program(1.0)
[buildInfo = dict<tensor<string, []>, tensor<string, []>>({{"coremlc-component-MIL", "3510.2.1"}, {"coremlc-version", "3500.32.1"}, {"coremltools-component-torch", "2.7.0"}, {"coremltools-source-dialect", "TorchScript"}, {"coremltools-version", "9.0b1"}})]
{
    func main<ios17>(tensor<int32, [1]> audio_length, tensor<fp32, [1, 240000]> audio_signal) {
            tensor<int32, []> var_21 = const()[name = tensor<string, []>("op_21"), val = tensor<int32, []>(160)];
            tensor<int32, []> var_22 = const()[name = tensor<string, []>("op_22"), val = tensor<int32, []>(1)];
            tensor<int32, []> var_32 = const()[name = tensor<string, []>("op_32"), val = tensor<int32, []>(512)];
            tensor<int32, [1]> var_33 = add(x = audio_length, y = var_32)[name = tensor<string, []>("op_33")];
            tensor<int32, []> var_34 = const()[name = tensor<string, []>("op_34"), val = tensor<int32, []>(512)];
            tensor<int32, [1]> var_35 = sub(x = var_33, y = var_34)[name = tensor<string, []>("op_35")];
            tensor<int32, [1]> floor_div_0 = floor_div(x = var_35, y = var_21)[name = tensor<string, []>("floor_div_0")];
            tensor<string, []> var_36_to_fp16_dtype_0 = const()[name = tensor<string, []>("op_36_to_fp16_dtype_0"), val = tensor<string, []>("fp16")];
            tensor<fp16, []> var_37_promoted_to_fp16 = const()[name = tensor<string, []>("op_37_promoted_to_fp16"), val = tensor<fp16, []>(0x1p+0)];
            tensor<fp16, [1]> floor_div_0_to_fp16 = cast(dtype = var_36_to_fp16_dtype_0, x = floor_div_0)[name = tensor<string, []>("cast_181")];
            tensor<fp16, [1]> seq_len_1_cast_fp16 = add(x = floor_div_0_to_fp16, y = var_37_promoted_to_fp16)[name = tensor<string, []>("seq_len_1_cast_fp16")];
            tensor<string, []> seq_len_dtype_0 = const()[name = tensor<string, []>("seq_len_dtype_0"), val = tensor<string, []>("int32")];
            tensor<int32, [2]> var_41_begin_0 = const()[name = tensor<string, []>("op_41_begin_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [2]> var_41_end_0 = const()[name = tensor<string, []>("op_41_end_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<bool, [2]> var_41_end_mask_0 = const()[name = tensor<string, []>("op_41_end_mask_0"), val = tensor<bool, [2]>([true, false])];
            tensor<bool, [2]> var_41_squeeze_mask_0 = const()[name = tensor<string, []>("op_41_squeeze_mask_0"), val = tensor<bool, [2]>([false, true])];
            tensor<string, []> audio_signal_to_fp16_dtype_0 = const()[name = tensor<string, []>("audio_signal_to_fp16_dtype_0"), val = tensor<string, []>("fp16")];
            tensor<fp16, [1, 240000]> audio_signal_to_fp16 = cast(dtype = audio_signal_to_fp16_dtype_0, x = audio_signal)[name = tensor<string, []>("cast_179")];
            tensor<fp16, [1]> var_41_cast_fp16 = slice_by_index(begin = var_41_begin_0, end = var_41_end_0, end_mask = var_41_end_mask_0, squeeze_mask = var_41_squeeze_mask_0, x = audio_signal_to_fp16)[name = tensor<string, []>("op_41_cast_fp16")];
            tensor<int32, [1]> var_42_axes_0 = const()[name = tensor<string, []>("op_42_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1, 1]> var_42_cast_fp16 = expand_dims(axes = var_42_axes_0, x = var_41_cast_fp16)[name = tensor<string, []>("op_42_cast_fp16")];
            tensor<int32, [2]> var_44_begin_0 = const()[name = tensor<string, []>("op_44_begin_0"), val = tensor<int32, [2]>([0, 1])];
            tensor<int32, [2]> var_44_end_0 = const()[name = tensor<string, []>("op_44_end_0"), val = tensor<int32, [2]>([1, 240000])];
            tensor<bool, [2]> var_44_end_mask_0 = const()[name = tensor<string, []>("op_44_end_mask_0"), val = tensor<bool, [2]>([true, true])];
            tensor<fp16, [1, 239999]> var_44_cast_fp16 = slice_by_index(begin = var_44_begin_0, end = var_44_end_0, end_mask = var_44_end_mask_0, x = audio_signal_to_fp16)[name = tensor<string, []>("op_44_cast_fp16")];
            tensor<int32, [2]> var_46_begin_0 = const()[name = tensor<string, []>("op_46_begin_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [2]> var_46_end_0 = const()[name = tensor<string, []>("op_46_end_0"), val = tensor<int32, [2]>([1, 239999])];
            tensor<bool, [2]> var_46_end_mask_0 = const()[name = tensor<string, []>("op_46_end_mask_0"), val = tensor<bool, [2]>([true, false])];
            tensor<fp16, [1, 239999]> var_46_cast_fp16 = slice_by_index(begin = var_46_begin_0, end = var_46_end_0, end_mask = var_46_end_mask_0, x = audio_signal_to_fp16)[name = tensor<string, []>("op_46_cast_fp16")];
            tensor<fp16, []> var_47_to_fp16 = const()[name = tensor<string, []>("op_47_to_fp16"), val = tensor<fp16, []>(0x1.f0cp-1)];
            tensor<fp16, [1, 239999]> var_48_cast_fp16 = mul(x = var_46_cast_fp16, y = var_47_to_fp16)[name = tensor<string, []>("op_48_cast_fp16")];
            tensor<fp16, [1, 239999]> var_49_cast_fp16 = sub(x = var_44_cast_fp16, y = var_48_cast_fp16)[name = tensor<string, []>("op_49_cast_fp16")];
            tensor<bool, []> input_1_interleave_0 = const()[name = tensor<string, []>("input_1_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 240000]> input_1_cast_fp16 = concat(axis = var_22, interleave = input_1_interleave_0, values = (var_42_cast_fp16, var_49_cast_fp16))[name = tensor<string, []>("input_1_cast_fp16")];
            tensor<int32, [3]> var_55 = const()[name = tensor<string, []>("op_55"), val = tensor<int32, [3]>([1, 1, 240000])];
            tensor<fp16, [1, 1, 240000]> input_3_cast_fp16 = reshape(shape = var_55, x = input_1_cast_fp16)[name = tensor<string, []>("input_3_cast_fp16")];
            tensor<int32, [6]> input_5_pad_0 = const()[name = tensor<string, []>("input_5_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 256, 256])];
            tensor<string, []> input_5_mode_0 = const()[name = tensor<string, []>("input_5_mode_0"), val = tensor<string, []>("reflect")];
            tensor<fp16, []> const_3_to_fp16 = const()[name = tensor<string, []>("const_3_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 1, 240512]> input_5_cast_fp16 = pad(constant_val = const_3_to_fp16, mode = input_5_mode_0, pad = input_5_pad_0, x = input_3_cast_fp16)[name = tensor<string, []>("input_5_cast_fp16")];
            tensor<int32, [2]> var_61 = const()[name = tensor<string, []>("op_61"), val = tensor<int32, [2]>([1, 240512])];
            tensor<fp16, [1, 240512]> input_7_cast_fp16 = reshape(shape = var_61, x = input_5_cast_fp16)[name = tensor<string, []>("input_7_cast_fp16")];
            tensor<int32, [1]> expand_dims_6 = const()[name = tensor<string, []>("expand_dims_6"), val = tensor<int32, [1]>([160])];
            tensor<int32, [1]> expand_dims_7_axes_0 = const()[name = tensor<string, []>("expand_dims_7_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1, 1, 240512]> expand_dims_7_cast_fp16 = expand_dims(axes = expand_dims_7_axes_0, x = input_7_cast_fp16)[name = tensor<string, []>("expand_dims_7_cast_fp16")];
            tensor<string, []> conv_0_pad_type_0 = const()[name = tensor<string, []>("conv_0_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [2]> conv_0_pad_0 = const()[name = tensor<string, []>("conv_0_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> conv_0_dilations_0 = const()[name = tensor<string, []>("conv_0_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> conv_0_groups_0 = const()[name = tensor<string, []>("conv_0_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [257, 1, 512]> expand_dims_4_to_fp16 = const()[name = tensor<string, []>("expand_dims_4_to_fp16"), val = tensor<fp16, [257, 1, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(64)))];
            tensor<fp16, [1, 257, 1501]> conv_0_cast_fp16 = conv(dilations = conv_0_dilations_0, groups = conv_0_groups_0, pad = conv_0_pad_0, pad_type = conv_0_pad_type_0, strides = expand_dims_6, weight = expand_dims_4_to_fp16, x = expand_dims_7_cast_fp16)[name = tensor<string, []>("conv_0_cast_fp16")];
            tensor<string, []> conv_1_pad_type_0 = const()[name = tensor<string, []>("conv_1_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [2]> conv_1_pad_0 = const()[name = tensor<string, []>("conv_1_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> conv_1_dilations_0 = const()[name = tensor<string, []>("conv_1_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> conv_1_groups_0 = const()[name = tensor<string, []>("conv_1_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [257, 1, 512]> expand_dims_5_to_fp16 = const()[name = tensor<string, []>("expand_dims_5_to_fp16"), val = tensor<fp16, [257, 1, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(263296)))];
            tensor<fp16, [1, 257, 1501]> conv_1_cast_fp16 = conv(dilations = conv_1_dilations_0, groups = conv_1_groups_0, pad = conv_1_pad_0, pad_type = conv_1_pad_type_0, strides = expand_dims_6, weight = expand_dims_5_to_fp16, x = expand_dims_7_cast_fp16)[name = tensor<string, []>("conv_1_cast_fp16")];
            tensor<int32, []> stack_0_axis_0 = const()[name = tensor<string, []>("stack_0_axis_0"), val = tensor<int32, []>(-1)];
            tensor<fp16, [1, 257, 1501, 2]> stack_0_cast_fp16 = stack(axis = stack_0_axis_0, values = (conv_0_cast_fp16, conv_1_cast_fp16))[name = tensor<string, []>("stack_0_cast_fp16")];
            tensor<fp16, []> var_15_promoted_to_fp16 = const()[name = tensor<string, []>("op_15_promoted_to_fp16"), val = tensor<fp16, []>(0x1p+1)];
            tensor<fp16, [1, 257, 1501, 2]> var_65_cast_fp16 = pow(x = stack_0_cast_fp16, y = var_15_promoted_to_fp16)[name = tensor<string, []>("op_65_cast_fp16")];
            tensor<int32, [1]> var_67_axes_0 = const()[name = tensor<string, []>("op_67_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_67_keep_dims_0 = const()[name = tensor<string, []>("op_67_keep_dims_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 257, 1501]> var_67_cast_fp16 = reduce_sum(axes = var_67_axes_0, keep_dims = var_67_keep_dims_0, x = var_65_cast_fp16)[name = tensor<string, []>("op_67_cast_fp16")];
            tensor<fp16, [1, 257, 1501]> x_9_cast_fp16 = identity(x = var_67_cast_fp16)[name = tensor<string, []>("x_9_cast_fp16")];
            tensor<bool, []> x_11_transpose_x_0 = const()[name = tensor<string, []>("x_11_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_11_transpose_y_0 = const()[name = tensor<string, []>("x_11_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 80, 257]> const_6_to_fp16 = const()[name = tensor<string, []>("const_6_to_fp16"), val = tensor<fp16, [1, 80, 257]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(526528)))];
            tensor<fp16, [1, 80, 1501]> x_11_cast_fp16 = matmul(transpose_x = x_11_transpose_x_0, transpose_y = x_11_transpose_y_0, x = const_6_to_fp16, y = x_9_cast_fp16)[name = tensor<string, []>("x_11_cast_fp16")];
            tensor<fp16, []> var_74_to_fp16 = const()[name = tensor<string, []>("op_74_to_fp16"), val = tensor<fp16, []>(0x1p-24)];
            tensor<fp16, [1, 80, 1501]> var_75_cast_fp16 = add(x = x_11_cast_fp16, y = var_74_to_fp16)[name = tensor<string, []>("op_75_cast_fp16")];
            tensor<fp32, []> x_13_epsilon_0 = const()[name = tensor<string, []>("x_13_epsilon_0"), val = tensor<fp32, []>(0x1p-149)];
            tensor<fp16, [1, 80, 1501]> x_13_cast_fp16 = log(epsilon = x_13_epsilon_0, x = var_75_cast_fp16)[name = tensor<string, []>("x_13_cast_fp16")];
            tensor<int32, [1, 1501]> var_80 = const()[name = tensor<string, []>("op_80"), val = tensor<int32, [1, 1501]>([[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, 188, 189, 190, 191, 192, 193, 194, 195, 196, 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1496, 1497, 1498, 1499, 1500]])];
            tensor<int32, [1]> var_83_axes_0 = const()[name = tensor<string, []>("op_83_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [1]> seq_len_1_cast_fp16_to_int32 = cast(dtype = seq_len_dtype_0, x = seq_len_1_cast_fp16)[name = tensor<string, []>("cast_180")];
            tensor<int32, [1, 1]> var_83 = expand_dims(axes = var_83_axes_0, x = seq_len_1_cast_fp16_to_int32)[name = tensor<string, []>("op_83")];
            tensor<bool, [1, 1501]> valid_mask = less(x = var_80, y = var_83)[name = tensor<string, []>("valid_mask")];
            tensor<int32, [1]> var_85_axes_0 = const()[name = tensor<string, []>("op_85_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<bool, [1, 1, 1501]> var_85 = expand_dims(axes = var_85_axes_0, x = valid_mask)[name = tensor<string, []>("op_85")];
            tensor<int32, [3]> var_85_after_broadcast_reps_0 = const()[name = tensor<string, []>("op_85_after_broadcast_reps_0"), val = tensor<int32, [3]>([1, 80, 1])];
            tensor<bool, [1, 80, 1501]> var_85_after_broadcast = tile(reps = var_85_after_broadcast_reps_0, x = var_85)[name = tensor<string, []>("op_85_after_broadcast")];
            tensor<fp16, [1, 80, 1501]> var_8_after_broadcast_to_fp16 = const()[name = tensor<string, []>("op_8_after_broadcast_to_fp16"), val = tensor<fp16, [1, 80, 1501]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(567744)))];
            tensor<fp16, [1, 80, 1501]> var_86_cast_fp16 = select(a = x_13_cast_fp16, b = var_8_after_broadcast_to_fp16, cond = var_85_after_broadcast)[name = tensor<string, []>("op_86_cast_fp16")];
            tensor<int32, [1]> x_mean_numerator_axes_0 = const()[name = tensor<string, []>("x_mean_numerator_axes_0"), val = tensor<int32, [1]>([2])];
            tensor<bool, []> x_mean_numerator_keep_dims_0 = const()[name = tensor<string, []>("x_mean_numerator_keep_dims_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 80]> x_mean_numerator_cast_fp16 = reduce_sum(axes = x_mean_numerator_axes_0, keep_dims = x_mean_numerator_keep_dims_0, x = var_86_cast_fp16)[name = tensor<string, []>("x_mean_numerator_cast_fp16")];
            tensor<int32, [1]> x_mean_denominator_axes_0 = const()[name = tensor<string, []>("x_mean_denominator_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<bool, []> x_mean_denominator_keep_dims_0 = const()[name = tensor<string, []>("x_mean_denominator_keep_dims_0"), val = tensor<bool, []>(false)];
            tensor<string, []> cast_2_to_fp16_dtype_0 = const()[name = tensor<string, []>("cast_2_to_fp16_dtype_0"), val = tensor<string, []>("fp16")];
            tensor<fp16, [1, 1501]> valid_mask_to_fp16 = cast(dtype = cast_2_to_fp16_dtype_0, x = valid_mask)[name = tensor<string, []>("cast_178")];
            tensor<fp16, [1]> x_mean_denominator_cast_fp16 = reduce_sum(axes = x_mean_denominator_axes_0, keep_dims = x_mean_denominator_keep_dims_0, x = valid_mask_to_fp16)[name = tensor<string, []>("x_mean_denominator_cast_fp16")];
            tensor<int32, [1]> var_91_axes_0 = const()[name = tensor<string, []>("op_91_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1, 1]> var_91_cast_fp16 = expand_dims(axes = var_91_axes_0, x = x_mean_denominator_cast_fp16)[name = tensor<string, []>("op_91_cast_fp16")];
            tensor<fp16, [1, 80]> x_mean_cast_fp16 = real_div(x = x_mean_numerator_cast_fp16, y = var_91_cast_fp16)[name = tensor<string, []>("x_mean_cast_fp16")];
            tensor<int32, [1]> var_94_axes_0 = const()[name = tensor<string, []>("op_94_axes_0"), val = tensor<int32, [1]>([2])];
            tensor<fp16, [1, 80, 1]> var_94_cast_fp16 = expand_dims(axes = var_94_axes_0, x = x_mean_cast_fp16)[name = tensor<string, []>("op_94_cast_fp16")];
            tensor<fp16, [1, 80, 1501]> var_95_cast_fp16 = sub(x = x_13_cast_fp16, y = var_94_cast_fp16)[name = tensor<string, []>("op_95_cast_fp16")];
            tensor<fp16, [1, 80, 1501]> var_96_cast_fp16 = select(a = var_95_cast_fp16, b = var_8_after_broadcast_to_fp16, cond = var_85_after_broadcast)[name = tensor<string, []>("op_96_cast_fp16")];
            tensor<fp16, []> var_15_promoted_1_to_fp16 = const()[name = tensor<string, []>("op_15_promoted_1_to_fp16"), val = tensor<fp16, []>(0x1p+1)];
            tensor<fp16, [1, 80, 1501]> var_97_cast_fp16 = pow(x = var_96_cast_fp16, y = var_15_promoted_1_to_fp16)[name = tensor<string, []>("op_97_cast_fp16")];
            tensor<int32, [1]> var_99_axes_0 = const()[name = tensor<string, []>("op_99_axes_0"), val = tensor<int32, [1]>([2])];
            tensor<bool, []> var_99_keep_dims_0 = const()[name = tensor<string, []>("op_99_keep_dims_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 80]> var_99_cast_fp16 = reduce_sum(axes = var_99_axes_0, keep_dims = var_99_keep_dims_0, x = var_97_cast_fp16)[name = tensor<string, []>("op_99_cast_fp16")];
            tensor<fp16, []> var_101_to_fp16 = const()[name = tensor<string, []>("op_101_to_fp16"), val = tensor<fp16, []>(0x1p+0)];
            tensor<fp16, [1, 1]> var_102_cast_fp16 = sub(x = var_91_cast_fp16, y = var_101_to_fp16)[name = tensor<string, []>("op_102_cast_fp16")];
            tensor<fp16, [1, 80]> var_103_cast_fp16 = real_div(x = var_99_cast_fp16, y = var_102_cast_fp16)[name = tensor<string, []>("op_103_cast_fp16")];
            tensor<fp16, [1, 80]> x_std_1_cast_fp16 = sqrt(x = var_103_cast_fp16)[name = tensor<string, []>("x_std_1_cast_fp16")];
            tensor<fp16, []> var_7_to_fp16 = const()[name = tensor<string, []>("op_7_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 80]> x_std_cast_fp16 = add(x = x_std_1_cast_fp16, y = var_7_to_fp16)[name = tensor<string, []>("x_std_cast_fp16")];
            tensor<int32, [1]> var_108_axes_0 = const()[name = tensor<string, []>("op_108_axes_0"), val = tensor<int32, [1]>([2])];
            tensor<fp16, [1, 80, 1]> var_108_cast_fp16 = expand_dims(axes = var_108_axes_0, x = x_std_cast_fp16)[name = tensor<string, []>("op_108_cast_fp16")];
            tensor<fp16, [1, 80, 1501]> x_15_cast_fp16 = real_div(x = var_95_cast_fp16, y = var_108_cast_fp16)[name = tensor<string, []>("x_15_cast_fp16")];
            tensor<bool, [1, 1501]> mask_3 = greater_equal(x = var_80, y = var_83)[name = tensor<string, []>("mask_3")];
            tensor<int32, [1]> var_117_axes_0 = const()[name = tensor<string, []>("op_117_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<bool, [1, 1, 1501]> var_117 = expand_dims(axes = var_117_axes_0, x = mask_3)[name = tensor<string, []>("op_117")];
            tensor<fp16, []> cast_9_to_fp16 = const()[name = tensor<string, []>("cast_9_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 80, 1501]> processed_signal_cast_fp16 = select(a = cast_9_to_fp16, b = x_15_cast_fp16, cond = var_117)[name = tensor<string, []>("processed_signal_cast_fp16")];
            tensor<int32, []> var_138 = const()[name = tensor<string, []>("op_138"), val = tensor<int32, []>(-1)];
            tensor<int32, [3]> x_17_perm_0 = const()[name = tensor<string, []>("x_17_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> var_201_to_fp16_dtype_0 = const()[name = tensor<string, []>("op_201_to_fp16_dtype_0"), val = tensor<string, []>("fp16")];
            tensor<fp16, []> var_202_promoted_to_fp16 = const()[name = tensor<string, []>("op_202_promoted_to_fp16"), val = tensor<fp16, []>(-0x1p+0)];
            tensor<fp16, [1]> seq_len_1_cast_fp16_to_int32_to_fp16 = cast(dtype = var_201_to_fp16_dtype_0, x = seq_len_1_cast_fp16_to_int32)[name = tensor<string, []>("cast_177")];
            tensor<fp16, [1]> var_203_cast_fp16 = add(x = seq_len_1_cast_fp16_to_int32_to_fp16, y = var_202_promoted_to_fp16)[name = tensor<string, []>("op_203_cast_fp16")];
            tensor<fp16, []> _inversed_205_y_0_to_fp16 = const()[name = tensor<string, []>("_inversed_205_y_0_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1]> _inversed_205_cast_fp16 = mul(x = var_203_cast_fp16, y = _inversed_205_y_0_to_fp16)[name = tensor<string, []>("_inversed_205_cast_fp16")];
            tensor<fp16, []> var_206_to_fp16 = const()[name = tensor<string, []>("op_206_to_fp16"), val = tensor<fp16, []>(0x1p+0)];
            tensor<fp16, [1]> lengths_1_cast_fp16 = add(x = _inversed_205_cast_fp16, y = var_206_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_210_promoted_to_fp16 = const()[name = tensor<string, []>("op_210_promoted_to_fp16"), val = tensor<fp16, []>(-0x1p+0)];
            tensor<fp16, [1]> var_211_cast_fp16 = add(x = lengths_3_cast_fp16, y = var_210_promoted_to_fp16)[name = tensor<string, []>("op_211_cast_fp16")];
            tensor<fp16, []> _inversed_213_y_0_to_fp16 = const()[name = tensor<string, []>("_inversed_213_y_0_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1]> _inversed_213_cast_fp16 = mul(x = var_211_cast_fp16, y = _inversed_213_y_0_to_fp16)[name = tensor<string, []>("_inversed_213_cast_fp16")];
            tensor<fp16, []> var_214_to_fp16 = const()[name = tensor<string, []>("op_214_to_fp16"), val = tensor<fp16, []>(0x1p+0)];
            tensor<fp16, [1]> lengths_7_cast_fp16 = add(x = _inversed_213_cast_fp16, y = var_214_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_218_promoted_to_fp16 = const()[name = tensor<string, []>("op_218_promoted_to_fp16"), val = tensor<fp16, []>(-0x1p+0)];
            tensor<fp16, [1]> var_219_cast_fp16 = add(x = lengths_9_cast_fp16, y = var_218_promoted_to_fp16)[name = tensor<string, []>("op_219_cast_fp16")];
            tensor<fp16, []> _inversed_221_y_0_to_fp16 = const()[name = tensor<string, []>("_inversed_221_y_0_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1]> _inversed_221_cast_fp16 = mul(x = var_219_cast_fp16, y = _inversed_221_y_0_to_fp16)[name = tensor<string, []>("_inversed_221_cast_fp16")];
            tensor<fp16, []> var_222_to_fp16 = const()[name = tensor<string, []>("op_222_to_fp16"), val = tensor<fp16, []>(0x1p+0)];
            tensor<fp16, [1]> lengths_13_cast_fp16 = add(x = _inversed_221_cast_fp16, y = var_222_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_9_axes_0 = const()[name = tensor<string, []>("input_9_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [1, 1501, 80]> x_17_cast_fp16 = transpose(perm = x_17_perm_0, x = processed_signal_cast_fp16)[name = tensor<string, []>("transpose_207")];
            tensor<fp16, [1, 1, 1501, 80]> input_9_cast_fp16 = expand_dims(axes = input_9_axes_0, x = x_17_cast_fp16)[name = tensor<string, []>("input_9_cast_fp16")];
            tensor<string, []> input_11_pad_type_0 = const()[name = tensor<string, []>("input_11_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_11_pad_0 = const()[name = tensor<string, []>("input_11_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_11_strides_0 = const()[name = tensor<string, []>("input_11_strides_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [2]> input_11_dilations_0 = const()[name = tensor<string, []>("input_11_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_11_groups_0 = const()[name = tensor<string, []>("input_11_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 1, 3, 3]> encoder_module_pre_encode_conv_0_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_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, []>(808000)))];
            tensor<fp16, [256]> encoder_module_pre_encode_conv_0_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_pre_encode_conv_0_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(812672)))];
            tensor<fp16, [1, 256, 751, 40]> input_11_cast_fp16 = conv(bias = encoder_module_pre_encode_conv_0_bias_to_fp16, dilations = input_11_dilations_0, groups = input_11_groups_0, pad = input_11_pad_0, pad_type = input_11_pad_type_0, strides = input_11_strides_0, weight = encoder_module_pre_encode_conv_0_weight_to_fp16, x = input_9_cast_fp16)[name = tensor<string, []>("input_11_cast_fp16")];
            tensor<fp16, [1, 256, 751, 40]> input_13_cast_fp16 = relu(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, []>("custom")];
            tensor<int32, [4]> input_15_pad_0 = const()[name = tensor<string, []>("input_15_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_15_strides_0 = const()[name = tensor<string, []>("input_15_strides_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, []> input_15_groups_0 = const()[name = tensor<string, []>("input_15_groups_0"), val = tensor<int32, []>(256)];
            tensor<int32, [2]> input_15_dilations_0 = const()[name = tensor<string, []>("input_15_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [256, 1, 3, 3]> encoder_module_pre_encode_conv_2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_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, []>(813248)))];
            tensor<fp16, [256]> encoder_module_pre_encode_conv_2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_pre_encode_conv_2_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(817920)))];
            tensor<fp16, [1, 256, 376, 20]> input_15_cast_fp16 = conv(bias = encoder_module_pre_encode_conv_2_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_module_pre_encode_conv_2_weight_to_fp16, x = input_13_cast_fp16)[name = tensor<string, []>("input_15_cast_fp16")];
            tensor<string, []> input_17_pad_type_0 = const()[name = tensor<string, []>("input_17_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [2]> input_17_strides_0 = const()[name = tensor<string, []>("input_17_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_17_pad_0 = const()[name = tensor<string, []>("input_17_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> input_17_dilations_0 = const()[name = tensor<string, []>("input_17_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_17_groups_0 = const()[name = tensor<string, []>("input_17_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 1, 1]> encoder_module_pre_encode_conv_3_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_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, []>(818496)))];
            tensor<fp16, [256]> encoder_module_pre_encode_conv_3_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_pre_encode_conv_3_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(949632)))];
            tensor<fp16, [1, 256, 376, 20]> input_17_cast_fp16 = conv(bias = encoder_module_pre_encode_conv_3_bias_to_fp16, dilations = input_17_dilations_0, groups = input_17_groups_0, pad = input_17_pad_0, pad_type = input_17_pad_type_0, strides = input_17_strides_0, weight = encoder_module_pre_encode_conv_3_weight_to_fp16, x = input_15_cast_fp16)[name = tensor<string, []>("input_17_cast_fp16")];
            tensor<fp16, [1, 256, 376, 20]> input_19_cast_fp16 = relu(x = input_17_cast_fp16)[name = tensor<string, []>("input_19_cast_fp16")];
            tensor<string, []> input_21_pad_type_0 = const()[name = tensor<string, []>("input_21_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_21_pad_0 = const()[name = tensor<string, []>("input_21_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_21_strides_0 = const()[name = tensor<string, []>("input_21_strides_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, []> input_21_groups_0 = const()[name = tensor<string, []>("input_21_groups_0"), val = tensor<int32, []>(256)];
            tensor<int32, [2]> input_21_dilations_0 = const()[name = tensor<string, []>("input_21_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<fp16, [256, 1, 3, 3]> encoder_module_pre_encode_conv_5_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_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, []>(950208)))];
            tensor<fp16, [256]> encoder_module_pre_encode_conv_5_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_pre_encode_conv_5_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(954880)))];
            tensor<fp16, [1, 256, 188, 10]> input_21_cast_fp16 = conv(bias = encoder_module_pre_encode_conv_5_bias_to_fp16, dilations = input_21_dilations_0, groups = input_21_groups_0, pad = input_21_pad_0, pad_type = input_21_pad_type_0, strides = input_21_strides_0, weight = encoder_module_pre_encode_conv_5_weight_to_fp16, x = input_19_cast_fp16)[name = tensor<string, []>("input_21_cast_fp16")];
            tensor<string, []> input_23_pad_type_0 = const()[name = tensor<string, []>("input_23_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [2]> input_23_strides_0 = const()[name = tensor<string, []>("input_23_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [4]> input_23_pad_0 = const()[name = tensor<string, []>("input_23_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> input_23_dilations_0 = const()[name = tensor<string, []>("input_23_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_23_groups_0 = const()[name = tensor<string, []>("input_23_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [256, 256, 1, 1]> encoder_module_pre_encode_conv_6_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_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, []>(955456)))];
            tensor<fp16, [256]> encoder_module_pre_encode_conv_6_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_pre_encode_conv_6_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1086592)))];
            tensor<fp16, [1, 256, 188, 10]> input_23_cast_fp16 = conv(bias = encoder_module_pre_encode_conv_6_bias_to_fp16, dilations = input_23_dilations_0, groups = input_23_groups_0, pad = input_23_pad_0, pad_type = input_23_pad_type_0, strides = input_23_strides_0, weight = encoder_module_pre_encode_conv_6_weight_to_fp16, x = input_21_cast_fp16)[name = tensor<string, []>("input_23_cast_fp16")];
            tensor<fp16, [1, 256, 188, 10]> x_19_cast_fp16 = relu(x = input_23_cast_fp16)[name = tensor<string, []>("x_19_cast_fp16")];
            tensor<int32, [4]> var_272_perm_0 = const()[name = tensor<string, []>("op_272_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_273 = const()[name = tensor<string, []>("op_273"), val = tensor<int32, [3]>([1, 188, -1])];
            tensor<fp16, [1, 188, 256, 10]> var_272_cast_fp16 = transpose(perm = var_272_perm_0, x = x_19_cast_fp16)[name = tensor<string, []>("transpose_206")];
            tensor<fp16, [1, 188, 2560]> input_25_cast_fp16 = reshape(shape = var_273, x = var_272_cast_fp16)[name = tensor<string, []>("input_25_cast_fp16")];
            tensor<fp16, [512, 2560]> encoder_module_pre_encode_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_pre_encode_out_weight_to_fp16"), val = tensor<fp16, [512, 2560]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1087168)))];
            tensor<fp16, [512]> encoder_module_pre_encode_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_pre_encode_out_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3708672)))];
