_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1310833472)))];
            tensor<fp16, [1, 188, 1024]> linear_241_cast_fp16 = linear(bias = encoder_layers_26_self_attn_linear_out_bias_to_fp16, weight = encoder_layers_26_self_attn_linear_out_weight_to_fp16, x = input_1387_cast_fp16)[name = tensor<string, []>("linear_241_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1391_cast_fp16 = add(x = input_1383_cast_fp16, y = linear_241_cast_fp16)[name = tensor<string, []>("input_1391_cast_fp16")];
            tensor<int32, [1]> x_589_axes_0 = const()[name = tensor<string, []>("x_589_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_26_norm_conv_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_26_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1310835584)))];
            tensor<fp16, [1024]> encoder_layers_26_norm_conv_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_26_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1310837696)))];
            tensor<fp16, [1, 188, 1024]> x_589_cast_fp16 = layer_norm(axes = x_589_axes_0, beta = encoder_layers_26_norm_conv_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_26_norm_conv_weight_to_fp16, x = input_1391_cast_fp16)[name = tensor<string, []>("x_589_cast_fp16")];
            tensor<int32, [3]> input_1393_perm_0 = const()[name = tensor<string, []>("input_1393_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> input_1395_pad_type_0 = const()[name = tensor<string, []>("input_1395_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_1395_strides_0 = const()[name = tensor<string, []>("input_1395_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1395_pad_0 = const()[name = tensor<string, []>("input_1395_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1395_dilations_0 = const()[name = tensor<string, []>("input_1395_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_1395_groups_0 = const()[name = tensor<string, []>("input_1395_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [2048, 1024, 1]> encoder_layers_26_conv_pointwise_conv1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_26_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1310839808)))];
            tensor<fp16, [2048]> encoder_layers_26_conv_pointwise_conv1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_26_conv_pointwise_conv1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1315034176)))];
            tensor<fp16, [1, 1024, 188]> input_1393_cast_fp16 = transpose(perm = input_1393_perm_0, x = x_589_cast_fp16)[name = tensor<string, []>("transpose_196")];
            tensor<fp16, [1, 2048, 188]> input_1395_cast_fp16 = conv(bias = encoder_layers_26_conv_pointwise_conv1_bias_to_fp16, dilations = input_1395_dilations_0, groups = input_1395_groups_0, pad = input_1395_pad_0, pad_type = input_1395_pad_type_0, strides = input_1395_strides_0, weight = encoder_layers_26_conv_pointwise_conv1_weight_to_fp16, x = input_1393_cast_fp16)[name = tensor<string, []>("input_1395_cast_fp16")];
            tensor<int32, []> x_591_split_num_splits_0 = const()[name = tensor<string, []>("x_591_split_num_splits_0"), val = tensor<int32, []>(2)];
            tensor<int32, []> x_591_split_axis_0 = const()[name = tensor<string, []>("x_591_split_axis_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1, 1024, 188]> x_591_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_591_split_cast_fp16_1 = split(axis = x_591_split_axis_0, num_splits = x_591_split_num_splits_0, x = input_1395_cast_fp16)[name = tensor<string, []>("x_591_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_591_split_1_sigmoid_cast_fp16 = sigmoid(x = x_591_split_cast_fp16_1)[name = tensor<string, []>("x_591_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_591_cast_fp16 = mul(x = x_591_split_cast_fp16_0, y = x_591_split_1_sigmoid_cast_fp16)[name = tensor<string, []>("x_591_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_1397_cast_fp16 = select(a = var_11_to_fp16, b = x_591_cast_fp16, cond = var_351)[name = tensor<string, []>("input_1397_cast_fp16")];
            tensor<int32, [6]> input_1399_pad_0 = const()[name = tensor<string, []>("input_1399_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            tensor<string, []> input_1399_mode_0 = const()[name = tensor<string, []>("input_1399_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_277_to_fp16 = const()[name = tensor<string, []>("const_277_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_1399_cast_fp16 = pad(constant_val = const_277_to_fp16, mode = input_1399_mode_0, pad = input_1399_pad_0, x = input_1397_cast_fp16)[name = tensor<string, []>("input_1399_cast_fp16")];
            tensor<string, []> input_1401_pad_type_0 = const()[name = tensor<string, []>("input_1401_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, []> input_1401_groups_0 = const()[name = tensor<string, []>("input_1401_groups_0"), val = tensor<int32, []>(1024)];
            tensor<int32, [1]> input_1401_strides_0 = const()[name = tensor<string, []>("input_1401_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1401_pad_0 = const()[name = tensor<string, []>("input_1401_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1401_dilations_0 = const()[name = tensor<string, []>("input_1401_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_380_to_fp16 = const()[name = tensor<string, []>("const_380_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1315038336)))];
            tensor<fp16, [1024]> const_381_to_fp16 = const()[name = tensor<string, []>("const_381_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1315056832)))];
            tensor<fp16, [1, 1024, 188]> input_1403_cast_fp16 = conv(bias = const_381_to_fp16, dilations = input_1401_dilations_0, groups = input_1401_groups_0, pad = input_1401_pad_0, pad_type = input_1401_pad_type_0, strides = input_1401_strides_0, weight = const_380_to_fp16, x = input_1399_cast_fp16)[name = tensor<string, []>("input_1403_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_1405_cast_fp16 = silu(x = input_1403_cast_fp16)[name = tensor<string, []>("input_1405_cast_fp16")];
            tensor<string, []> x_593_pad_type_0 = const()[name = tensor<string, []>("x_593_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> x_593_strides_0 = const()[name = tensor<string, []>("x_593_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_593_pad_0 = const()[name = tensor<string, []>("x_593_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_593_dilations_0 = const()[name = tensor<string, []>("x_593_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> x_593_groups_0 = const()[name = tensor<string, []>("x_593_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1024, 1024, 1]> encoder_layers_26_conv_pointwise_conv2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_26_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1315058944)))];
            tensor<fp16, [1024]> encoder_layers_26_conv_pointwise_conv2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_26_conv_pointwise_conv2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1317156160)))];
            tensor<fp16, [1, 1024, 188]> x_593_cast_fp16 = conv(bias = encoder_layers_26_conv_pointwise_conv2_bias_to_fp16, dilations = x_593_dilations_0, groups = x_593_groups_0, pad = x_593_pad_0, pad_type = x_593_pad_type_0, strides = x_593_strides_0, weight = encoder_layers_26_conv_pointwise_conv2_weight_to_fp16, x = input_1405_cast_fp16)[name = tensor<string, []>("x_593_cast_fp16")];
            tensor<int32, [3]> input_1407_perm_0 = const()[name = tensor<string, []>("input_1407_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_1407_cast_fp16 = transpose(perm = input_1407_perm_0, x = x_593_cast_fp16)[name = tensor<string, []>("transpose_195")];
            tensor<fp16, [1, 188, 1024]> input_1409_cast_fp16 = add(x = input_1391_cast_fp16, y = input_1407_cast_fp16)[name = tensor<string, []>("input_1409_cast_fp16")];
            tensor<int32, [1]> input_1411_axes_0 = const()[name = tensor<string, []>("input_1411_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_26_norm_feed_forward2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_26_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1317158272)))];
            tensor<fp16, [1024]> encoder_layers_26_norm_feed_forward2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_26_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1317160384)))];
            tensor<fp16, [1, 188, 1024]> input_1411_cast_fp16 = layer_norm(axes = input_1411_axes_0, beta = encoder_layers_26_norm_feed_forward2_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_26_norm_feed_forward2_weight_to_fp16, x = input_1409_cast_fp16)[name = tensor<string, []>("input_1411_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_26_feed_forward2_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_26_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1317162496)))];
            tensor<fp16, [4096]> encoder_layers_26_feed_forward2_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_26_feed_forward2_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1325551168)))];
            tensor<fp16, [1, 188, 4096]> linear_242_cast_fp16 = linear(bias = encoder_layers_26_feed_forward2_linear1_bias_to_fp16, weight = encoder_layers_26_feed_forward2_linear1_weight_to_fp16, x = input_1411_cast_fp16)[name = tensor<string, []>("linear_242_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_1415_cast_fp16 = silu(x = linear_242_cast_fp16)[name = tensor<string, []>("input_1415_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_26_feed_forward2_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_26_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1325559424)))];
            tensor<fp16, [1024]> encoder_layers_26_feed_forward2_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_26_feed_forward2_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1333948096)))];
            tensor<fp16, [1, 188, 1024]> linear_243_cast_fp16 = linear(bias = encoder_layers_26_feed_forward2_linear2_bias_to_fp16, weight = encoder_layers_26_feed_forward2_linear2_weight_to_fp16, x = input_1415_cast_fp16)[name = tensor<string, []>("linear_243_cast_fp16")];
            tensor<fp16, []> var_4917_to_fp16 = const()[name = tensor<string, []>("op_4917_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_4918_cast_fp16 = mul(x = linear_243_cast_fp16, y = var_4917_to_fp16)[name = tensor<string, []>("op_4918_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1421_cast_fp16 = add(x = input_1409_cast_fp16, y = var_4918_cast_fp16)[name = tensor<string, []>("input_1421_cast_fp16")];
            tensor<int32, [1]> input_1423_axes_0 = const()[name = tensor<string, []>("input_1423_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_26_norm_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_26_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1333950208)))];
            tensor<fp16, [1024]> encoder_layers_26_norm_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_26_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1333952320)))];
            tensor<fp16, [1, 188, 1024]> input_1423_cast_fp16 = layer_norm(axes = input_1423_axes_0, beta = encoder_layers_26_norm_out_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_26_norm_out_weight_to_fp16, x = input_1421_cast_fp16)[name = tensor<string, []>("input_1423_cast_fp16")];
            tensor<int32, [1]> input_1425_axes_0 = const()[name = tensor<string, []>("input_1425_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_27_norm_feed_forward1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_27_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1333954432)))];
            tensor<fp16, [1024]> encoder_layers_27_norm_feed_forward1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_27_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1333956544)))];
            tensor<fp16, [1, 188, 1024]> input_1425_cast_fp16 = layer_norm(axes = input_1425_axes_0, beta = encoder_layers_27_norm_feed_forward1_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_27_norm_feed_forward1_weight_to_fp16, x = input_1423_cast_fp16)[name = tensor<string, []>("input_1425_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_27_feed_forward1_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_27_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1333958656)))];
            tensor<fp16, [4096]> encoder_layers_27_feed_forward1_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_27_feed_forward1_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1342347328)))];
            tensor<fp16, [1, 188, 4096]> linear_244_cast_fp16 = linear(bias = encoder_layers_27_feed_forward1_linear1_bias_to_fp16, weight = encoder_layers_27_feed_forward1_linear1_weight_to_fp16, x = input_1425_cast_fp16)[name = tensor<string, []>("linear_244_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_1429_cast_fp16 = silu(x = linear_244_cast_fp16)[name = tensor<string, []>("input_1429_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_27_feed_forward1_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_27_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1342355584)))];
            tensor<fp16, [1024]> encoder_layers_27_feed_forward1_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_27_feed_forward1_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1350744256)))];
            tensor<fp16, [1, 188, 1024]> linear_245_cast_fp16 = linear(bias = encoder_layers_27_feed_forward1_linear2_bias_to_fp16, weight = encoder_layers_27_feed_forward1_linear2_weight_to_fp16, x = input_1429_cast_fp16)[name = tensor<string, []>("linear_245_cast_fp16")];
            tensor<fp16, []> var_4948_to_fp16 = const()[name = tensor<string, []>("op_4948_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_4949_cast_fp16 = mul(x = linear_245_cast_fp16, y = var_4948_to_fp16)[name = tensor<string, []>("op_4949_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1435_cast_fp16 = add(x = input_1423_cast_fp16, y = var_4949_cast_fp16)[name = tensor<string, []>("input_1435_cast_fp16")];
            tensor<int32, [1]> query_55_axes_0 = const()[name = tensor<string, []>("query_55_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_27_norm_self_att_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_27_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1350746368)))];
            tensor<fp16, [1024]> encoder_layers_27_norm_self_att_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_27_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1350748480)))];
            tensor<fp16, [1, 188, 1024]> query_55_cast_fp16 = layer_norm(axes = query_55_axes_0, beta = encoder_layers_27_norm_self_att_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_27_norm_self_att_weight_to_fp16, x = input_1435_cast_fp16)[name = tensor<string, []>("query_55_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_27_self_attn_linear_q_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_27_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1350750592)))];
            tensor<fp16, [1024]> encoder_layers_27_self_attn_linear_q_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_27_self_attn_linear_q_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1352847808)))];
            tensor<fp16, [1, 188, 1024]> linear_246_cast_fp16 = linear(bias = encoder_layers_27_self_attn_linear_q_bias_to_fp16, weight = encoder_layers_27_self_attn_linear_q_weight_to_fp16, x = query_55_cast_fp16)[name = tensor<string, []>("linear_246_cast_fp16")];
            tensor<int32, [4]> var_4966 = const()[name = tensor<string, []>("op_4966"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_163_cast_fp16 = reshape(shape = var_4966, x = linear_246_cast_fp16)[name = tensor<string, []>("q_163_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_27_self_attn_linear_k_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_27_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1352849920)))];
            tensor<fp16, [1024]> encoder_layers_27_self_attn_linear_k_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_27_self_attn_linear_k_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1354947136)))];
            tensor<fp16, [1, 188, 1024]> linear_247_cast_fp16 = linear(bias = encoder_layers_27_self_attn_linear_k_bias_to_fp16, weight = encoder_layers_27_self_attn_linear_k_weight_to_fp16, x = query_55_cast_fp16)[name = tensor<string, []>("linear_247_cast_fp16")];
            tensor<int32, [4]> var_4971 = const()[name = tensor<string, []>("op_4971"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_109_cast_fp16 = reshape(shape = var_4971, x = linear_247_cast_fp16)[name = tensor<string, []>("k_109_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_27_self_attn_linear_v_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_27_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1354949248)))];
            tensor<fp16, [1024]> encoder_layers_27_self_attn_linear_v_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_27_self_attn_linear_v_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1357046464)))];
            tensor<fp16, [1, 188, 1024]> linear_248_cast_fp16 = linear(bias = encoder_layers_27_self_attn_linear_v_bias_to_fp16, weight = encoder_layers_27_self_attn_linear_v_weight_to_fp16, x = query_55_cast_fp16)[name = tensor<string, []>("linear_248_cast_fp16")];
            tensor<int32, [4]> var_4976 = const()[name = tensor<string, []>("op_4976"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_55_cast_fp16 = reshape(shape = var_4976, x = linear_248_cast_fp16)[name = tensor<string, []>("v_55_cast_fp16")];
            tensor<int32, [4]> value_57_perm_0 = const()[name = tensor<string, []>("value_57_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> encoder_layers_27_self_attn_pos_bias_u_to_fp16 = const()[name = tensor<string, []>("encoder_layers_27_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1357048576)))];
            tensor<fp16, [1, 188, 8, 128]> var_4988_cast_fp16 = add(x = q_163_cast_fp16, y = encoder_layers_27_self_attn_pos_bias_u_to_fp16)[name = tensor<string, []>("op_4988_cast_fp16")];
            tensor<fp16, [8, 128]> encoder_layers_27_self_attn_pos_bias_v_to_fp16 = const()[name = tensor<string, []>("encoder_layers_27_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1357050688)))];
            tensor<fp16, [1, 188, 8, 128]> var_4990_cast_fp16 = add(x = q_163_cast_fp16, y = encoder_layers_27_self_attn_pos_bias_v_to_fp16)[name = tensor<string, []>("op_4990_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_55_perm_0 = const()[name = tensor<string, []>("q_with_bias_v_55_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<bool, []> x_601_transpose_x_0 = const()[name = tensor<string, []>("x_601_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_601_transpose_y_0 = const()[name = tensor<string, []>("x_601_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 128, 375]> var_4992_to_fp16 = const()[name = tensor<string, []>("op_4992_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1357052800)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_55_cast_fp16 = transpose(perm = q_with_bias_v_55_perm_0, x = var_4990_cast_fp16)[name = tensor<string, []>("transpose_193")];
            tensor<fp16, [1, 8, 188, 375]> x_601_cast_fp16 = matmul(transpose_x = x_601_transpose_x_0, transpose_y = x_601_transpose_y_0, x = q_with_bias_v_55_cast_fp16, y = var_4992_to_fp16)[name = tensor<string, []>("x_601_cast_fp16")];
            tensor<int32, [8]> x_603_pad_0 = const()[name = tensor<string, []>("x_603_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            tensor<string, []> x_603_mode_0 = const()[name = tensor<string, []>("x_603_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_284_to_fp16 = const()[name = tensor<string, []>("const_284_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_603_cast_fp16 = pad(constant_val = const_284_to_fp16, mode = x_603_mode_0, pad = x_603_pad_0, x = x_601_cast_fp16)[name = tensor<string, []>("x_603_cast_fp16")];
            tensor<int32, [4]> var_5000 = const()[name = tensor<string, []>("op_5000"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_605_cast_fp16 = reshape(shape = var_5000, x = x_603_cast_fp16)[name = tensor<string, []>("x_605_cast_fp16")];
            tensor<int32, [4]> var_5004_begin_0 = const()[name = tensor<string, []>("op_5004_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_5004_end_0 = const()[name = tensor<string, []>("op_5004_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_5004_end_mask_0 = const()[name = tensor<string, []>("op_5004_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_5004_cast_fp16 = slice_by_index(begin = var_5004_begin_0, end = var_5004_end_0, end_mask = var_5004_end_mask_0, x = x_605_cast_fp16)[name = tensor<string, []>("op_5004_cast_fp16")];
            tensor<int32, [4]> var_5005 = const()[name = tensor<string, []>("op_5005"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_109_cast_fp16 = reshape(shape = var_5005, x = var_5004_cast_fp16)[name = tensor<string, []>("matrix_bd_109_cast_fp16")];
            tensor<bool, []> matrix_ac_55_transpose_x_0 = const()[name = tensor<string, []>("matrix_ac_55_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> matrix_ac_55_transpose_y_0 = const()[name = tensor<string, []>("matrix_ac_55_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<int32, [4]> transpose_150_perm_0 = const()[name = tensor<string, []>("transpose_150_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_151_perm_0 = const()[name = tensor<string, []>("transpose_151_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_151 = transpose(perm = transpose_151_perm_0, x = k_109_cast_fp16)[name = tensor<string, []>("transpose_191")];
            tensor<fp16, [1, 8, 188, 128]> transpose_150 = transpose(perm = transpose_150_perm_0, x = var_4988_cast_fp16)[name = tensor<string, []>("transpose_192")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_55_cast_fp16 = matmul(transpose_x = matrix_ac_55_transpose_x_0, transpose_y = matrix_ac_55_transpose_y_0, x = transpose_150, y = transpose_151)[name = tensor<string, []>("matrix_ac_55_cast_fp16")];
            tensor<int32, [4]> matrix_bd_111_begin_0 = const()[name = tensor<string, []>("matrix_bd_111_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_111_end_0 = const()[name = tensor<string, []>("matrix_bd_111_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_111_end_mask_0 = const()[name = tensor<string, []>("matrix_bd_111_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_111_cast_fp16 = slice_by_index(begin = matrix_bd_111_begin_0, end = matrix_bd_111_end_0, end_mask = matrix_bd_111_end_mask_0, x = matrix_bd_109_cast_fp16)[name = tensor<string, []>("matrix_bd_111_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_5014_cast_fp16 = add(x = matrix_ac_55_cast_fp16, y = matrix_bd_111_cast_fp16)[name = tensor<string, []>("op_5014_cast_fp16")];
            tensor<fp16, []> _inversed_scores_109_y_0_to_fp16 = const()[name = tensor<string, []>("_inversed_scores_109_y_0_to_fp16"), val = tensor<fp16, []>(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_109_cast_fp16 = mul(x = var_5014_cast_fp16, y = _inversed_scores_109_y_0_to_fp16)[name = tensor<string, []>("_inversed_scores_109_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_111_cast_fp16 = select(a = var_12_to_fp16, b = _inversed_scores_109_cast_fp16, cond = mask_3)[name = tensor<string, []>("scores_111_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_5020_cast_fp16 = softmax(axis = var_30, x = scores_111_cast_fp16)[name = tensor<string, []>("op_5020_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_1437_cast_fp16 = select(a = var_11_to_fp16, b = var_5020_cast_fp16, cond = mask_3)[name = tensor<string, []>("input_1437_cast_fp16")];
            tensor<bool, []> x_607_transpose_x_0 = const()[name = tensor<string, []>("x_607_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_607_transpose_y_0 = const()[name = tensor<string, []>("x_607_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 188, 128]> value_57_cast_fp16 = transpose(perm = value_57_perm_0, x = v_55_cast_fp16)[name = tensor<string, []>("transpose_194")];
            tensor<fp16, [1, 8, 188, 128]> x_607_cast_fp16 = matmul(transpose_x = x_607_transpose_x_0, transpose_y = x_607_transpose_y_0, x = input_1437_cast_fp16, y = value_57_cast_fp16)[name = tensor<string, []>("x_607_cast_fp16")];
            tensor<int32, [4]> var_5024_perm_0 = const()[name = tensor<string, []>("op_5024_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_5025 = const()[name = tensor<string, []>("op_5025"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_5024_cast_fp16 = transpose(perm = var_5024_perm_0, x = x_607_cast_fp16)[name = tensor<string, []>("transpose_190")];
            tensor<fp16, [1, 188, 1024]> input_1439_cast_fp16 = reshape(shape = var_5025, x = var_5024_cast_fp16)[name = tensor<string, []>("input_1439_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_27_self_attn_linear_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_27_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1357820864)))];
            tensor<fp16, [1024]> encoder_layers_27_self_attn_linear_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_27_self_attn_linear_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1359918080)))];
            tensor<fp16, [1, 188, 1024]> linear_250_cast_fp16 = linear(bias = encoder_layers_27_self_attn_linear_out_bias_to_fp16, weight = encoder_layers_27_self_attn_linear_out_weight_to_fp16, x = input_1439_cast_fp16)[name = tensor<string, []>("linear_250_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1443_cast_fp16 = add(x = input_1435_cast_fp16, y = linear_250_cast_fp16)[name = tensor<string, []>("input_1443_cast_fp16")];
            tensor<int32, [1]> x_611_axes_0 = const()[name = tensor<string, []>("x_611_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_27_norm_conv_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_27_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1359920192)))];
            tensor<fp16, [1024]> encoder_layers_27_norm_conv_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_27_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1359922304)))];
            tensor<fp16, [1, 188, 1024]> x_611_cast_fp16 = layer_norm(axes = x_611_axes_0, beta = encoder_layers_27_norm_conv_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_27_norm_conv_weight_to_fp16, x = input_1443_cast_fp16)[name = tensor<string, []>("x_611_cast_fp16")];
            tensor<int32, [3]> input_1445_perm_0 = const()[name = tensor<string, []>("input_1445_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> input_1447_pad_type_0 = const()[name = tensor<string, []>("input_1447_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_1447_strides_0 = const()[name = tensor<string, []>("input_1447_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1447_pad_0 = const()[name = tensor<string, []>("input_1447_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1447_dilations_0 = const()[name = tensor<string, []>("input_1447_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_1447_groups_0 = const()[name = tensor<string, []>("input_1447_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [2048, 1024, 1]> encoder_layers_27_conv_pointwise_conv1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_27_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1359924416)))];
            tensor<fp16, [2048]> encoder_layers_27_conv_pointwise_conv1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_27_conv_pointwise_conv1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1364118784)))];
            tensor<fp16, [1, 1024, 188]> input_1445_cast_fp16 = transpose(perm = input_1445_perm_0, x = x_611_cast_fp16)[name = tensor<string, []>("transpose_189")];
            tensor<fp16, [1, 2048, 188]> input_1447_cast_fp16 = conv(bias = encoder_layers_27_conv_pointwise_conv1_bias_to_fp16, dilations = input_1447_dilations_0, groups = input_1447_groups_0, pad = input_1447_pad_0, pad_type = input_1447_pad_type_0, strides = input_1447_strides_0, weight = encoder_layers_27_conv_pointwise_conv1_weight_to_fp16, x = input_1445_cast_fp16)[name = tensor<string, []>("input_1447_cast_fp16")];
            tensor<int32, []> x_613_split_num_splits_0 = const()[name = tensor<string, []>("x_613_split_num_splits_0"), val = tensor<int32, []>(2)];
            tensor<int32, []> x_613_split_axis_0 = const()[name = tensor<string, []>("x_613_split_axis_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1, 1024, 188]> x_613_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_613_split_cast_fp16_1 = split(axis = x_613_split_axis_0, num_splits = x_613_split_num_splits_0, x = input_1447_cast_fp16)[name = tensor<string, []>("x_613_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_613_split_1_sigmoid_cast_fp16 = sigmoid(x = x_613_split_cast_fp16_1)[name = tensor<string, []>("x_613_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_613_cast_fp16 = mul(x = x_613_split_cast_fp16_0, y = x_613_split_1_sigmoid_cast_fp16)[name = tensor<string, []>("x_613_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_1449_cast_fp16 = select(a = var_11_to_fp16, b = x_613_cast_fp16, cond = var_351)[name = tensor<string, []>("input_1449_cast_fp16")];
            tensor<int32, [6]> input_1451_pad_0 = const()[name = tensor<string, []>("input_1451_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            tensor<string, []> input_1451_mode_0 = const()[name = tensor<string, []>("input_1451_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_287_to_fp16 = const()[name = tensor<string, []>("const_287_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_1451_cast_fp16 = pad(constant_val = const_287_to_fp16, mode = input_1451_mode_0, pad = input_1451_pad_0, x = input_1449_cast_fp16)[name = tensor<string, []>("input_1451_cast_fp16")];
            tensor<string, []> input_1453_pad_type_0 = const()[name = tensor<string, []>("input_1453_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, []> input_1453_groups_0 = const()[name = tensor<string, []>("input_1453_groups_0"), val = tensor<int32, []>(1024)];
            tensor<int32, [1]> input_1453_strides_0 = const()[name = tensor<string, []>("input_1453_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1453_pad_0 = const()[name = tensor<string, []>("input_1453_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1453_dilations_0 = const()[name = tensor<string, []>("input_1453_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_382_to_fp16 = const()[name = tensor<string, []>("const_382_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1364122944)))];
            tensor<fp16, [1024]> const_383_to_fp16 = const()[name = tensor<string, []>("const_383_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1364141440)))];
            tensor<fp16, [1, 1024, 188]> input_1455_cast_fp16 = conv(bias = const_383_to_fp16, dilations = input_1453_dilations_0, groups = input_1453_groups_0, pad = input_1453_pad_0, pad_type = input_1453_pad_type_0, strides = input_1453_strides_0, weight = const_382_to_fp16, x = input_1451_cast_fp16)[name = tensor<string, []>("input_1455_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_1457_cast_fp16 = silu(x = input_1455_cast_fp16)[name = tensor<string, []>("input_1457_cast_fp16")];
            tensor<string, []> x_615_pad_type_0 = const()[name = tensor<string, []>("x_615_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> x_615_strides_0 = const()[name = tensor<string, []>("x_615_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_615_pad_0 = const()[name = tensor<string, []>("x_615_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_615_dilations_0 = const()[name = tensor<string, []>("x_615_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> x_615_groups_0 = const()[name = tensor<string, []>("x_615_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1024, 1024, 1]> encoder_layers_27_conv_pointwise_conv2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_27_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1364143552)))];
            tensor<fp16, [1024]> encoder_layers_27_conv_pointwise_conv2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_27_conv_pointwise_conv2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1366240768)))];
            tensor<fp16, [1, 1024, 188]> x_615_cast_fp16 = conv(bias = encoder_layers_27_conv_pointwise_conv2_bias_to_fp16, dilations = x_615_dilations_0, groups = x_615_groups_0, pad = x_615_pad_0, pad_type = x_615_pad_type_0, strides = x_615_strides_0, weight = encoder_layers_27_conv_pointwise_conv2_weight_to_fp16, x = input_1457_cast_fp16)[name = tensor<string, []>("x_615_cast_fp16")];
            tensor<int32, [3]> input_1459_perm_0 = const()[name = tensor<string, []>("input_1459_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_1459_cast_fp16 = transpose(perm = input_1459_perm_0, x = x_615_cast_fp16)[name = tensor<string, []>("transpose_188")];
            tensor<fp16, [1, 188, 1024]> input_1461_cast_fp16 = add(x = input_1443_cast_fp16, y = input_1459_cast_fp16)[name = tensor<string, []>("input_1461_cast_fp16")];
            tensor<int32, [1]> input_1463_axes_0 = const()[name = tensor<string, []>("input_1463_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_27_norm_feed_forward2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_27_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1366242880)))];
            tensor<fp16, [1024]> encoder_layers_27_norm_feed_forward2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_27_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1366244992)))];
            tensor<fp16, [1, 188, 1024]> input_1463_cast_fp16 = layer_norm(axes = input_1463_axes_0, beta = encoder_layers_27_norm_feed_forward2_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_27_norm_feed_forward2_weight_to_fp16, x = input_1461_cast_fp16)[name = tensor<string, []>("input_1463_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_27_feed_forward2_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_27_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1366247104)))];
            tensor<fp16, [4096]> encoder_layers_27_feed_forward2_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_27_feed_forward2_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1374635776)))];
            tensor<fp16, [1, 188, 4096]> linear_251_cast_fp16 = linear(bias = encoder_layers_27_feed_forward2_linear1_bias_to_fp16, weight = encoder_layers_27_feed_forward2_linear1_weight_to_fp16, x = input_1463_cast_fp16)[name = tensor<string, []>("linear_251_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_1467_cast_fp16 = silu(x = linear_251_cast_fp16)[name = tensor<string, []>("input_1467_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_27_feed_forward2_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_27_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1374644032)))];