            tensor<fp16, [1, 188, 512]> linear_0_cast_fp16 = linear(bias = encoder_module_pre_encode_out_bias_to_fp16, weight = encoder_module_pre_encode_out_weight_to_fp16, x = input_25_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_3 = const()[name = tensor<string, []>("expand_dims_3"), 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_311_axes_0 = const()[name = tensor<string, []>("op_311_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_176")];
            tensor<int32, [1, 1]> var_311 = expand_dims(axes = var_311_axes_0, x = encoder_length)[name = tensor<string, []>("op_311")];
            tensor<bool, [1, 188]> pad_mask_1 = less(x = expand_dims_3, y = var_311)[name = tensor<string, []>("pad_mask_1")];
            tensor<int32, [1]> var_313_axes_0 = const()[name = tensor<string, []>("op_313_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<bool, [1, 1, 188]> var_313 = expand_dims(axes = var_313_axes_0, x = pad_mask_1)[name = tensor<string, []>("op_313")];
            tensor<int32, [3]> var_314 = const()[name = tensor<string, []>("op_314"), val = tensor<int32, [3]>([1, 188, 1])];
            tensor<bool, [1, 188, 188]> pad_mask_for_att_mask_1 = tile(reps = var_314, x = var_313)[name = tensor<string, []>("pad_mask_for_att_mask_1")];
            tensor<int32, [3]> var_316_perm_0 = const()[name = tensor<string, []>("op_316_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<bool, [1, 188, 188]> var_316 = transpose(perm = var_316_perm_0, x = pad_mask_for_att_mask_1)[name = tensor<string, []>("transpose_205")];
            tensor<bool, [1, 188, 188]> pad_mask_for_att_mask = logical_and(x = pad_mask_for_att_mask_1, y = var_316)[name = tensor<string, []>("pad_mask_for_att_mask")];
            tensor<bool, [1, 188, 188]> const_22 = const()[name = tensor<string, []>("const_22"), 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_22)[name = tensor<string, []>("att_mask")];
            tensor<bool, [1, 188, 188]> mask_5 = logical_not(x = att_mask)[name = tensor<string, []>("mask_5")];
            tensor<bool, [1, 188]> pad_mask = logical_not(x = pad_mask_1)[name = tensor<string, []>("pad_mask")];
            tensor<int32, [1]> input_29_axes_0 = const()[name = tensor<string, []>("input_29_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_0_norm_feed_forward1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_0_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3709760)))];
            tensor<fp16, [512]> encoder_module_layers_0_norm_feed_forward1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_0_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3710848)))];
            tensor<fp16, []> var_156_to_fp16 = const()[name = tensor<string, []>("op_156_to_fp16"), val = tensor<fp16, []>(0x1.5p-17)];
            tensor<fp16, [1, 188, 512]> input_29_cast_fp16 = layer_norm(axes = input_29_axes_0, beta = encoder_module_layers_0_norm_feed_forward1_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_0_norm_feed_forward1_weight_to_fp16, x = linear_0_cast_fp16)[name = tensor<string, []>("input_29_cast_fp16")];
            tensor<fp16, [2048, 512]> encoder_module_layers_0_feed_forward1_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_0_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [2048, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3711936)))];
            tensor<fp16, [2048]> encoder_module_layers_0_feed_forward1_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_0_feed_forward1_linear1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5809152)))];
            tensor<fp16, [1, 188, 2048]> linear_1_cast_fp16 = linear(bias = encoder_module_layers_0_feed_forward1_linear1_bias_to_fp16, weight = encoder_module_layers_0_feed_forward1_linear1_weight_to_fp16, x = input_29_cast_fp16)[name = tensor<string, []>("linear_1_cast_fp16")];
            tensor<fp16, [1, 188, 2048]> input_33_cast_fp16 = silu(x = linear_1_cast_fp16)[name = tensor<string, []>("input_33_cast_fp16")];
            tensor<fp16, [512, 2048]> encoder_module_layers_0_feed_forward1_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_0_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [512, 2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5813312)))];
            tensor<fp16, [512]> encoder_module_layers_0_feed_forward1_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_0_feed_forward1_linear2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7910528)))];
            tensor<fp16, [1, 188, 512]> linear_2_cast_fp16 = linear(bias = encoder_module_layers_0_feed_forward1_linear2_bias_to_fp16, weight = encoder_module_layers_0_feed_forward1_linear2_weight_to_fp16, x = input_33_cast_fp16)[name = tensor<string, []>("linear_2_cast_fp16")];
            tensor<fp16, []> var_349_to_fp16 = const()[name = tensor<string, []>("op_349_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 512]> var_350_cast_fp16 = mul(x = linear_2_cast_fp16, y = var_349_to_fp16)[name = tensor<string, []>("op_350_cast_fp16")];
            tensor<fp16, [1, 188, 512]> input_39_cast_fp16 = add(x = linear_0_cast_fp16, y = var_350_cast_fp16)[name = tensor<string, []>("input_39_cast_fp16")];
            tensor<int32, [1]> query_1_axes_0 = const()[name = tensor<string, []>("query_1_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_0_norm_self_att_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_0_norm_self_att_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7911616)))];
            tensor<fp16, [512]> encoder_module_layers_0_norm_self_att_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_0_norm_self_att_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7912704)))];
            tensor<fp16, [1, 188, 512]> query_1_cast_fp16 = layer_norm(axes = query_1_axes_0, beta = encoder_module_layers_0_norm_self_att_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_0_norm_self_att_weight_to_fp16, x = input_39_cast_fp16)[name = tensor<string, []>("query_1_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_0_self_attn_linear_q_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_0_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7913792)))];
            tensor<fp16, [512]> encoder_module_layers_0_self_attn_linear_q_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_0_self_attn_linear_q_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8438144)))];
            tensor<fp16, [1, 188, 512]> linear_3_cast_fp16 = linear(bias = encoder_module_layers_0_self_attn_linear_q_bias_to_fp16, weight = encoder_module_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_367 = const()[name = tensor<string, []>("op_367"), val = tensor<int32, [4]>([1, -1, 8, 64])];
            tensor<fp16, [1, 188, 8, 64]> q_1_cast_fp16 = reshape(shape = var_367, x = linear_3_cast_fp16)[name = tensor<string, []>("q_1_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_0_self_attn_linear_k_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_0_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8439232)))];
            tensor<fp16, [512]> encoder_module_layers_0_self_attn_linear_k_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_0_self_attn_linear_k_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8963584)))];
            tensor<fp16, [1, 188, 512]> linear_4_cast_fp16 = linear(bias = encoder_module_layers_0_self_attn_linear_k_bias_to_fp16, weight = encoder_module_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_372 = const()[name = tensor<string, []>("op_372"), val = tensor<int32, [4]>([1, -1, 8, 64])];
            tensor<fp16, [1, 188, 8, 64]> k_1_cast_fp16 = reshape(shape = var_372, x = linear_4_cast_fp16)[name = tensor<string, []>("k_1_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_0_self_attn_linear_v_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_0_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8964672)))];
            tensor<fp16, [512]> encoder_module_layers_0_self_attn_linear_v_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_0_self_attn_linear_v_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9489024)))];
            tensor<fp16, [1, 188, 512]> linear_5_cast_fp16 = linear(bias = encoder_module_layers_0_self_attn_linear_v_bias_to_fp16, weight = encoder_module_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_377 = const()[name = tensor<string, []>("op_377"), val = tensor<int32, [4]>([1, -1, 8, 64])];
            tensor<fp16, [1, 188, 8, 64]> v_1_cast_fp16 = reshape(shape = var_377, x = linear_5_cast_fp16)[name = tensor<string, []>("v_1_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, 64]> encoder_module_layers_0_self_attn_pos_bias_u_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_0_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9490112)))];
            tensor<fp16, [1, 188, 8, 64]> var_389_cast_fp16 = add(x = q_1_cast_fp16, y = encoder_module_layers_0_self_attn_pos_bias_u_to_fp16)[name = tensor<string, []>("op_389_cast_fp16")];
            tensor<fp16, [8, 64]> encoder_module_layers_0_self_attn_pos_bias_v_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_0_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9491200)))];
            tensor<fp16, [1, 188, 8, 64]> var_391_cast_fp16 = add(x = q_1_cast_fp16, y = encoder_module_layers_0_self_attn_pos_bias_v_to_fp16)[name = tensor<string, []>("op_391_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_23_transpose_x_0 = const()[name = tensor<string, []>("x_23_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_23_transpose_y_0 = const()[name = tensor<string, []>("x_23_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 64, 375]> var_393_to_fp16 = const()[name = tensor<string, []>("op_393_to_fp16"), val = tensor<fp16, [1, 8, 64, 375]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9492288)))];
            tensor<fp16, [1, 8, 188, 64]> q_with_bias_v_1_cast_fp16 = transpose(perm = q_with_bias_v_1_perm_0, x = var_391_cast_fp16)[name = tensor<string, []>("transpose_203")];
            tensor<fp16, [1, 8, 188, 375]> x_23_cast_fp16 = matmul(transpose_x = x_23_transpose_x_0, transpose_y = x_23_transpose_y_0, x = q_with_bias_v_1_cast_fp16, y = var_393_to_fp16)[name = tensor<string, []>("x_23_cast_fp16")];
            tensor<int32, [8]> x_25_pad_0 = const()[name = tensor<string, []>("x_25_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            tensor<string, []> x_25_mode_0 = const()[name = tensor<string, []>("x_25_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_29_to_fp16 = const()[name = tensor<string, []>("const_29_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_25_cast_fp16 = pad(constant_val = const_29_to_fp16, mode = x_25_mode_0, pad = x_25_pad_0, x = x_23_cast_fp16)[name = tensor<string, []>("x_25_cast_fp16")];
            tensor<int32, [4]> var_401 = const()[name = tensor<string, []>("op_401"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_27_cast_fp16 = reshape(shape = var_401, x = x_25_cast_fp16)[name = tensor<string, []>("x_27_cast_fp16")];
            tensor<int32, [4]> var_405_begin_0 = const()[name = tensor<string, []>("op_405_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_405_end_0 = const()[name = tensor<string, []>("op_405_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_405_end_mask_0 = const()[name = tensor<string, []>("op_405_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_405_cast_fp16 = slice_by_index(begin = var_405_begin_0, end = var_405_end_0, end_mask = var_405_end_mask_0, x = x_27_cast_fp16)[name = tensor<string, []>("op_405_cast_fp16")];
            tensor<int32, [4]> var_406 = const()[name = tensor<string, []>("op_406"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_1_cast_fp16 = reshape(shape = var_406, x = var_405_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_51_perm_0 = const()[name = tensor<string, []>("transpose_51_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_52_perm_0 = const()[name = tensor<string, []>("transpose_52_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 64, 188]> transpose_52 = transpose(perm = transpose_52_perm_0, x = k_1_cast_fp16)[name = tensor<string, []>("transpose_201")];
            tensor<fp16, [1, 8, 188, 64]> transpose_51 = transpose(perm = transpose_51_perm_0, x = var_389_cast_fp16)[name = tensor<string, []>("transpose_202")];
            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_51, y = transpose_52)[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_415_cast_fp16 = add(x = matrix_ac_1_cast_fp16, y = matrix_bd_3_cast_fp16)[name = tensor<string, []>("op_415_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, []>(0x1p-3)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_1_cast_fp16 = mul(x = var_415_cast_fp16, y = _inversed_scores_1_y_0_to_fp16)[name = tensor<string, []>("_inversed_scores_1_cast_fp16")];
            tensor<int32, [1]> mask_7_axes_0 = const()[name = tensor<string, []>("mask_7_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<bool, [1, 1, 188, 188]> mask_7 = expand_dims(axes = mask_7_axes_0, x = mask_5)[name = tensor<string, []>("mask_7")];
            tensor<fp16, []> var_153_to_fp16 = const()[name = tensor<string, []>("op_153_to_fp16"), val = tensor<fp16, []>(-0x1.388p+13)];
            tensor<fp16, [1, 8, 188, 188]> scores_3_cast_fp16 = select(a = var_153_to_fp16, b = _inversed_scores_1_cast_fp16, cond = mask_7)[name = tensor<string, []>("scores_3_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_421_cast_fp16 = softmax(axis = var_138, x = scores_3_cast_fp16)[name = tensor<string, []>("op_421_cast_fp16")];
            tensor<fp16, []> var_154_to_fp16 = const()[name = tensor<string, []>("op_154_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 8, 188, 188]> input_41_cast_fp16 = select(a = var_154_to_fp16, b = var_421_cast_fp16, cond = mask_7)[name = tensor<string, []>("input_41_cast_fp16")];
            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, 188, 64]> value_5_cast_fp16 = transpose(perm = value_5_perm_0, x = v_1_cast_fp16)[name = tensor<string, []>("transpose_204")];
            tensor<fp16, [1, 8, 188, 64]> x_29_cast_fp16 = matmul(transpose_x = x_29_transpose_x_0, transpose_y = x_29_transpose_y_0, x = input_41_cast_fp16, y = value_5_cast_fp16)[name = tensor<string, []>("x_29_cast_fp16")];
            tensor<int32, [4]> var_425_perm_0 = const()[name = tensor<string, []>("op_425_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_426 = const()[name = tensor<string, []>("op_426"), val = tensor<int32, [3]>([1, -1, 512])];
            tensor<fp16, [1, 188, 8, 64]> var_425_cast_fp16 = transpose(perm = var_425_perm_0, x = x_29_cast_fp16)[name = tensor<string, []>("transpose_200")];
            tensor<fp16, [1, 188, 512]> input_43_cast_fp16 = reshape(shape = var_426, x = var_425_cast_fp16)[name = tensor<string, []>("input_43_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_0_self_attn_linear_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_0_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9876352)))];
            tensor<fp16, [512]> encoder_module_layers_0_self_attn_linear_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_0_self_attn_linear_out_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10400704)))];
            tensor<fp16, [1, 188, 512]> linear_7_cast_fp16 = linear(bias = encoder_module_layers_0_self_attn_linear_out_bias_to_fp16, weight = encoder_module_layers_0_self_attn_linear_out_weight_to_fp16, x = input_43_cast_fp16)[name = tensor<string, []>("linear_7_cast_fp16")];
            tensor<fp16, [1, 188, 512]> input_47_cast_fp16 = add(x = input_39_cast_fp16, y = linear_7_cast_fp16)[name = tensor<string, []>("input_47_cast_fp16")];
            tensor<int32, [1]> x_33_axes_0 = const()[name = tensor<string, []>("x_33_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_0_norm_conv_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_0_norm_conv_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10401792)))];
            tensor<fp16, [512]> encoder_module_layers_0_norm_conv_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_0_norm_conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10402880)))];
            tensor<fp16, [1, 188, 512]> x_33_cast_fp16 = layer_norm(axes = x_33_axes_0, beta = encoder_module_layers_0_norm_conv_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_0_norm_conv_weight_to_fp16, x = input_47_cast_fp16)[name = tensor<string, []>("x_33_cast_fp16")];
            tensor<int32, [3]> input_49_perm_0 = const()[name = tensor<string, []>("input_49_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> input_51_pad_type_0 = const()[name = tensor<string, []>("input_51_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_51_strides_0 = const()[name = tensor<string, []>("input_51_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_51_pad_0 = const()[name = tensor<string, []>("input_51_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_51_dilations_0 = const()[name = tensor<string, []>("input_51_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_51_groups_0 = const()[name = tensor<string, []>("input_51_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1024, 512, 1]> encoder_module_layers_0_conv_pointwise_conv1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_0_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [1024, 512, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10403968)))];
            tensor<fp16, [1024]> encoder_module_layers_0_conv_pointwise_conv1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_0_conv_pointwise_conv1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11452608)))];
            tensor<fp16, [1, 512, 188]> input_49_cast_fp16 = transpose(perm = input_49_perm_0, x = x_33_cast_fp16)[name = tensor<string, []>("transpose_199")];
            tensor<fp16, [1, 1024, 188]> input_51_cast_fp16 = conv(bias = encoder_module_layers_0_conv_pointwise_conv1_bias_to_fp16, dilations = input_51_dilations_0, groups = input_51_groups_0, pad = input_51_pad_0, pad_type = input_51_pad_type_0, strides = input_51_strides_0, weight = encoder_module_layers_0_conv_pointwise_conv1_weight_to_fp16, x = input_49_cast_fp16)[name = tensor<string, []>("input_51_cast_fp16")];
            tensor<int32, []> x_35_split_num_splits_0 = const()[name = tensor<string, []>("x_35_split_num_splits_0"), val = tensor<int32, []>(2)];
            tensor<int32, []> x_35_split_axis_0 = const()[name = tensor<string, []>("x_35_split_axis_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1, 512, 188]> x_35_split_cast_fp16_0, tensor<fp16, [1, 512, 188]> x_35_split_cast_fp16_1 = split(axis = x_35_split_axis_0, num_splits = x_35_split_num_splits_0, x = input_51_cast_fp16)[name = tensor<string, []>("x_35_split_cast_fp16")];
            tensor<fp16, [1, 512, 188]> x_35_split_1_sigmoid_cast_fp16 = sigmoid(x = x_35_split_cast_fp16_1)[name = tensor<string, []>("x_35_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 512, 188]> x_35_cast_fp16 = mul(x = x_35_split_cast_fp16_0, y = x_35_split_1_sigmoid_cast_fp16)[name = tensor<string, []>("x_35_cast_fp16")];
            tensor<int32, [1]> var_450_axes_0 = const()[name = tensor<string, []>("op_450_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<bool, [1, 1, 188]> var_450 = expand_dims(axes = var_450_axes_0, x = pad_mask)[name = tensor<string, []>("op_450")];
            tensor<fp16, [1, 512, 188]> input_53_cast_fp16 = select(a = var_154_to_fp16, b = x_35_cast_fp16, cond = var_450)[name = tensor<string, []>("input_53_cast_fp16")];
            tensor<int32, [6]> input_55_pad_0 = const()[name = tensor<string, []>("input_55_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            tensor<string, []> input_55_mode_0 = const()[name = tensor<string, []>("input_55_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_32_to_fp16 = const()[name = tensor<string, []>("const_32_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 512, 196]> input_55_cast_fp16 = pad(constant_val = const_32_to_fp16, mode = input_55_mode_0, pad = input_55_pad_0, x = input_53_cast_fp16)[name = tensor<string, []>("input_55_cast_fp16")];
            tensor<string, []> input_57_pad_type_0 = const()[name = tensor<string, []>("input_57_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, []> input_57_groups_0 = const()[name = tensor<string, []>("input_57_groups_0"), val = tensor<int32, []>(512)];
            tensor<int32, [1]> input_57_strides_0 = const()[name = tensor<string, []>("input_57_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_57_pad_0 = const()[name = tensor<string, []>("input_57_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_57_dilations_0 = const()[name = tensor<string, []>("input_57_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 9]> const_193_to_fp16 = const()[name = tensor<string, []>("const_193_to_fp16"), val = tensor<fp16, [512, 1, 9]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11454720)))];
            tensor<fp16, [512]> const_194_to_fp16 = const()[name = tensor<string, []>("const_194_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11464000)))];
            tensor<fp16, [1, 512, 188]> input_59_cast_fp16 = conv(bias = const_194_to_fp16, dilations = input_57_dilations_0, groups = input_57_groups_0, pad = input_57_pad_0, pad_type = input_57_pad_type_0, strides = input_57_strides_0, weight = const_193_to_fp16, x = input_55_cast_fp16)[name = tensor<string, []>("input_59_cast_fp16")];
            tensor<fp16, [1, 512, 188]> input_61_cast_fp16 = silu(x = input_59_cast_fp16)[name = tensor<string, []>("input_61_cast_fp16")];
            tensor<string, []> x_37_pad_type_0 = const()[name = tensor<string, []>("x_37_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> x_37_strides_0 = const()[name = tensor<string, []>("x_37_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_37_pad_0 = const()[name = tensor<string, []>("x_37_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_37_dilations_0 = const()[name = tensor<string, []>("x_37_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> x_37_groups_0 = const()[name = tensor<string, []>("x_37_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [512, 512, 1]> encoder_module_layers_0_conv_pointwise_conv2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_0_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [512, 512, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11465088)))];
            tensor<fp16, [512]> encoder_module_layers_0_conv_pointwise_conv2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_0_conv_pointwise_conv2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11989440)))];
            tensor<fp16, [1, 512, 188]> x_37_cast_fp16 = conv(bias = encoder_module_layers_0_conv_pointwise_conv2_bias_to_fp16, dilations = x_37_dilations_0, groups = x_37_groups_0, pad = x_37_pad_0, pad_type = x_37_pad_type_0, strides = x_37_strides_0, weight = encoder_module_layers_0_conv_pointwise_conv2_weight_to_fp16, x = input_61_cast_fp16)[name = tensor<string, []>("x_37_cast_fp16")];
            tensor<int32, [3]> input_63_perm_0 = const()[name = tensor<string, []>("input_63_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 512]> input_63_cast_fp16 = transpose(perm = input_63_perm_0, x = x_37_cast_fp16)[name = tensor<string, []>("transpose_198")];
            tensor<fp16, [1, 188, 512]> input_65_cast_fp16 = add(x = input_47_cast_fp16, y = input_63_cast_fp16)[name = tensor<string, []>("input_65_cast_fp16")];
            tensor<int32, [1]> input_67_axes_0 = const()[name = tensor<string, []>("input_67_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_0_norm_feed_forward2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_0_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11990528)))];
            tensor<fp16, [512]> encoder_module_layers_0_norm_feed_forward2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_0_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11991616)))];
            tensor<fp16, [1, 188, 512]> input_67_cast_fp16 = layer_norm(axes = input_67_axes_0, beta = encoder_module_layers_0_norm_feed_forward2_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_0_norm_feed_forward2_weight_to_fp16, x = input_65_cast_fp16)[name = tensor<string, []>("input_67_cast_fp16")];
            tensor<fp16, [2048, 512]> encoder_module_layers_0_feed_forward2_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_0_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [2048, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11992704)))];
            tensor<fp16, [2048]> encoder_module_layers_0_feed_forward2_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_0_feed_forward2_linear1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14089920)))];
            tensor<fp16, [1, 188, 2048]> linear_8_cast_fp16 = linear(bias = encoder_module_layers_0_feed_forward2_linear1_bias_to_fp16, weight = encoder_module_layers_0_feed_forward2_linear1_weight_to_fp16, x = input_67_cast_fp16)[name = tensor<string, []>("linear_8_cast_fp16")];
            tensor<fp16, [1, 188, 2048]> input_71_cast_fp16 = silu(x = linear_8_cast_fp16)[name = tensor<string, []>("input_71_cast_fp16")];
            tensor<fp16, [512, 2048]> encoder_module_layers_0_feed_forward2_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_0_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [512, 2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14094080)))];
            tensor<fp16, [512]> encoder_module_layers_0_feed_forward2_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_0_feed_forward2_linear2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(16191296)))];
            tensor<fp16, [1, 188, 512]> linear_9_cast_fp16 = linear(bias = encoder_module_layers_0_feed_forward2_linear2_bias_to_fp16, weight = encoder_module_layers_0_feed_forward2_linear2_weight_to_fp16, x = input_71_cast_fp16)[name = tensor<string, []>("linear_9_cast_fp16")];
            tensor<fp16, []> var_492_to_fp16 = const()[name = tensor<string, []>("op_492_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 512]> var_493_cast_fp16 = mul(x = linear_9_cast_fp16, y = var_492_to_fp16)[name = tensor<string, []>("op_493_cast_fp16")];
            tensor<fp16, [1, 188, 512]> input_77_cast_fp16 = add(x = input_65_cast_fp16, y = var_493_cast_fp16)[name = tensor<string, []>("input_77_cast_fp16")];
            tensor<int32, [1]> input_79_axes_0 = const()[name = tensor<string, []>("input_79_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_0_norm_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_0_norm_out_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(16192384)))];
            tensor<fp16, [512]> encoder_module_layers_0_norm_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_0_norm_out_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(16193472)))];
            tensor<fp16, [1, 188, 512]> input_79_cast_fp16 = layer_norm(axes = input_79_axes_0, beta = encoder_module_layers_0_norm_out_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_0_norm_out_weight_to_fp16, x = input_77_cast_fp16)[name = tensor<string, []>("input_79_cast_fp16")];
            tensor<int32, [1]> input_81_axes_0 = const()[name = tensor<string, []>("input_81_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_1_norm_feed_forward1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_1_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(16194560)))];
            tensor<fp16, [512]> encoder_module_layers_1_norm_feed_forward1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_1_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(16195648)))];
            tensor<fp16, [1, 188, 512]> input_81_cast_fp16 = layer_norm(axes = input_81_axes_0, beta = encoder_module_layers_1_norm_feed_forward1_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_1_norm_feed_forward1_weight_to_fp16, x = input_79_cast_fp16)[name = tensor<string, []>("input_81_cast_fp16")];
            tensor<fp16, [2048, 512]> encoder_module_layers_1_feed_forward1_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_1_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [2048, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(16196736)))];
            tensor<fp16, [2048]> encoder_module_layers_1_feed_forward1_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_1_feed_forward1_linear1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(18293952)))];
            tensor<fp16, [1, 188, 2048]> linear_10_cast_fp16 = linear(bias = encoder_module_layers_1_feed_forward1_linear1_bias_to_fp16, weight = encoder_module_layers_1_feed_forward1_linear1_weight_to_fp16, x = input_81_cast_fp16)[name = tensor<string, []>("linear_10_cast_fp16")];
            tensor<fp16, [1, 188, 2048]> input_85_cast_fp16 = silu(x = linear_10_cast_fp16)[name = tensor<string, []>("input_85_cast_fp16")];
            tensor<fp16, [512, 2048]> encoder_module_layers_1_feed_forward1_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_1_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [512, 2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(18298112)))];
            tensor<fp16, [512]> encoder_module_layers_1_feed_forward1_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_1_feed_forward1_linear2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(20395328)))];
            tensor<fp16, [1, 188, 512]> linear_11_cast_fp16 = linear(bias = encoder_module_layers_1_feed_forward1_linear2_bias_to_fp16, weight = encoder_module_layers_1_feed_forward1_linear2_weight_to_fp16, x = input_85_cast_fp16)[name = tensor<string, []>("linear_11_cast_fp16")];
            tensor<fp16, []> var_523_to_fp16 = const()[name = tensor<string, []>("op_523_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 512]> var_524_cast_fp16 = mul(x = linear_11_cast_fp16, y = var_523_to_fp16)[name = tensor<string, []>("op_524_cast_fp16")];
            tensor<fp16, [1, 188, 512]> input_91_cast_fp16 = add(x = input_79_cast_fp16, y = var_524_cast_fp16)[name = tensor<string, []>("input_91_cast_fp16")];
            tensor<int32, [1]> query_3_axes_0 = const()[name = tensor<string, []>("query_3_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_1_norm_self_att_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_1_norm_self_att_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(20396416)))];
            tensor<fp16, [512]> encoder_module_layers_1_norm_self_att_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_1_norm_self_att_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(20397504)))];
            tensor<fp16, [1, 188, 512]> query_3_cast_fp16 = layer_norm(axes = query_3_axes_0, beta = encoder_module_layers_1_norm_self_att_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_1_norm_self_att_weight_to_fp16, x = input_91_cast_fp16)[name = tensor<string, []>("query_3_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_1_self_attn_linear_q_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_1_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(20398592)))];
            tensor<fp16, [512]> encoder_module_layers_1_self_attn_linear_q_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_1_self_attn_linear_q_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(20922944)))];
            tensor<fp16, [1, 188, 512]> linear_12_cast_fp16 = linear(bias = encoder_module_layers_1_self_attn_linear_q_bias_to_fp16, weight = encoder_module_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_541 = const()[name = tensor<string, []>("op_541"), val = tensor<int32, [4]>([1, -1, 8, 64])];
            tensor<fp16, [1, 188, 8, 64]> q_7_cast_fp16 = reshape(shape = var_541, x = linear_12_cast_fp16)[name = tensor<string, []>("q_7_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_1_self_attn_linear_k_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_1_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(20924032)))];
            tensor<fp16, [512]> encoder_module_layers_1_self_attn_linear_k_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_1_self_attn_linear_k_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(21448384)))];
            tensor<fp16, [1, 188, 512]> linear_13_cast_fp16 = linear(bias = encoder_module_layers_1_self_attn_linear_k_bias_to_fp16, weight = encoder_module_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_546 = const()[name = tensor<string, []>("op_546"), val = tensor<int32, [4]>([1, -1, 8, 64])];
            tensor<fp16, [1, 188, 8, 64]> k_5_cast_fp16 = reshape(shape = var_546, x = linear_13_cast_fp16)[name = tensor<string, []>("k_5_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_1_self_attn_linear_v_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_1_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(21449472)))];
            tensor<fp16, [512]> encoder_module_layers_1_self_attn_linear_v_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_1_self_attn_linear_v_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(21973824)))];
            tensor<fp16, [1, 188, 512]> linear_14_cast_fp16 = linear(bias = encoder_module_layers_1_self_attn_linear_v_bias_to_fp16, weight = encoder_module_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_551 = const()[name = tensor<string, []>("op_551"), val = tensor<int32, [4]>([1, -1, 8, 64])];
            tensor<fp16, [1, 188, 8, 64]> v_3_cast_fp16 = reshape(shape = var_551, x = linear_14_cast_fp16)[name = tensor<string, []>("v_3_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, 64]> encoder_module_layers_1_self_attn_pos_bias_u_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_1_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(21974912)))];
            tensor<fp16, [1, 188, 8, 64]> var_563_cast_fp16 = add(x = q_7_cast_fp16, y = encoder_module_layers_1_self_attn_pos_bias_u_to_fp16)[name = tensor<string, []>("op_563_cast_fp16")];
            tensor<fp16, [8, 64]> encoder_module_layers_1_self_attn_pos_bias_v_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_1_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(21976000)))];
            tensor<fp16, [1, 188, 8, 64]> var_565_cast_fp16 = add(x = q_7_cast_fp16, y = encoder_module_layers_1_self_attn_pos_bias_v_to_fp16)[name = tensor<string, []>("op_565_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_45_transpose_x_0 = const()[name = tensor<string, []>("x_45_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_45_transpose_y_0 = const()[name = tensor<string, []>("x_45_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 64, 375]> var_567_to_fp16 = const()[name = tensor<string, []>("op_567_to_fp16"), val = tensor<fp16, [1, 8, 64, 375]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(21977088)))];
            tensor<fp16, [1, 8, 188, 64]> q_with_bias_v_3_cast_fp16 = transpose(perm = q_with_bias_v_3_perm_0, x = var_565_cast_fp16)[name = tensor<string, []>("transpose_196")];
            tensor<fp16, [1, 8, 188, 375]> x_45_cast_fp16 = matmul(transpose_x = x_45_transpose_x_0, transpose_y = x_45_transpose_y_0, x = q_with_bias_v_3_cast_fp16, y = var_567_to_fp16)[name = tensor<string, []>("x_45_cast_fp16")];
            tensor<int32, [8]> x_47_pad_0 = const()[name = tensor<string, []>("x_47_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            tensor<string, []> x_47_mode_0 = const()[name = tensor<string, []>("x_47_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_39_to_fp16 = const()[name = tensor<string, []>("const_39_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_47_cast_fp16 = pad(constant_val = const_39_to_fp16, mode = x_47_mode_0, pad = x_47_pad_0, x = x_45_cast_fp16)[name = tensor<string, []>("x_47_cast_fp16")];
            tensor<int32, [4]> var_575 = const()[name = tensor<string, []>("op_575"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_49_cast_fp16 = reshape(shape = var_575, x = x_47_cast_fp16)[name = tensor<string, []>("x_49_cast_fp16")];
            tensor<int32, [4]> var_579_begin_0 = const()[name = tensor<string, []>("op_579_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_579_end_0 = const()[name = tensor<string, []>("op_579_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_579_end_mask_0 = const()[name = tensor<string, []>("op_579_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_579_cast_fp16 = slice_by_index(begin = var_579_begin_0, end = var_579_end_0, end_mask = var_579_end_mask_0, x = x_49_cast_fp16)[name = tensor<string, []>("op_579_cast_fp16")];
            tensor<int32, [4]> var_580 = const()[name = tensor<string, []>("op_580"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_5_cast_fp16 = reshape(shape = var_580, x = var_579_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_53_perm_0 = const()[name = tensor<string, []>("transpose_53_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_54_perm_0 = const()[name = tensor<string, []>("transpose_54_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 64, 188]> transpose_54 = transpose(perm = transpose_54_perm_0, x = k_5_cast_fp16)[name = tensor<string, []>("transpose_194")];
            tensor<fp16, [1, 8, 188, 64]> transpose_53 = transpose(perm = transpose_53_perm_0, x = var_563_cast_fp16)[name = tensor<string, []>("transpose_195")];
            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_53, y = transpose_54)[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_589_cast_fp16 = add(x = matrix_ac_3_cast_fp16, y = matrix_bd_7_cast_fp16)[name = tensor<string, []>("op_589_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, []>(0x1p-3)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_5_cast_fp16 = mul(x = var_589_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_153_to_fp16, b = _inversed_scores_5_cast_fp16, cond = mask_7)[name = tensor<string, []>("scores_7_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_595_cast_fp16 = softmax(axis = var_138, x = scores_7_cast_fp16)[name = tensor<string, []>("op_595_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_93_cast_fp16 = select(a = var_154_to_fp16, b = var_595_cast_fp16, cond = mask_7)[name = tensor<string, []>("input_93_cast_fp16")];
            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, 188, 64]> value_7_cast_fp16 = transpose(perm = value_7_perm_0, x = v_3_cast_fp16)[name = tensor<string, []>("transpose_197")];
            tensor<fp16, [1, 8, 188, 64]> x_51_cast_fp16 = matmul(transpose_x = x_51_transpose_x_0, transpose_y = x_51_transpose_y_0, x = input_93_cast_fp16, y = value_7_cast_fp16)[name = tensor<string, []>("x_51_cast_fp16")];
            tensor<int32, [4]> var_599_perm_0 = const()[name = tensor<string, []>("op_599_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_600 = const()[name = tensor<string, []>("op_600"), val = tensor<int32, [3]>([1, -1, 512])];
            tensor<fp16, [1, 188, 8, 64]> var_599_cast_fp16 = transpose(perm = var_599_perm_0, x = x_51_cast_fp16)[name = tensor<string, []>("transpose_193")];
            tensor<fp16, [1, 188, 512]> input_95_cast_fp16 = reshape(shape = var_600, x = var_599_cast_fp16)[name = tensor<string, []>("input_95_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_1_self_attn_linear_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_1_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(22361152)))];
            tensor<fp16, [512]> encoder_module_layers_1_self_attn_linear_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_1_self_attn_linear_out_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(22885504)))];
            tensor<fp16, [1, 188, 512]> linear_16_cast_fp16 = linear(bias = encoder_module_layers_1_self_attn_linear_out_bias_to_fp16, weight = encoder_module_layers_1_self_attn_linear_out_weight_to_fp16, x = input_95_cast_fp16)[name = tensor<string, []>("linear_16_cast_fp16")];
            tensor<fp16, [1, 188, 512]> input_99_cast_fp16 = add(x = input_91_cast_fp16, y = linear_16_cast_fp16)[name = tensor<string, []>("input_99_cast_fp16")];
            tensor<int32, [1]> x_55_axes_0 = const()[name = tensor<string, []>("x_55_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_1_norm_conv_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_1_norm_conv_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(22886592)))];
            tensor<fp16, [512]> encoder_module_layers_1_norm_conv_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_1_norm_conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(22887680)))];
            tensor<fp16, [1, 188, 512]> x_55_cast_fp16 = layer_norm(axes = x_55_axes_0, beta = encoder_module_layers_1_norm_conv_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_1_norm_conv_weight_to_fp16, x = input_99_cast_fp16)[name = tensor<string, []>("x_55_cast_fp16")];
            tensor<int32, [3]> input_101_perm_0 = const()[name = tensor<string, []>("input_101_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> input_103_pad_type_0 = const()[name = tensor<string, []>("input_103_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_103_strides_0 = const()[name = tensor<string, []>("input_103_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_103_pad_0 = const()[name = tensor<string, []>("input_103_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_103_dilations_0 = const()[name = tensor<string, []>("input_103_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_103_groups_0 = const()[name = tensor<string, []>("input_103_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1024, 512, 1]> encoder_module_layers_1_conv_pointwise_conv1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_1_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [1024, 512, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(22888768)))];
            tensor<fp16, [1024]> encoder_module_layers_1_conv_pointwise_conv1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_1_conv_pointwise_conv1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(23937408)))];
            tensor<fp16, [1, 512, 188]> input_101_cast_fp16 = transpose(perm = input_101_perm_0, x = x_55_cast_fp16)[name = tensor<string, []>("transpose_192")];
            tensor<fp16, [1, 1024, 188]> input_103_cast_fp16 = conv(bias = encoder_module_layers_1_conv_pointwise_conv1_bias_to_fp16, dilations = input_103_dilations_0, groups = input_103_groups_0, pad = input_103_pad_0, pad_type = input_103_pad_type_0, strides = input_103_strides_0, weight = encoder_module_layers_1_conv_pointwise_conv1_weight_to_fp16, x = input_101_cast_fp16)[name = tensor<string, []>("input_103_cast_fp16")];
            tensor<int32, []> x_57_split_num_splits_0 = const()[name = tensor<string, []>("x_57_split_num_splits_0"), val = tensor<int32, []>(2)];
            tensor<int32, []> x_57_split_axis_0 = const()[name = tensor<string, []>("x_57_split_axis_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1, 512, 188]> x_57_split_cast_fp16_0, tensor<fp16, [1, 512, 188]> x_57_split_cast_fp16_1 = split(axis = x_57_split_axis_0, num_splits = x_57_split_num_splits_0, x = input_103_cast_fp16)[name = tensor<string, []>("x_57_split_cast_fp16")];
            tensor<fp16, [1, 512, 188]> x_57_split_1_sigmoid_cast_fp16 = sigmoid(x = x_57_split_cast_fp16_1)[name = tensor<string, []>("x_57_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 512, 188]> x_57_cast_fp16 = mul(x = x_57_split_cast_fp16_0, y = x_57_split_1_sigmoid_cast_fp16)[name = tensor<string, []>("x_57_cast_fp16")];
            tensor<fp16, [1, 512, 188]> input_105_cast_fp16 = select(a = var_154_to_fp16, b = x_57_cast_fp16, cond = var_450)[name = tensor<string, []>("input_105_cast_fp16")];
            tensor<int32, [6]> input_107_pad_0 = const()[name = tensor<string, []>("input_107_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            tensor<string, []> input_107_mode_0 = const()[name = tensor<string, []>("input_107_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_42_to_fp16 = const()[name = tensor<string, []>("const_42_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 512, 196]> input_107_cast_fp16 = pad(constant_val = const_42_to_fp16, mode = input_107_mode_0, pad = input_107_pad_0, x = input_105_cast_fp16)[name = tensor<string, []>("input_107_cast_fp16")];
            tensor<string, []> input_109_pad_type_0 = const()[name = tensor<string, []>("input_109_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, []> input_109_groups_0 = const()[name = tensor<string, []>("input_109_groups_0"), val = tensor<int32, []>(512)];
            tensor<int32, [1]> input_109_strides_0 = const()[name = tensor<string, []>("input_109_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_109_pad_0 = const()[name = tensor<string, []>("input_109_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_109_dilations_0 = const()[name = tensor<string, []>("input_109_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 9]> const_195_to_fp16 = const()[name = tensor<string, []>("const_195_to_fp16"), val = tensor<fp16, [512, 1, 9]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(23939520)))];
            tensor<fp16, [512]> const_196_to_fp16 = const()[name = tensor<string, []>("const_196_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(23948800)))];
            tensor<fp16, [1, 512, 188]> input_111_cast_fp16 = conv(bias = const_196_to_fp16, dilations = input_109_dilations_0, groups = input_109_groups_0, pad = input_109_pad_0, pad_type = input_109_pad_type_0, strides = input_109_strides_0, weight = const_195_to_fp16, x = input_107_cast_fp16)[name = tensor<string, []>("input_111_cast_fp16")];
            tensor<fp16, [1, 512, 188]> input_113_cast_fp16 = silu(x = input_111_cast_fp16)[name = tensor<string, []>("input_113_cast_fp16")];
            tensor<string, []> x_59_pad_type_0 = const()[name = tensor<string, []>("x_59_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> x_59_strides_0 = const()[name = tensor<string, []>("x_59_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_59_pad_0 = const()[name = tensor<string, []>("x_59_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_59_dilations_0 = const()[name = tensor<string, []>("x_59_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> x_59_groups_0 = const()[name = tensor<string, []>("x_59_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [512, 512, 1]> encoder_module_layers_1_conv_pointwise_conv2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_1_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [512, 512, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(23949888)))];
            tensor<fp16, [512]> encoder_module_layers_1_conv_pointwise_conv2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_1_conv_pointwise_conv2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(24474240)))];
            tensor<fp16, [1, 512, 188]> x_59_cast_fp16 = conv(bias = encoder_module_layers_1_conv_pointwise_conv2_bias_to_fp16, dilations = x_59_dilations_0, groups = x_59_groups_0, pad = x_59_pad_0, pad_type = x_59_pad_type_0, strides = x_59_strides_0, weight = encoder_module_layers_1_conv_pointwise_conv2_weight_to_fp16, x = input_113_cast_fp16)[name = tensor<string, []>("x_59_cast_fp16")];
            tensor<int32, [3]> input_115_perm_0 = const()[name = tensor<string, []>("input_115_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 512]> input_115_cast_fp16 = transpose(perm = input_115_perm_0, x = x_59_cast_fp16)[name = tensor<string, []>("transpose_191")];
            tensor<fp16, [1, 188, 512]> input_117_cast_fp16 = add(x = input_99_cast_fp16, y = input_115_cast_fp16)[name = tensor<string, []>("input_117_cast_fp16")];
            tensor<int32, [1]> input_119_axes_0 = const()[name = tensor<string, []>("input_119_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_1_norm_feed_forward2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_1_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(24475328)))];
            tensor<fp16, [512]> encoder_module_layers_1_norm_feed_forward2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_1_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(24476416)))];
            tensor<fp16, [1, 188, 512]> input_119_cast_fp16 = layer_norm(axes = input_119_axes_0, beta = encoder_module_layers_1_norm_feed_forward2_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_1_norm_feed_forward2_weight_to_fp16, x = input_117_cast_fp16)[name = tensor<string, []>("input_119_cast_fp16")];
            tensor<fp16, [2048, 512]> encoder_module_layers_1_feed_forward2_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_1_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [2048, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(24477504)))];
            tensor<fp16, [2048]> encoder_module_layers_1_feed_forward2_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_1_feed_forward2_linear1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(26574720)))];
            tensor<fp16, [1, 188, 2048]> linear_17_cast_fp16 = linear(bias = encoder_module_layers_1_feed_forward2_linear1_bias_to_fp16, weight = encoder_module_layers_1_feed_forward2_linear1_weight_to_fp16, x = input_119_cast_fp16)[name = tensor<string, []>("linear_17_cast_fp16")];
            tensor<fp16, [1, 188, 2048]> input_123_cast_fp16 = silu(x = linear_17_cast_fp16)[name = tensor<string, []>("input_123_cast_fp16")];
            tensor<fp16, [512, 2048]> encoder_module_layers_1_feed_forward2_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_1_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [512, 2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(26578880)))];
            tensor<fp16, [512]> encoder_module_layers_1_feed_forward2_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_1_feed_forward2_linear2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(28676096)))];
            tensor<fp16, [1, 188, 512]> linear_18_cast_fp16 = linear(bias = encoder_module_layers_1_feed_forward2_linear2_bias_to_fp16, weight = encoder_module_layers_1_feed_forward2_linear2_weight_to_fp16, x = input_123_cast_fp16)[name = tensor<string, []>("linear_18_cast_fp16")];
            tensor<fp16, []> var_666_to_fp16 = const()[name = tensor<string, []>("op_666_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 512]> var_667_cast_fp16 = mul(x = linear_18_cast_fp16, y = var_666_to_fp16)[name = tensor<string, []>("op_667_cast_fp16")];
            tensor<fp16, [1, 188, 512]> input_129_cast_fp16 = add(x = input_117_cast_fp16, y = var_667_cast_fp16)[name = tensor<string, []>("input_129_cast_fp16")];
            tensor<int32, [1]> input_131_axes_0 = const()[name = tensor<string, []>("input_131_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_1_norm_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_1_norm_out_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(28677184)))];
            tensor<fp16, [512]> encoder_module_layers_1_norm_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_1_norm_out_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(28678272)))];
            tensor<fp16, [1, 188, 512]> input_131_cast_fp16 = layer_norm(axes = input_131_axes_0, beta = encoder_module_layers_1_norm_out_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_1_norm_out_weight_to_fp16, x = input_129_cast_fp16)[name = tensor<string, []>("input_131_cast_fp16")];
            tensor<int32, [1]> input_133_axes_0 = const()[name = tensor<string, []>("input_133_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_2_norm_feed_forward1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_2_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(28679360)))];
            tensor<fp16, [512]> encoder_module_layers_2_norm_feed_forward1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_2_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(28680448)))];
            tensor<fp16, [1, 188, 512]> input_133_cast_fp16 = layer_norm(axes = input_133_axes_0, beta = encoder_module_layers_2_norm_feed_forward1_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_2_norm_feed_forward1_weight_to_fp16, x = input_131_cast_fp16)[name = tensor<string, []>("input_133_cast_fp16")];
            tensor<fp16, [2048, 512]> encoder_module_layers_2_feed_forward1_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_2_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [2048, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(28681536)))];
            tensor<fp16, [2048]> encoder_module_layers_2_feed_forward1_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_2_feed_forward1_linear1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(30778752)))];
            tensor<fp16, [1, 188, 2048]> linear_19_cast_fp16 = linear(bias = encoder_module_layers_2_feed_forward1_linear1_bias_to_fp16, weight = encoder_module_layers_2_feed_forward1_linear1_weight_to_fp16, x = input_133_cast_fp16)[name = tensor<string, []>("linear_19_cast_fp16")];
            tensor<fp16, [1, 188, 2048]> input_137_cast_fp16 = silu(x = linear_19_cast_fp16)[name = tensor<string, []>("input_137_cast_fp16")];
            tensor<fp16, [512, 2048]> encoder_module_layers_2_feed_forward1_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_2_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [512, 2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(30782912)))];
            tensor<fp16, [512]> encoder_module_layers_2_feed_forward1_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_2_feed_forward1_linear2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(32880128)))];
            tensor<fp16, [1, 188, 512]> linear_20_cast_fp16 = linear(bias = encoder_module_layers_2_feed_forward1_linear2_bias_to_fp16, weight = encoder_module_layers_2_feed_forward1_linear2_weight_to_fp16, x = input_137_cast_fp16)[name = tensor<string, []>("linear_20_cast_fp16")];
            tensor<fp16, []> var_697_to_fp16 = const()[name = tensor<string, []>("op_697_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 512]> var_698_cast_fp16 = mul(x = linear_20_cast_fp16, y = var_697_to_fp16)[name = tensor<string, []>("op_698_cast_fp16")];
            tensor<fp16, [1, 188, 512]> input_143_cast_fp16 = add(x = input_131_cast_fp16, y = var_698_cast_fp16)[name = tensor<string, []>("input_143_cast_fp16")];
            tensor<int32, [1]> query_5_axes_0 = const()[name = tensor<string, []>("query_5_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_2_norm_self_att_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_2_norm_self_att_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(32881216)))];
            tensor<fp16, [512]> encoder_module_layers_2_norm_self_att_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_2_norm_self_att_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(32882304)))];
            tensor<fp16, [1, 188, 512]> query_5_cast_fp16 = layer_norm(axes = query_5_axes_0, beta = encoder_module_layers_2_norm_self_att_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_2_norm_self_att_weight_to_fp16, x = input_143_cast_fp16)[name = tensor<string, []>("query_5_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_2_self_attn_linear_q_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_2_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(32883392)))];
            tensor<fp16, [512]> encoder_module_layers_2_self_attn_linear_q_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_2_self_attn_linear_q_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(33407744)))];
            tensor<fp16, [1, 188, 512]> linear_21_cast_fp16 = linear(bias = encoder_module_layers_2_self_attn_linear_q_bias_to_fp16, weight = encoder_module_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_715 = const()[name = tensor<string, []>("op_715"), val = tensor<int32, [4]>([1, -1, 8, 64])];
            tensor<fp16, [1, 188, 8, 64]> q_13_cast_fp16 = reshape(shape = var_715, x = linear_21_cast_fp16)[name = tensor<string, []>("q_13_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_2_self_attn_linear_k_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_2_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(33408832)))];
            tensor<fp16, [512]> encoder_module_layers_2_self_attn_linear_k_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_2_self_attn_linear_k_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(33933184)))];
            tensor<fp16, [1, 188, 512]> linear_22_cast_fp16 = linear(bias = encoder_module_layers_2_self_attn_linear_k_bias_to_fp16, weight = encoder_module_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_720 = const()[name = tensor<string, []>("op_720"), val = tensor<int32, [4]>([1, -1, 8, 64])];
            tensor<fp16, [1, 188, 8, 64]> k_9_cast_fp16 = reshape(shape = var_720, x = linear_22_cast_fp16)[name = tensor<string, []>("k_9_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_2_self_attn_linear_v_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_2_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(33934272)))];
            tensor<fp16, [512]> encoder_module_layers_2_self_attn_linear_v_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_2_self_attn_linear_v_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(34458624)))];
            tensor<fp16, [1, 188, 512]> linear_23_cast_fp16 = linear(bias = encoder_module_layers_2_self_attn_linear_v_bias_to_fp16, weight = encoder_module_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_725 = const()[name = tensor<string, []>("op_725"), val = tensor<int32, [4]>([1, -1, 8, 64])];
            tensor<fp16, [1, 188, 8, 64]> v_5_cast_fp16 = reshape(shape = var_725, x = linear_23_cast_fp16)[name = tensor<string, []>("v_5_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, 64]> encoder_module_layers_2_self_attn_pos_bias_u_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_2_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(34459712)))];
            tensor<fp16, [1, 188, 8, 64]> var_737_cast_fp16 = add(x = q_13_cast_fp16, y = encoder_module_layers_2_self_attn_pos_bias_u_to_fp16)[name = tensor<string, []>("op_737_cast_fp16")];
            tensor<fp16, [8, 64]> encoder_module_layers_2_self_attn_pos_bias_v_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_2_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(34460800)))];
            tensor<fp16, [1, 188, 8, 64]> var_739_cast_fp16 = add(x = q_13_cast_fp16, y = encoder_module_layers_2_self_attn_pos_bias_v_to_fp16)[name = tensor<string, []>("op_739_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_67_transpose_x_0 = const()[name = tensor<string, []>("x_67_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_67_transpose_y_0 = const()[name = tensor<string, []>("x_67_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 64, 375]> var_741_to_fp16 = const()[name = tensor<string, []>("op_741_to_fp16"), val = tensor<fp16, [1, 8, 64, 375]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(34461888)))];
            tensor<fp16, [1, 8, 188, 64]> q_with_bias_v_5_cast_fp16 = transpose(perm = q_with_bias_v_5_perm_0, x = var_739_cast_fp16)[name = tensor<string, []>("transpose_189")];
            tensor<fp16, [1, 8, 188, 375]> x_67_cast_fp16 = matmul(transpose_x = x_67_transpose_x_0, transpose_y = x_67_transpose_y_0, x = q_with_bias_v_5_cast_fp16, y = var_741_to_fp16)[name = tensor<string, []>("x_67_cast_fp16")];
            tensor<int32, [8]> x_69_pad_0 = const()[name = tensor<string, []>("x_69_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            tensor<string, []> x_69_mode_0 = const()[name = tensor<string, []>("x_69_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_49_to_fp16 = const()[name = tensor<string, []>("const_49_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_69_cast_fp16 = pad(constant_val = const_49_to_fp16, mode = x_69_mode_0, pad = x_69_pad_0, x = x_67_cast_fp16)[name = tensor<string, []>("x_69_cast_fp16")];
            tensor<int32, [4]> var_749 = const()[name = tensor<string, []>("op_749"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_71_cast_fp16 = reshape(shape = var_749, x = x_69_cast_fp16)[name = tensor<string, []>("x_71_cast_fp16")];
            tensor<int32, [4]> var_753_begin_0 = const()[name = tensor<string, []>("op_753_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_753_end_0 = const()[name = tensor<string, []>("op_753_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_753_end_mask_0 = const()[name = tensor<string, []>("op_753_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_753_cast_fp16 = slice_by_index(begin = var_753_begin_0, end = var_753_end_0, end_mask = var_753_end_mask_0, x = x_71_cast_fp16)[name = tensor<string, []>("op_753_cast_fp16")];
            tensor<int32, [4]> var_754 = const()[name = tensor<string, []>("op_754"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_9_cast_fp16 = reshape(shape = var_754, x = var_753_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_55_perm_0 = const()[name = tensor<string, []>("transpose_55_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_56_perm_0 = const()[name = tensor<string, []>("transpose_56_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 64, 188]> transpose_56 = transpose(perm = transpose_56_perm_0, x = k_9_cast_fp16)[name = tensor<string, []>("transpose_187")];