            tensor<fp16, [1024]> encoder_layers_27_feed_forward2_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_27_feed_forward2_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1383032704)))];
            tensor<fp16, [1, 188, 1024]> linear_252_cast_fp16 = linear(bias = encoder_layers_27_feed_forward2_linear2_bias_to_fp16, weight = encoder_layers_27_feed_forward2_linear2_weight_to_fp16, x = input_1467_cast_fp16)[name = tensor<string, []>("linear_252_cast_fp16")];
            tensor<fp16, []> var_5091_to_fp16 = const()[name = tensor<string, []>("op_5091_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_5092_cast_fp16 = mul(x = linear_252_cast_fp16, y = var_5091_to_fp16)[name = tensor<string, []>("op_5092_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1473_cast_fp16 = add(x = input_1461_cast_fp16, y = var_5092_cast_fp16)[name = tensor<string, []>("input_1473_cast_fp16")];
            tensor<int32, [1]> input_1475_axes_0 = const()[name = tensor<string, []>("input_1475_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_27_norm_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_27_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1383034816)))];
            tensor<fp16, [1024]> encoder_layers_27_norm_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_27_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1383036928)))];
            tensor<fp16, [1, 188, 1024]> input_1475_cast_fp16 = layer_norm(axes = input_1475_axes_0, beta = encoder_layers_27_norm_out_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_27_norm_out_weight_to_fp16, x = input_1473_cast_fp16)[name = tensor<string, []>("input_1475_cast_fp16")];
            tensor<int32, [1]> input_1477_axes_0 = const()[name = tensor<string, []>("input_1477_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_28_norm_feed_forward1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_28_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1383039040)))];
            tensor<fp16, [1024]> encoder_layers_28_norm_feed_forward1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_28_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1383041152)))];
            tensor<fp16, [1, 188, 1024]> input_1477_cast_fp16 = layer_norm(axes = input_1477_axes_0, beta = encoder_layers_28_norm_feed_forward1_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_28_norm_feed_forward1_weight_to_fp16, x = input_1475_cast_fp16)[name = tensor<string, []>("input_1477_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_28_feed_forward1_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_28_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1383043264)))];
            tensor<fp16, [4096]> encoder_layers_28_feed_forward1_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_28_feed_forward1_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1391431936)))];
            tensor<fp16, [1, 188, 4096]> linear_253_cast_fp16 = linear(bias = encoder_layers_28_feed_forward1_linear1_bias_to_fp16, weight = encoder_layers_28_feed_forward1_linear1_weight_to_fp16, x = input_1477_cast_fp16)[name = tensor<string, []>("linear_253_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_1481_cast_fp16 = silu(x = linear_253_cast_fp16)[name = tensor<string, []>("input_1481_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_28_feed_forward1_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_28_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1391440192)))];
            tensor<fp16, [1024]> encoder_layers_28_feed_forward1_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_28_feed_forward1_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1399828864)))];
            tensor<fp16, [1, 188, 1024]> linear_254_cast_fp16 = linear(bias = encoder_layers_28_feed_forward1_linear2_bias_to_fp16, weight = encoder_layers_28_feed_forward1_linear2_weight_to_fp16, x = input_1481_cast_fp16)[name = tensor<string, []>("linear_254_cast_fp16")];
            tensor<fp16, []> var_5122_to_fp16 = const()[name = tensor<string, []>("op_5122_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_5123_cast_fp16 = mul(x = linear_254_cast_fp16, y = var_5122_to_fp16)[name = tensor<string, []>("op_5123_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1487_cast_fp16 = add(x = input_1475_cast_fp16, y = var_5123_cast_fp16)[name = tensor<string, []>("input_1487_cast_fp16")];
            tensor<int32, [1]> query_57_axes_0 = const()[name = tensor<string, []>("query_57_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_28_norm_self_att_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_28_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1399830976)))];
            tensor<fp16, [1024]> encoder_layers_28_norm_self_att_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_28_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1399833088)))];
            tensor<fp16, [1, 188, 1024]> query_57_cast_fp16 = layer_norm(axes = query_57_axes_0, beta = encoder_layers_28_norm_self_att_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_28_norm_self_att_weight_to_fp16, x = input_1487_cast_fp16)[name = tensor<string, []>("query_57_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_28_self_attn_linear_q_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_28_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1399835200)))];
            tensor<fp16, [1024]> encoder_layers_28_self_attn_linear_q_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_28_self_attn_linear_q_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1401932416)))];
            tensor<fp16, [1, 188, 1024]> linear_255_cast_fp16 = linear(bias = encoder_layers_28_self_attn_linear_q_bias_to_fp16, weight = encoder_layers_28_self_attn_linear_q_weight_to_fp16, x = query_57_cast_fp16)[name = tensor<string, []>("linear_255_cast_fp16")];
            tensor<int32, [4]> var_5140 = const()[name = tensor<string, []>("op_5140"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_169_cast_fp16 = reshape(shape = var_5140, x = linear_255_cast_fp16)[name = tensor<string, []>("q_169_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_28_self_attn_linear_k_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_28_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1401934528)))];
            tensor<fp16, [1024]> encoder_layers_28_self_attn_linear_k_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_28_self_attn_linear_k_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1404031744)))];
            tensor<fp16, [1, 188, 1024]> linear_256_cast_fp16 = linear(bias = encoder_layers_28_self_attn_linear_k_bias_to_fp16, weight = encoder_layers_28_self_attn_linear_k_weight_to_fp16, x = query_57_cast_fp16)[name = tensor<string, []>("linear_256_cast_fp16")];
            tensor<int32, [4]> var_5145 = const()[name = tensor<string, []>("op_5145"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_113_cast_fp16 = reshape(shape = var_5145, x = linear_256_cast_fp16)[name = tensor<string, []>("k_113_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_28_self_attn_linear_v_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_28_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1404033856)))];
            tensor<fp16, [1024]> encoder_layers_28_self_attn_linear_v_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_28_self_attn_linear_v_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1406131072)))];
            tensor<fp16, [1, 188, 1024]> linear_257_cast_fp16 = linear(bias = encoder_layers_28_self_attn_linear_v_bias_to_fp16, weight = encoder_layers_28_self_attn_linear_v_weight_to_fp16, x = query_57_cast_fp16)[name = tensor<string, []>("linear_257_cast_fp16")];
            tensor<int32, [4]> var_5150 = const()[name = tensor<string, []>("op_5150"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_57_cast_fp16 = reshape(shape = var_5150, x = linear_257_cast_fp16)[name = tensor<string, []>("v_57_cast_fp16")];
            tensor<int32, [4]> value_59_perm_0 = const()[name = tensor<string, []>("value_59_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> encoder_layers_28_self_attn_pos_bias_u_to_fp16 = const()[name = tensor<string, []>("encoder_layers_28_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1406133184)))];
            tensor<fp16, [1, 188, 8, 128]> var_5162_cast_fp16 = add(x = q_169_cast_fp16, y = encoder_layers_28_self_attn_pos_bias_u_to_fp16)[name = tensor<string, []>("op_5162_cast_fp16")];
            tensor<fp16, [8, 128]> encoder_layers_28_self_attn_pos_bias_v_to_fp16 = const()[name = tensor<string, []>("encoder_layers_28_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1406135296)))];
            tensor<fp16, [1, 188, 8, 128]> var_5164_cast_fp16 = add(x = q_169_cast_fp16, y = encoder_layers_28_self_attn_pos_bias_v_to_fp16)[name = tensor<string, []>("op_5164_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_57_perm_0 = const()[name = tensor<string, []>("q_with_bias_v_57_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<bool, []> x_623_transpose_x_0 = const()[name = tensor<string, []>("x_623_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_623_transpose_y_0 = const()[name = tensor<string, []>("x_623_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 128, 375]> var_5166_to_fp16 = const()[name = tensor<string, []>("op_5166_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1406137408)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_57_cast_fp16 = transpose(perm = q_with_bias_v_57_perm_0, x = var_5164_cast_fp16)[name = tensor<string, []>("transpose_186")];
            tensor<fp16, [1, 8, 188, 375]> x_623_cast_fp16 = matmul(transpose_x = x_623_transpose_x_0, transpose_y = x_623_transpose_y_0, x = q_with_bias_v_57_cast_fp16, y = var_5166_to_fp16)[name = tensor<string, []>("x_623_cast_fp16")];
            tensor<int32, [8]> x_625_pad_0 = const()[name = tensor<string, []>("x_625_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            tensor<string, []> x_625_mode_0 = const()[name = tensor<string, []>("x_625_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_294_to_fp16 = const()[name = tensor<string, []>("const_294_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_625_cast_fp16 = pad(constant_val = const_294_to_fp16, mode = x_625_mode_0, pad = x_625_pad_0, x = x_623_cast_fp16)[name = tensor<string, []>("x_625_cast_fp16")];
            tensor<int32, [4]> var_5174 = const()[name = tensor<string, []>("op_5174"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_627_cast_fp16 = reshape(shape = var_5174, x = x_625_cast_fp16)[name = tensor<string, []>("x_627_cast_fp16")];
            tensor<int32, [4]> var_5178_begin_0 = const()[name = tensor<string, []>("op_5178_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_5178_end_0 = const()[name = tensor<string, []>("op_5178_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_5178_end_mask_0 = const()[name = tensor<string, []>("op_5178_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_5178_cast_fp16 = slice_by_index(begin = var_5178_begin_0, end = var_5178_end_0, end_mask = var_5178_end_mask_0, x = x_627_cast_fp16)[name = tensor<string, []>("op_5178_cast_fp16")];
            tensor<int32, [4]> var_5179 = const()[name = tensor<string, []>("op_5179"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_113_cast_fp16 = reshape(shape = var_5179, x = var_5178_cast_fp16)[name = tensor<string, []>("matrix_bd_113_cast_fp16")];
            tensor<bool, []> matrix_ac_57_transpose_x_0 = const()[name = tensor<string, []>("matrix_ac_57_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> matrix_ac_57_transpose_y_0 = const()[name = tensor<string, []>("matrix_ac_57_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<int32, [4]> transpose_152_perm_0 = const()[name = tensor<string, []>("transpose_152_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_153_perm_0 = const()[name = tensor<string, []>("transpose_153_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_153 = transpose(perm = transpose_153_perm_0, x = k_113_cast_fp16)[name = tensor<string, []>("transpose_184")];
            tensor<fp16, [1, 8, 188, 128]> transpose_152 = transpose(perm = transpose_152_perm_0, x = var_5162_cast_fp16)[name = tensor<string, []>("transpose_185")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_57_cast_fp16 = matmul(transpose_x = matrix_ac_57_transpose_x_0, transpose_y = matrix_ac_57_transpose_y_0, x = transpose_152, y = transpose_153)[name = tensor<string, []>("matrix_ac_57_cast_fp16")];
            tensor<int32, [4]> matrix_bd_115_begin_0 = const()[name = tensor<string, []>("matrix_bd_115_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_115_end_0 = const()[name = tensor<string, []>("matrix_bd_115_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_115_end_mask_0 = const()[name = tensor<string, []>("matrix_bd_115_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_115_cast_fp16 = slice_by_index(begin = matrix_bd_115_begin_0, end = matrix_bd_115_end_0, end_mask = matrix_bd_115_end_mask_0, x = matrix_bd_113_cast_fp16)[name = tensor<string, []>("matrix_bd_115_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_5188_cast_fp16 = add(x = matrix_ac_57_cast_fp16, y = matrix_bd_115_cast_fp16)[name = tensor<string, []>("op_5188_cast_fp16")];
            tensor<fp16, []> _inversed_scores_113_y_0_to_fp16 = const()[name = tensor<string, []>("_inversed_scores_113_y_0_to_fp16"), val = tensor<fp16, []>(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_113_cast_fp16 = mul(x = var_5188_cast_fp16, y = _inversed_scores_113_y_0_to_fp16)[name = tensor<string, []>("_inversed_scores_113_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_115_cast_fp16 = select(a = var_12_to_fp16, b = _inversed_scores_113_cast_fp16, cond = mask_3)[name = tensor<string, []>("scores_115_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_5194_cast_fp16 = softmax(axis = var_30, x = scores_115_cast_fp16)[name = tensor<string, []>("op_5194_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_1489_cast_fp16 = select(a = var_11_to_fp16, b = var_5194_cast_fp16, cond = mask_3)[name = tensor<string, []>("input_1489_cast_fp16")];
            tensor<bool, []> x_629_transpose_x_0 = const()[name = tensor<string, []>("x_629_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_629_transpose_y_0 = const()[name = tensor<string, []>("x_629_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 188, 128]> value_59_cast_fp16 = transpose(perm = value_59_perm_0, x = v_57_cast_fp16)[name = tensor<string, []>("transpose_187")];
            tensor<fp16, [1, 8, 188, 128]> x_629_cast_fp16 = matmul(transpose_x = x_629_transpose_x_0, transpose_y = x_629_transpose_y_0, x = input_1489_cast_fp16, y = value_59_cast_fp16)[name = tensor<string, []>("x_629_cast_fp16")];
            tensor<int32, [4]> var_5198_perm_0 = const()[name = tensor<string, []>("op_5198_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_5199 = const()[name = tensor<string, []>("op_5199"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_5198_cast_fp16 = transpose(perm = var_5198_perm_0, x = x_629_cast_fp16)[name = tensor<string, []>("transpose_183")];
            tensor<fp16, [1, 188, 1024]> input_1491_cast_fp16 = reshape(shape = var_5199, x = var_5198_cast_fp16)[name = tensor<string, []>("input_1491_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_28_self_attn_linear_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_28_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1406905472)))];
            tensor<fp16, [1024]> encoder_layers_28_self_attn_linear_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_28_self_attn_linear_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1409002688)))];
            tensor<fp16, [1, 188, 1024]> linear_259_cast_fp16 = linear(bias = encoder_layers_28_self_attn_linear_out_bias_to_fp16, weight = encoder_layers_28_self_attn_linear_out_weight_to_fp16, x = input_1491_cast_fp16)[name = tensor<string, []>("linear_259_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1495_cast_fp16 = add(x = input_1487_cast_fp16, y = linear_259_cast_fp16)[name = tensor<string, []>("input_1495_cast_fp16")];
            tensor<int32, [1]> x_633_axes_0 = const()[name = tensor<string, []>("x_633_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_28_norm_conv_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_28_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1409004800)))];
            tensor<fp16, [1024]> encoder_layers_28_norm_conv_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_28_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1409006912)))];
            tensor<fp16, [1, 188, 1024]> x_633_cast_fp16 = layer_norm(axes = x_633_axes_0, beta = encoder_layers_28_norm_conv_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_28_norm_conv_weight_to_fp16, x = input_1495_cast_fp16)[name = tensor<string, []>("x_633_cast_fp16")];