            tensor<fp16, [1, 8, 188, 64]> transpose_55 = transpose(perm = transpose_55_perm_0, x = var_737_cast_fp16)[name = tensor<string, []>("transpose_188")];
            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_55, y = transpose_56)[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_763_cast_fp16 = add(x = matrix_ac_5_cast_fp16, y = matrix_bd_11_cast_fp16)[name = tensor<string, []>("op_763_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, []>(0x1p-3)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_9_cast_fp16 = mul(x = var_763_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_153_to_fp16, b = _inversed_scores_9_cast_fp16, cond = mask_7)[name = tensor<string, []>("scores_11_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_769_cast_fp16 = softmax(axis = var_138, x = scores_11_cast_fp16)[name = tensor<string, []>("op_769_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_145_cast_fp16 = select(a = var_154_to_fp16, b = var_769_cast_fp16, cond = mask_7)[name = tensor<string, []>("input_145_cast_fp16")];
            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, 188, 64]> value_9_cast_fp16 = transpose(perm = value_9_perm_0, x = v_5_cast_fp16)[name = tensor<string, []>("transpose_190")];
            tensor<fp16, [1, 8, 188, 64]> x_73_cast_fp16 = matmul(transpose_x = x_73_transpose_x_0, transpose_y = x_73_transpose_y_0, x = input_145_cast_fp16, y = value_9_cast_fp16)[name = tensor<string, []>("x_73_cast_fp16")];
            tensor<int32, [4]> var_773_perm_0 = const()[name = tensor<string, []>("op_773_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_774 = const()[name = tensor<string, []>("op_774"), val = tensor<int32, [3]>([1, -1, 512])];
            tensor<fp16, [1, 188, 8, 64]> var_773_cast_fp16 = transpose(perm = var_773_perm_0, x = x_73_cast_fp16)[name = tensor<string, []>("transpose_186")];
            tensor<fp16, [1, 188, 512]> input_147_cast_fp16 = reshape(shape = var_774, x = var_773_cast_fp16)[name = tensor<string, []>("input_147_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_2_self_attn_linear_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_2_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(34845952)))];
            tensor<fp16, [512]> encoder_module_layers_2_self_attn_linear_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_2_self_attn_linear_out_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(35370304)))];
            tensor<fp16, [1, 188, 512]> linear_25_cast_fp16 = linear(bias = encoder_module_layers_2_self_attn_linear_out_bias_to_fp16, weight = encoder_module_layers_2_self_attn_linear_out_weight_to_fp16, x = input_147_cast_fp16)[name = tensor<string, []>("linear_25_cast_fp16")];
            tensor<fp16, [1, 188, 512]> input_151_cast_fp16 = add(x = input_143_cast_fp16, y = linear_25_cast_fp16)[name = tensor<string, []>("input_151_cast_fp16")];
            tensor<int32, [1]> x_77_axes_0 = const()[name = tensor<string, []>("x_77_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_2_norm_conv_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_2_norm_conv_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(35371392)))];
            tensor<fp16, [512]> encoder_module_layers_2_norm_conv_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_2_norm_conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(35372480)))];
            tensor<fp16, [1, 188, 512]> x_77_cast_fp16 = layer_norm(axes = x_77_axes_0, beta = encoder_module_layers_2_norm_conv_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_2_norm_conv_weight_to_fp16, x = input_151_cast_fp16)[name = tensor<string, []>("x_77_cast_fp16")];
            tensor<int32, [3]> input_153_perm_0 = const()[name = tensor<string, []>("input_153_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> input_155_pad_type_0 = const()[name = tensor<string, []>("input_155_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_155_strides_0 = const()[name = tensor<string, []>("input_155_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_155_pad_0 = const()[name = tensor<string, []>("input_155_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_155_dilations_0 = const()[name = tensor<string, []>("input_155_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_155_groups_0 = const()[name = tensor<string, []>("input_155_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1024, 512, 1]> encoder_module_layers_2_conv_pointwise_conv1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_2_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [1024, 512, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(35373568)))];
            tensor<fp16, [1024]> encoder_module_layers_2_conv_pointwise_conv1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_2_conv_pointwise_conv1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(36422208)))];
            tensor<fp16, [1, 512, 188]> input_153_cast_fp16 = transpose(perm = input_153_perm_0, x = x_77_cast_fp16)[name = tensor<string, []>("transpose_185")];
            tensor<fp16, [1, 1024, 188]> input_155_cast_fp16 = conv(bias = encoder_module_layers_2_conv_pointwise_conv1_bias_to_fp16, dilations = input_155_dilations_0, groups = input_155_groups_0, pad = input_155_pad_0, pad_type = input_155_pad_type_0, strides = input_155_strides_0, weight = encoder_module_layers_2_conv_pointwise_conv1_weight_to_fp16, x = input_153_cast_fp16)[name = tensor<string, []>("input_155_cast_fp16")];
            tensor<int32, []> x_79_split_num_splits_0 = const()[name = tensor<string, []>("x_79_split_num_splits_0"), val = tensor<int32, []>(2)];
            tensor<int32, []> x_79_split_axis_0 = const()[name = tensor<string, []>("x_79_split_axis_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1, 512, 188]> x_79_split_cast_fp16_0, tensor<fp16, [1, 512, 188]> x_79_split_cast_fp16_1 = split(axis = x_79_split_axis_0, num_splits = x_79_split_num_splits_0, x = input_155_cast_fp16)[name = tensor<string, []>("x_79_split_cast_fp16")];
            tensor<fp16, [1, 512, 188]> x_79_split_1_sigmoid_cast_fp16 = sigmoid(x = x_79_split_cast_fp16_1)[name = tensor<string, []>("x_79_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 512, 188]> x_79_cast_fp16 = mul(x = x_79_split_cast_fp16_0, y = x_79_split_1_sigmoid_cast_fp16)[name = tensor<string, []>("x_79_cast_fp16")];
            tensor<fp16, [1, 512, 188]> input_157_cast_fp16 = select(a = var_154_to_fp16, b = x_79_cast_fp16, cond = var_450)[name = tensor<string, []>("input_157_cast_fp16")];
            tensor<int32, [6]> input_159_pad_0 = const()[name = tensor<string, []>("input_159_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            tensor<string, []> input_159_mode_0 = const()[name = tensor<string, []>("input_159_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_52_to_fp16 = const()[name = tensor<string, []>("const_52_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 512, 196]> input_159_cast_fp16 = pad(constant_val = const_52_to_fp16, mode = input_159_mode_0, pad = input_159_pad_0, x = input_157_cast_fp16)[name = tensor<string, []>("input_159_cast_fp16")];
            tensor<string, []> input_161_pad_type_0 = const()[name = tensor<string, []>("input_161_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, []> input_161_groups_0 = const()[name = tensor<string, []>("input_161_groups_0"), val = tensor<int32, []>(512)];
            tensor<int32, [1]> input_161_strides_0 = const()[name = tensor<string, []>("input_161_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_161_pad_0 = const()[name = tensor<string, []>("input_161_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_161_dilations_0 = const()[name = tensor<string, []>("input_161_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 9]> const_197_to_fp16 = const()[name = tensor<string, []>("const_197_to_fp16"), val = tensor<fp16, [512, 1, 9]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(36424320)))];
            tensor<fp16, [512]> const_198_to_fp16 = const()[name = tensor<string, []>("const_198_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(36433600)))];
            tensor<fp16, [1, 512, 188]> input_163_cast_fp16 = conv(bias = const_198_to_fp16, dilations = input_161_dilations_0, groups = input_161_groups_0, pad = input_161_pad_0, pad_type = input_161_pad_type_0, strides = input_161_strides_0, weight = const_197_to_fp16, x = input_159_cast_fp16)[name = tensor<string, []>("input_163_cast_fp16")];
            tensor<fp16, [1, 512, 188]> input_165_cast_fp16 = silu(x = input_163_cast_fp16)[name = tensor<string, []>("input_165_cast_fp16")];
            tensor<string, []> x_81_pad_type_0 = const()[name = tensor<string, []>("x_81_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> x_81_strides_0 = const()[name = tensor<string, []>("x_81_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_81_pad_0 = const()[name = tensor<string, []>("x_81_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_81_dilations_0 = const()[name = tensor<string, []>("x_81_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> x_81_groups_0 = const()[name = tensor<string, []>("x_81_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [512, 512, 1]> encoder_module_layers_2_conv_pointwise_conv2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_2_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [512, 512, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(36434688)))];
            tensor<fp16, [512]> encoder_module_layers_2_conv_pointwise_conv2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_2_conv_pointwise_conv2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(36959040)))];
            tensor<fp16, [1, 512, 188]> x_81_cast_fp16 = conv(bias = encoder_module_layers_2_conv_pointwise_conv2_bias_to_fp16, dilations = x_81_dilations_0, groups = x_81_groups_0, pad = x_81_pad_0, pad_type = x_81_pad_type_0, strides = x_81_strides_0, weight = encoder_module_layers_2_conv_pointwise_conv2_weight_to_fp16, x = input_165_cast_fp16)[name = tensor<string, []>("x_81_cast_fp16")];
            tensor<int32, [3]> input_167_perm_0 = const()[name = tensor<string, []>("input_167_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 512]> input_167_cast_fp16 = transpose(perm = input_167_perm_0, x = x_81_cast_fp16)[name = tensor<string, []>("transpose_184")];
            tensor<fp16, [1, 188, 512]> input_169_cast_fp16 = add(x = input_151_cast_fp16, y = input_167_cast_fp16)[name = tensor<string, []>("input_169_cast_fp16")];
            tensor<int32, [1]> input_171_axes_0 = const()[name = tensor<string, []>("input_171_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_2_norm_feed_forward2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_2_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(36960128)))];
            tensor<fp16, [512]> encoder_module_layers_2_norm_feed_forward2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_2_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(36961216)))];
            tensor<fp16, [1, 188, 512]> input_171_cast_fp16 = layer_norm(axes = input_171_axes_0, beta = encoder_module_layers_2_norm_feed_forward2_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_2_norm_feed_forward2_weight_to_fp16, x = input_169_cast_fp16)[name = tensor<string, []>("input_171_cast_fp16")];
            tensor<fp16, [2048, 512]> encoder_module_layers_2_feed_forward2_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_2_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [2048, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(36962304)))];
            tensor<fp16, [2048]> encoder_module_layers_2_feed_forward2_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_2_feed_forward2_linear1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(39059520)))];
            tensor<fp16, [1, 188, 2048]> linear_26_cast_fp16 = linear(bias = encoder_module_layers_2_feed_forward2_linear1_bias_to_fp16, weight = encoder_module_layers_2_feed_forward2_linear1_weight_to_fp16, x = input_171_cast_fp16)[name = tensor<string, []>("linear_26_cast_fp16")];
            tensor<fp16, [1, 188, 2048]> input_175_cast_fp16 = silu(x = linear_26_cast_fp16)[name = tensor<string, []>("input_175_cast_fp16")];
            tensor<fp16, [512, 2048]> encoder_module_layers_2_feed_forward2_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_2_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [512, 2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(39063680)))];
            tensor<fp16, [512]> encoder_module_layers_2_feed_forward2_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_2_feed_forward2_linear2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(41160896)))];
            tensor<fp16, [1, 188, 512]> linear_27_cast_fp16 = linear(bias = encoder_module_layers_2_feed_forward2_linear2_bias_to_fp16, weight = encoder_module_layers_2_feed_forward2_linear2_weight_to_fp16, x = input_175_cast_fp16)[name = tensor<string, []>("linear_27_cast_fp16")];
            tensor<fp16, []> var_840_to_fp16 = const()[name = tensor<string, []>("op_840_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 512]> var_841_cast_fp16 = mul(x = linear_27_cast_fp16, y = var_840_to_fp16)[name = tensor<string, []>("op_841_cast_fp16")];
            tensor<fp16, [1, 188, 512]> input_181_cast_fp16 = add(x = input_169_cast_fp16, y = var_841_cast_fp16)[name = tensor<string, []>("input_181_cast_fp16")];
            tensor<int32, [1]> input_183_axes_0 = const()[name = tensor<string, []>("input_183_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_2_norm_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_2_norm_out_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(41161984)))];
            tensor<fp16, [512]> encoder_module_layers_2_norm_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_2_norm_out_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(41163072)))];
            tensor<fp16, [1, 188, 512]> input_183_cast_fp16 = layer_norm(axes = input_183_axes_0, beta = encoder_module_layers_2_norm_out_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_2_norm_out_weight_to_fp16, x = input_181_cast_fp16)[name = tensor<string, []>("input_183_cast_fp16")];
            tensor<int32, [1]> input_185_axes_0 = const()[name = tensor<string, []>("input_185_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_3_norm_feed_forward1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_3_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(41164160)))];
            tensor<fp16, [512]> encoder_module_layers_3_norm_feed_forward1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_3_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(41165248)))];
            tensor<fp16, [1, 188, 512]> input_185_cast_fp16 = layer_norm(axes = input_185_axes_0, beta = encoder_module_layers_3_norm_feed_forward1_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_3_norm_feed_forward1_weight_to_fp16, x = input_183_cast_fp16)[name = tensor<string, []>("input_185_cast_fp16")];
            tensor<fp16, [2048, 512]> encoder_module_layers_3_feed_forward1_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_3_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [2048, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(41166336)))];
            tensor<fp16, [2048]> encoder_module_layers_3_feed_forward1_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_3_feed_forward1_linear1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(43263552)))];
            tensor<fp16, [1, 188, 2048]> linear_28_cast_fp16 = linear(bias = encoder_module_layers_3_feed_forward1_linear1_bias_to_fp16, weight = encoder_module_layers_3_feed_forward1_linear1_weight_to_fp16, x = input_185_cast_fp16)[name = tensor<string, []>("linear_28_cast_fp16")];
            tensor<fp16, [1, 188, 2048]> input_189_cast_fp16 = silu(x = linear_28_cast_fp16)[name = tensor<string, []>("input_189_cast_fp16")];
            tensor<fp16, [512, 2048]> encoder_module_layers_3_feed_forward1_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_3_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [512, 2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(43267712)))];
            tensor<fp16, [512]> encoder_module_layers_3_feed_forward1_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_3_feed_forward1_linear2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(45364928)))];
            tensor<fp16, [1, 188, 512]> linear_29_cast_fp16 = linear(bias = encoder_module_layers_3_feed_forward1_linear2_bias_to_fp16, weight = encoder_module_layers_3_feed_forward1_linear2_weight_to_fp16, x = input_189_cast_fp16)[name = tensor<string, []>("linear_29_cast_fp16")];
            tensor<fp16, []> var_871_to_fp16 = const()[name = tensor<string, []>("op_871_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 512]> var_872_cast_fp16 = mul(x = linear_29_cast_fp16, y = var_871_to_fp16)[name = tensor<string, []>("op_872_cast_fp16")];
            tensor<fp16, [1, 188, 512]> input_195_cast_fp16 = add(x = input_183_cast_fp16, y = var_872_cast_fp16)[name = tensor<string, []>("input_195_cast_fp16")];
            tensor<int32, [1]> query_7_axes_0 = const()[name = tensor<string, []>("query_7_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_3_norm_self_att_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_3_norm_self_att_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(45366016)))];
            tensor<fp16, [512]> encoder_module_layers_3_norm_self_att_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_3_norm_self_att_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(45367104)))];
            tensor<fp16, [1, 188, 512]> query_7_cast_fp16 = layer_norm(axes = query_7_axes_0, beta = encoder_module_layers_3_norm_self_att_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_3_norm_self_att_weight_to_fp16, x = input_195_cast_fp16)[name = tensor<string, []>("query_7_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_3_self_attn_linear_q_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_3_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(45368192)))];
            tensor<fp16, [512]> encoder_module_layers_3_self_attn_linear_q_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_3_self_attn_linear_q_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(45892544)))];
            tensor<fp16, [1, 188, 512]> linear_30_cast_fp16 = linear(bias = encoder_module_layers_3_self_attn_linear_q_bias_to_fp16, weight = encoder_module_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_889 = const()[name = tensor<string, []>("op_889"), val = tensor<int32, [4]>([1, -1, 8, 64])];
            tensor<fp16, [1, 188, 8, 64]> q_19_cast_fp16 = reshape(shape = var_889, x = linear_30_cast_fp16)[name = tensor<string, []>("q_19_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_3_self_attn_linear_k_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_3_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(45893632)))];
            tensor<fp16, [512]> encoder_module_layers_3_self_attn_linear_k_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_3_self_attn_linear_k_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46417984)))];
            tensor<fp16, [1, 188, 512]> linear_31_cast_fp16 = linear(bias = encoder_module_layers_3_self_attn_linear_k_bias_to_fp16, weight = encoder_module_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_894 = const()[name = tensor<string, []>("op_894"), val = tensor<int32, [4]>([1, -1, 8, 64])];
            tensor<fp16, [1, 188, 8, 64]> k_13_cast_fp16 = reshape(shape = var_894, x = linear_31_cast_fp16)[name = tensor<string, []>("k_13_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_3_self_attn_linear_v_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_3_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46419072)))];
            tensor<fp16, [512]> encoder_module_layers_3_self_attn_linear_v_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_3_self_attn_linear_v_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46943424)))];
            tensor<fp16, [1, 188, 512]> linear_32_cast_fp16 = linear(bias = encoder_module_layers_3_self_attn_linear_v_bias_to_fp16, weight = encoder_module_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_899 = const()[name = tensor<string, []>("op_899"), val = tensor<int32, [4]>([1, -1, 8, 64])];
            tensor<fp16, [1, 188, 8, 64]> v_7_cast_fp16 = reshape(shape = var_899, x = linear_32_cast_fp16)[name = tensor<string, []>("v_7_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, 64]> encoder_module_layers_3_self_attn_pos_bias_u_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_3_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46944512)))];
            tensor<fp16, [1, 188, 8, 64]> var_911_cast_fp16 = add(x = q_19_cast_fp16, y = encoder_module_layers_3_self_attn_pos_bias_u_to_fp16)[name = tensor<string, []>("op_911_cast_fp16")];
            tensor<fp16, [8, 64]> encoder_module_layers_3_self_attn_pos_bias_v_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_3_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46945600)))];
            tensor<fp16, [1, 188, 8, 64]> var_913_cast_fp16 = add(x = q_19_cast_fp16, y = encoder_module_layers_3_self_attn_pos_bias_v_to_fp16)[name = tensor<string, []>("op_913_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_89_transpose_x_0 = const()[name = tensor<string, []>("x_89_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_89_transpose_y_0 = const()[name = tensor<string, []>("x_89_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 64, 375]> var_915_to_fp16 = const()[name = tensor<string, []>("op_915_to_fp16"), val = tensor<fp16, [1, 8, 64, 375]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(46946688)))];
            tensor<fp16, [1, 8, 188, 64]> q_with_bias_v_7_cast_fp16 = transpose(perm = q_with_bias_v_7_perm_0, x = var_913_cast_fp16)[name = tensor<string, []>("transpose_182")];
            tensor<fp16, [1, 8, 188, 375]> x_89_cast_fp16 = matmul(transpose_x = x_89_transpose_x_0, transpose_y = x_89_transpose_y_0, x = q_with_bias_v_7_cast_fp16, y = var_915_to_fp16)[name = tensor<string, []>("x_89_cast_fp16")];
            tensor<int32, [8]> x_91_pad_0 = const()[name = tensor<string, []>("x_91_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            tensor<string, []> x_91_mode_0 = const()[name = tensor<string, []>("x_91_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_59_to_fp16 = const()[name = tensor<string, []>("const_59_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_91_cast_fp16 = pad(constant_val = const_59_to_fp16, mode = x_91_mode_0, pad = x_91_pad_0, x = x_89_cast_fp16)[name = tensor<string, []>("x_91_cast_fp16")];
            tensor<int32, [4]> var_923 = const()[name = tensor<string, []>("op_923"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_93_cast_fp16 = reshape(shape = var_923, x = x_91_cast_fp16)[name = tensor<string, []>("x_93_cast_fp16")];
            tensor<int32, [4]> var_927_begin_0 = const()[name = tensor<string, []>("op_927_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_927_end_0 = const()[name = tensor<string, []>("op_927_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_927_end_mask_0 = const()[name = tensor<string, []>("op_927_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_927_cast_fp16 = slice_by_index(begin = var_927_begin_0, end = var_927_end_0, end_mask = var_927_end_mask_0, x = x_93_cast_fp16)[name = tensor<string, []>("op_927_cast_fp16")];
            tensor<int32, [4]> var_928 = const()[name = tensor<string, []>("op_928"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_13_cast_fp16 = reshape(shape = var_928, x = var_927_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_57_perm_0 = const()[name = tensor<string, []>("transpose_57_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_58_perm_0 = const()[name = tensor<string, []>("transpose_58_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 64, 188]> transpose_58 = transpose(perm = transpose_58_perm_0, x = k_13_cast_fp16)[name = tensor<string, []>("transpose_180")];
            tensor<fp16, [1, 8, 188, 64]> transpose_57 = transpose(perm = transpose_57_perm_0, x = var_911_cast_fp16)[name = tensor<string, []>("transpose_181")];
            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_57, y = transpose_58)[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_937_cast_fp16 = add(x = matrix_ac_7_cast_fp16, y = matrix_bd_15_cast_fp16)[name = tensor<string, []>("op_937_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, []>(0x1p-3)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_13_cast_fp16 = mul(x = var_937_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_153_to_fp16, b = _inversed_scores_13_cast_fp16, cond = mask_7)[name = tensor<string, []>("scores_15_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_943_cast_fp16 = softmax(axis = var_138, x = scores_15_cast_fp16)[name = tensor<string, []>("op_943_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_197_cast_fp16 = select(a = var_154_to_fp16, b = var_943_cast_fp16, cond = mask_7)[name = tensor<string, []>("input_197_cast_fp16")];
            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, 188, 64]> value_11_cast_fp16 = transpose(perm = value_11_perm_0, x = v_7_cast_fp16)[name = tensor<string, []>("transpose_183")];
            tensor<fp16, [1, 8, 188, 64]> x_95_cast_fp16 = matmul(transpose_x = x_95_transpose_x_0, transpose_y = x_95_transpose_y_0, x = input_197_cast_fp16, y = value_11_cast_fp16)[name = tensor<string, []>("x_95_cast_fp16")];
            tensor<int32, [4]> var_947_perm_0 = const()[name = tensor<string, []>("op_947_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_948 = const()[name = tensor<string, []>("op_948"), val = tensor<int32, [3]>([1, -1, 512])];
            tensor<fp16, [1, 188, 8, 64]> var_947_cast_fp16 = transpose(perm = var_947_perm_0, x = x_95_cast_fp16)[name = tensor<string, []>("transpose_179")];
            tensor<fp16, [1, 188, 512]> input_199_cast_fp16 = reshape(shape = var_948, x = var_947_cast_fp16)[name = tensor<string, []>("input_199_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_3_self_attn_linear_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_3_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47330752)))];
            tensor<fp16, [512]> encoder_module_layers_3_self_attn_linear_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_3_self_attn_linear_out_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47855104)))];
            tensor<fp16, [1, 188, 512]> linear_34_cast_fp16 = linear(bias = encoder_module_layers_3_self_attn_linear_out_bias_to_fp16, weight = encoder_module_layers_3_self_attn_linear_out_weight_to_fp16, x = input_199_cast_fp16)[name = tensor<string, []>("linear_34_cast_fp16")];
            tensor<fp16, [1, 188, 512]> input_203_cast_fp16 = add(x = input_195_cast_fp16, y = linear_34_cast_fp16)[name = tensor<string, []>("input_203_cast_fp16")];
            tensor<int32, [1]> x_99_axes_0 = const()[name = tensor<string, []>("x_99_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_3_norm_conv_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_3_norm_conv_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47856192)))];
            tensor<fp16, [512]> encoder_module_layers_3_norm_conv_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_3_norm_conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47857280)))];
            tensor<fp16, [1, 188, 512]> x_99_cast_fp16 = layer_norm(axes = x_99_axes_0, beta = encoder_module_layers_3_norm_conv_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_3_norm_conv_weight_to_fp16, x = input_203_cast_fp16)[name = tensor<string, []>("x_99_cast_fp16")];
            tensor<int32, [3]> input_205_perm_0 = const()[name = tensor<string, []>("input_205_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> input_207_pad_type_0 = const()[name = tensor<string, []>("input_207_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_207_strides_0 = const()[name = tensor<string, []>("input_207_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_207_pad_0 = const()[name = tensor<string, []>("input_207_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_207_dilations_0 = const()[name = tensor<string, []>("input_207_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_207_groups_0 = const()[name = tensor<string, []>("input_207_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1024, 512, 1]> encoder_module_layers_3_conv_pointwise_conv1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_3_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [1024, 512, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(47858368)))];
            tensor<fp16, [1024]> encoder_module_layers_3_conv_pointwise_conv1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_3_conv_pointwise_conv1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48907008)))];
            tensor<fp16, [1, 512, 188]> input_205_cast_fp16 = transpose(perm = input_205_perm_0, x = x_99_cast_fp16)[name = tensor<string, []>("transpose_178")];
            tensor<fp16, [1, 1024, 188]> input_207_cast_fp16 = conv(bias = encoder_module_layers_3_conv_pointwise_conv1_bias_to_fp16, dilations = input_207_dilations_0, groups = input_207_groups_0, pad = input_207_pad_0, pad_type = input_207_pad_type_0, strides = input_207_strides_0, weight = encoder_module_layers_3_conv_pointwise_conv1_weight_to_fp16, x = input_205_cast_fp16)[name = tensor<string, []>("input_207_cast_fp16")];
            tensor<int32, []> x_101_split_num_splits_0 = const()[name = tensor<string, []>("x_101_split_num_splits_0"), val = tensor<int32, []>(2)];
            tensor<int32, []> x_101_split_axis_0 = const()[name = tensor<string, []>("x_101_split_axis_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1, 512, 188]> x_101_split_cast_fp16_0, tensor<fp16, [1, 512, 188]> x_101_split_cast_fp16_1 = split(axis = x_101_split_axis_0, num_splits = x_101_split_num_splits_0, x = input_207_cast_fp16)[name = tensor<string, []>("x_101_split_cast_fp16")];