            tensor<int32, [3]> input_1497_perm_0 = const()[name = tensor<string, []>("input_1497_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> input_1499_pad_type_0 = const()[name = tensor<string, []>("input_1499_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_1499_strides_0 = const()[name = tensor<string, []>("input_1499_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1499_pad_0 = const()[name = tensor<string, []>("input_1499_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1499_dilations_0 = const()[name = tensor<string, []>("input_1499_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_1499_groups_0 = const()[name = tensor<string, []>("input_1499_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [2048, 1024, 1]> encoder_layers_28_conv_pointwise_conv1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_28_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1409009024)))];
            tensor<fp16, [2048]> encoder_layers_28_conv_pointwise_conv1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_28_conv_pointwise_conv1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1413203392)))];
            tensor<fp16, [1, 1024, 188]> input_1497_cast_fp16 = transpose(perm = input_1497_perm_0, x = x_633_cast_fp16)[name = tensor<string, []>("transpose_182")];
            tensor<fp16, [1, 2048, 188]> input_1499_cast_fp16 = conv(bias = encoder_layers_28_conv_pointwise_conv1_bias_to_fp16, dilations = input_1499_dilations_0, groups = input_1499_groups_0, pad = input_1499_pad_0, pad_type = input_1499_pad_type_0, strides = input_1499_strides_0, weight = encoder_layers_28_conv_pointwise_conv1_weight_to_fp16, x = input_1497_cast_fp16)[name = tensor<string, []>("input_1499_cast_fp16")];
            tensor<int32, []> x_635_split_num_splits_0 = const()[name = tensor<string, []>("x_635_split_num_splits_0"), val = tensor<int32, []>(2)];
            tensor<int32, []> x_635_split_axis_0 = const()[name = tensor<string, []>("x_635_split_axis_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1, 1024, 188]> x_635_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_635_split_cast_fp16_1 = split(axis = x_635_split_axis_0, num_splits = x_635_split_num_splits_0, x = input_1499_cast_fp16)[name = tensor<string, []>("x_635_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_635_split_1_sigmoid_cast_fp16 = sigmoid(x = x_635_split_cast_fp16_1)[name = tensor<string, []>("x_635_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_635_cast_fp16 = mul(x = x_635_split_cast_fp16_0, y = x_635_split_1_sigmoid_cast_fp16)[name = tensor<string, []>("x_635_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_1501_cast_fp16 = select(a = var_11_to_fp16, b = x_635_cast_fp16, cond = var_351)[name = tensor<string, []>("input_1501_cast_fp16")];
            tensor<int32, [6]> input_1503_pad_0 = const()[name = tensor<string, []>("input_1503_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            tensor<string, []> input_1503_mode_0 = const()[name = tensor<string, []>("input_1503_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_297_to_fp16 = const()[name = tensor<string, []>("const_297_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_1503_cast_fp16 = pad(constant_val = const_297_to_fp16, mode = input_1503_mode_0, pad = input_1503_pad_0, x = input_1501_cast_fp16)[name = tensor<string, []>("input_1503_cast_fp16")];
            tensor<string, []> input_1505_pad_type_0 = const()[name = tensor<string, []>("input_1505_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, []> input_1505_groups_0 = const()[name = tensor<string, []>("input_1505_groups_0"), val = tensor<int32, []>(1024)];
            tensor<int32, [1]> input_1505_strides_0 = const()[name = tensor<string, []>("input_1505_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1505_pad_0 = const()[name = tensor<string, []>("input_1505_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1505_dilations_0 = const()[name = tensor<string, []>("input_1505_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_384_to_fp16 = const()[name = tensor<string, []>("const_384_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1413207552)))];
            tensor<fp16, [1024]> const_385_to_fp16 = const()[name = tensor<string, []>("const_385_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1413226048)))];
            tensor<fp16, [1, 1024, 188]> input_1507_cast_fp16 = conv(bias = const_385_to_fp16, dilations = input_1505_dilations_0, groups = input_1505_groups_0, pad = input_1505_pad_0, pad_type = input_1505_pad_type_0, strides = input_1505_strides_0, weight = const_384_to_fp16, x = input_1503_cast_fp16)[name = tensor<string, []>("input_1507_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_1509_cast_fp16 = silu(x = input_1507_cast_fp16)[name = tensor<string, []>("input_1509_cast_fp16")];
            tensor<string, []> x_637_pad_type_0 = const()[name = tensor<string, []>("x_637_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> x_637_strides_0 = const()[name = tensor<string, []>("x_637_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_637_pad_0 = const()[name = tensor<string, []>("x_637_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_637_dilations_0 = const()[name = tensor<string, []>("x_637_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> x_637_groups_0 = const()[name = tensor<string, []>("x_637_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1024, 1024, 1]> encoder_layers_28_conv_pointwise_conv2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_28_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1413228160)))];
            tensor<fp16, [1024]> encoder_layers_28_conv_pointwise_conv2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_28_conv_pointwise_conv2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1415325376)))];
            tensor<fp16, [1, 1024, 188]> x_637_cast_fp16 = conv(bias = encoder_layers_28_conv_pointwise_conv2_bias_to_fp16, dilations = x_637_dilations_0, groups = x_637_groups_0, pad = x_637_pad_0, pad_type = x_637_pad_type_0, strides = x_637_strides_0, weight = encoder_layers_28_conv_pointwise_conv2_weight_to_fp16, x = input_1509_cast_fp16)[name = tensor<string, []>("x_637_cast_fp16")];
            tensor<int32, [3]> input_1511_perm_0 = const()[name = tensor<string, []>("input_1511_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_1511_cast_fp16 = transpose(perm = input_1511_perm_0, x = x_637_cast_fp16)[name = tensor<string, []>("transpose_181")];
            tensor<fp16, [1, 188, 1024]> input_1513_cast_fp16 = add(x = input_1495_cast_fp16, y = input_1511_cast_fp16)[name = tensor<string, []>("input_1513_cast_fp16")];
            tensor<int32, [1]> input_1515_axes_0 = const()[name = tensor<string, []>("input_1515_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_28_norm_feed_forward2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_28_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1415327488)))];
            tensor<fp16, [1024]> encoder_layers_28_norm_feed_forward2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_28_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1415329600)))];
            tensor<fp16, [1, 188, 1024]> input_1515_cast_fp16 = layer_norm(axes = input_1515_axes_0, beta = encoder_layers_28_norm_feed_forward2_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_28_norm_feed_forward2_weight_to_fp16, x = input_1513_cast_fp16)[name = tensor<string, []>("input_1515_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_28_feed_forward2_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_28_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1415331712)))];
            tensor<fp16, [4096]> encoder_layers_28_feed_forward2_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_28_feed_forward2_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1423720384)))];
            tensor<fp16, [1, 188, 4096]> linear_260_cast_fp16 = linear(bias = encoder_layers_28_feed_forward2_linear1_bias_to_fp16, weight = encoder_layers_28_feed_forward2_linear1_weight_to_fp16, x = input_1515_cast_fp16)[name = tensor<string, []>("linear_260_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_1519_cast_fp16 = silu(x = linear_260_cast_fp16)[name = tensor<string, []>("input_1519_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_28_feed_forward2_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_28_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1423728640)))];
            tensor<fp16, [1024]> encoder_layers_28_feed_forward2_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_28_feed_forward2_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1432117312)))];
            tensor<fp16, [1, 188, 1024]> linear_261_cast_fp16 = linear(bias = encoder_layers_28_feed_forward2_linear2_bias_to_fp16, weight = encoder_layers_28_feed_forward2_linear2_weight_to_fp16, x = input_1519_cast_fp16)[name = tensor<string, []>("linear_261_cast_fp16")];
            tensor<fp16, []> var_5265_to_fp16 = const()[name = tensor<string, []>("op_5265_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_5266_cast_fp16 = mul(x = linear_261_cast_fp16, y = var_5265_to_fp16)[name = tensor<string, []>("op_5266_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1525_cast_fp16 = add(x = input_1513_cast_fp16, y = var_5266_cast_fp16)[name = tensor<string, []>("input_1525_cast_fp16")];
            tensor<int32, [1]> input_1527_axes_0 = const()[name = tensor<string, []>("input_1527_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_28_norm_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_28_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1432119424)))];
            tensor<fp16, [1024]> encoder_layers_28_norm_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_28_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1432121536)))];
            tensor<fp16, [1, 188, 1024]> input_1527_cast_fp16 = layer_norm(axes = input_1527_axes_0, beta = encoder_layers_28_norm_out_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_28_norm_out_weight_to_fp16, x = input_1525_cast_fp16)[name = tensor<string, []>("input_1527_cast_fp16")];
            tensor<int32, [1]> input_1529_axes_0 = const()[name = tensor<string, []>("input_1529_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_29_norm_feed_forward1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_29_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1432123648)))];
            tensor<fp16, [1024]> encoder_layers_29_norm_feed_forward1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_29_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1432125760)))];
            tensor<fp16, [1, 188, 1024]> input_1529_cast_fp16 = layer_norm(axes = input_1529_axes_0, beta = encoder_layers_29_norm_feed_forward1_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_29_norm_feed_forward1_weight_to_fp16, x = input_1527_cast_fp16)[name = tensor<string, []>("input_1529_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_29_feed_forward1_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_29_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1432127872)))];
            tensor<fp16, [4096]> encoder_layers_29_feed_forward1_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_29_feed_forward1_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1440516544)))];
            tensor<fp16, [1, 188, 4096]> linear_262_cast_fp16 = linear(bias = encoder_layers_29_feed_forward1_linear1_bias_to_fp16, weight = encoder_layers_29_feed_forward1_linear1_weight_to_fp16, x = input_1529_cast_fp16)[name = tensor<string, []>("linear_262_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_1533_cast_fp16 = silu(x = linear_262_cast_fp16)[name = tensor<string, []>("input_1533_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_29_feed_forward1_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_29_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1440524800)))];
            tensor<fp16, [1024]> encoder_layers_29_feed_forward1_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_29_feed_forward1_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1448913472)))];
            tensor<fp16, [1, 188, 1024]> linear_263_cast_fp16 = linear(bias = encoder_layers_29_feed_forward1_linear2_bias_to_fp16, weight = encoder_layers_29_feed_forward1_linear2_weight_to_fp16, x = input_1533_cast_fp16)[name = tensor<string, []>("linear_263_cast_fp16")];
            tensor<fp16, []> var_5296_to_fp16 = const()[name = tensor<string, []>("op_5296_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_5297_cast_fp16 = mul(x = linear_263_cast_fp16, y = var_5296_to_fp16)[name = tensor<string, []>("op_5297_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1539_cast_fp16 = add(x = input_1527_cast_fp16, y = var_5297_cast_fp16)[name = tensor<string, []>("input_1539_cast_fp16")];
            tensor<int32, [1]> query_59_axes_0 = const()[name = tensor<string, []>("query_59_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_29_norm_self_att_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_29_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1448915584)))];
            tensor<fp16, [1024]> encoder_layers_29_norm_self_att_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_29_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1448917696)))];
            tensor<fp16, [1, 188, 1024]> query_59_cast_fp16 = layer_norm(axes = query_59_axes_0, beta = encoder_layers_29_norm_self_att_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_29_norm_self_att_weight_to_fp16, x = input_1539_cast_fp16)[name = tensor<string, []>("query_59_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_29_self_attn_linear_q_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_29_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1448919808)))];
            tensor<fp16, [1024]> encoder_layers_29_self_attn_linear_q_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_29_self_attn_linear_q_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1451017024)))];
            tensor<fp16, [1, 188, 1024]> linear_264_cast_fp16 = linear(bias = encoder_layers_29_self_attn_linear_q_bias_to_fp16, weight = encoder_layers_29_self_attn_linear_q_weight_to_fp16, x = query_59_cast_fp16)[name = tensor<string, []>("linear_264_cast_fp16")];
            tensor<int32, [4]> var_5314 = const()[name = tensor<string, []>("op_5314"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_175_cast_fp16 = reshape(shape = var_5314, x = linear_264_cast_fp16)[name = tensor<string, []>("q_175_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_29_self_attn_linear_k_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_29_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1451019136)))];
            tensor<fp16, [1024]> encoder_layers_29_self_attn_linear_k_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_29_self_attn_linear_k_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1453116352)))];
            tensor<fp16, [1, 188, 1024]> linear_265_cast_fp16 = linear(bias = encoder_layers_29_self_attn_linear_k_bias_to_fp16, weight = encoder_layers_29_self_attn_linear_k_weight_to_fp16, x = query_59_cast_fp16)[name = tensor<string, []>("linear_265_cast_fp16")];
            tensor<int32, [4]> var_5319 = const()[name = tensor<string, []>("op_5319"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_117_cast_fp16 = reshape(shape = var_5319, x = linear_265_cast_fp16)[name = tensor<string, []>("k_117_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_29_self_attn_linear_v_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_29_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1453118464)))];
            tensor<fp16, [1024]> encoder_layers_29_self_attn_linear_v_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_29_self_attn_linear_v_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1455215680)))];
            tensor<fp16, [1, 188, 1024]> linear_266_cast_fp16 = linear(bias = encoder_layers_29_self_attn_linear_v_bias_to_fp16, weight = encoder_layers_29_self_attn_linear_v_weight_to_fp16, x = query_59_cast_fp16)[name = tensor<string, []>("linear_266_cast_fp16")];
            tensor<int32, [4]> var_5324 = const()[name = tensor<string, []>("op_5324"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_59_cast_fp16 = reshape(shape = var_5324, x = linear_266_cast_fp16)[name = tensor<string, []>("v_59_cast_fp16")];
            tensor<int32, [4]> value_61_perm_0 = const()[name = tensor<string, []>("value_61_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> encoder_layers_29_self_attn_pos_bias_u_to_fp16 = const()[name = tensor<string, []>("encoder_layers_29_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1455217792)))];
            tensor<fp16, [1, 188, 8, 128]> var_5336_cast_fp16 = add(x = q_175_cast_fp16, y = encoder_layers_29_self_attn_pos_bias_u_to_fp16)[name = tensor<string, []>("op_5336_cast_fp16")];
            tensor<fp16, [8, 128]> encoder_layers_29_self_attn_pos_bias_v_to_fp16 = const()[name = tensor<string, []>("encoder_layers_29_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1455219904)))];
            tensor<fp16, [1, 188, 8, 128]> var_5338_cast_fp16 = add(x = q_175_cast_fp16, y = encoder_layers_29_self_attn_pos_bias_v_to_fp16)[name = tensor<string, []>("op_5338_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_59_perm_0 = const()[name = tensor<string, []>("q_with_bias_v_59_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<bool, []> x_645_transpose_x_0 = const()[name = tensor<string, []>("x_645_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_645_transpose_y_0 = const()[name = tensor<string, []>("x_645_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 128, 375]> var_5340_to_fp16 = const()[name = tensor<string, []>("op_5340_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1455222016)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_59_cast_fp16 = transpose(perm = q_with_bias_v_59_perm_0, x = var_5338_cast_fp16)[name = tensor<string, []>("transpose_179")];