            tensor<fp16, [1, 512, 188]> x_101_split_1_sigmoid_cast_fp16 = sigmoid(x = x_101_split_cast_fp16_1)[name = tensor<string, []>("x_101_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 512, 188]> x_101_cast_fp16 = mul(x = x_101_split_cast_fp16_0, y = x_101_split_1_sigmoid_cast_fp16)[name = tensor<string, []>("x_101_cast_fp16")];
            tensor<fp16, [1, 512, 188]> input_209_cast_fp16 = select(a = var_154_to_fp16, b = x_101_cast_fp16, cond = var_450)[name = tensor<string, []>("input_209_cast_fp16")];
            tensor<int32, [6]> input_211_pad_0 = const()[name = tensor<string, []>("input_211_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            tensor<string, []> input_211_mode_0 = const()[name = tensor<string, []>("input_211_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_62_to_fp16 = const()[name = tensor<string, []>("const_62_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 512, 196]> input_211_cast_fp16 = pad(constant_val = const_62_to_fp16, mode = input_211_mode_0, pad = input_211_pad_0, x = input_209_cast_fp16)[name = tensor<string, []>("input_211_cast_fp16")];
            tensor<string, []> input_213_pad_type_0 = const()[name = tensor<string, []>("input_213_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, []> input_213_groups_0 = const()[name = tensor<string, []>("input_213_groups_0"), val = tensor<int32, []>(512)];
            tensor<int32, [1]> input_213_strides_0 = const()[name = tensor<string, []>("input_213_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_213_pad_0 = const()[name = tensor<string, []>("input_213_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_213_dilations_0 = const()[name = tensor<string, []>("input_213_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 9]> const_199_to_fp16 = const()[name = tensor<string, []>("const_199_to_fp16"), val = tensor<fp16, [512, 1, 9]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48909120)))];
            tensor<fp16, [512]> const_200_to_fp16 = const()[name = tensor<string, []>("const_200_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48918400)))];
            tensor<fp16, [1, 512, 188]> input_215_cast_fp16 = conv(bias = const_200_to_fp16, dilations = input_213_dilations_0, groups = input_213_groups_0, pad = input_213_pad_0, pad_type = input_213_pad_type_0, strides = input_213_strides_0, weight = const_199_to_fp16, x = input_211_cast_fp16)[name = tensor<string, []>("input_215_cast_fp16")];
            tensor<fp16, [1, 512, 188]> input_217_cast_fp16 = silu(x = input_215_cast_fp16)[name = tensor<string, []>("input_217_cast_fp16")];
            tensor<string, []> x_103_pad_type_0 = const()[name = tensor<string, []>("x_103_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> x_103_strides_0 = const()[name = tensor<string, []>("x_103_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_103_pad_0 = const()[name = tensor<string, []>("x_103_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_103_dilations_0 = const()[name = tensor<string, []>("x_103_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> x_103_groups_0 = const()[name = tensor<string, []>("x_103_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [512, 512, 1]> encoder_module_layers_3_conv_pointwise_conv2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_3_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [512, 512, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(48919488)))];
            tensor<fp16, [512]> encoder_module_layers_3_conv_pointwise_conv2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_3_conv_pointwise_conv2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(49443840)))];
            tensor<fp16, [1, 512, 188]> x_103_cast_fp16 = conv(bias = encoder_module_layers_3_conv_pointwise_conv2_bias_to_fp16, dilations = x_103_dilations_0, groups = x_103_groups_0, pad = x_103_pad_0, pad_type = x_103_pad_type_0, strides = x_103_strides_0, weight = encoder_module_layers_3_conv_pointwise_conv2_weight_to_fp16, x = input_217_cast_fp16)[name = tensor<string, []>("x_103_cast_fp16")];
            tensor<int32, [3]> input_219_perm_0 = const()[name = tensor<string, []>("input_219_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 512]> input_219_cast_fp16 = transpose(perm = input_219_perm_0, x = x_103_cast_fp16)[name = tensor<string, []>("transpose_177")];
            tensor<fp16, [1, 188, 512]> input_221_cast_fp16 = add(x = input_203_cast_fp16, y = input_219_cast_fp16)[name = tensor<string, []>("input_221_cast_fp16")];
            tensor<int32, [1]> input_223_axes_0 = const()[name = tensor<string, []>("input_223_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_3_norm_feed_forward2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_3_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(49444928)))];
            tensor<fp16, [512]> encoder_module_layers_3_norm_feed_forward2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_3_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(49446016)))];
            tensor<fp16, [1, 188, 512]> input_223_cast_fp16 = layer_norm(axes = input_223_axes_0, beta = encoder_module_layers_3_norm_feed_forward2_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_3_norm_feed_forward2_weight_to_fp16, x = input_221_cast_fp16)[name = tensor<string, []>("input_223_cast_fp16")];
            tensor<fp16, [2048, 512]> encoder_module_layers_3_feed_forward2_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_3_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [2048, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(49447104)))];
            tensor<fp16, [2048]> encoder_module_layers_3_feed_forward2_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_3_feed_forward2_linear1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(51544320)))];
            tensor<fp16, [1, 188, 2048]> linear_35_cast_fp16 = linear(bias = encoder_module_layers_3_feed_forward2_linear1_bias_to_fp16, weight = encoder_module_layers_3_feed_forward2_linear1_weight_to_fp16, x = input_223_cast_fp16)[name = tensor<string, []>("linear_35_cast_fp16")];
            tensor<fp16, [1, 188, 2048]> input_227_cast_fp16 = silu(x = linear_35_cast_fp16)[name = tensor<string, []>("input_227_cast_fp16")];
            tensor<fp16, [512, 2048]> encoder_module_layers_3_feed_forward2_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_3_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [512, 2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(51548480)))];
            tensor<fp16, [512]> encoder_module_layers_3_feed_forward2_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_3_feed_forward2_linear2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(53645696)))];
            tensor<fp16, [1, 188, 512]> linear_36_cast_fp16 = linear(bias = encoder_module_layers_3_feed_forward2_linear2_bias_to_fp16, weight = encoder_module_layers_3_feed_forward2_linear2_weight_to_fp16, x = input_227_cast_fp16)[name = tensor<string, []>("linear_36_cast_fp16")];
            tensor<fp16, []> var_1014_to_fp16 = const()[name = tensor<string, []>("op_1014_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 512]> var_1015_cast_fp16 = mul(x = linear_36_cast_fp16, y = var_1014_to_fp16)[name = tensor<string, []>("op_1015_cast_fp16")];
            tensor<fp16, [1, 188, 512]> input_233_cast_fp16 = add(x = input_221_cast_fp16, y = var_1015_cast_fp16)[name = tensor<string, []>("input_233_cast_fp16")];
            tensor<int32, [1]> input_235_axes_0 = const()[name = tensor<string, []>("input_235_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_3_norm_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_3_norm_out_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(53646784)))];
            tensor<fp16, [512]> encoder_module_layers_3_norm_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_3_norm_out_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(53647872)))];
            tensor<fp16, [1, 188, 512]> input_235_cast_fp16 = layer_norm(axes = input_235_axes_0, beta = encoder_module_layers_3_norm_out_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_3_norm_out_weight_to_fp16, x = input_233_cast_fp16)[name = tensor<string, []>("input_235_cast_fp16")];
            tensor<int32, [1]> input_237_axes_0 = const()[name = tensor<string, []>("input_237_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_4_norm_feed_forward1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_4_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(53648960)))];
            tensor<fp16, [512]> encoder_module_layers_4_norm_feed_forward1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_4_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(53650048)))];
            tensor<fp16, [1, 188, 512]> input_237_cast_fp16 = layer_norm(axes = input_237_axes_0, beta = encoder_module_layers_4_norm_feed_forward1_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_4_norm_feed_forward1_weight_to_fp16, x = input_235_cast_fp16)[name = tensor<string, []>("input_237_cast_fp16")];
            tensor<fp16, [2048, 512]> encoder_module_layers_4_feed_forward1_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_4_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [2048, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(53651136)))];
            tensor<fp16, [2048]> encoder_module_layers_4_feed_forward1_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_4_feed_forward1_linear1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(55748352)))];
            tensor<fp16, [1, 188, 2048]> linear_37_cast_fp16 = linear(bias = encoder_module_layers_4_feed_forward1_linear1_bias_to_fp16, weight = encoder_module_layers_4_feed_forward1_linear1_weight_to_fp16, x = input_237_cast_fp16)[name = tensor<string, []>("linear_37_cast_fp16")];
            tensor<fp16, [1, 188, 2048]> input_241_cast_fp16 = silu(x = linear_37_cast_fp16)[name = tensor<string, []>("input_241_cast_fp16")];
            tensor<fp16, [512, 2048]> encoder_module_layers_4_feed_forward1_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_4_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [512, 2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(55752512)))];
            tensor<fp16, [512]> encoder_module_layers_4_feed_forward1_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_4_feed_forward1_linear2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(57849728)))];
            tensor<fp16, [1, 188, 512]> linear_38_cast_fp16 = linear(bias = encoder_module_layers_4_feed_forward1_linear2_bias_to_fp16, weight = encoder_module_layers_4_feed_forward1_linear2_weight_to_fp16, x = input_241_cast_fp16)[name = tensor<string, []>("linear_38_cast_fp16")];
            tensor<fp16, []> var_1045_to_fp16 = const()[name = tensor<string, []>("op_1045_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 512]> var_1046_cast_fp16 = mul(x = linear_38_cast_fp16, y = var_1045_to_fp16)[name = tensor<string, []>("op_1046_cast_fp16")];
            tensor<fp16, [1, 188, 512]> input_247_cast_fp16 = add(x = input_235_cast_fp16, y = var_1046_cast_fp16)[name = tensor<string, []>("input_247_cast_fp16")];
            tensor<int32, [1]> query_9_axes_0 = const()[name = tensor<string, []>("query_9_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_4_norm_self_att_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_4_norm_self_att_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(57850816)))];
            tensor<fp16, [512]> encoder_module_layers_4_norm_self_att_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_4_norm_self_att_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(57851904)))];
            tensor<fp16, [1, 188, 512]> query_9_cast_fp16 = layer_norm(axes = query_9_axes_0, beta = encoder_module_layers_4_norm_self_att_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_4_norm_self_att_weight_to_fp16, x = input_247_cast_fp16)[name = tensor<string, []>("query_9_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_4_self_attn_linear_q_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_4_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(57852992)))];
            tensor<fp16, [512]> encoder_module_layers_4_self_attn_linear_q_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_4_self_attn_linear_q_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(58377344)))];
            tensor<fp16, [1, 188, 512]> linear_39_cast_fp16 = linear(bias = encoder_module_layers_4_self_attn_linear_q_bias_to_fp16, weight = encoder_module_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_1063 = const()[name = tensor<string, []>("op_1063"), val = tensor<int32, [4]>([1, -1, 8, 64])];
            tensor<fp16, [1, 188, 8, 64]> q_25_cast_fp16 = reshape(shape = var_1063, x = linear_39_cast_fp16)[name = tensor<string, []>("q_25_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_4_self_attn_linear_k_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_4_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(58378432)))];
            tensor<fp16, [512]> encoder_module_layers_4_self_attn_linear_k_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_4_self_attn_linear_k_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(58902784)))];
            tensor<fp16, [1, 188, 512]> linear_40_cast_fp16 = linear(bias = encoder_module_layers_4_self_attn_linear_k_bias_to_fp16, weight = encoder_module_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_1068 = const()[name = tensor<string, []>("op_1068"), val = tensor<int32, [4]>([1, -1, 8, 64])];
            tensor<fp16, [1, 188, 8, 64]> k_17_cast_fp16 = reshape(shape = var_1068, x = linear_40_cast_fp16)[name = tensor<string, []>("k_17_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_4_self_attn_linear_v_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_4_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(58903872)))];
            tensor<fp16, [512]> encoder_module_layers_4_self_attn_linear_v_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_4_self_attn_linear_v_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(59428224)))];
            tensor<fp16, [1, 188, 512]> linear_41_cast_fp16 = linear(bias = encoder_module_layers_4_self_attn_linear_v_bias_to_fp16, weight = encoder_module_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_1073 = const()[name = tensor<string, []>("op_1073"), val = tensor<int32, [4]>([1, -1, 8, 64])];
            tensor<fp16, [1, 188, 8, 64]> v_9_cast_fp16 = reshape(shape = var_1073, x = linear_41_cast_fp16)[name = tensor<string, []>("v_9_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, 64]> encoder_module_layers_4_self_attn_pos_bias_u_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_4_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(59429312)))];
            tensor<fp16, [1, 188, 8, 64]> var_1085_cast_fp16 = add(x = q_25_cast_fp16, y = encoder_module_layers_4_self_attn_pos_bias_u_to_fp16)[name = tensor<string, []>("op_1085_cast_fp16")];
            tensor<fp16, [8, 64]> encoder_module_layers_4_self_attn_pos_bias_v_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_4_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(59430400)))];
            tensor<fp16, [1, 188, 8, 64]> var_1087_cast_fp16 = add(x = q_25_cast_fp16, y = encoder_module_layers_4_self_attn_pos_bias_v_to_fp16)[name = tensor<string, []>("op_1087_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_111_transpose_x_0 = const()[name = tensor<string, []>("x_111_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_111_transpose_y_0 = const()[name = tensor<string, []>("x_111_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 64, 375]> var_1089_to_fp16 = const()[name = tensor<string, []>("op_1089_to_fp16"), val = tensor<fp16, [1, 8, 64, 375]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(59431488)))];
            tensor<fp16, [1, 8, 188, 64]> q_with_bias_v_9_cast_fp16 = transpose(perm = q_with_bias_v_9_perm_0, x = var_1087_cast_fp16)[name = tensor<string, []>("transpose_175")];
            tensor<fp16, [1, 8, 188, 375]> x_111_cast_fp16 = matmul(transpose_x = x_111_transpose_x_0, transpose_y = x_111_transpose_y_0, x = q_with_bias_v_9_cast_fp16, y = var_1089_to_fp16)[name = tensor<string, []>("x_111_cast_fp16")];
            tensor<int32, [8]> x_113_pad_0 = const()[name = tensor<string, []>("x_113_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            tensor<string, []> x_113_mode_0 = const()[name = tensor<string, []>("x_113_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_69_to_fp16 = const()[name = tensor<string, []>("const_69_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_113_cast_fp16 = pad(constant_val = const_69_to_fp16, mode = x_113_mode_0, pad = x_113_pad_0, x = x_111_cast_fp16)[name = tensor<string, []>("x_113_cast_fp16")];
            tensor<int32, [4]> var_1097 = const()[name = tensor<string, []>("op_1097"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_115_cast_fp16 = reshape(shape = var_1097, x = x_113_cast_fp16)[name = tensor<string, []>("x_115_cast_fp16")];
            tensor<int32, [4]> var_1101_begin_0 = const()[name = tensor<string, []>("op_1101_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_1101_end_0 = const()[name = tensor<string, []>("op_1101_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_1101_end_mask_0 = const()[name = tensor<string, []>("op_1101_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_1101_cast_fp16 = slice_by_index(begin = var_1101_begin_0, end = var_1101_end_0, end_mask = var_1101_end_mask_0, x = x_115_cast_fp16)[name = tensor<string, []>("op_1101_cast_fp16")];
            tensor<int32, [4]> var_1102 = const()[name = tensor<string, []>("op_1102"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_17_cast_fp16 = reshape(shape = var_1102, x = var_1101_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_59_perm_0 = const()[name = tensor<string, []>("transpose_59_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_60_perm_0 = const()[name = tensor<string, []>("transpose_60_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 64, 188]> transpose_60 = transpose(perm = transpose_60_perm_0, x = k_17_cast_fp16)[name = tensor<string, []>("transpose_173")];
            tensor<fp16, [1, 8, 188, 64]> transpose_59 = transpose(perm = transpose_59_perm_0, x = var_1085_cast_fp16)[name = tensor<string, []>("transpose_174")];
            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_59, y = transpose_60)[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_1111_cast_fp16 = add(x = matrix_ac_9_cast_fp16, y = matrix_bd_19_cast_fp16)[name = tensor<string, []>("op_1111_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, []>(0x1p-3)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_17_cast_fp16 = mul(x = var_1111_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_153_to_fp16, b = _inversed_scores_17_cast_fp16, cond = mask_7)[name = tensor<string, []>("scores_19_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_1117_cast_fp16 = softmax(axis = var_138, x = scores_19_cast_fp16)[name = tensor<string, []>("op_1117_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_249_cast_fp16 = select(a = var_154_to_fp16, b = var_1117_cast_fp16, cond = mask_7)[name = tensor<string, []>("input_249_cast_fp16")];
            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, 188, 64]> value_13_cast_fp16 = transpose(perm = value_13_perm_0, x = v_9_cast_fp16)[name = tensor<string, []>("transpose_176")];
            tensor<fp16, [1, 8, 188, 64]> x_117_cast_fp16 = matmul(transpose_x = x_117_transpose_x_0, transpose_y = x_117_transpose_y_0, x = input_249_cast_fp16, y = value_13_cast_fp16)[name = tensor<string, []>("x_117_cast_fp16")];
            tensor<int32, [4]> var_1121_perm_0 = const()[name = tensor<string, []>("op_1121_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1122 = const()[name = tensor<string, []>("op_1122"), val = tensor<int32, [3]>([1, -1, 512])];
            tensor<fp16, [1, 188, 8, 64]> var_1121_cast_fp16 = transpose(perm = var_1121_perm_0, x = x_117_cast_fp16)[name = tensor<string, []>("transpose_172")];
            tensor<fp16, [1, 188, 512]> input_251_cast_fp16 = reshape(shape = var_1122, x = var_1121_cast_fp16)[name = tensor<string, []>("input_251_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_4_self_attn_linear_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_4_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(59815552)))];
            tensor<fp16, [512]> encoder_module_layers_4_self_attn_linear_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_4_self_attn_linear_out_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(60339904)))];
            tensor<fp16, [1, 188, 512]> linear_43_cast_fp16 = linear(bias = encoder_module_layers_4_self_attn_linear_out_bias_to_fp16, weight = encoder_module_layers_4_self_attn_linear_out_weight_to_fp16, x = input_251_cast_fp16)[name = tensor<string, []>("linear_43_cast_fp16")];
            tensor<fp16, [1, 188, 512]> input_255_cast_fp16 = add(x = input_247_cast_fp16, y = linear_43_cast_fp16)[name = tensor<string, []>("input_255_cast_fp16")];
            tensor<int32, [1]> x_121_axes_0 = const()[name = tensor<string, []>("x_121_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_4_norm_conv_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_4_norm_conv_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(60340992)))];
            tensor<fp16, [512]> encoder_module_layers_4_norm_conv_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_4_norm_conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(60342080)))];
            tensor<fp16, [1, 188, 512]> x_121_cast_fp16 = layer_norm(axes = x_121_axes_0, beta = encoder_module_layers_4_norm_conv_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_4_norm_conv_weight_to_fp16, x = input_255_cast_fp16)[name = tensor<string, []>("x_121_cast_fp16")];
            tensor<int32, [3]> input_257_perm_0 = const()[name = tensor<string, []>("input_257_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> input_259_pad_type_0 = const()[name = tensor<string, []>("input_259_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_259_strides_0 = const()[name = tensor<string, []>("input_259_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_259_pad_0 = const()[name = tensor<string, []>("input_259_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_259_dilations_0 = const()[name = tensor<string, []>("input_259_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_259_groups_0 = const()[name = tensor<string, []>("input_259_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1024, 512, 1]> encoder_module_layers_4_conv_pointwise_conv1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_4_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [1024, 512, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(60343168)))];
            tensor<fp16, [1024]> encoder_module_layers_4_conv_pointwise_conv1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_4_conv_pointwise_conv1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(61391808)))];
            tensor<fp16, [1, 512, 188]> input_257_cast_fp16 = transpose(perm = input_257_perm_0, x = x_121_cast_fp16)[name = tensor<string, []>("transpose_171")];
            tensor<fp16, [1, 1024, 188]> input_259_cast_fp16 = conv(bias = encoder_module_layers_4_conv_pointwise_conv1_bias_to_fp16, dilations = input_259_dilations_0, groups = input_259_groups_0, pad = input_259_pad_0, pad_type = input_259_pad_type_0, strides = input_259_strides_0, weight = encoder_module_layers_4_conv_pointwise_conv1_weight_to_fp16, x = input_257_cast_fp16)[name = tensor<string, []>("input_259_cast_fp16")];
            tensor<int32, []> x_123_split_num_splits_0 = const()[name = tensor<string, []>("x_123_split_num_splits_0"), val = tensor<int32, []>(2)];
            tensor<int32, []> x_123_split_axis_0 = const()[name = tensor<string, []>("x_123_split_axis_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1, 512, 188]> x_123_split_cast_fp16_0, tensor<fp16, [1, 512, 188]> x_123_split_cast_fp16_1 = split(axis = x_123_split_axis_0, num_splits = x_123_split_num_splits_0, x = input_259_cast_fp16)[name = tensor<string, []>("x_123_split_cast_fp16")];
            tensor<fp16, [1, 512, 188]> x_123_split_1_sigmoid_cast_fp16 = sigmoid(x = x_123_split_cast_fp16_1)[name = tensor<string, []>("x_123_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 512, 188]> x_123_cast_fp16 = mul(x = x_123_split_cast_fp16_0, y = x_123_split_1_sigmoid_cast_fp16)[name = tensor<string, []>("x_123_cast_fp16")];
            tensor<fp16, [1, 512, 188]> input_261_cast_fp16 = select(a = var_154_to_fp16, b = x_123_cast_fp16, cond = var_450)[name = tensor<string, []>("input_261_cast_fp16")];
            tensor<int32, [6]> input_263_pad_0 = const()[name = tensor<string, []>("input_263_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            tensor<string, []> input_263_mode_0 = const()[name = tensor<string, []>("input_263_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_72_to_fp16 = const()[name = tensor<string, []>("const_72_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 512, 196]> input_263_cast_fp16 = pad(constant_val = const_72_to_fp16, mode = input_263_mode_0, pad = input_263_pad_0, x = input_261_cast_fp16)[name = tensor<string, []>("input_263_cast_fp16")];
            tensor<string, []> input_265_pad_type_0 = const()[name = tensor<string, []>("input_265_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, []> input_265_groups_0 = const()[name = tensor<string, []>("input_265_groups_0"), val = tensor<int32, []>(512)];
            tensor<int32, [1]> input_265_strides_0 = const()[name = tensor<string, []>("input_265_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_265_pad_0 = const()[name = tensor<string, []>("input_265_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_265_dilations_0 = const()[name = tensor<string, []>("input_265_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 9]> const_201_to_fp16 = const()[name = tensor<string, []>("const_201_to_fp16"), val = tensor<fp16, [512, 1, 9]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(61393920)))];
            tensor<fp16, [512]> const_202_to_fp16 = const()[name = tensor<string, []>("const_202_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(61403200)))];
            tensor<fp16, [1, 512, 188]> input_267_cast_fp16 = conv(bias = const_202_to_fp16, dilations = input_265_dilations_0, groups = input_265_groups_0, pad = input_265_pad_0, pad_type = input_265_pad_type_0, strides = input_265_strides_0, weight = const_201_to_fp16, x = input_263_cast_fp16)[name = tensor<string, []>("input_267_cast_fp16")];
            tensor<fp16, [1, 512, 188]> input_269_cast_fp16 = silu(x = input_267_cast_fp16)[name = tensor<string, []>("input_269_cast_fp16")];
            tensor<string, []> x_125_pad_type_0 = const()[name = tensor<string, []>("x_125_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> x_125_strides_0 = const()[name = tensor<string, []>("x_125_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_125_pad_0 = const()[name = tensor<string, []>("x_125_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_125_dilations_0 = const()[name = tensor<string, []>("x_125_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> x_125_groups_0 = const()[name = tensor<string, []>("x_125_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [512, 512, 1]> encoder_module_layers_4_conv_pointwise_conv2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_4_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [512, 512, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(61404288)))];
            tensor<fp16, [512]> encoder_module_layers_4_conv_pointwise_conv2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_4_conv_pointwise_conv2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(61928640)))];
            tensor<fp16, [1, 512, 188]> x_125_cast_fp16 = conv(bias = encoder_module_layers_4_conv_pointwise_conv2_bias_to_fp16, dilations = x_125_dilations_0, groups = x_125_groups_0, pad = x_125_pad_0, pad_type = x_125_pad_type_0, strides = x_125_strides_0, weight = encoder_module_layers_4_conv_pointwise_conv2_weight_to_fp16, x = input_269_cast_fp16)[name = tensor<string, []>("x_125_cast_fp16")];
            tensor<int32, [3]> input_271_perm_0 = const()[name = tensor<string, []>("input_271_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 512]> input_271_cast_fp16 = transpose(perm = input_271_perm_0, x = x_125_cast_fp16)[name = tensor<string, []>("transpose_170")];
            tensor<fp16, [1, 188, 512]> input_273_cast_fp16 = add(x = input_255_cast_fp16, y = input_271_cast_fp16)[name = tensor<string, []>("input_273_cast_fp16")];
            tensor<int32, [1]> input_275_axes_0 = const()[name = tensor<string, []>("input_275_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_4_norm_feed_forward2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_4_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(61929728)))];
            tensor<fp16, [512]> encoder_module_layers_4_norm_feed_forward2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_4_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(61930816)))];
            tensor<fp16, [1, 188, 512]> input_275_cast_fp16 = layer_norm(axes = input_275_axes_0, beta = encoder_module_layers_4_norm_feed_forward2_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_4_norm_feed_forward2_weight_to_fp16, x = input_273_cast_fp16)[name = tensor<string, []>("input_275_cast_fp16")];
            tensor<fp16, [2048, 512]> encoder_module_layers_4_feed_forward2_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_4_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [2048, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(61931904)))];
            tensor<fp16, [2048]> encoder_module_layers_4_feed_forward2_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_4_feed_forward2_linear1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(64029120)))];
            tensor<fp16, [1, 188, 2048]> linear_44_cast_fp16 = linear(bias = encoder_module_layers_4_feed_forward2_linear1_bias_to_fp16, weight = encoder_module_layers_4_feed_forward2_linear1_weight_to_fp16, x = input_275_cast_fp16)[name = tensor<string, []>("linear_44_cast_fp16")];
            tensor<fp16, [1, 188, 2048]> input_279_cast_fp16 = silu(x = linear_44_cast_fp16)[name = tensor<string, []>("input_279_cast_fp16")];