            tensor<fp16, [1, 8, 188, 375]> x_645_cast_fp16 = matmul(transpose_x = x_645_transpose_x_0, transpose_y = x_645_transpose_y_0, x = q_with_bias_v_59_cast_fp16, y = var_5340_to_fp16)[name = tensor<string, []>("x_645_cast_fp16")];
            tensor<int32, [8]> x_647_pad_0 = const()[name = tensor<string, []>("x_647_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            tensor<string, []> x_647_mode_0 = const()[name = tensor<string, []>("x_647_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_304_to_fp16 = const()[name = tensor<string, []>("const_304_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_647_cast_fp16 = pad(constant_val = const_304_to_fp16, mode = x_647_mode_0, pad = x_647_pad_0, x = x_645_cast_fp16)[name = tensor<string, []>("x_647_cast_fp16")];
            tensor<int32, [4]> var_5348 = const()[name = tensor<string, []>("op_5348"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_649_cast_fp16 = reshape(shape = var_5348, x = x_647_cast_fp16)[name = tensor<string, []>("x_649_cast_fp16")];
            tensor<int32, [4]> var_5352_begin_0 = const()[name = tensor<string, []>("op_5352_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_5352_end_0 = const()[name = tensor<string, []>("op_5352_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_5352_end_mask_0 = const()[name = tensor<string, []>("op_5352_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_5352_cast_fp16 = slice_by_index(begin = var_5352_begin_0, end = var_5352_end_0, end_mask = var_5352_end_mask_0, x = x_649_cast_fp16)[name = tensor<string, []>("op_5352_cast_fp16")];
            tensor<int32, [4]> var_5353 = const()[name = tensor<string, []>("op_5353"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_117_cast_fp16 = reshape(shape = var_5353, x = var_5352_cast_fp16)[name = tensor<string, []>("matrix_bd_117_cast_fp16")];
            tensor<bool, []> matrix_ac_59_transpose_x_0 = const()[name = tensor<string, []>("matrix_ac_59_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> matrix_ac_59_transpose_y_0 = const()[name = tensor<string, []>("matrix_ac_59_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<int32, [4]> transpose_154_perm_0 = const()[name = tensor<string, []>("transpose_154_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_155_perm_0 = const()[name = tensor<string, []>("transpose_155_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_155 = transpose(perm = transpose_155_perm_0, x = k_117_cast_fp16)[name = tensor<string, []>("transpose_177")];
            tensor<fp16, [1, 8, 188, 128]> transpose_154 = transpose(perm = transpose_154_perm_0, x = var_5336_cast_fp16)[name = tensor<string, []>("transpose_178")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_59_cast_fp16 = matmul(transpose_x = matrix_ac_59_transpose_x_0, transpose_y = matrix_ac_59_transpose_y_0, x = transpose_154, y = transpose_155)[name = tensor<string, []>("matrix_ac_59_cast_fp16")];
            tensor<int32, [4]> matrix_bd_119_begin_0 = const()[name = tensor<string, []>("matrix_bd_119_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_119_end_0 = const()[name = tensor<string, []>("matrix_bd_119_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_119_end_mask_0 = const()[name = tensor<string, []>("matrix_bd_119_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_119_cast_fp16 = slice_by_index(begin = matrix_bd_119_begin_0, end = matrix_bd_119_end_0, end_mask = matrix_bd_119_end_mask_0, x = matrix_bd_117_cast_fp16)[name = tensor<string, []>("matrix_bd_119_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_5362_cast_fp16 = add(x = matrix_ac_59_cast_fp16, y = matrix_bd_119_cast_fp16)[name = tensor<string, []>("op_5362_cast_fp16")];
            tensor<fp16, []> _inversed_scores_117_y_0_to_fp16 = const()[name = tensor<string, []>("_inversed_scores_117_y_0_to_fp16"), val = tensor<fp16, []>(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_117_cast_fp16 = mul(x = var_5362_cast_fp16, y = _inversed_scores_117_y_0_to_fp16)[name = tensor<string, []>("_inversed_scores_117_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_119_cast_fp16 = select(a = var_12_to_fp16, b = _inversed_scores_117_cast_fp16, cond = mask_3)[name = tensor<string, []>("scores_119_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_5368_cast_fp16 = softmax(axis = var_30, x = scores_119_cast_fp16)[name = tensor<string, []>("op_5368_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_1541_cast_fp16 = select(a = var_11_to_fp16, b = var_5368_cast_fp16, cond = mask_3)[name = tensor<string, []>("input_1541_cast_fp16")];
            tensor<bool, []> x_651_transpose_x_0 = const()[name = tensor<string, []>("x_651_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_651_transpose_y_0 = const()[name = tensor<string, []>("x_651_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 188, 128]> value_61_cast_fp16 = transpose(perm = value_61_perm_0, x = v_59_cast_fp16)[name = tensor<string, []>("transpose_180")];
            tensor<fp16, [1, 8, 188, 128]> x_651_cast_fp16 = matmul(transpose_x = x_651_transpose_x_0, transpose_y = x_651_transpose_y_0, x = input_1541_cast_fp16, y = value_61_cast_fp16)[name = tensor<string, []>("x_651_cast_fp16")];
            tensor<int32, [4]> var_5372_perm_0 = const()[name = tensor<string, []>("op_5372_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_5373 = const()[name = tensor<string, []>("op_5373"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_5372_cast_fp16 = transpose(perm = var_5372_perm_0, x = x_651_cast_fp16)[name = tensor<string, []>("transpose_176")];
            tensor<fp16, [1, 188, 1024]> input_1543_cast_fp16 = reshape(shape = var_5373, x = var_5372_cast_fp16)[name = tensor<string, []>("input_1543_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_29_self_attn_linear_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_29_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1455990080)))];
            tensor<fp16, [1024]> encoder_layers_29_self_attn_linear_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_29_self_attn_linear_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1458087296)))];
            tensor<fp16, [1, 188, 1024]> linear_268_cast_fp16 = linear(bias = encoder_layers_29_self_attn_linear_out_bias_to_fp16, weight = encoder_layers_29_self_attn_linear_out_weight_to_fp16, x = input_1543_cast_fp16)[name = tensor<string, []>("linear_268_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1547_cast_fp16 = add(x = input_1539_cast_fp16, y = linear_268_cast_fp16)[name = tensor<string, []>("input_1547_cast_fp16")];
            tensor<int32, [1]> x_655_axes_0 = const()[name = tensor<string, []>("x_655_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_29_norm_conv_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_29_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1458089408)))];
            tensor<fp16, [1024]> encoder_layers_29_norm_conv_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_29_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1458091520)))];
            tensor<fp16, [1, 188, 1024]> x_655_cast_fp16 = layer_norm(axes = x_655_axes_0, beta = encoder_layers_29_norm_conv_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_29_norm_conv_weight_to_fp16, x = input_1547_cast_fp16)[name = tensor<string, []>("x_655_cast_fp16")];
            tensor<int32, [3]> input_1549_perm_0 = const()[name = tensor<string, []>("input_1549_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> input_1551_pad_type_0 = const()[name = tensor<string, []>("input_1551_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_1551_strides_0 = const()[name = tensor<string, []>("input_1551_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1551_pad_0 = const()[name = tensor<string, []>("input_1551_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1551_dilations_0 = const()[name = tensor<string, []>("input_1551_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_1551_groups_0 = const()[name = tensor<string, []>("input_1551_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [2048, 1024, 1]> encoder_layers_29_conv_pointwise_conv1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_29_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1458093632)))];
            tensor<fp16, [2048]> encoder_layers_29_conv_pointwise_conv1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_29_conv_pointwise_conv1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1462288000)))];
            tensor<fp16, [1, 1024, 188]> input_1549_cast_fp16 = transpose(perm = input_1549_perm_0, x = x_655_cast_fp16)[name = tensor<string, []>("transpose_175")];
            tensor<fp16, [1, 2048, 188]> input_1551_cast_fp16 = conv(bias = encoder_layers_29_conv_pointwise_conv1_bias_to_fp16, dilations = input_1551_dilations_0, groups = input_1551_groups_0, pad = input_1551_pad_0, pad_type = input_1551_pad_type_0, strides = input_1551_strides_0, weight = encoder_layers_29_conv_pointwise_conv1_weight_to_fp16, x = input_1549_cast_fp16)[name = tensor<string, []>("input_1551_cast_fp16")];
            tensor<int32, []> x_657_split_num_splits_0 = const()[name = tensor<string, []>("x_657_split_num_splits_0"), val = tensor<int32, []>(2)];
            tensor<int32, []> x_657_split_axis_0 = const()[name = tensor<string, []>("x_657_split_axis_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1, 1024, 188]> x_657_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_657_split_cast_fp16_1 = split(axis = x_657_split_axis_0, num_splits = x_657_split_num_splits_0, x = input_1551_cast_fp16)[name = tensor<string, []>("x_657_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_657_split_1_sigmoid_cast_fp16 = sigmoid(x = x_657_split_cast_fp16_1)[name = tensor<string, []>("x_657_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_657_cast_fp16 = mul(x = x_657_split_cast_fp16_0, y = x_657_split_1_sigmoid_cast_fp16)[name = tensor<string, []>("x_657_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_1553_cast_fp16 = select(a = var_11_to_fp16, b = x_657_cast_fp16, cond = var_351)[name = tensor<string, []>("input_1553_cast_fp16")];
            tensor<int32, [6]> input_1555_pad_0 = const()[name = tensor<string, []>("input_1555_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            tensor<string, []> input_1555_mode_0 = const()[name = tensor<string, []>("input_1555_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_307_to_fp16 = const()[name = tensor<string, []>("const_307_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_1555_cast_fp16 = pad(constant_val = const_307_to_fp16, mode = input_1555_mode_0, pad = input_1555_pad_0, x = input_1553_cast_fp16)[name = tensor<string, []>("input_1555_cast_fp16")];
            tensor<string, []> input_1557_pad_type_0 = const()[name = tensor<string, []>("input_1557_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, []> input_1557_groups_0 = const()[name = tensor<string, []>("input_1557_groups_0"), val = tensor<int32, []>(1024)];
            tensor<int32, [1]> input_1557_strides_0 = const()[name = tensor<string, []>("input_1557_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1557_pad_0 = const()[name = tensor<string, []>("input_1557_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1557_dilations_0 = const()[name = tensor<string, []>("input_1557_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_386_to_fp16 = const()[name = tensor<string, []>("const_386_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1462292160)))];
            tensor<fp16, [1024]> const_387_to_fp16 = const()[name = tensor<string, []>("const_387_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1462310656)))];
            tensor<fp16, [1, 1024, 188]> input_1559_cast_fp16 = conv(bias = const_387_to_fp16, dilations = input_1557_dilations_0, groups = input_1557_groups_0, pad = input_1557_pad_0, pad_type = input_1557_pad_type_0, strides = input_1557_strides_0, weight = const_386_to_fp16, x = input_1555_cast_fp16)[name = tensor<string, []>("input_1559_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_1561_cast_fp16 = silu(x = input_1559_cast_fp16)[name = tensor<string, []>("input_1561_cast_fp16")];
            tensor<string, []> x_659_pad_type_0 = const()[name = tensor<string, []>("x_659_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> x_659_strides_0 = const()[name = tensor<string, []>("x_659_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_659_pad_0 = const()[name = tensor<string, []>("x_659_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_659_dilations_0 = const()[name = tensor<string, []>("x_659_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> x_659_groups_0 = const()[name = tensor<string, []>("x_659_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1024, 1024, 1]> encoder_layers_29_conv_pointwise_conv2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_29_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1462312768)))];
            tensor<fp16, [1024]> encoder_layers_29_conv_pointwise_conv2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_29_conv_pointwise_conv2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1464409984)))];
            tensor<fp16, [1, 1024, 188]> x_659_cast_fp16 = conv(bias = encoder_layers_29_conv_pointwise_conv2_bias_to_fp16, dilations = x_659_dilations_0, groups = x_659_groups_0, pad = x_659_pad_0, pad_type = x_659_pad_type_0, strides = x_659_strides_0, weight = encoder_layers_29_conv_pointwise_conv2_weight_to_fp16, x = input_1561_cast_fp16)[name = tensor<string, []>("x_659_cast_fp16")];
            tensor<int32, [3]> input_1563_perm_0 = const()[name = tensor<string, []>("input_1563_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_1563_cast_fp16 = transpose(perm = input_1563_perm_0, x = x_659_cast_fp16)[name = tensor<string, []>("transpose_174")];
            tensor<fp16, [1, 188, 1024]> input_1565_cast_fp16 = add(x = input_1547_cast_fp16, y = input_1563_cast_fp16)[name = tensor<string, []>("input_1565_cast_fp16")];
            tensor<int32, [1]> input_1567_axes_0 = const()[name = tensor<string, []>("input_1567_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_29_norm_feed_forward2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_29_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1464412096)))];
            tensor<fp16, [1024]> encoder_layers_29_norm_feed_forward2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_29_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1464414208)))];
            tensor<fp16, [1, 188, 1024]> input_1567_cast_fp16 = layer_norm(axes = input_1567_axes_0, beta = encoder_layers_29_norm_feed_forward2_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_29_norm_feed_forward2_weight_to_fp16, x = input_1565_cast_fp16)[name = tensor<string, []>("input_1567_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_29_feed_forward2_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_29_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1464416320)))];
            tensor<fp16, [4096]> encoder_layers_29_feed_forward2_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_29_feed_forward2_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1472804992)))];
            tensor<fp16, [1, 188, 4096]> linear_269_cast_fp16 = linear(bias = encoder_layers_29_feed_forward2_linear1_bias_to_fp16, weight = encoder_layers_29_feed_forward2_linear1_weight_to_fp16, x = input_1567_cast_fp16)[name = tensor<string, []>("linear_269_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_1571_cast_fp16 = silu(x = linear_269_cast_fp16)[name = tensor<string, []>("input_1571_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_29_feed_forward2_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_29_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1472813248)))];
            tensor<fp16, [1024]> encoder_layers_29_feed_forward2_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_29_feed_forward2_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1481201920)))];
            tensor<fp16, [1, 188, 1024]> linear_270_cast_fp16 = linear(bias = encoder_layers_29_feed_forward2_linear2_bias_to_fp16, weight = encoder_layers_29_feed_forward2_linear2_weight_to_fp16, x = input_1571_cast_fp16)[name = tensor<string, []>("linear_270_cast_fp16")];
            tensor<fp16, []> var_5439_to_fp16 = const()[name = tensor<string, []>("op_5439_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_5440_cast_fp16 = mul(x = linear_270_cast_fp16, y = var_5439_to_fp16)[name = tensor<string, []>("op_5440_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1577_cast_fp16 = add(x = input_1565_cast_fp16, y = var_5440_cast_fp16)[name = tensor<string, []>("input_1577_cast_fp16")];
            tensor<int32, [1]> input_1579_axes_0 = const()[name = tensor<string, []>("input_1579_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_29_norm_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_29_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1481204032)))];
            tensor<fp16, [1024]> encoder_layers_29_norm_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_29_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1481206144)))];
            tensor<fp16, [1, 188, 1024]> input_1579_cast_fp16 = layer_norm(axes = input_1579_axes_0, beta = encoder_layers_29_norm_out_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_29_norm_out_weight_to_fp16, x = input_1577_cast_fp16)[name = tensor<string, []>("input_1579_cast_fp16")];
            tensor<int32, [1]> input_1581_axes_0 = const()[name = tensor<string, []>("input_1581_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_30_norm_feed_forward1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_30_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1481208256)))];
            tensor<fp16, [1024]> encoder_layers_30_norm_feed_forward1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_30_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1481210368)))];
            tensor<fp16, [1, 188, 1024]> input_1581_cast_fp16 = layer_norm(axes = input_1581_axes_0, beta = encoder_layers_30_norm_feed_forward1_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_30_norm_feed_forward1_weight_to_fp16, x = input_1579_cast_fp16)[name = tensor<string, []>("input_1581_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_30_feed_forward1_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_30_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1481212480)))];
            tensor<fp16, [4096]> encoder_layers_30_feed_forward1_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_30_feed_forward1_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1489601152)))];
            tensor<fp16, [1, 188, 4096]> linear_271_cast_fp16 = linear(bias = encoder_layers_30_feed_forward1_linear1_bias_to_fp16, weight = encoder_layers_30_feed_forward1_linear1_weight_to_fp16, x = input_1581_cast_fp16)[name = tensor<string, []>("linear_271_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_1585_cast_fp16 = silu(x = linear_271_cast_fp16)[name = tensor<string, []>("input_1585_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_30_feed_forward1_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_30_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1489609408)))];
            tensor<fp16, [1024]> encoder_layers_30_feed_forward1_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_30_feed_forward1_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1497998080)))];
            tensor<fp16, [1, 188, 1024]> linear_272_cast_fp16 = linear(bias = encoder_layers_30_feed_forward1_linear2_bias_to_fp16, weight = encoder_layers_30_feed_forward1_linear2_weight_to_fp16, x = input_1585_cast_fp16)[name = tensor<string, []>("linear_272_cast_fp16")];
            tensor<fp16, []> var_5470_to_fp16 = const()[name = tensor<string, []>("op_5470_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_5471_cast_fp16 = mul(x = linear_272_cast_fp16, y = var_5470_to_fp16)[name = tensor<string, []>("op_5471_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1591_cast_fp16 = add(x = input_1579_cast_fp16, y = var_5471_cast_fp16)[name = tensor<string, []>("input_1591_cast_fp16")];
            tensor<int32, [1]> query_61_axes_0 = const()[name = tensor<string, []>("query_61_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_30_norm_self_att_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_30_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1498000192)))];
            tensor<fp16, [1024]> encoder_layers_30_norm_self_att_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_30_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1498002304)))];
            tensor<fp16, [1, 188, 1024]> query_61_cast_fp16 = layer_norm(axes = query_61_axes_0, beta = encoder_layers_30_norm_self_att_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_30_norm_self_att_weight_to_fp16, x = input_1591_cast_fp16)[name = tensor<string, []>("query_61_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_30_self_attn_linear_q_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_30_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1498004416)))];
            tensor<fp16, [1024]> encoder_layers_30_self_attn_linear_q_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_30_self_attn_linear_q_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1500101632)))];
            tensor<fp16, [1, 188, 1024]> linear_273_cast_fp16 = linear(bias = encoder_layers_30_self_attn_linear_q_bias_to_fp16, weight = encoder_layers_30_self_attn_linear_q_weight_to_fp16, x = query_61_cast_fp16)[name = tensor<string, []>("linear_273_cast_fp16")];
            tensor<int32, [4]> var_5488 = const()[name = tensor<string, []>("op_5488"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_181_cast_fp16 = reshape(shape = var_5488, x = linear_273_cast_fp16)[name = tensor<string, []>("q_181_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_30_self_attn_linear_k_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_30_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1500103744)))];
            tensor<fp16, [1024]> encoder_layers_30_self_attn_linear_k_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_30_self_attn_linear_k_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1502200960)))];
            tensor<fp16, [1, 188, 1024]> linear_274_cast_fp16 = linear(bias = encoder_layers_30_self_attn_linear_k_bias_to_fp16, weight = encoder_layers_30_self_attn_linear_k_weight_to_fp16, x = query_61_cast_fp16)[name = tensor<string, []>("linear_274_cast_fp16")];
            tensor<int32, [4]> var_5493 = const()[name = tensor<string, []>("op_5493"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_121_cast_fp16 = reshape(shape = var_5493, x = linear_274_cast_fp16)[name = tensor<string, []>("k_121_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_30_self_attn_linear_v_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_30_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1502203072)))];
            tensor<fp16, [1024]> encoder_layers_30_self_attn_linear_v_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_30_self_attn_linear_v_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1504300288)))];
            tensor<fp16, [1, 188, 1024]> linear_275_cast_fp16 = linear(bias = encoder_layers_30_self_attn_linear_v_bias_to_fp16, weight = encoder_layers_30_self_attn_linear_v_weight_to_fp16, x = query_61_cast_fp16)[name = tensor<string, []>("linear_275_cast_fp16")];
            tensor<int32, [4]> var_5498 = const()[name = tensor<string, []>("op_5498"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_61_cast_fp16 = reshape(shape = var_5498, x = linear_275_cast_fp16)[name = tensor<string, []>("v_61_cast_fp16")];
            tensor<int32, [4]> value_63_perm_0 = const()[name = tensor<string, []>("value_63_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> encoder_layers_30_self_attn_pos_bias_u_to_fp16 = const()[name = tensor<string, []>("encoder_layers_30_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1504302400)))];
            tensor<fp16, [1, 188, 8, 128]> var_5510_cast_fp16 = add(x = q_181_cast_fp16, y = encoder_layers_30_self_attn_pos_bias_u_to_fp16)[name = tensor<string, []>("op_5510_cast_fp16")];
            tensor<fp16, [8, 128]> encoder_layers_30_self_attn_pos_bias_v_to_fp16 = const()[name = tensor<string, []>("encoder_layers_30_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1504304512)))];
            tensor<fp16, [1, 188, 8, 128]> var_5512_cast_fp16 = add(x = q_181_cast_fp16, y = encoder_layers_30_self_attn_pos_bias_v_to_fp16)[name = tensor<string, []>("op_5512_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_61_perm_0 = const()[name = tensor<string, []>("q_with_bias_v_61_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<bool, []> x_667_transpose_x_0 = const()[name = tensor<string, []>("x_667_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_667_transpose_y_0 = const()[name = tensor<string, []>("x_667_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 128, 375]> var_5514_to_fp16 = const()[name = tensor<string, []>("op_5514_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1504306624)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_61_cast_fp16 = transpose(perm = q_with_bias_v_61_perm_0, x = var_5512_cast_fp16)[name = tensor<string, []>("transpose_172")];
            tensor<fp16, [1, 8, 188, 375]> x_667_cast_fp16 = matmul(transpose_x = x_667_transpose_x_0, transpose_y = x_667_transpose_y_0, x = q_with_bias_v_61_cast_fp16, y = var_5514_to_fp16)[name = tensor<string, []>("x_667_cast_fp16")];
            tensor<int32, [8]> x_669_pad_0 = const()[name = tensor<string, []>("x_669_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            tensor<string, []> x_669_mode_0 = const()[name = tensor<string, []>("x_669_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_314_to_fp16 = const()[name = tensor<string, []>("const_314_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_669_cast_fp16 = pad(constant_val = const_314_to_fp16, mode = x_669_mode_0, pad = x_669_pad_0, x = x_667_cast_fp16)[name = tensor<string, []>("x_669_cast_fp16")];
            tensor<int32, [4]> var_5522 = const()[name = tensor<string, []>("op_5522"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_671_cast_fp16 = reshape(shape = var_5522, x = x_669_cast_fp16)[name = tensor<string, []>("x_671_cast_fp16")];
            tensor<int32, [4]> var_5526_begin_0 = const()[name = tensor<string, []>("op_5526_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_5526_end_0 = const()[name = tensor<string, []>("op_5526_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_5526_end_mask_0 = const()[name = tensor<string, []>("op_5526_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_5526_cast_fp16 = slice_by_index(begin = var_5526_begin_0, end = var_5526_end_0, end_mask = var_5526_end_mask_0, x = x_671_cast_fp16)[name = tensor<string, []>("op_5526_cast_fp16")];
            tensor<int32, [4]> var_5527 = const()[name = tensor<string, []>("op_5527"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_121_cast_fp16 = reshape(shape = var_5527, x = var_5526_cast_fp16)[name = tensor<string, []>("matrix_bd_121_cast_fp16")];
            tensor<bool, []> matrix_ac_61_transpose_x_0 = const()[name = tensor<string, []>("matrix_ac_61_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> matrix_ac_61_transpose_y_0 = const()[name = tensor<string, []>("matrix_ac_61_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<int32, [4]> transpose_156_perm_0 = const()[name = tensor<string, []>("transpose_156_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_157_perm_0 = const()[name = tensor<string, []>("transpose_157_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_157 = transpose(perm = transpose_157_perm_0, x = k_121_cast_fp16)[name = tensor<string, []>("transpose_170")];
            tensor<fp16, [1, 8, 188, 128]> transpose_156 = transpose(perm = transpose_156_perm_0, x = var_5510_cast_fp16)[name = tensor<string, []>("transpose_171")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_61_cast_fp16 = matmul(transpose_x = matrix_ac_61_transpose_x_0, transpose_y = matrix_ac_61_transpose_y_0, x = transpose_156, y = transpose_157)[name = tensor<string, []>("matrix_ac_61_cast_fp16")];
            tensor<int32, [4]> matrix_bd_123_begin_0 = const()[name = tensor<string, []>("matrix_bd_123_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_123_end_0 = const()[name = tensor<string, []>("matrix_bd_123_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_123_end_mask_0 = const()[name = tensor<string, []>("matrix_bd_123_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_123_cast_fp16 = slice_by_index(begin = matrix_bd_123_begin_0, end = matrix_bd_123_end_0, end_mask = matrix_bd_123_end_mask_0, x = matrix_bd_121_cast_fp16)[name = tensor<string, []>("matrix_bd_123_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_5536_cast_fp16 = add(x = matrix_ac_61_cast_fp16, y = matrix_bd_123_cast_fp16)[name = tensor<string, []>("op_5536_cast_fp16")];
            tensor<fp16, []> _inversed_scores_121_y_0_to_fp16 = const()[name = tensor<string, []>("_inversed_scores_121_y_0_to_fp16"), val = tensor<fp16, []>(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_121_cast_fp16 = mul(x = var_5536_cast_fp16, y = _inversed_scores_121_y_0_to_fp16)[name = tensor<string, []>("_inversed_scores_121_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_123_cast_fp16 = select(a = var_12_to_fp16, b = _inversed_scores_121_cast_fp16, cond = mask_3)[name = tensor<string, []>("scores_123_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_5542_cast_fp16 = softmax(axis = var_30, x = scores_123_cast_fp16)[name = tensor<string, []>("op_5542_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_1593_cast_fp16 = select(a = var_11_to_fp16, b = var_5542_cast_fp16, cond = mask_3)[name = tensor<string, []>("input_1593_cast_fp16")];
            tensor<bool, []> x_673_transpose_x_0 = const()[name = tensor<string, []>("x_673_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_673_transpose_y_0 = const()[name = tensor<string, []>("x_673_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 188, 128]> value_63_cast_fp16 = transpose(perm = value_63_perm_0, x = v_61_cast_fp16)[name = tensor<string, []>("transpose_173")];
            tensor<fp16, [1, 8, 188, 128]> x_673_cast_fp16 = matmul(transpose_x = x_673_transpose_x_0, transpose_y = x_673_transpose_y_0, x = input_1593_cast_fp16, y = value_63_cast_fp16)[name = tensor<string, []>("x_673_cast_fp16")];
            tensor<int32, [4]> var_5546_perm_0 = const()[name = tensor<string, []>("op_5546_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_5547 = const()[name = tensor<string, []>("op_5547"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_5546_cast_fp16 = transpose(perm = var_5546_perm_0, x = x_673_cast_fp16)[name = tensor<string, []>("transpose_169")];
            tensor<fp16, [1, 188, 1024]> input_1595_cast_fp16 = reshape(shape = var_5547, x = var_5546_cast_fp16)[name = tensor<string, []>("input_1595_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_30_self_attn_linear_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_30_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1505074688)))];
            tensor<fp16, [1024]> encoder_layers_30_self_attn_linear_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_30_self_attn_linear_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1507171904)))];
            tensor<fp16, [1, 188, 1024]> linear_277_cast_fp16 = linear(bias = encoder_layers_30_self_attn_linear_out_bias_to_fp16, weight = encoder_layers_30_self_attn_linear_out_weight_to_fp16, x = input_1595_cast_fp16)[name = tensor<string, []>("linear_277_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1599_cast_fp16 = add(x = input_1591_cast_fp16, y = linear_277_cast_fp16)[name = tensor<string, []>("input_1599_cast_fp16")];
            tensor<int32, [1]> x_677_axes_0 = const()[name = tensor<string, []>("x_677_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_30_norm_conv_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_30_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1507174016)))];
            tensor<fp16, [1024]> encoder_layers_30_norm_conv_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_30_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1507176128)))];
            tensor<fp16, [1, 188, 1024]> x_677_cast_fp16 = layer_norm(axes = x_677_axes_0, beta = encoder_layers_30_norm_conv_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_30_norm_conv_weight_to_fp16, x = input_1599_cast_fp16)[name = tensor<string, []>("x_677_cast_fp16")];
            tensor<int32, [3]> input_1601_perm_0 = const()[name = tensor<string, []>("input_1601_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> input_1603_pad_type_0 = const()[name = tensor<string, []>("input_1603_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_1603_strides_0 = const()[name = tensor<string, []>("input_1603_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1603_pad_0 = const()[name = tensor<string, []>("input_1603_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1603_dilations_0 = const()[name = tensor<string, []>("input_1603_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_1603_groups_0 = const()[name = tensor<string, []>("input_1603_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [2048, 1024, 1]> encoder_layers_30_conv_pointwise_conv1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_30_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1507178240)))];
            tensor<fp16, [2048]> encoder_layers_30_conv_pointwise_conv1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_30_conv_pointwise_conv1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1511372608)))];
            tensor<fp16, [1, 1024, 188]> input_1601_cast_fp16 = transpose(perm = input_1601_perm_0, x = x_677_cast_fp16)[name = tensor<string, []>("transpose_168")];
            tensor<fp16, [1, 2048, 188]> input_1603_cast_fp16 = conv(bias = encoder_layers_30_conv_pointwise_conv1_bias_to_fp16, dilations = input_1603_dilations_0, groups = input_1603_groups_0, pad = input_1603_pad_0, pad_type = input_1603_pad_type_0, strides = input_1603_strides_0, weight = encoder_layers_30_conv_pointwise_conv1_weight_to_fp16, x = input_1601_cast_fp16)[name = tensor<string, []>("input_1603_cast_fp16")];
            tensor<int32, []> x_679_split_num_splits_0 = const()[name = tensor<string, []>("x_679_split_num_splits_0"), val = tensor<int32, []>(2)];