            tensor<fp16, [512, 2048]> encoder_module_layers_4_feed_forward2_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_4_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [512, 2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(64033280)))];
            tensor<fp16, [512]> encoder_module_layers_4_feed_forward2_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_4_feed_forward2_linear2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(66130496)))];
            tensor<fp16, [1, 188, 512]> linear_45_cast_fp16 = linear(bias = encoder_module_layers_4_feed_forward2_linear2_bias_to_fp16, weight = encoder_module_layers_4_feed_forward2_linear2_weight_to_fp16, x = input_279_cast_fp16)[name = tensor<string, []>("linear_45_cast_fp16")];
            tensor<fp16, []> var_1188_to_fp16 = const()[name = tensor<string, []>("op_1188_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 512]> var_1189_cast_fp16 = mul(x = linear_45_cast_fp16, y = var_1188_to_fp16)[name = tensor<string, []>("op_1189_cast_fp16")];
            tensor<fp16, [1, 188, 512]> input_285_cast_fp16 = add(x = input_273_cast_fp16, y = var_1189_cast_fp16)[name = tensor<string, []>("input_285_cast_fp16")];
            tensor<int32, [1]> input_287_axes_0 = const()[name = tensor<string, []>("input_287_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_4_norm_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_4_norm_out_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(66131584)))];
            tensor<fp16, [512]> encoder_module_layers_4_norm_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_4_norm_out_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(66132672)))];
            tensor<fp16, [1, 188, 512]> input_287_cast_fp16 = layer_norm(axes = input_287_axes_0, beta = encoder_module_layers_4_norm_out_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_4_norm_out_weight_to_fp16, x = input_285_cast_fp16)[name = tensor<string, []>("input_287_cast_fp16")];
            tensor<int32, [1]> input_289_axes_0 = const()[name = tensor<string, []>("input_289_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_5_norm_feed_forward1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_5_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(66133760)))];
            tensor<fp16, [512]> encoder_module_layers_5_norm_feed_forward1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_5_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(66134848)))];
            tensor<fp16, [1, 188, 512]> input_289_cast_fp16 = layer_norm(axes = input_289_axes_0, beta = encoder_module_layers_5_norm_feed_forward1_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_5_norm_feed_forward1_weight_to_fp16, x = input_287_cast_fp16)[name = tensor<string, []>("input_289_cast_fp16")];
            tensor<fp16, [2048, 512]> encoder_module_layers_5_feed_forward1_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_5_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [2048, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(66135936)))];
            tensor<fp16, [2048]> encoder_module_layers_5_feed_forward1_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_5_feed_forward1_linear1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(68233152)))];
            tensor<fp16, [1, 188, 2048]> linear_46_cast_fp16 = linear(bias = encoder_module_layers_5_feed_forward1_linear1_bias_to_fp16, weight = encoder_module_layers_5_feed_forward1_linear1_weight_to_fp16, x = input_289_cast_fp16)[name = tensor<string, []>("linear_46_cast_fp16")];
            tensor<fp16, [1, 188, 2048]> input_293_cast_fp16 = silu(x = linear_46_cast_fp16)[name = tensor<string, []>("input_293_cast_fp16")];
            tensor<fp16, [512, 2048]> encoder_module_layers_5_feed_forward1_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_5_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [512, 2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(68237312)))];
            tensor<fp16, [512]> encoder_module_layers_5_feed_forward1_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_5_feed_forward1_linear2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(70334528)))];
            tensor<fp16, [1, 188, 512]> linear_47_cast_fp16 = linear(bias = encoder_module_layers_5_feed_forward1_linear2_bias_to_fp16, weight = encoder_module_layers_5_feed_forward1_linear2_weight_to_fp16, x = input_293_cast_fp16)[name = tensor<string, []>("linear_47_cast_fp16")];
            tensor<fp16, []> var_1219_to_fp16 = const()[name = tensor<string, []>("op_1219_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 512]> var_1220_cast_fp16 = mul(x = linear_47_cast_fp16, y = var_1219_to_fp16)[name = tensor<string, []>("op_1220_cast_fp16")];
            tensor<fp16, [1, 188, 512]> input_299_cast_fp16 = add(x = input_287_cast_fp16, y = var_1220_cast_fp16)[name = tensor<string, []>("input_299_cast_fp16")];
            tensor<int32, [1]> query_11_axes_0 = const()[name = tensor<string, []>("query_11_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_5_norm_self_att_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_5_norm_self_att_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(70335616)))];
            tensor<fp16, [512]> encoder_module_layers_5_norm_self_att_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_5_norm_self_att_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(70336704)))];
            tensor<fp16, [1, 188, 512]> query_11_cast_fp16 = layer_norm(axes = query_11_axes_0, beta = encoder_module_layers_5_norm_self_att_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_5_norm_self_att_weight_to_fp16, x = input_299_cast_fp16)[name = tensor<string, []>("query_11_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_5_self_attn_linear_q_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_5_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(70337792)))];
            tensor<fp16, [512]> encoder_module_layers_5_self_attn_linear_q_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_5_self_attn_linear_q_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(70862144)))];
            tensor<fp16, [1, 188, 512]> linear_48_cast_fp16 = linear(bias = encoder_module_layers_5_self_attn_linear_q_bias_to_fp16, weight = encoder_module_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_1237 = const()[name = tensor<string, []>("op_1237"), val = tensor<int32, [4]>([1, -1, 8, 64])];
            tensor<fp16, [1, 188, 8, 64]> q_31_cast_fp16 = reshape(shape = var_1237, x = linear_48_cast_fp16)[name = tensor<string, []>("q_31_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_5_self_attn_linear_k_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_5_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(70863232)))];
            tensor<fp16, [512]> encoder_module_layers_5_self_attn_linear_k_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_5_self_attn_linear_k_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(71387584)))];
            tensor<fp16, [1, 188, 512]> linear_49_cast_fp16 = linear(bias = encoder_module_layers_5_self_attn_linear_k_bias_to_fp16, weight = encoder_module_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_1242 = const()[name = tensor<string, []>("op_1242"), val = tensor<int32, [4]>([1, -1, 8, 64])];
            tensor<fp16, [1, 188, 8, 64]> k_21_cast_fp16 = reshape(shape = var_1242, x = linear_49_cast_fp16)[name = tensor<string, []>("k_21_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_5_self_attn_linear_v_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_5_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(71388672)))];
            tensor<fp16, [512]> encoder_module_layers_5_self_attn_linear_v_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_5_self_attn_linear_v_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(71913024)))];
            tensor<fp16, [1, 188, 512]> linear_50_cast_fp16 = linear(bias = encoder_module_layers_5_self_attn_linear_v_bias_to_fp16, weight = encoder_module_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_1247 = const()[name = tensor<string, []>("op_1247"), val = tensor<int32, [4]>([1, -1, 8, 64])];
            tensor<fp16, [1, 188, 8, 64]> v_11_cast_fp16 = reshape(shape = var_1247, x = linear_50_cast_fp16)[name = tensor<string, []>("v_11_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, 64]> encoder_module_layers_5_self_attn_pos_bias_u_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_5_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(71914112)))];
            tensor<fp16, [1, 188, 8, 64]> var_1259_cast_fp16 = add(x = q_31_cast_fp16, y = encoder_module_layers_5_self_attn_pos_bias_u_to_fp16)[name = tensor<string, []>("op_1259_cast_fp16")];
            tensor<fp16, [8, 64]> encoder_module_layers_5_self_attn_pos_bias_v_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_5_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(71915200)))];
            tensor<fp16, [1, 188, 8, 64]> var_1261_cast_fp16 = add(x = q_31_cast_fp16, y = encoder_module_layers_5_self_attn_pos_bias_v_to_fp16)[name = tensor<string, []>("op_1261_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_133_transpose_x_0 = const()[name = tensor<string, []>("x_133_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_133_transpose_y_0 = const()[name = tensor<string, []>("x_133_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 64, 375]> var_1263_to_fp16 = const()[name = tensor<string, []>("op_1263_to_fp16"), val = tensor<fp16, [1, 8, 64, 375]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(71916288)))];
            tensor<fp16, [1, 8, 188, 64]> q_with_bias_v_11_cast_fp16 = transpose(perm = q_with_bias_v_11_perm_0, x = var_1261_cast_fp16)[name = tensor<string, []>("transpose_168")];
            tensor<fp16, [1, 8, 188, 375]> x_133_cast_fp16 = matmul(transpose_x = x_133_transpose_x_0, transpose_y = x_133_transpose_y_0, x = q_with_bias_v_11_cast_fp16, y = var_1263_to_fp16)[name = tensor<string, []>("x_133_cast_fp16")];
            tensor<int32, [8]> x_135_pad_0 = const()[name = tensor<string, []>("x_135_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            tensor<string, []> x_135_mode_0 = const()[name = tensor<string, []>("x_135_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_79_to_fp16 = const()[name = tensor<string, []>("const_79_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_135_cast_fp16 = pad(constant_val = const_79_to_fp16, mode = x_135_mode_0, pad = x_135_pad_0, x = x_133_cast_fp16)[name = tensor<string, []>("x_135_cast_fp16")];
            tensor<int32, [4]> var_1271 = const()[name = tensor<string, []>("op_1271"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_137_cast_fp16 = reshape(shape = var_1271, x = x_135_cast_fp16)[name = tensor<string, []>("x_137_cast_fp16")];
            tensor<int32, [4]> var_1275_begin_0 = const()[name = tensor<string, []>("op_1275_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_1275_end_0 = const()[name = tensor<string, []>("op_1275_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_1275_end_mask_0 = const()[name = tensor<string, []>("op_1275_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_1275_cast_fp16 = slice_by_index(begin = var_1275_begin_0, end = var_1275_end_0, end_mask = var_1275_end_mask_0, x = x_137_cast_fp16)[name = tensor<string, []>("op_1275_cast_fp16")];
            tensor<int32, [4]> var_1276 = const()[name = tensor<string, []>("op_1276"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_21_cast_fp16 = reshape(shape = var_1276, x = var_1275_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_61_perm_0 = const()[name = tensor<string, []>("transpose_61_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_62_perm_0 = const()[name = tensor<string, []>("transpose_62_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 64, 188]> transpose_62 = transpose(perm = transpose_62_perm_0, x = k_21_cast_fp16)[name = tensor<string, []>("transpose_166")];
            tensor<fp16, [1, 8, 188, 64]> transpose_61 = transpose(perm = transpose_61_perm_0, x = var_1259_cast_fp16)[name = tensor<string, []>("transpose_167")];
            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_61, y = transpose_62)[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_1285_cast_fp16 = add(x = matrix_ac_11_cast_fp16, y = matrix_bd_23_cast_fp16)[name = tensor<string, []>("op_1285_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, []>(0x1p-3)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_21_cast_fp16 = mul(x = var_1285_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_153_to_fp16, b = _inversed_scores_21_cast_fp16, cond = mask_7)[name = tensor<string, []>("scores_23_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_1291_cast_fp16 = softmax(axis = var_138, x = scores_23_cast_fp16)[name = tensor<string, []>("op_1291_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_301_cast_fp16 = select(a = var_154_to_fp16, b = var_1291_cast_fp16, cond = mask_7)[name = tensor<string, []>("input_301_cast_fp16")];
            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, 188, 64]> value_15_cast_fp16 = transpose(perm = value_15_perm_0, x = v_11_cast_fp16)[name = tensor<string, []>("transpose_169")];
            tensor<fp16, [1, 8, 188, 64]> x_139_cast_fp16 = matmul(transpose_x = x_139_transpose_x_0, transpose_y = x_139_transpose_y_0, x = input_301_cast_fp16, y = value_15_cast_fp16)[name = tensor<string, []>("x_139_cast_fp16")];
            tensor<int32, [4]> var_1295_perm_0 = const()[name = tensor<string, []>("op_1295_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1296 = const()[name = tensor<string, []>("op_1296"), val = tensor<int32, [3]>([1, -1, 512])];
            tensor<fp16, [1, 188, 8, 64]> var_1295_cast_fp16 = transpose(perm = var_1295_perm_0, x = x_139_cast_fp16)[name = tensor<string, []>("transpose_165")];
            tensor<fp16, [1, 188, 512]> input_303_cast_fp16 = reshape(shape = var_1296, x = var_1295_cast_fp16)[name = tensor<string, []>("input_303_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_5_self_attn_linear_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_5_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(72300352)))];
            tensor<fp16, [512]> encoder_module_layers_5_self_attn_linear_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_5_self_attn_linear_out_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(72824704)))];
            tensor<fp16, [1, 188, 512]> linear_52_cast_fp16 = linear(bias = encoder_module_layers_5_self_attn_linear_out_bias_to_fp16, weight = encoder_module_layers_5_self_attn_linear_out_weight_to_fp16, x = input_303_cast_fp16)[name = tensor<string, []>("linear_52_cast_fp16")];
            tensor<fp16, [1, 188, 512]> input_307_cast_fp16 = add(x = input_299_cast_fp16, y = linear_52_cast_fp16)[name = tensor<string, []>("input_307_cast_fp16")];
            tensor<int32, [1]> x_143_axes_0 = const()[name = tensor<string, []>("x_143_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_5_norm_conv_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_5_norm_conv_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(72825792)))];
            tensor<fp16, [512]> encoder_module_layers_5_norm_conv_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_5_norm_conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(72826880)))];
            tensor<fp16, [1, 188, 512]> x_143_cast_fp16 = layer_norm(axes = x_143_axes_0, beta = encoder_module_layers_5_norm_conv_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_5_norm_conv_weight_to_fp16, x = input_307_cast_fp16)[name = tensor<string, []>("x_143_cast_fp16")];
            tensor<int32, [3]> input_309_perm_0 = const()[name = tensor<string, []>("input_309_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> input_311_pad_type_0 = const()[name = tensor<string, []>("input_311_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_311_strides_0 = const()[name = tensor<string, []>("input_311_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_311_pad_0 = const()[name = tensor<string, []>("input_311_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_311_dilations_0 = const()[name = tensor<string, []>("input_311_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_311_groups_0 = const()[name = tensor<string, []>("input_311_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1024, 512, 1]> encoder_module_layers_5_conv_pointwise_conv1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_5_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [1024, 512, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(72827968)))];
            tensor<fp16, [1024]> encoder_module_layers_5_conv_pointwise_conv1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_5_conv_pointwise_conv1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(73876608)))];
            tensor<fp16, [1, 512, 188]> input_309_cast_fp16 = transpose(perm = input_309_perm_0, x = x_143_cast_fp16)[name = tensor<string, []>("transpose_164")];
            tensor<fp16, [1, 1024, 188]> input_311_cast_fp16 = conv(bias = encoder_module_layers_5_conv_pointwise_conv1_bias_to_fp16, dilations = input_311_dilations_0, groups = input_311_groups_0, pad = input_311_pad_0, pad_type = input_311_pad_type_0, strides = input_311_strides_0, weight = encoder_module_layers_5_conv_pointwise_conv1_weight_to_fp16, x = input_309_cast_fp16)[name = tensor<string, []>("input_311_cast_fp16")];
            tensor<int32, []> x_145_split_num_splits_0 = const()[name = tensor<string, []>("x_145_split_num_splits_0"), val = tensor<int32, []>(2)];
            tensor<int32, []> x_145_split_axis_0 = const()[name = tensor<string, []>("x_145_split_axis_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1, 512, 188]> x_145_split_cast_fp16_0, tensor<fp16, [1, 512, 188]> x_145_split_cast_fp16_1 = split(axis = x_145_split_axis_0, num_splits = x_145_split_num_splits_0, x = input_311_cast_fp16)[name = tensor<string, []>("x_145_split_cast_fp16")];
            tensor<fp16, [1, 512, 188]> x_145_split_1_sigmoid_cast_fp16 = sigmoid(x = x_145_split_cast_fp16_1)[name = tensor<string, []>("x_145_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 512, 188]> x_145_cast_fp16 = mul(x = x_145_split_cast_fp16_0, y = x_145_split_1_sigmoid_cast_fp16)[name = tensor<string, []>("x_145_cast_fp16")];
            tensor<fp16, [1, 512, 188]> input_313_cast_fp16 = select(a = var_154_to_fp16, b = x_145_cast_fp16, cond = var_450)[name = tensor<string, []>("input_313_cast_fp16")];
            tensor<int32, [6]> input_315_pad_0 = const()[name = tensor<string, []>("input_315_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            tensor<string, []> input_315_mode_0 = const()[name = tensor<string, []>("input_315_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_82_to_fp16 = const()[name = tensor<string, []>("const_82_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 512, 196]> input_315_cast_fp16 = pad(constant_val = const_82_to_fp16, mode = input_315_mode_0, pad = input_315_pad_0, x = input_313_cast_fp16)[name = tensor<string, []>("input_315_cast_fp16")];
            tensor<string, []> input_317_pad_type_0 = const()[name = tensor<string, []>("input_317_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, []> input_317_groups_0 = const()[name = tensor<string, []>("input_317_groups_0"), val = tensor<int32, []>(512)];
            tensor<int32, [1]> input_317_strides_0 = const()[name = tensor<string, []>("input_317_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_317_pad_0 = const()[name = tensor<string, []>("input_317_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_317_dilations_0 = const()[name = tensor<string, []>("input_317_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 9]> const_203_to_fp16 = const()[name = tensor<string, []>("const_203_to_fp16"), val = tensor<fp16, [512, 1, 9]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(73878720)))];
            tensor<fp16, [512]> const_204_to_fp16 = const()[name = tensor<string, []>("const_204_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(73888000)))];
            tensor<fp16, [1, 512, 188]> input_319_cast_fp16 = conv(bias = const_204_to_fp16, dilations = input_317_dilations_0, groups = input_317_groups_0, pad = input_317_pad_0, pad_type = input_317_pad_type_0, strides = input_317_strides_0, weight = const_203_to_fp16, x = input_315_cast_fp16)[name = tensor<string, []>("input_319_cast_fp16")];
            tensor<fp16, [1, 512, 188]> input_321_cast_fp16 = silu(x = input_319_cast_fp16)[name = tensor<string, []>("input_321_cast_fp16")];
            tensor<string, []> x_147_pad_type_0 = const()[name = tensor<string, []>("x_147_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> x_147_strides_0 = const()[name = tensor<string, []>("x_147_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_147_pad_0 = const()[name = tensor<string, []>("x_147_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_147_dilations_0 = const()[name = tensor<string, []>("x_147_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> x_147_groups_0 = const()[name = tensor<string, []>("x_147_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [512, 512, 1]> encoder_module_layers_5_conv_pointwise_conv2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_5_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [512, 512, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(73889088)))];
            tensor<fp16, [512]> encoder_module_layers_5_conv_pointwise_conv2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_5_conv_pointwise_conv2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(74413440)))];
            tensor<fp16, [1, 512, 188]> x_147_cast_fp16 = conv(bias = encoder_module_layers_5_conv_pointwise_conv2_bias_to_fp16, dilations = x_147_dilations_0, groups = x_147_groups_0, pad = x_147_pad_0, pad_type = x_147_pad_type_0, strides = x_147_strides_0, weight = encoder_module_layers_5_conv_pointwise_conv2_weight_to_fp16, x = input_321_cast_fp16)[name = tensor<string, []>("x_147_cast_fp16")];
            tensor<int32, [3]> input_323_perm_0 = const()[name = tensor<string, []>("input_323_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 512]> input_323_cast_fp16 = transpose(perm = input_323_perm_0, x = x_147_cast_fp16)[name = tensor<string, []>("transpose_163")];
            tensor<fp16, [1, 188, 512]> input_325_cast_fp16 = add(x = input_307_cast_fp16, y = input_323_cast_fp16)[name = tensor<string, []>("input_325_cast_fp16")];
            tensor<int32, [1]> input_327_axes_0 = const()[name = tensor<string, []>("input_327_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_5_norm_feed_forward2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_5_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(74414528)))];
            tensor<fp16, [512]> encoder_module_layers_5_norm_feed_forward2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_5_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(74415616)))];
            tensor<fp16, [1, 188, 512]> input_327_cast_fp16 = layer_norm(axes = input_327_axes_0, beta = encoder_module_layers_5_norm_feed_forward2_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_5_norm_feed_forward2_weight_to_fp16, x = input_325_cast_fp16)[name = tensor<string, []>("input_327_cast_fp16")];
            tensor<fp16, [2048, 512]> encoder_module_layers_5_feed_forward2_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_5_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [2048, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(74416704)))];
            tensor<fp16, [2048]> encoder_module_layers_5_feed_forward2_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_5_feed_forward2_linear1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(76513920)))];
            tensor<fp16, [1, 188, 2048]> linear_53_cast_fp16 = linear(bias = encoder_module_layers_5_feed_forward2_linear1_bias_to_fp16, weight = encoder_module_layers_5_feed_forward2_linear1_weight_to_fp16, x = input_327_cast_fp16)[name = tensor<string, []>("linear_53_cast_fp16")];
            tensor<fp16, [1, 188, 2048]> input_331_cast_fp16 = silu(x = linear_53_cast_fp16)[name = tensor<string, []>("input_331_cast_fp16")];
            tensor<fp16, [512, 2048]> encoder_module_layers_5_feed_forward2_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_5_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [512, 2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(76518080)))];
            tensor<fp16, [512]> encoder_module_layers_5_feed_forward2_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_5_feed_forward2_linear2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(78615296)))];
            tensor<fp16, [1, 188, 512]> linear_54_cast_fp16 = linear(bias = encoder_module_layers_5_feed_forward2_linear2_bias_to_fp16, weight = encoder_module_layers_5_feed_forward2_linear2_weight_to_fp16, x = input_331_cast_fp16)[name = tensor<string, []>("linear_54_cast_fp16")];
            tensor<fp16, []> var_1362_to_fp16 = const()[name = tensor<string, []>("op_1362_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 512]> var_1363_cast_fp16 = mul(x = linear_54_cast_fp16, y = var_1362_to_fp16)[name = tensor<string, []>("op_1363_cast_fp16")];
            tensor<fp16, [1, 188, 512]> input_337_cast_fp16 = add(x = input_325_cast_fp16, y = var_1363_cast_fp16)[name = tensor<string, []>("input_337_cast_fp16")];
            tensor<int32, [1]> input_339_axes_0 = const()[name = tensor<string, []>("input_339_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_5_norm_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_5_norm_out_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(78616384)))];
            tensor<fp16, [512]> encoder_module_layers_5_norm_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_5_norm_out_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(78617472)))];
            tensor<fp16, [1, 188, 512]> input_339_cast_fp16 = layer_norm(axes = input_339_axes_0, beta = encoder_module_layers_5_norm_out_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_5_norm_out_weight_to_fp16, x = input_337_cast_fp16)[name = tensor<string, []>("input_339_cast_fp16")];
            tensor<int32, [1]> input_341_axes_0 = const()[name = tensor<string, []>("input_341_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_6_norm_feed_forward1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_6_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(78618560)))];
            tensor<fp16, [512]> encoder_module_layers_6_norm_feed_forward1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_6_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(78619648)))];
            tensor<fp16, [1, 188, 512]> input_341_cast_fp16 = layer_norm(axes = input_341_axes_0, beta = encoder_module_layers_6_norm_feed_forward1_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_6_norm_feed_forward1_weight_to_fp16, x = input_339_cast_fp16)[name = tensor<string, []>("input_341_cast_fp16")];
            tensor<fp16, [2048, 512]> encoder_module_layers_6_feed_forward1_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_6_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [2048, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(78620736)))];
            tensor<fp16, [2048]> encoder_module_layers_6_feed_forward1_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_6_feed_forward1_linear1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(80717952)))];
            tensor<fp16, [1, 188, 2048]> linear_55_cast_fp16 = linear(bias = encoder_module_layers_6_feed_forward1_linear1_bias_to_fp16, weight = encoder_module_layers_6_feed_forward1_linear1_weight_to_fp16, x = input_341_cast_fp16)[name = tensor<string, []>("linear_55_cast_fp16")];
            tensor<fp16, [1, 188, 2048]> input_345_cast_fp16 = silu(x = linear_55_cast_fp16)[name = tensor<string, []>("input_345_cast_fp16")];
            tensor<fp16, [512, 2048]> encoder_module_layers_6_feed_forward1_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_6_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [512, 2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(80722112)))];
            tensor<fp16, [512]> encoder_module_layers_6_feed_forward1_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_6_feed_forward1_linear2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(82819328)))];
            tensor<fp16, [1, 188, 512]> linear_56_cast_fp16 = linear(bias = encoder_module_layers_6_feed_forward1_linear2_bias_to_fp16, weight = encoder_module_layers_6_feed_forward1_linear2_weight_to_fp16, x = input_345_cast_fp16)[name = tensor<string, []>("linear_56_cast_fp16")];
            tensor<fp16, []> var_1393_to_fp16 = const()[name = tensor<string, []>("op_1393_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 512]> var_1394_cast_fp16 = mul(x = linear_56_cast_fp16, y = var_1393_to_fp16)[name = tensor<string, []>("op_1394_cast_fp16")];
            tensor<fp16, [1, 188, 512]> input_351_cast_fp16 = add(x = input_339_cast_fp16, y = var_1394_cast_fp16)[name = tensor<string, []>("input_351_cast_fp16")];
            tensor<int32, [1]> query_13_axes_0 = const()[name = tensor<string, []>("query_13_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_6_norm_self_att_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_6_norm_self_att_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(82820416)))];
            tensor<fp16, [512]> encoder_module_layers_6_norm_self_att_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_6_norm_self_att_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(82821504)))];
            tensor<fp16, [1, 188, 512]> query_13_cast_fp16 = layer_norm(axes = query_13_axes_0, beta = encoder_module_layers_6_norm_self_att_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_6_norm_self_att_weight_to_fp16, x = input_351_cast_fp16)[name = tensor<string, []>("query_13_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_6_self_attn_linear_q_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_6_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(82822592)))];
            tensor<fp16, [512]> encoder_module_layers_6_self_attn_linear_q_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_6_self_attn_linear_q_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(83346944)))];
            tensor<fp16, [1, 188, 512]> linear_57_cast_fp16 = linear(bias = encoder_module_layers_6_self_attn_linear_q_bias_to_fp16, weight = encoder_module_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_1411 = const()[name = tensor<string, []>("op_1411"), val = tensor<int32, [4]>([1, -1, 8, 64])];
            tensor<fp16, [1, 188, 8, 64]> q_37_cast_fp16 = reshape(shape = var_1411, x = linear_57_cast_fp16)[name = tensor<string, []>("q_37_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_6_self_attn_linear_k_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_6_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(83348032)))];
            tensor<fp16, [512]> encoder_module_layers_6_self_attn_linear_k_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_6_self_attn_linear_k_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(83872384)))];
            tensor<fp16, [1, 188, 512]> linear_58_cast_fp16 = linear(bias = encoder_module_layers_6_self_attn_linear_k_bias_to_fp16, weight = encoder_module_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_1416 = const()[name = tensor<string, []>("op_1416"), val = tensor<int32, [4]>([1, -1, 8, 64])];
            tensor<fp16, [1, 188, 8, 64]> k_25_cast_fp16 = reshape(shape = var_1416, x = linear_58_cast_fp16)[name = tensor<string, []>("k_25_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_6_self_attn_linear_v_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_6_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(83873472)))];
            tensor<fp16, [512]> encoder_module_layers_6_self_attn_linear_v_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_6_self_attn_linear_v_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(84397824)))];
            tensor<fp16, [1, 188, 512]> linear_59_cast_fp16 = linear(bias = encoder_module_layers_6_self_attn_linear_v_bias_to_fp16, weight = encoder_module_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_1421 = const()[name = tensor<string, []>("op_1421"), val = tensor<int32, [4]>([1, -1, 8, 64])];
            tensor<fp16, [1, 188, 8, 64]> v_13_cast_fp16 = reshape(shape = var_1421, x = linear_59_cast_fp16)[name = tensor<string, []>("v_13_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, 64]> encoder_module_layers_6_self_attn_pos_bias_u_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_6_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(84398912)))];
            tensor<fp16, [1, 188, 8, 64]> var_1433_cast_fp16 = add(x = q_37_cast_fp16, y = encoder_module_layers_6_self_attn_pos_bias_u_to_fp16)[name = tensor<string, []>("op_1433_cast_fp16")];
            tensor<fp16, [8, 64]> encoder_module_layers_6_self_attn_pos_bias_v_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_6_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(84400000)))];
            tensor<fp16, [1, 188, 8, 64]> var_1435_cast_fp16 = add(x = q_37_cast_fp16, y = encoder_module_layers_6_self_attn_pos_bias_v_to_fp16)[name = tensor<string, []>("op_1435_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_155_transpose_x_0 = const()[name = tensor<string, []>("x_155_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_155_transpose_y_0 = const()[name = tensor<string, []>("x_155_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 64, 375]> var_1437_to_fp16 = const()[name = tensor<string, []>("op_1437_to_fp16"), val = tensor<fp16, [1, 8, 64, 375]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(84401088)))];
            tensor<fp16, [1, 8, 188, 64]> q_with_bias_v_13_cast_fp16 = transpose(perm = q_with_bias_v_13_perm_0, x = var_1435_cast_fp16)[name = tensor<string, []>("transpose_161")];
            tensor<fp16, [1, 8, 188, 375]> x_155_cast_fp16 = matmul(transpose_x = x_155_transpose_x_0, transpose_y = x_155_transpose_y_0, x = q_with_bias_v_13_cast_fp16, y = var_1437_to_fp16)[name = tensor<string, []>("x_155_cast_fp16")];
            tensor<int32, [8]> x_157_pad_0 = const()[name = tensor<string, []>("x_157_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            tensor<string, []> x_157_mode_0 = const()[name = tensor<string, []>("x_157_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_89_to_fp16 = const()[name = tensor<string, []>("const_89_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_157_cast_fp16 = pad(constant_val = const_89_to_fp16, mode = x_157_mode_0, pad = x_157_pad_0, x = x_155_cast_fp16)[name = tensor<string, []>("x_157_cast_fp16")];
            tensor<int32, [4]> var_1445 = const()[name = tensor<string, []>("op_1445"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_159_cast_fp16 = reshape(shape = var_1445, x = x_157_cast_fp16)[name = tensor<string, []>("x_159_cast_fp16")];
            tensor<int32, [4]> var_1449_begin_0 = const()[name = tensor<string, []>("op_1449_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_1449_end_0 = const()[name = tensor<string, []>("op_1449_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_1449_end_mask_0 = const()[name = tensor<string, []>("op_1449_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_1449_cast_fp16 = slice_by_index(begin = var_1449_begin_0, end = var_1449_end_0, end_mask = var_1449_end_mask_0, x = x_159_cast_fp16)[name = tensor<string, []>("op_1449_cast_fp16")];
            tensor<int32, [4]> var_1450 = const()[name = tensor<string, []>("op_1450"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_25_cast_fp16 = reshape(shape = var_1450, x = var_1449_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_63_perm_0 = const()[name = tensor<string, []>("transpose_63_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_64_perm_0 = const()[name = tensor<string, []>("transpose_64_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 64, 188]> transpose_64 = transpose(perm = transpose_64_perm_0, x = k_25_cast_fp16)[name = tensor<string, []>("transpose_159")];
            tensor<fp16, [1, 8, 188, 64]> transpose_63 = transpose(perm = transpose_63_perm_0, x = var_1433_cast_fp16)[name = tensor<string, []>("transpose_160")];
            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_63, y = transpose_64)[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_1459_cast_fp16 = add(x = matrix_ac_13_cast_fp16, y = matrix_bd_27_cast_fp16)[name = tensor<string, []>("op_1459_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, []>(0x1p-3)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_25_cast_fp16 = mul(x = var_1459_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_153_to_fp16, b = _inversed_scores_25_cast_fp16, cond = mask_7)[name = tensor<string, []>("scores_27_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_1465_cast_fp16 = softmax(axis = var_138, x = scores_27_cast_fp16)[name = tensor<string, []>("op_1465_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_353_cast_fp16 = select(a = var_154_to_fp16, b = var_1465_cast_fp16, cond = mask_7)[name = tensor<string, []>("input_353_cast_fp16")];
            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, 188, 64]> value_17_cast_fp16 = transpose(perm = value_17_perm_0, x = v_13_cast_fp16)[name = tensor<string, []>("transpose_162")];
            tensor<fp16, [1, 8, 188, 64]> x_161_cast_fp16 = matmul(transpose_x = x_161_transpose_x_0, transpose_y = x_161_transpose_y_0, x = input_353_cast_fp16, y = value_17_cast_fp16)[name = tensor<string, []>("x_161_cast_fp16")];
            tensor<int32, [4]> var_1469_perm_0 = const()[name = tensor<string, []>("op_1469_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1470 = const()[name = tensor<string, []>("op_1470"), val = tensor<int32, [3]>([1, -1, 512])];
            tensor<fp16, [1, 188, 8, 64]> var_1469_cast_fp16 = transpose(perm = var_1469_perm_0, x = x_161_cast_fp16)[name = tensor<string, []>("transpose_158")];
            tensor<fp16, [1, 188, 512]> input_355_cast_fp16 = reshape(shape = var_1470, x = var_1469_cast_fp16)[name = tensor<string, []>("input_355_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_6_self_attn_linear_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_6_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(84785152)))];
            tensor<fp16, [512]> encoder_module_layers_6_self_attn_linear_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_6_self_attn_linear_out_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(85309504)))];
            tensor<fp16, [1, 188, 512]> linear_61_cast_fp16 = linear(bias = encoder_module_layers_6_self_attn_linear_out_bias_to_fp16, weight = encoder_module_layers_6_self_attn_linear_out_weight_to_fp16, x = input_355_cast_fp16)[name = tensor<string, []>("linear_61_cast_fp16")];
            tensor<fp16, [1, 188, 512]> input_359_cast_fp16 = add(x = input_351_cast_fp16, y = linear_61_cast_fp16)[name = tensor<string, []>("input_359_cast_fp16")];
            tensor<int32, [1]> x_165_axes_0 = const()[name = tensor<string, []>("x_165_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_6_norm_conv_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_6_norm_conv_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(85310592)))];
            tensor<fp16, [512]> encoder_module_layers_6_norm_conv_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_6_norm_conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(85311680)))];
            tensor<fp16, [1, 188, 512]> x_165_cast_fp16 = layer_norm(axes = x_165_axes_0, beta = encoder_module_layers_6_norm_conv_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_6_norm_conv_weight_to_fp16, x = input_359_cast_fp16)[name = tensor<string, []>("x_165_cast_fp16")];
            tensor<int32, [3]> input_361_perm_0 = const()[name = tensor<string, []>("input_361_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> input_363_pad_type_0 = const()[name = tensor<string, []>("input_363_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_363_strides_0 = const()[name = tensor<string, []>("input_363_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_363_pad_0 = const()[name = tensor<string, []>("input_363_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_363_dilations_0 = const()[name = tensor<string, []>("input_363_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_363_groups_0 = const()[name = tensor<string, []>("input_363_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1024, 512, 1]> encoder_module_layers_6_conv_pointwise_conv1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_6_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [1024, 512, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(85312768)))];
            tensor<fp16, [1024]> encoder_module_layers_6_conv_pointwise_conv1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_6_conv_pointwise_conv1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(86361408)))];
            tensor<fp16, [1, 512, 188]> input_361_cast_fp16 = transpose(perm = input_361_perm_0, x = x_165_cast_fp16)[name = tensor<string, []>("transpose_157")];
            tensor<fp16, [1, 1024, 188]> input_363_cast_fp16 = conv(bias = encoder_module_layers_6_conv_pointwise_conv1_bias_to_fp16, dilations = input_363_dilations_0, groups = input_363_groups_0, pad = input_363_pad_0, pad_type = input_363_pad_type_0, strides = input_363_strides_0, weight = encoder_module_layers_6_conv_pointwise_conv1_weight_to_fp16, x = input_361_cast_fp16)[name = tensor<string, []>("input_363_cast_fp16")];
            tensor<int32, []> x_167_split_num_splits_0 = const()[name = tensor<string, []>("x_167_split_num_splits_0"), val = tensor<int32, []>(2)];
            tensor<int32, []> x_167_split_axis_0 = const()[name = tensor<string, []>("x_167_split_axis_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1, 512, 188]> x_167_split_cast_fp16_0, tensor<fp16, [1, 512, 188]> x_167_split_cast_fp16_1 = split(axis = x_167_split_axis_0, num_splits = x_167_split_num_splits_0, x = input_363_cast_fp16)[name = tensor<string, []>("x_167_split_cast_fp16")];
            tensor<fp16, [1, 512, 188]> x_167_split_1_sigmoid_cast_fp16 = sigmoid(x = x_167_split_cast_fp16_1)[name = tensor<string, []>("x_167_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 512, 188]> x_167_cast_fp16 = mul(x = x_167_split_cast_fp16_0, y = x_167_split_1_sigmoid_cast_fp16)[name = tensor<string, []>("x_167_cast_fp16")];
            tensor<fp16, [1, 512, 188]> input_365_cast_fp16 = select(a = var_154_to_fp16, b = x_167_cast_fp16, cond = var_450)[name = tensor<string, []>("input_365_cast_fp16")];
            tensor<int32, [6]> input_367_pad_0 = const()[name = tensor<string, []>("input_367_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            tensor<string, []> input_367_mode_0 = const()[name = tensor<string, []>("input_367_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_92_to_fp16 = const()[name = tensor<string, []>("const_92_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 512, 196]> input_367_cast_fp16 = pad(constant_val = const_92_to_fp16, mode = input_367_mode_0, pad = input_367_pad_0, x = input_365_cast_fp16)[name = tensor<string, []>("input_367_cast_fp16")];
            tensor<string, []> input_369_pad_type_0 = const()[name = tensor<string, []>("input_369_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, []> input_369_groups_0 = const()[name = tensor<string, []>("input_369_groups_0"), val = tensor<int32, []>(512)];
            tensor<int32, [1]> input_369_strides_0 = const()[name = tensor<string, []>("input_369_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_369_pad_0 = const()[name = tensor<string, []>("input_369_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_369_dilations_0 = const()[name = tensor<string, []>("input_369_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 9]> const_205_to_fp16 = const()[name = tensor<string, []>("const_205_to_fp16"), val = tensor<fp16, [512, 1, 9]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(86363520)))];
            tensor<fp16, [512]> const_206_to_fp16 = const()[name = tensor<string, []>("const_206_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(86372800)))];
            tensor<fp16, [1, 512, 188]> input_371_cast_fp16 = conv(bias = const_206_to_fp16, dilations = input_369_dilations_0, groups = input_369_groups_0, pad = input_369_pad_0, pad_type = input_369_pad_type_0, strides = input_369_strides_0, weight = const_205_to_fp16, x = input_367_cast_fp16)[name = tensor<string, []>("input_371_cast_fp16")];
            tensor<fp16, [1, 512, 188]> input_373_cast_fp16 = silu(x = input_371_cast_fp16)[name = tensor<string, []>("input_373_cast_fp16")];
            tensor<string, []> x_169_pad_type_0 = const()[name = tensor<string, []>("x_169_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> x_169_strides_0 = const()[name = tensor<string, []>("x_169_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_169_pad_0 = const()[name = tensor<string, []>("x_169_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_169_dilations_0 = const()[name = tensor<string, []>("x_169_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> x_169_groups_0 = const()[name = tensor<string, []>("x_169_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [512, 512, 1]> encoder_module_layers_6_conv_pointwise_conv2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_6_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [512, 512, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(86373888)))];
            tensor<fp16, [512]> encoder_module_layers_6_conv_pointwise_conv2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_6_conv_pointwise_conv2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(86898240)))];
            tensor<fp16, [1, 512, 188]> x_169_cast_fp16 = conv(bias = encoder_module_layers_6_conv_pointwise_conv2_bias_to_fp16, dilations = x_169_dilations_0, groups = x_169_groups_0, pad = x_169_pad_0, pad_type = x_169_pad_type_0, strides = x_169_strides_0, weight = encoder_module_layers_6_conv_pointwise_conv2_weight_to_fp16, x = input_373_cast_fp16)[name = tensor<string, []>("x_169_cast_fp16")];
            tensor<int32, [3]> input_375_perm_0 = const()[name = tensor<string, []>("input_375_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 512]> input_375_cast_fp16 = transpose(perm = input_375_perm_0, x = x_169_cast_fp16)[name = tensor<string, []>("transpose_156")];
            tensor<fp16, [1, 188, 512]> input_377_cast_fp16 = add(x = input_359_cast_fp16, y = input_375_cast_fp16)[name = tensor<string, []>("input_377_cast_fp16")];
            tensor<int32, [1]> input_379_axes_0 = const()[name = tensor<string, []>("input_379_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_6_norm_feed_forward2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_6_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(86899328)))];
            tensor<fp16, [512]> encoder_module_layers_6_norm_feed_forward2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_6_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(86900416)))];
            tensor<fp16, [1, 188, 512]> input_379_cast_fp16 = layer_norm(axes = input_379_axes_0, beta = encoder_module_layers_6_norm_feed_forward2_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_6_norm_feed_forward2_weight_to_fp16, x = input_377_cast_fp16)[name = tensor<string, []>("input_379_cast_fp16")];
            tensor<fp16, [2048, 512]> encoder_module_layers_6_feed_forward2_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_6_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [2048, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(86901504)))];
            tensor<fp16, [2048]> encoder_module_layers_6_feed_forward2_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_6_feed_forward2_linear1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(88998720)))];
            tensor<fp16, [1, 188, 2048]> linear_62_cast_fp16 = linear(bias = encoder_module_layers_6_feed_forward2_linear1_bias_to_fp16, weight = encoder_module_layers_6_feed_forward2_linear1_weight_to_fp16, x = input_379_cast_fp16)[name = tensor<string, []>("linear_62_cast_fp16")];
            tensor<fp16, [1, 188, 2048]> input_383_cast_fp16 = silu(x = linear_62_cast_fp16)[name = tensor<string, []>("input_383_cast_fp16")];
            tensor<fp16, [512, 2048]> encoder_module_layers_6_feed_forward2_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_6_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [512, 2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(89002880)))];
            tensor<fp16, [512]> encoder_module_layers_6_feed_forward2_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_6_feed_forward2_linear2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(91100096)))];
            tensor<fp16, [1, 188, 512]> linear_63_cast_fp16 = linear(bias = encoder_module_layers_6_feed_forward2_linear2_bias_to_fp16, weight = encoder_module_layers_6_feed_forward2_linear2_weight_to_fp16, x = input_383_cast_fp16)[name = tensor<string, []>("linear_63_cast_fp16")];
            tensor<fp16, []> var_1536_to_fp16 = const()[name = tensor<string, []>("op_1536_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 512]> var_1537_cast_fp16 = mul(x = linear_63_cast_fp16, y = var_1536_to_fp16)[name = tensor<string, []>("op_1537_cast_fp16")];
            tensor<fp16, [1, 188, 512]> input_389_cast_fp16 = add(x = input_377_cast_fp16, y = var_1537_cast_fp16)[name = tensor<string, []>("input_389_cast_fp16")];
            tensor<int32, [1]> input_391_axes_0 = const()[name = tensor<string, []>("input_391_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_6_norm_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_6_norm_out_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(91101184)))];
            tensor<fp16, [512]> encoder_module_layers_6_norm_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_6_norm_out_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(91102272)))];
            tensor<fp16, [1, 188, 512]> input_391_cast_fp16 = layer_norm(axes = input_391_axes_0, beta = encoder_module_layers_6_norm_out_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_6_norm_out_weight_to_fp16, x = input_389_cast_fp16)[name = tensor<string, []>("input_391_cast_fp16")];
            tensor<int32, [1]> input_393_axes_0 = const()[name = tensor<string, []>("input_393_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_7_norm_feed_forward1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_7_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(91103360)))];
            tensor<fp16, [512]> encoder_module_layers_7_norm_feed_forward1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_7_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(91104448)))];
            tensor<fp16, [1, 188, 512]> input_393_cast_fp16 = layer_norm(axes = input_393_axes_0, beta = encoder_module_layers_7_norm_feed_forward1_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_7_norm_feed_forward1_weight_to_fp16, x = input_391_cast_fp16)[name = tensor<string, []>("input_393_cast_fp16")];
            tensor<fp16, [2048, 512]> encoder_module_layers_7_feed_forward1_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_7_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [2048, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(91105536)))];
            tensor<fp16, [2048]> encoder_module_layers_7_feed_forward1_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_7_feed_forward1_linear1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(93202752)))];
            tensor<fp16, [1, 188, 2048]> linear_64_cast_fp16 = linear(bias = encoder_module_layers_7_feed_forward1_linear1_bias_to_fp16, weight = encoder_module_layers_7_feed_forward1_linear1_weight_to_fp16, x = input_393_cast_fp16)[name = tensor<string, []>("linear_64_cast_fp16")];
            tensor<fp16, [1, 188, 2048]> input_397_cast_fp16 = silu(x = linear_64_cast_fp16)[name = tensor<string, []>("input_397_cast_fp16")];
            tensor<fp16, [512, 2048]> encoder_module_layers_7_feed_forward1_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_7_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [512, 2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(93206912)))];
            tensor<fp16, [512]> encoder_module_layers_7_feed_forward1_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_7_feed_forward1_linear2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(95304128)))];
            tensor<fp16, [1, 188, 512]> linear_65_cast_fp16 = linear(bias = encoder_module_layers_7_feed_forward1_linear2_bias_to_fp16, weight = encoder_module_layers_7_feed_forward1_linear2_weight_to_fp16, x = input_397_cast_fp16)[name = tensor<string, []>("linear_65_cast_fp16")];
            tensor<fp16, []> var_1567_to_fp16 = const()[name = tensor<string, []>("op_1567_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 512]> var_1568_cast_fp16 = mul(x = linear_65_cast_fp16, y = var_1567_to_fp16)[name = tensor<string, []>("op_1568_cast_fp16")];
            tensor<fp16, [1, 188, 512]> input_403_cast_fp16 = add(x = input_391_cast_fp16, y = var_1568_cast_fp16)[name = tensor<string, []>("input_403_cast_fp16")];
            tensor<int32, [1]> query_15_axes_0 = const()[name = tensor<string, []>("query_15_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_7_norm_self_att_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_7_norm_self_att_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(95305216)))];
            tensor<fp16, [512]> encoder_module_layers_7_norm_self_att_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_7_norm_self_att_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(95306304)))];
            tensor<fp16, [1, 188, 512]> query_15_cast_fp16 = layer_norm(axes = query_15_axes_0, beta = encoder_module_layers_7_norm_self_att_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_7_norm_self_att_weight_to_fp16, x = input_403_cast_fp16)[name = tensor<string, []>("query_15_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_7_self_attn_linear_q_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_7_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(95307392)))];
            tensor<fp16, [512]> encoder_module_layers_7_self_attn_linear_q_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_7_self_attn_linear_q_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(95831744)))];
            tensor<fp16, [1, 188, 512]> linear_66_cast_fp16 = linear(bias = encoder_module_layers_7_self_attn_linear_q_bias_to_fp16, weight = encoder_module_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_1585 = const()[name = tensor<string, []>("op_1585"), val = tensor<int32, [4]>([1, -1, 8, 64])];
            tensor<fp16, [1, 188, 8, 64]> q_43_cast_fp16 = reshape(shape = var_1585, x = linear_66_cast_fp16)[name = tensor<string, []>("q_43_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_7_self_attn_linear_k_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_7_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(95832832)))];
            tensor<fp16, [512]> encoder_module_layers_7_self_attn_linear_k_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_7_self_attn_linear_k_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(96357184)))];
            tensor<fp16, [1, 188, 512]> linear_67_cast_fp16 = linear(bias = encoder_module_layers_7_self_attn_linear_k_bias_to_fp16, weight = encoder_module_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_1590 = const()[name = tensor<string, []>("op_1590"), val = tensor<int32, [4]>([1, -1, 8, 64])];
            tensor<fp16, [1, 188, 8, 64]> k_29_cast_fp16 = reshape(shape = var_1590, x = linear_67_cast_fp16)[name = tensor<string, []>("k_29_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_7_self_attn_linear_v_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_7_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(96358272)))];
            tensor<fp16, [512]> encoder_module_layers_7_self_attn_linear_v_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_7_self_attn_linear_v_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(96882624)))];
            tensor<fp16, [1, 188, 512]> linear_68_cast_fp16 = linear(bias = encoder_module_layers_7_self_attn_linear_v_bias_to_fp16, weight = encoder_module_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_1595 = const()[name = tensor<string, []>("op_1595"), val = tensor<int32, [4]>([1, -1, 8, 64])];
            tensor<fp16, [1, 188, 8, 64]> v_15_cast_fp16 = reshape(shape = var_1595, x = linear_68_cast_fp16)[name = tensor<string, []>("v_15_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, 64]> encoder_module_layers_7_self_attn_pos_bias_u_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_7_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(96883712)))];
            tensor<fp16, [1, 188, 8, 64]> var_1607_cast_fp16 = add(x = q_43_cast_fp16, y = encoder_module_layers_7_self_attn_pos_bias_u_to_fp16)[name = tensor<string, []>("op_1607_cast_fp16")];
            tensor<fp16, [8, 64]> encoder_module_layers_7_self_attn_pos_bias_v_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_7_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(96884800)))];
            tensor<fp16, [1, 188, 8, 64]> var_1609_cast_fp16 = add(x = q_43_cast_fp16, y = encoder_module_layers_7_self_attn_pos_bias_v_to_fp16)[name = tensor<string, []>("op_1609_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_177_transpose_x_0 = const()[name = tensor<string, []>("x_177_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_177_transpose_y_0 = const()[name = tensor<string, []>("x_177_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 64, 375]> var_1611_to_fp16 = const()[name = tensor<string, []>("op_1611_to_fp16"), val = tensor<fp16, [1, 8, 64, 375]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(96885888)))];
            tensor<fp16, [1, 8, 188, 64]> q_with_bias_v_15_cast_fp16 = transpose(perm = q_with_bias_v_15_perm_0, x = var_1609_cast_fp16)[name = tensor<string, []>("transpose_154")];
            tensor<fp16, [1, 8, 188, 375]> x_177_cast_fp16 = matmul(transpose_x = x_177_transpose_x_0, transpose_y = x_177_transpose_y_0, x = q_with_bias_v_15_cast_fp16, y = var_1611_to_fp16)[name = tensor<string, []>("x_177_cast_fp16")];
            tensor<int32, [8]> x_179_pad_0 = const()[name = tensor<string, []>("x_179_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            tensor<string, []> x_179_mode_0 = const()[name = tensor<string, []>("x_179_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_99_to_fp16 = const()[name = tensor<string, []>("const_99_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_179_cast_fp16 = pad(constant_val = const_99_to_fp16, mode = x_179_mode_0, pad = x_179_pad_0, x = x_177_cast_fp16)[name = tensor<string, []>("x_179_cast_fp16")];
            tensor<int32, [4]> var_1619 = const()[name = tensor<string, []>("op_1619"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_181_cast_fp16 = reshape(shape = var_1619, x = x_179_cast_fp16)[name = tensor<string, []>("x_181_cast_fp16")];
            tensor<int32, [4]> var_1623_begin_0 = const()[name = tensor<string, []>("op_1623_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_1623_end_0 = const()[name = tensor<string, []>("op_1623_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_1623_end_mask_0 = const()[name = tensor<string, []>("op_1623_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_1623_cast_fp16 = slice_by_index(begin = var_1623_begin_0, end = var_1623_end_0, end_mask = var_1623_end_mask_0, x = x_181_cast_fp16)[name = tensor<string, []>("op_1623_cast_fp16")];
            tensor<int32, [4]> var_1624 = const()[name = tensor<string, []>("op_1624"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_29_cast_fp16 = reshape(shape = var_1624, x = var_1623_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_65_perm_0 = const()[name = tensor<string, []>("transpose_65_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_66_perm_0 = const()[name = tensor<string, []>("transpose_66_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 64, 188]> transpose_66 = transpose(perm = transpose_66_perm_0, x = k_29_cast_fp16)[name = tensor<string, []>("transpose_152")];
            tensor<fp16, [1, 8, 188, 64]> transpose_65 = transpose(perm = transpose_65_perm_0, x = var_1607_cast_fp16)[name = tensor<string, []>("transpose_153")];