            tensor<int32, []> x_679_split_axis_0 = const()[name = tensor<string, []>("x_679_split_axis_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1, 1024, 188]> x_679_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_679_split_cast_fp16_1 = split(axis = x_679_split_axis_0, num_splits = x_679_split_num_splits_0, x = input_1603_cast_fp16)[name = tensor<string, []>("x_679_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_679_split_1_sigmoid_cast_fp16 = sigmoid(x = x_679_split_cast_fp16_1)[name = tensor<string, []>("x_679_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_679_cast_fp16 = mul(x = x_679_split_cast_fp16_0, y = x_679_split_1_sigmoid_cast_fp16)[name = tensor<string, []>("x_679_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_1605_cast_fp16 = select(a = var_11_to_fp16, b = x_679_cast_fp16, cond = var_351)[name = tensor<string, []>("input_1605_cast_fp16")];
            tensor<int32, [6]> input_1607_pad_0 = const()[name = tensor<string, []>("input_1607_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            tensor<string, []> input_1607_mode_0 = const()[name = tensor<string, []>("input_1607_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_317_to_fp16 = const()[name = tensor<string, []>("const_317_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_1607_cast_fp16 = pad(constant_val = const_317_to_fp16, mode = input_1607_mode_0, pad = input_1607_pad_0, x = input_1605_cast_fp16)[name = tensor<string, []>("input_1607_cast_fp16")];
            tensor<string, []> input_1609_pad_type_0 = const()[name = tensor<string, []>("input_1609_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, []> input_1609_groups_0 = const()[name = tensor<string, []>("input_1609_groups_0"), val = tensor<int32, []>(1024)];
            tensor<int32, [1]> input_1609_strides_0 = const()[name = tensor<string, []>("input_1609_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1609_pad_0 = const()[name = tensor<string, []>("input_1609_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1609_dilations_0 = const()[name = tensor<string, []>("input_1609_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_388_to_fp16 = const()[name = tensor<string, []>("const_388_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1511376768)))];
            tensor<fp16, [1024]> const_389_to_fp16 = const()[name = tensor<string, []>("const_389_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1511395264)))];
            tensor<fp16, [1, 1024, 188]> input_1611_cast_fp16 = conv(bias = const_389_to_fp16, dilations = input_1609_dilations_0, groups = input_1609_groups_0, pad = input_1609_pad_0, pad_type = input_1609_pad_type_0, strides = input_1609_strides_0, weight = const_388_to_fp16, x = input_1607_cast_fp16)[name = tensor<string, []>("input_1611_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_1613_cast_fp16 = silu(x = input_1611_cast_fp16)[name = tensor<string, []>("input_1613_cast_fp16")];
            tensor<string, []> x_681_pad_type_0 = const()[name = tensor<string, []>("x_681_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> x_681_strides_0 = const()[name = tensor<string, []>("x_681_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_681_pad_0 = const()[name = tensor<string, []>("x_681_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_681_dilations_0 = const()[name = tensor<string, []>("x_681_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> x_681_groups_0 = const()[name = tensor<string, []>("x_681_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1024, 1024, 1]> encoder_layers_30_conv_pointwise_conv2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_30_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1511397376)))];
            tensor<fp16, [1024]> encoder_layers_30_conv_pointwise_conv2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_30_conv_pointwise_conv2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1513494592)))];
            tensor<fp16, [1, 1024, 188]> x_681_cast_fp16 = conv(bias = encoder_layers_30_conv_pointwise_conv2_bias_to_fp16, dilations = x_681_dilations_0, groups = x_681_groups_0, pad = x_681_pad_0, pad_type = x_681_pad_type_0, strides = x_681_strides_0, weight = encoder_layers_30_conv_pointwise_conv2_weight_to_fp16, x = input_1613_cast_fp16)[name = tensor<string, []>("x_681_cast_fp16")];
            tensor<int32, [3]> input_1615_perm_0 = const()[name = tensor<string, []>("input_1615_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_1615_cast_fp16 = transpose(perm = input_1615_perm_0, x = x_681_cast_fp16)[name = tensor<string, []>("transpose_167")];
            tensor<fp16, [1, 188, 1024]> input_1617_cast_fp16 = add(x = input_1599_cast_fp16, y = input_1615_cast_fp16)[name = tensor<string, []>("input_1617_cast_fp16")];
            tensor<int32, [1]> input_1619_axes_0 = const()[name = tensor<string, []>("input_1619_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_30_norm_feed_forward2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_30_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1513496704)))];
            tensor<fp16, [1024]> encoder_layers_30_norm_feed_forward2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_30_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1513498816)))];
            tensor<fp16, [1, 188, 1024]> input_1619_cast_fp16 = layer_norm(axes = input_1619_axes_0, beta = encoder_layers_30_norm_feed_forward2_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_30_norm_feed_forward2_weight_to_fp16, x = input_1617_cast_fp16)[name = tensor<string, []>("input_1619_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_30_feed_forward2_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_30_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1513500928)))];
            tensor<fp16, [4096]> encoder_layers_30_feed_forward2_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_30_feed_forward2_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1521889600)))];
            tensor<fp16, [1, 188, 4096]> linear_278_cast_fp16 = linear(bias = encoder_layers_30_feed_forward2_linear1_bias_to_fp16, weight = encoder_layers_30_feed_forward2_linear1_weight_to_fp16, x = input_1619_cast_fp16)[name = tensor<string, []>("linear_278_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_1623_cast_fp16 = silu(x = linear_278_cast_fp16)[name = tensor<string, []>("input_1623_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_30_feed_forward2_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_30_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1521897856)))];
            tensor<fp16, [1024]> encoder_layers_30_feed_forward2_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_30_feed_forward2_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1530286528)))];
            tensor<fp16, [1, 188, 1024]> linear_279_cast_fp16 = linear(bias = encoder_layers_30_feed_forward2_linear2_bias_to_fp16, weight = encoder_layers_30_feed_forward2_linear2_weight_to_fp16, x = input_1623_cast_fp16)[name = tensor<string, []>("linear_279_cast_fp16")];
            tensor<fp16, []> var_5613_to_fp16 = const()[name = tensor<string, []>("op_5613_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_5614_cast_fp16 = mul(x = linear_279_cast_fp16, y = var_5613_to_fp16)[name = tensor<string, []>("op_5614_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1629_cast_fp16 = add(x = input_1617_cast_fp16, y = var_5614_cast_fp16)[name = tensor<string, []>("input_1629_cast_fp16")];
            tensor<int32, [1]> input_1631_axes_0 = const()[name = tensor<string, []>("input_1631_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_30_norm_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_30_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1530288640)))];
            tensor<fp16, [1024]> encoder_layers_30_norm_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_30_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1530290752)))];
            tensor<fp16, [1, 188, 1024]> input_1631_cast_fp16 = layer_norm(axes = input_1631_axes_0, beta = encoder_layers_30_norm_out_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_30_norm_out_weight_to_fp16, x = input_1629_cast_fp16)[name = tensor<string, []>("input_1631_cast_fp16")];
            tensor<int32, [1]> input_1633_axes_0 = const()[name = tensor<string, []>("input_1633_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_31_norm_feed_forward1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_31_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1530292864)))];
            tensor<fp16, [1024]> encoder_layers_31_norm_feed_forward1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_31_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1530294976)))];
            tensor<fp16, [1, 188, 1024]> input_1633_cast_fp16 = layer_norm(axes = input_1633_axes_0, beta = encoder_layers_31_norm_feed_forward1_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_31_norm_feed_forward1_weight_to_fp16, x = input_1631_cast_fp16)[name = tensor<string, []>("input_1633_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_31_feed_forward1_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_31_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1530297088)))];
            tensor<fp16, [4096]> encoder_layers_31_feed_forward1_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_31_feed_forward1_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1538685760)))];
            tensor<fp16, [1, 188, 4096]> linear_280_cast_fp16 = linear(bias = encoder_layers_31_feed_forward1_linear1_bias_to_fp16, weight = encoder_layers_31_feed_forward1_linear1_weight_to_fp16, x = input_1633_cast_fp16)[name = tensor<string, []>("linear_280_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_1637_cast_fp16 = silu(x = linear_280_cast_fp16)[name = tensor<string, []>("input_1637_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_31_feed_forward1_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_31_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1538694016)))];
            tensor<fp16, [1024]> encoder_layers_31_feed_forward1_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_31_feed_forward1_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1547082688)))];
            tensor<fp16, [1, 188, 1024]> linear_281_cast_fp16 = linear(bias = encoder_layers_31_feed_forward1_linear2_bias_to_fp16, weight = encoder_layers_31_feed_forward1_linear2_weight_to_fp16, x = input_1637_cast_fp16)[name = tensor<string, []>("linear_281_cast_fp16")];
            tensor<fp16, []> var_5644_to_fp16 = const()[name = tensor<string, []>("op_5644_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_5645_cast_fp16 = mul(x = linear_281_cast_fp16, y = var_5644_to_fp16)[name = tensor<string, []>("op_5645_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1643_cast_fp16 = add(x = input_1631_cast_fp16, y = var_5645_cast_fp16)[name = tensor<string, []>("input_1643_cast_fp16")];
            tensor<int32, [1]> query_axes_0 = const()[name = tensor<string, []>("query_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_31_norm_self_att_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_31_norm_self_att_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1547084800)))];
            tensor<fp16, [1024]> encoder_layers_31_norm_self_att_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_31_norm_self_att_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1547086912)))];
            tensor<fp16, [1, 188, 1024]> query_cast_fp16 = layer_norm(axes = query_axes_0, beta = encoder_layers_31_norm_self_att_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_31_norm_self_att_weight_to_fp16, x = input_1643_cast_fp16)[name = tensor<string, []>("query_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_31_self_attn_linear_q_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_31_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1547089024)))];
            tensor<fp16, [1024]> encoder_layers_31_self_attn_linear_q_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_31_self_attn_linear_q_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1549186240)))];
            tensor<fp16, [1, 188, 1024]> linear_282_cast_fp16 = linear(bias = encoder_layers_31_self_attn_linear_q_bias_to_fp16, weight = encoder_layers_31_self_attn_linear_q_weight_to_fp16, x = query_cast_fp16)[name = tensor<string, []>("linear_282_cast_fp16")];
            tensor<int32, [4]> var_5662 = const()[name = tensor<string, []>("op_5662"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> q_187_cast_fp16 = reshape(shape = var_5662, x = linear_282_cast_fp16)[name = tensor<string, []>("q_187_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_31_self_attn_linear_k_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_31_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1549188352)))];
            tensor<fp16, [1024]> encoder_layers_31_self_attn_linear_k_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_31_self_attn_linear_k_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1551285568)))];
            tensor<fp16, [1, 188, 1024]> linear_283_cast_fp16 = linear(bias = encoder_layers_31_self_attn_linear_k_bias_to_fp16, weight = encoder_layers_31_self_attn_linear_k_weight_to_fp16, x = query_cast_fp16)[name = tensor<string, []>("linear_283_cast_fp16")];
            tensor<int32, [4]> var_5667 = const()[name = tensor<string, []>("op_5667"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> k_125_cast_fp16 = reshape(shape = var_5667, x = linear_283_cast_fp16)[name = tensor<string, []>("k_125_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_31_self_attn_linear_v_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_31_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1551287680)))];
            tensor<fp16, [1024]> encoder_layers_31_self_attn_linear_v_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_31_self_attn_linear_v_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1553384896)))];
            tensor<fp16, [1, 188, 1024]> linear_284_cast_fp16 = linear(bias = encoder_layers_31_self_attn_linear_v_bias_to_fp16, weight = encoder_layers_31_self_attn_linear_v_weight_to_fp16, x = query_cast_fp16)[name = tensor<string, []>("linear_284_cast_fp16")];
            tensor<int32, [4]> var_5672 = const()[name = tensor<string, []>("op_5672"), val = tensor<int32, [4]>([1, -1, 8, 128])];
            tensor<fp16, [1, 188, 8, 128]> v_cast_fp16 = reshape(shape = var_5672, x = linear_284_cast_fp16)[name = tensor<string, []>("v_cast_fp16")];
            tensor<int32, [4]> value_perm_0 = const()[name = tensor<string, []>("value_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<fp16, [8, 128]> encoder_layers_31_self_attn_pos_bias_u_to_fp16 = const()[name = tensor<string, []>("encoder_layers_31_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1553387008)))];
            tensor<fp16, [1, 188, 8, 128]> var_5684_cast_fp16 = add(x = q_187_cast_fp16, y = encoder_layers_31_self_attn_pos_bias_u_to_fp16)[name = tensor<string, []>("op_5684_cast_fp16")];
            tensor<fp16, [8, 128]> encoder_layers_31_self_attn_pos_bias_v_to_fp16 = const()[name = tensor<string, []>("encoder_layers_31_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1553389120)))];
            tensor<fp16, [1, 188, 8, 128]> var_5686_cast_fp16 = add(x = q_187_cast_fp16, y = encoder_layers_31_self_attn_pos_bias_v_to_fp16)[name = tensor<string, []>("op_5686_cast_fp16")];
            tensor<int32, [4]> q_with_bias_v_perm_0 = const()[name = tensor<string, []>("q_with_bias_v_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<bool, []> x_689_transpose_x_0 = const()[name = tensor<string, []>("x_689_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_689_transpose_y_0 = const()[name = tensor<string, []>("x_689_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 128, 375]> var_5688_to_fp16 = const()[name = tensor<string, []>("op_5688_to_fp16"), val = tensor<fp16, [1, 8, 128, 375]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1553391232)))];
            tensor<fp16, [1, 8, 188, 128]> q_with_bias_v_cast_fp16 = transpose(perm = q_with_bias_v_perm_0, x = var_5686_cast_fp16)[name = tensor<string, []>("transpose_165")];
            tensor<fp16, [1, 8, 188, 375]> x_689_cast_fp16 = matmul(transpose_x = x_689_transpose_x_0, transpose_y = x_689_transpose_y_0, x = q_with_bias_v_cast_fp16, y = var_5688_to_fp16)[name = tensor<string, []>("x_689_cast_fp16")];
            tensor<int32, [8]> x_691_pad_0 = const()[name = tensor<string, []>("x_691_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            tensor<string, []> x_691_mode_0 = const()[name = tensor<string, []>("x_691_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_324_to_fp16 = const()[name = tensor<string, []>("const_324_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_691_cast_fp16 = pad(constant_val = const_324_to_fp16, mode = x_691_mode_0, pad = x_691_pad_0, x = x_689_cast_fp16)[name = tensor<string, []>("x_691_cast_fp16")];
            tensor<int32, [4]> var_5696 = const()[name = tensor<string, []>("op_5696"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_693_cast_fp16 = reshape(shape = var_5696, x = x_691_cast_fp16)[name = tensor<string, []>("x_693_cast_fp16")];
            tensor<int32, [4]> var_5700_begin_0 = const()[name = tensor<string, []>("op_5700_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_5700_end_0 = const()[name = tensor<string, []>("op_5700_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_5700_end_mask_0 = const()[name = tensor<string, []>("op_5700_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_5700_cast_fp16 = slice_by_index(begin = var_5700_begin_0, end = var_5700_end_0, end_mask = var_5700_end_mask_0, x = x_693_cast_fp16)[name = tensor<string, []>("op_5700_cast_fp16")];
            tensor<int32, [4]> var_5701 = const()[name = tensor<string, []>("op_5701"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_125_cast_fp16 = reshape(shape = var_5701, x = var_5700_cast_fp16)[name = tensor<string, []>("matrix_bd_125_cast_fp16")];
            tensor<bool, []> matrix_ac_transpose_x_0 = const()[name = tensor<string, []>("matrix_ac_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> matrix_ac_transpose_y_0 = const()[name = tensor<string, []>("matrix_ac_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<int32, [4]> transpose_158_perm_0 = const()[name = tensor<string, []>("transpose_158_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_159_perm_0 = const()[name = tensor<string, []>("transpose_159_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 128, 188]> transpose_159 = transpose(perm = transpose_159_perm_0, x = k_125_cast_fp16)[name = tensor<string, []>("transpose_163")];
            tensor<fp16, [1, 8, 188, 128]> transpose_158 = transpose(perm = transpose_158_perm_0, x = var_5684_cast_fp16)[name = tensor<string, []>("transpose_164")];
            tensor<fp16, [1, 8, 188, 188]> matrix_ac_cast_fp16 = matmul(transpose_x = matrix_ac_transpose_x_0, transpose_y = matrix_ac_transpose_y_0, x = transpose_158, y = transpose_159)[name = tensor<string, []>("matrix_ac_cast_fp16")];
            tensor<int32, [4]> matrix_bd_begin_0 = const()[name = tensor<string, []>("matrix_bd_begin_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [4]> matrix_bd_end_0 = const()[name = tensor<string, []>("matrix_bd_end_0"), val = tensor<int32, [4]>([1, 8, 188, 188])];
            tensor<bool, [4]> matrix_bd_end_mask_0 = const()[name = tensor<string, []>("matrix_bd_end_mask_0"), val = tensor<bool, [4]>([true, true, true, false])];
            tensor<fp16, [1, 8, 188, 188]> matrix_bd_cast_fp16 = slice_by_index(begin = matrix_bd_begin_0, end = matrix_bd_end_0, end_mask = matrix_bd_end_mask_0, x = matrix_bd_125_cast_fp16)[name = tensor<string, []>("matrix_bd_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_5710_cast_fp16 = add(x = matrix_ac_cast_fp16, y = matrix_bd_cast_fp16)[name = tensor<string, []>("op_5710_cast_fp16")];
            tensor<fp16, []> _inversed_scores_125_y_0_to_fp16 = const()[name = tensor<string, []>("_inversed_scores_125_y_0_to_fp16"), val = tensor<fp16, []>(0x1.6ap-4)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_125_cast_fp16 = mul(x = var_5710_cast_fp16, y = _inversed_scores_125_y_0_to_fp16)[name = tensor<string, []>("_inversed_scores_125_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> scores_cast_fp16 = select(a = var_12_to_fp16, b = _inversed_scores_125_cast_fp16, cond = mask_3)[name = tensor<string, []>("scores_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_5716_cast_fp16 = softmax(axis = var_30, x = scores_cast_fp16)[name = tensor<string, []>("op_5716_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_1645_cast_fp16 = select(a = var_11_to_fp16, b = var_5716_cast_fp16, cond = mask_3)[name = tensor<string, []>("input_1645_cast_fp16")];
            tensor<bool, []> x_695_transpose_x_0 = const()[name = tensor<string, []>("x_695_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_695_transpose_y_0 = const()[name = tensor<string, []>("x_695_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 188, 128]> value_cast_fp16 = transpose(perm = value_perm_0, x = v_cast_fp16)[name = tensor<string, []>("transpose_166")];
            tensor<fp16, [1, 8, 188, 128]> x_695_cast_fp16 = matmul(transpose_x = x_695_transpose_x_0, transpose_y = x_695_transpose_y_0, x = input_1645_cast_fp16, y = value_cast_fp16)[name = tensor<string, []>("x_695_cast_fp16")];
            tensor<int32, [4]> var_5720_perm_0 = const()[name = tensor<string, []>("op_5720_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_5721 = const()[name = tensor<string, []>("op_5721"), val = tensor<int32, [3]>([1, -1, 1024])];
            tensor<fp16, [1, 188, 8, 128]> var_5720_cast_fp16 = transpose(perm = var_5720_perm_0, x = x_695_cast_fp16)[name = tensor<string, []>("transpose_162")];
            tensor<fp16, [1, 188, 1024]> input_1647_cast_fp16 = reshape(shape = var_5721, x = var_5720_cast_fp16)[name = tensor<string, []>("input_1647_cast_fp16")];
            tensor<fp16, [1024, 1024]> encoder_layers_31_self_attn_linear_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_31_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [1024, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1554159296)))];
            tensor<fp16, [1024]> encoder_layers_31_self_attn_linear_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_31_self_attn_linear_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1556256512)))];
            tensor<fp16, [1, 188, 1024]> linear_286_cast_fp16 = linear(bias = encoder_layers_31_self_attn_linear_out_bias_to_fp16, weight = encoder_layers_31_self_attn_linear_out_weight_to_fp16, x = input_1647_cast_fp16)[name = tensor<string, []>("linear_286_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_1651_cast_fp16 = add(x = input_1643_cast_fp16, y = linear_286_cast_fp16)[name = tensor<string, []>("input_1651_cast_fp16")];
            tensor<int32, [1]> x_699_axes_0 = const()[name = tensor<string, []>("x_699_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_31_norm_conv_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_31_norm_conv_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1556258624)))];
            tensor<fp16, [1024]> encoder_layers_31_norm_conv_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_31_norm_conv_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1556260736)))];
            tensor<fp16, [1, 188, 1024]> x_699_cast_fp16 = layer_norm(axes = x_699_axes_0, beta = encoder_layers_31_norm_conv_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_31_norm_conv_weight_to_fp16, x = input_1651_cast_fp16)[name = tensor<string, []>("x_699_cast_fp16")];
            tensor<int32, [3]> input_1653_perm_0 = const()[name = tensor<string, []>("input_1653_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> input_1655_pad_type_0 = const()[name = tensor<string, []>("input_1655_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_1655_strides_0 = const()[name = tensor<string, []>("input_1655_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1655_pad_0 = const()[name = tensor<string, []>("input_1655_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1655_dilations_0 = const()[name = tensor<string, []>("input_1655_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_1655_groups_0 = const()[name = tensor<string, []>("input_1655_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [2048, 1024, 1]> encoder_layers_31_conv_pointwise_conv1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_31_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [2048, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1556262848)))];
            tensor<fp16, [2048]> encoder_layers_31_conv_pointwise_conv1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_31_conv_pointwise_conv1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1560457216)))];
            tensor<fp16, [1, 1024, 188]> input_1653_cast_fp16 = transpose(perm = input_1653_perm_0, x = x_699_cast_fp16)[name = tensor<string, []>("transpose_161")];
            tensor<fp16, [1, 2048, 188]> input_1655_cast_fp16 = conv(bias = encoder_layers_31_conv_pointwise_conv1_bias_to_fp16, dilations = input_1655_dilations_0, groups = input_1655_groups_0, pad = input_1655_pad_0, pad_type = input_1655_pad_type_0, strides = input_1655_strides_0, weight = encoder_layers_31_conv_pointwise_conv1_weight_to_fp16, x = input_1653_cast_fp16)[name = tensor<string, []>("input_1655_cast_fp16")];
            tensor<int32, []> x_701_split_num_splits_0 = const()[name = tensor<string, []>("x_701_split_num_splits_0"), val = tensor<int32, []>(2)];
            tensor<int32, []> x_701_split_axis_0 = const()[name = tensor<string, []>("x_701_split_axis_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1, 1024, 188]> x_701_split_cast_fp16_0, tensor<fp16, [1, 1024, 188]> x_701_split_cast_fp16_1 = split(axis = x_701_split_axis_0, num_splits = x_701_split_num_splits_0, x = input_1655_cast_fp16)[name = tensor<string, []>("x_701_split_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_701_split_1_sigmoid_cast_fp16 = sigmoid(x = x_701_split_cast_fp16_1)[name = tensor<string, []>("x_701_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> x_701_cast_fp16 = mul(x = x_701_split_cast_fp16_0, y = x_701_split_1_sigmoid_cast_fp16)[name = tensor<string, []>("x_701_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_1657_cast_fp16 = select(a = var_11_to_fp16, b = x_701_cast_fp16, cond = var_351)[name = tensor<string, []>("input_1657_cast_fp16")];
            tensor<int32, [6]> input_1659_pad_0 = const()[name = tensor<string, []>("input_1659_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            tensor<string, []> input_1659_mode_0 = const()[name = tensor<string, []>("input_1659_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_327_to_fp16 = const()[name = tensor<string, []>("const_327_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 1024, 196]> input_1659_cast_fp16 = pad(constant_val = const_327_to_fp16, mode = input_1659_mode_0, pad = input_1659_pad_0, x = input_1657_cast_fp16)[name = tensor<string, []>("input_1659_cast_fp16")];
            tensor<string, []> input_1661_pad_type_0 = const()[name = tensor<string, []>("input_1661_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, []> input_1661_groups_0 = const()[name = tensor<string, []>("input_1661_groups_0"), val = tensor<int32, []>(1024)];
            tensor<int32, [1]> input_1661_strides_0 = const()[name = tensor<string, []>("input_1661_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_1661_pad_0 = const()[name = tensor<string, []>("input_1661_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_1661_dilations_0 = const()[name = tensor<string, []>("input_1661_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1024, 1, 9]> const_390_to_fp16 = const()[name = tensor<string, []>("const_390_to_fp16"), val = tensor<fp16, [1024, 1, 9]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1560461376)))];
            tensor<fp16, [1024]> const_391_to_fp16 = const()[name = tensor<string, []>("const_391_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1560479872)))];
            tensor<fp16, [1, 1024, 188]> input_1663_cast_fp16 = conv(bias = const_391_to_fp16, dilations = input_1661_dilations_0, groups = input_1661_groups_0, pad = input_1661_pad_0, pad_type = input_1661_pad_type_0, strides = input_1661_strides_0, weight = const_390_to_fp16, x = input_1659_cast_fp16)[name = tensor<string, []>("input_1663_cast_fp16")];
            tensor<fp16, [1, 1024, 188]> input_1665_cast_fp16 = silu(x = input_1663_cast_fp16)[name = tensor<string, []>("input_1665_cast_fp16")];
            tensor<string, []> x_703_pad_type_0 = const()[name = tensor<string, []>("x_703_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> x_703_strides_0 = const()[name = tensor<string, []>("x_703_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_703_pad_0 = const()[name = tensor<string, []>("x_703_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_703_dilations_0 = const()[name = tensor<string, []>("x_703_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> x_703_groups_0 = const()[name = tensor<string, []>("x_703_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1024, 1024, 1]> encoder_layers_31_conv_pointwise_conv2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_31_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [1024, 1024, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1560481984)))];
            tensor<fp16, [1024]> encoder_layers_31_conv_pointwise_conv2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_31_conv_pointwise_conv2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1562579200)))];
            tensor<fp16, [1, 1024, 188]> x_703_cast_fp16 = conv(bias = encoder_layers_31_conv_pointwise_conv2_bias_to_fp16, dilations = x_703_dilations_0, groups = x_703_groups_0, pad = x_703_pad_0, pad_type = x_703_pad_type_0, strides = x_703_strides_0, weight = encoder_layers_31_conv_pointwise_conv2_weight_to_fp16, x = input_1665_cast_fp16)[name = tensor<string, []>("x_703_cast_fp16")];
            tensor<int32, [3]> input_1667_perm_0 = const()[name = tensor<string, []>("input_1667_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 1024]> input_1667_cast_fp16 = transpose(perm = input_1667_perm_0, x = x_703_cast_fp16)[name = tensor<string, []>("transpose_160")];
            tensor<fp16, [1, 188, 1024]> input_1669_cast_fp16 = add(x = input_1651_cast_fp16, y = input_1667_cast_fp16)[name = tensor<string, []>("input_1669_cast_fp16")];
            tensor<int32, [1]> input_1671_axes_0 = const()[name = tensor<string, []>("input_1671_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_31_norm_feed_forward2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_31_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1562581312)))];
            tensor<fp16, [1024]> encoder_layers_31_norm_feed_forward2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_31_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1562583424)))];
            tensor<fp16, [1, 188, 1024]> input_1671_cast_fp16 = layer_norm(axes = input_1671_axes_0, beta = encoder_layers_31_norm_feed_forward2_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_31_norm_feed_forward2_weight_to_fp16, x = input_1669_cast_fp16)[name = tensor<string, []>("input_1671_cast_fp16")];
            tensor<fp16, [4096, 1024]> encoder_layers_31_feed_forward2_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_31_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [4096, 1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1562585536)))];
            tensor<fp16, [4096]> encoder_layers_31_feed_forward2_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_31_feed_forward2_linear1_bias_to_fp16"), val = tensor<fp16, [4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1570974208)))];
            tensor<fp16, [1, 188, 4096]> linear_287_cast_fp16 = linear(bias = encoder_layers_31_feed_forward2_linear1_bias_to_fp16, weight = encoder_layers_31_feed_forward2_linear1_weight_to_fp16, x = input_1671_cast_fp16)[name = tensor<string, []>("linear_287_cast_fp16")];
            tensor<fp16, [1, 188, 4096]> input_1675_cast_fp16 = silu(x = linear_287_cast_fp16)[name = tensor<string, []>("input_1675_cast_fp16")];
            tensor<fp16, [1024, 4096]> encoder_layers_31_feed_forward2_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_31_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [1024, 4096]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1570982464)))];
            tensor<fp16, [1024]> encoder_layers_31_feed_forward2_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_31_feed_forward2_linear2_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1579371136)))];
            tensor<fp16, [1, 188, 1024]> linear_288_cast_fp16 = linear(bias = encoder_layers_31_feed_forward2_linear2_bias_to_fp16, weight = encoder_layers_31_feed_forward2_linear2_weight_to_fp16, x = input_1675_cast_fp16)[name = tensor<string, []>("linear_288_cast_fp16")];
            tensor<fp16, []> var_5787_to_fp16 = const()[name = tensor<string, []>("op_5787_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 1024]> var_5788_cast_fp16 = mul(x = linear_288_cast_fp16, y = var_5787_to_fp16)[name = tensor<string, []>("op_5788_cast_fp16")];
            tensor<fp16, [1, 188, 1024]> input_cast_fp16 = add(x = input_1669_cast_fp16, y = var_5788_cast_fp16)[name = tensor<string, []>("input_cast_fp16")];
            tensor<int32, [1]> audio_signal_axes_0 = const()[name = tensor<string, []>("audio_signal_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [1024]> encoder_layers_31_norm_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_layers_31_norm_out_weight_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1579373248)))];
            tensor<fp16, [1024]> encoder_layers_31_norm_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_layers_31_norm_out_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1579375360)))];
            tensor<fp16, [1, 188, 1024]> var_5803_cast_fp16 = layer_norm(axes = audio_signal_axes_0, beta = encoder_layers_31_norm_out_bias_to_fp16, epsilon = var_9_to_fp16, gamma = encoder_layers_31_norm_out_weight_to_fp16, x = input_cast_fp16)[name = tensor<string, []>("op_5803_cast_fp16")];
            tensor<string, []> var_5803_cast_fp16_to_fp32_dtype_0 = const()[name = tensor<string, []>("op_5803_cast_fp16_to_fp32_dtype_0"), val = tensor<string, []>("fp32")];
            tensor<fp32, [1, 188, 1024]> enc_states = cast(dtype = var_5803_cast_fp16_to_fp32_dtype_0, x = var_5803_cast_fp16)[name = tensor<string, []>("cast_299")];
        } -> (enc_states, encoder_length);
}