            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_65, y = transpose_66)[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_1633_cast_fp16 = add(x = matrix_ac_15_cast_fp16, y = matrix_bd_31_cast_fp16)[name = tensor<string, []>("op_1633_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, []>(0x1p-3)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_29_cast_fp16 = mul(x = var_1633_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_153_to_fp16, b = _inversed_scores_29_cast_fp16, cond = mask_7)[name = tensor<string, []>("scores_31_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_1639_cast_fp16 = softmax(axis = var_138, x = scores_31_cast_fp16)[name = tensor<string, []>("op_1639_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_405_cast_fp16 = select(a = var_154_to_fp16, b = var_1639_cast_fp16, cond = mask_7)[name = tensor<string, []>("input_405_cast_fp16")];
            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, 188, 64]> value_19_cast_fp16 = transpose(perm = value_19_perm_0, x = v_15_cast_fp16)[name = tensor<string, []>("transpose_155")];
            tensor<fp16, [1, 8, 188, 64]> x_183_cast_fp16 = matmul(transpose_x = x_183_transpose_x_0, transpose_y = x_183_transpose_y_0, x = input_405_cast_fp16, y = value_19_cast_fp16)[name = tensor<string, []>("x_183_cast_fp16")];
            tensor<int32, [4]> var_1643_perm_0 = const()[name = tensor<string, []>("op_1643_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1644 = const()[name = tensor<string, []>("op_1644"), val = tensor<int32, [3]>([1, -1, 512])];
            tensor<fp16, [1, 188, 8, 64]> var_1643_cast_fp16 = transpose(perm = var_1643_perm_0, x = x_183_cast_fp16)[name = tensor<string, []>("transpose_151")];
            tensor<fp16, [1, 188, 512]> input_407_cast_fp16 = reshape(shape = var_1644, x = var_1643_cast_fp16)[name = tensor<string, []>("input_407_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_7_self_attn_linear_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_7_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(97269952)))];
            tensor<fp16, [512]> encoder_module_layers_7_self_attn_linear_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_7_self_attn_linear_out_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(97794304)))];
            tensor<fp16, [1, 188, 512]> linear_70_cast_fp16 = linear(bias = encoder_module_layers_7_self_attn_linear_out_bias_to_fp16, weight = encoder_module_layers_7_self_attn_linear_out_weight_to_fp16, x = input_407_cast_fp16)[name = tensor<string, []>("linear_70_cast_fp16")];
            tensor<fp16, [1, 188, 512]> input_411_cast_fp16 = add(x = input_403_cast_fp16, y = linear_70_cast_fp16)[name = tensor<string, []>("input_411_cast_fp16")];
            tensor<int32, [1]> x_187_axes_0 = const()[name = tensor<string, []>("x_187_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_7_norm_conv_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_7_norm_conv_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(97795392)))];
            tensor<fp16, [512]> encoder_module_layers_7_norm_conv_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_7_norm_conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(97796480)))];
            tensor<fp16, [1, 188, 512]> x_187_cast_fp16 = layer_norm(axes = x_187_axes_0, beta = encoder_module_layers_7_norm_conv_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_7_norm_conv_weight_to_fp16, x = input_411_cast_fp16)[name = tensor<string, []>("x_187_cast_fp16")];
            tensor<int32, [3]> input_413_perm_0 = const()[name = tensor<string, []>("input_413_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> input_415_pad_type_0 = const()[name = tensor<string, []>("input_415_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_415_strides_0 = const()[name = tensor<string, []>("input_415_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_415_pad_0 = const()[name = tensor<string, []>("input_415_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_415_dilations_0 = const()[name = tensor<string, []>("input_415_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_415_groups_0 = const()[name = tensor<string, []>("input_415_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1024, 512, 1]> encoder_module_layers_7_conv_pointwise_conv1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_7_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [1024, 512, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(97797568)))];
            tensor<fp16, [1024]> encoder_module_layers_7_conv_pointwise_conv1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_7_conv_pointwise_conv1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(98846208)))];
            tensor<fp16, [1, 512, 188]> input_413_cast_fp16 = transpose(perm = input_413_perm_0, x = x_187_cast_fp16)[name = tensor<string, []>("transpose_150")];
            tensor<fp16, [1, 1024, 188]> input_415_cast_fp16 = conv(bias = encoder_module_layers_7_conv_pointwise_conv1_bias_to_fp16, dilations = input_415_dilations_0, groups = input_415_groups_0, pad = input_415_pad_0, pad_type = input_415_pad_type_0, strides = input_415_strides_0, weight = encoder_module_layers_7_conv_pointwise_conv1_weight_to_fp16, x = input_413_cast_fp16)[name = tensor<string, []>("input_415_cast_fp16")];
            tensor<int32, []> x_189_split_num_splits_0 = const()[name = tensor<string, []>("x_189_split_num_splits_0"), val = tensor<int32, []>(2)];
            tensor<int32, []> x_189_split_axis_0 = const()[name = tensor<string, []>("x_189_split_axis_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1, 512, 188]> x_189_split_cast_fp16_0, tensor<fp16, [1, 512, 188]> x_189_split_cast_fp16_1 = split(axis = x_189_split_axis_0, num_splits = x_189_split_num_splits_0, x = input_415_cast_fp16)[name = tensor<string, []>("x_189_split_cast_fp16")];
            tensor<fp16, [1, 512, 188]> x_189_split_1_sigmoid_cast_fp16 = sigmoid(x = x_189_split_cast_fp16_1)[name = tensor<string, []>("x_189_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 512, 188]> x_189_cast_fp16 = mul(x = x_189_split_cast_fp16_0, y = x_189_split_1_sigmoid_cast_fp16)[name = tensor<string, []>("x_189_cast_fp16")];
            tensor<fp16, [1, 512, 188]> input_417_cast_fp16 = select(a = var_154_to_fp16, b = x_189_cast_fp16, cond = var_450)[name = tensor<string, []>("input_417_cast_fp16")];
            tensor<int32, [6]> input_419_pad_0 = const()[name = tensor<string, []>("input_419_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            tensor<string, []> input_419_mode_0 = const()[name = tensor<string, []>("input_419_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_102_to_fp16 = const()[name = tensor<string, []>("const_102_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 512, 196]> input_419_cast_fp16 = pad(constant_val = const_102_to_fp16, mode = input_419_mode_0, pad = input_419_pad_0, x = input_417_cast_fp16)[name = tensor<string, []>("input_419_cast_fp16")];
            tensor<string, []> input_421_pad_type_0 = const()[name = tensor<string, []>("input_421_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, []> input_421_groups_0 = const()[name = tensor<string, []>("input_421_groups_0"), val = tensor<int32, []>(512)];
            tensor<int32, [1]> input_421_strides_0 = const()[name = tensor<string, []>("input_421_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_421_pad_0 = const()[name = tensor<string, []>("input_421_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_421_dilations_0 = const()[name = tensor<string, []>("input_421_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 9]> const_207_to_fp16 = const()[name = tensor<string, []>("const_207_to_fp16"), val = tensor<fp16, [512, 1, 9]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(98848320)))];
            tensor<fp16, [512]> const_208_to_fp16 = const()[name = tensor<string, []>("const_208_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(98857600)))];
            tensor<fp16, [1, 512, 188]> input_423_cast_fp16 = conv(bias = const_208_to_fp16, dilations = input_421_dilations_0, groups = input_421_groups_0, pad = input_421_pad_0, pad_type = input_421_pad_type_0, strides = input_421_strides_0, weight = const_207_to_fp16, x = input_419_cast_fp16)[name = tensor<string, []>("input_423_cast_fp16")];
            tensor<fp16, [1, 512, 188]> input_425_cast_fp16 = silu(x = input_423_cast_fp16)[name = tensor<string, []>("input_425_cast_fp16")];
            tensor<string, []> x_191_pad_type_0 = const()[name = tensor<string, []>("x_191_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> x_191_strides_0 = const()[name = tensor<string, []>("x_191_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_191_pad_0 = const()[name = tensor<string, []>("x_191_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_191_dilations_0 = const()[name = tensor<string, []>("x_191_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> x_191_groups_0 = const()[name = tensor<string, []>("x_191_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [512, 512, 1]> encoder_module_layers_7_conv_pointwise_conv2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_7_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [512, 512, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(98858688)))];
            tensor<fp16, [512]> encoder_module_layers_7_conv_pointwise_conv2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_7_conv_pointwise_conv2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(99383040)))];
            tensor<fp16, [1, 512, 188]> x_191_cast_fp16 = conv(bias = encoder_module_layers_7_conv_pointwise_conv2_bias_to_fp16, dilations = x_191_dilations_0, groups = x_191_groups_0, pad = x_191_pad_0, pad_type = x_191_pad_type_0, strides = x_191_strides_0, weight = encoder_module_layers_7_conv_pointwise_conv2_weight_to_fp16, x = input_425_cast_fp16)[name = tensor<string, []>("x_191_cast_fp16")];
            tensor<int32, [3]> input_427_perm_0 = const()[name = tensor<string, []>("input_427_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 512]> input_427_cast_fp16 = transpose(perm = input_427_perm_0, x = x_191_cast_fp16)[name = tensor<string, []>("transpose_149")];
            tensor<fp16, [1, 188, 512]> input_429_cast_fp16 = add(x = input_411_cast_fp16, y = input_427_cast_fp16)[name = tensor<string, []>("input_429_cast_fp16")];
            tensor<int32, [1]> input_431_axes_0 = const()[name = tensor<string, []>("input_431_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_7_norm_feed_forward2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_7_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(99384128)))];
            tensor<fp16, [512]> encoder_module_layers_7_norm_feed_forward2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_7_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(99385216)))];
            tensor<fp16, [1, 188, 512]> input_431_cast_fp16 = layer_norm(axes = input_431_axes_0, beta = encoder_module_layers_7_norm_feed_forward2_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_7_norm_feed_forward2_weight_to_fp16, x = input_429_cast_fp16)[name = tensor<string, []>("input_431_cast_fp16")];
            tensor<fp16, [2048, 512]> encoder_module_layers_7_feed_forward2_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_7_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [2048, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(99386304)))];
            tensor<fp16, [2048]> encoder_module_layers_7_feed_forward2_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_7_feed_forward2_linear1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(101483520)))];
            tensor<fp16, [1, 188, 2048]> linear_71_cast_fp16 = linear(bias = encoder_module_layers_7_feed_forward2_linear1_bias_to_fp16, weight = encoder_module_layers_7_feed_forward2_linear1_weight_to_fp16, x = input_431_cast_fp16)[name = tensor<string, []>("linear_71_cast_fp16")];
            tensor<fp16, [1, 188, 2048]> input_435_cast_fp16 = silu(x = linear_71_cast_fp16)[name = tensor<string, []>("input_435_cast_fp16")];
            tensor<fp16, [512, 2048]> encoder_module_layers_7_feed_forward2_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_7_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [512, 2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(101487680)))];
            tensor<fp16, [512]> encoder_module_layers_7_feed_forward2_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_7_feed_forward2_linear2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(103584896)))];
            tensor<fp16, [1, 188, 512]> linear_72_cast_fp16 = linear(bias = encoder_module_layers_7_feed_forward2_linear2_bias_to_fp16, weight = encoder_module_layers_7_feed_forward2_linear2_weight_to_fp16, x = input_435_cast_fp16)[name = tensor<string, []>("linear_72_cast_fp16")];
            tensor<fp16, []> var_1710_to_fp16 = const()[name = tensor<string, []>("op_1710_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 512]> var_1711_cast_fp16 = mul(x = linear_72_cast_fp16, y = var_1710_to_fp16)[name = tensor<string, []>("op_1711_cast_fp16")];
            tensor<fp16, [1, 188, 512]> input_441_cast_fp16 = add(x = input_429_cast_fp16, y = var_1711_cast_fp16)[name = tensor<string, []>("input_441_cast_fp16")];
            tensor<int32, [1]> input_443_axes_0 = const()[name = tensor<string, []>("input_443_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_7_norm_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_7_norm_out_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(103585984)))];
            tensor<fp16, [512]> encoder_module_layers_7_norm_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_7_norm_out_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(103587072)))];
            tensor<fp16, [1, 188, 512]> input_443_cast_fp16 = layer_norm(axes = input_443_axes_0, beta = encoder_module_layers_7_norm_out_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_7_norm_out_weight_to_fp16, x = input_441_cast_fp16)[name = tensor<string, []>("input_443_cast_fp16")];
            tensor<int32, [1]> input_445_axes_0 = const()[name = tensor<string, []>("input_445_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_8_norm_feed_forward1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_8_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(103588160)))];
            tensor<fp16, [512]> encoder_module_layers_8_norm_feed_forward1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_8_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(103589248)))];
            tensor<fp16, [1, 188, 512]> input_445_cast_fp16 = layer_norm(axes = input_445_axes_0, beta = encoder_module_layers_8_norm_feed_forward1_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_8_norm_feed_forward1_weight_to_fp16, x = input_443_cast_fp16)[name = tensor<string, []>("input_445_cast_fp16")];
            tensor<fp16, [2048, 512]> encoder_module_layers_8_feed_forward1_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_8_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [2048, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(103590336)))];
            tensor<fp16, [2048]> encoder_module_layers_8_feed_forward1_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_8_feed_forward1_linear1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(105687552)))];
            tensor<fp16, [1, 188, 2048]> linear_73_cast_fp16 = linear(bias = encoder_module_layers_8_feed_forward1_linear1_bias_to_fp16, weight = encoder_module_layers_8_feed_forward1_linear1_weight_to_fp16, x = input_445_cast_fp16)[name = tensor<string, []>("linear_73_cast_fp16")];
            tensor<fp16, [1, 188, 2048]> input_449_cast_fp16 = silu(x = linear_73_cast_fp16)[name = tensor<string, []>("input_449_cast_fp16")];
            tensor<fp16, [512, 2048]> encoder_module_layers_8_feed_forward1_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_8_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [512, 2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(105691712)))];
            tensor<fp16, [512]> encoder_module_layers_8_feed_forward1_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_8_feed_forward1_linear2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(107788928)))];
            tensor<fp16, [1, 188, 512]> linear_74_cast_fp16 = linear(bias = encoder_module_layers_8_feed_forward1_linear2_bias_to_fp16, weight = encoder_module_layers_8_feed_forward1_linear2_weight_to_fp16, x = input_449_cast_fp16)[name = tensor<string, []>("linear_74_cast_fp16")];
            tensor<fp16, []> var_1741_to_fp16 = const()[name = tensor<string, []>("op_1741_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 512]> var_1742_cast_fp16 = mul(x = linear_74_cast_fp16, y = var_1741_to_fp16)[name = tensor<string, []>("op_1742_cast_fp16")];
            tensor<fp16, [1, 188, 512]> input_455_cast_fp16 = add(x = input_443_cast_fp16, y = var_1742_cast_fp16)[name = tensor<string, []>("input_455_cast_fp16")];
            tensor<int32, [1]> query_17_axes_0 = const()[name = tensor<string, []>("query_17_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_8_norm_self_att_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_8_norm_self_att_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(107790016)))];
            tensor<fp16, [512]> encoder_module_layers_8_norm_self_att_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_8_norm_self_att_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(107791104)))];
            tensor<fp16, [1, 188, 512]> query_17_cast_fp16 = layer_norm(axes = query_17_axes_0, beta = encoder_module_layers_8_norm_self_att_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_8_norm_self_att_weight_to_fp16, x = input_455_cast_fp16)[name = tensor<string, []>("query_17_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_8_self_attn_linear_q_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_8_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(107792192)))];
            tensor<fp16, [512]> encoder_module_layers_8_self_attn_linear_q_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_8_self_attn_linear_q_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(108316544)))];
            tensor<fp16, [1, 188, 512]> linear_75_cast_fp16 = linear(bias = encoder_module_layers_8_self_attn_linear_q_bias_to_fp16, weight = encoder_module_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_1759 = const()[name = tensor<string, []>("op_1759"), val = tensor<int32, [4]>([1, -1, 8, 64])];
            tensor<fp16, [1, 188, 8, 64]> q_49_cast_fp16 = reshape(shape = var_1759, x = linear_75_cast_fp16)[name = tensor<string, []>("q_49_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_8_self_attn_linear_k_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_8_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(108317632)))];
            tensor<fp16, [512]> encoder_module_layers_8_self_attn_linear_k_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_8_self_attn_linear_k_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(108841984)))];
            tensor<fp16, [1, 188, 512]> linear_76_cast_fp16 = linear(bias = encoder_module_layers_8_self_attn_linear_k_bias_to_fp16, weight = encoder_module_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_1764 = const()[name = tensor<string, []>("op_1764"), val = tensor<int32, [4]>([1, -1, 8, 64])];
            tensor<fp16, [1, 188, 8, 64]> k_33_cast_fp16 = reshape(shape = var_1764, x = linear_76_cast_fp16)[name = tensor<string, []>("k_33_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_8_self_attn_linear_v_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_8_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(108843072)))];
            tensor<fp16, [512]> encoder_module_layers_8_self_attn_linear_v_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_8_self_attn_linear_v_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(109367424)))];
            tensor<fp16, [1, 188, 512]> linear_77_cast_fp16 = linear(bias = encoder_module_layers_8_self_attn_linear_v_bias_to_fp16, weight = encoder_module_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_1769 = const()[name = tensor<string, []>("op_1769"), val = tensor<int32, [4]>([1, -1, 8, 64])];
            tensor<fp16, [1, 188, 8, 64]> v_17_cast_fp16 = reshape(shape = var_1769, x = linear_77_cast_fp16)[name = tensor<string, []>("v_17_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, 64]> encoder_module_layers_8_self_attn_pos_bias_u_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_8_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(109368512)))];
            tensor<fp16, [1, 188, 8, 64]> var_1781_cast_fp16 = add(x = q_49_cast_fp16, y = encoder_module_layers_8_self_attn_pos_bias_u_to_fp16)[name = tensor<string, []>("op_1781_cast_fp16")];
            tensor<fp16, [8, 64]> encoder_module_layers_8_self_attn_pos_bias_v_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_8_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(109369600)))];
            tensor<fp16, [1, 188, 8, 64]> var_1783_cast_fp16 = add(x = q_49_cast_fp16, y = encoder_module_layers_8_self_attn_pos_bias_v_to_fp16)[name = tensor<string, []>("op_1783_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_199_transpose_x_0 = const()[name = tensor<string, []>("x_199_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_199_transpose_y_0 = const()[name = tensor<string, []>("x_199_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 64, 375]> var_1785_to_fp16 = const()[name = tensor<string, []>("op_1785_to_fp16"), val = tensor<fp16, [1, 8, 64, 375]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(109370688)))];
            tensor<fp16, [1, 8, 188, 64]> q_with_bias_v_17_cast_fp16 = transpose(perm = q_with_bias_v_17_perm_0, x = var_1783_cast_fp16)[name = tensor<string, []>("transpose_147")];
            tensor<fp16, [1, 8, 188, 375]> x_199_cast_fp16 = matmul(transpose_x = x_199_transpose_x_0, transpose_y = x_199_transpose_y_0, x = q_with_bias_v_17_cast_fp16, y = var_1785_to_fp16)[name = tensor<string, []>("x_199_cast_fp16")];
            tensor<int32, [8]> x_201_pad_0 = const()[name = tensor<string, []>("x_201_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            tensor<string, []> x_201_mode_0 = const()[name = tensor<string, []>("x_201_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_109_to_fp16 = const()[name = tensor<string, []>("const_109_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_201_cast_fp16 = pad(constant_val = const_109_to_fp16, mode = x_201_mode_0, pad = x_201_pad_0, x = x_199_cast_fp16)[name = tensor<string, []>("x_201_cast_fp16")];
            tensor<int32, [4]> var_1793 = const()[name = tensor<string, []>("op_1793"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_203_cast_fp16 = reshape(shape = var_1793, x = x_201_cast_fp16)[name = tensor<string, []>("x_203_cast_fp16")];
            tensor<int32, [4]> var_1797_begin_0 = const()[name = tensor<string, []>("op_1797_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_1797_end_0 = const()[name = tensor<string, []>("op_1797_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_1797_end_mask_0 = const()[name = tensor<string, []>("op_1797_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_1797_cast_fp16 = slice_by_index(begin = var_1797_begin_0, end = var_1797_end_0, end_mask = var_1797_end_mask_0, x = x_203_cast_fp16)[name = tensor<string, []>("op_1797_cast_fp16")];
            tensor<int32, [4]> var_1798 = const()[name = tensor<string, []>("op_1798"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_33_cast_fp16 = reshape(shape = var_1798, x = var_1797_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_67_perm_0 = const()[name = tensor<string, []>("transpose_67_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_68_perm_0 = const()[name = tensor<string, []>("transpose_68_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 64, 188]> transpose_68 = transpose(perm = transpose_68_perm_0, x = k_33_cast_fp16)[name = tensor<string, []>("transpose_145")];
            tensor<fp16, [1, 8, 188, 64]> transpose_67 = transpose(perm = transpose_67_perm_0, x = var_1781_cast_fp16)[name = tensor<string, []>("transpose_146")];
            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_67, y = transpose_68)[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_1807_cast_fp16 = add(x = matrix_ac_17_cast_fp16, y = matrix_bd_35_cast_fp16)[name = tensor<string, []>("op_1807_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, []>(0x1p-3)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_33_cast_fp16 = mul(x = var_1807_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_153_to_fp16, b = _inversed_scores_33_cast_fp16, cond = mask_7)[name = tensor<string, []>("scores_35_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_1813_cast_fp16 = softmax(axis = var_138, x = scores_35_cast_fp16)[name = tensor<string, []>("op_1813_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_457_cast_fp16 = select(a = var_154_to_fp16, b = var_1813_cast_fp16, cond = mask_7)[name = tensor<string, []>("input_457_cast_fp16")];
            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, 188, 64]> value_21_cast_fp16 = transpose(perm = value_21_perm_0, x = v_17_cast_fp16)[name = tensor<string, []>("transpose_148")];
            tensor<fp16, [1, 8, 188, 64]> x_205_cast_fp16 = matmul(transpose_x = x_205_transpose_x_0, transpose_y = x_205_transpose_y_0, x = input_457_cast_fp16, y = value_21_cast_fp16)[name = tensor<string, []>("x_205_cast_fp16")];
            tensor<int32, [4]> var_1817_perm_0 = const()[name = tensor<string, []>("op_1817_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1818 = const()[name = tensor<string, []>("op_1818"), val = tensor<int32, [3]>([1, -1, 512])];
            tensor<fp16, [1, 188, 8, 64]> var_1817_cast_fp16 = transpose(perm = var_1817_perm_0, x = x_205_cast_fp16)[name = tensor<string, []>("transpose_144")];
            tensor<fp16, [1, 188, 512]> input_459_cast_fp16 = reshape(shape = var_1818, x = var_1817_cast_fp16)[name = tensor<string, []>("input_459_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_8_self_attn_linear_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_8_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(109754752)))];
            tensor<fp16, [512]> encoder_module_layers_8_self_attn_linear_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_8_self_attn_linear_out_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(110279104)))];
            tensor<fp16, [1, 188, 512]> linear_79_cast_fp16 = linear(bias = encoder_module_layers_8_self_attn_linear_out_bias_to_fp16, weight = encoder_module_layers_8_self_attn_linear_out_weight_to_fp16, x = input_459_cast_fp16)[name = tensor<string, []>("linear_79_cast_fp16")];
            tensor<fp16, [1, 188, 512]> input_463_cast_fp16 = add(x = input_455_cast_fp16, y = linear_79_cast_fp16)[name = tensor<string, []>("input_463_cast_fp16")];
            tensor<int32, [1]> x_209_axes_0 = const()[name = tensor<string, []>("x_209_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_8_norm_conv_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_8_norm_conv_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(110280192)))];
            tensor<fp16, [512]> encoder_module_layers_8_norm_conv_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_8_norm_conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(110281280)))];
            tensor<fp16, [1, 188, 512]> x_209_cast_fp16 = layer_norm(axes = x_209_axes_0, beta = encoder_module_layers_8_norm_conv_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_8_norm_conv_weight_to_fp16, x = input_463_cast_fp16)[name = tensor<string, []>("x_209_cast_fp16")];
            tensor<int32, [3]> input_465_perm_0 = const()[name = tensor<string, []>("input_465_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> input_467_pad_type_0 = const()[name = tensor<string, []>("input_467_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_467_strides_0 = const()[name = tensor<string, []>("input_467_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_467_pad_0 = const()[name = tensor<string, []>("input_467_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_467_dilations_0 = const()[name = tensor<string, []>("input_467_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_467_groups_0 = const()[name = tensor<string, []>("input_467_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1024, 512, 1]> encoder_module_layers_8_conv_pointwise_conv1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_8_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [1024, 512, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(110282368)))];
            tensor<fp16, [1024]> encoder_module_layers_8_conv_pointwise_conv1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_8_conv_pointwise_conv1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(111331008)))];
            tensor<fp16, [1, 512, 188]> input_465_cast_fp16 = transpose(perm = input_465_perm_0, x = x_209_cast_fp16)[name = tensor<string, []>("transpose_143")];
            tensor<fp16, [1, 1024, 188]> input_467_cast_fp16 = conv(bias = encoder_module_layers_8_conv_pointwise_conv1_bias_to_fp16, dilations = input_467_dilations_0, groups = input_467_groups_0, pad = input_467_pad_0, pad_type = input_467_pad_type_0, strides = input_467_strides_0, weight = encoder_module_layers_8_conv_pointwise_conv1_weight_to_fp16, x = input_465_cast_fp16)[name = tensor<string, []>("input_467_cast_fp16")];
            tensor<int32, []> x_211_split_num_splits_0 = const()[name = tensor<string, []>("x_211_split_num_splits_0"), val = tensor<int32, []>(2)];
            tensor<int32, []> x_211_split_axis_0 = const()[name = tensor<string, []>("x_211_split_axis_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1, 512, 188]> x_211_split_cast_fp16_0, tensor<fp16, [1, 512, 188]> x_211_split_cast_fp16_1 = split(axis = x_211_split_axis_0, num_splits = x_211_split_num_splits_0, x = input_467_cast_fp16)[name = tensor<string, []>("x_211_split_cast_fp16")];
            tensor<fp16, [1, 512, 188]> x_211_split_1_sigmoid_cast_fp16 = sigmoid(x = x_211_split_cast_fp16_1)[name = tensor<string, []>("x_211_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 512, 188]> x_211_cast_fp16 = mul(x = x_211_split_cast_fp16_0, y = x_211_split_1_sigmoid_cast_fp16)[name = tensor<string, []>("x_211_cast_fp16")];
            tensor<fp16, [1, 512, 188]> input_469_cast_fp16 = select(a = var_154_to_fp16, b = x_211_cast_fp16, cond = var_450)[name = tensor<string, []>("input_469_cast_fp16")];
            tensor<int32, [6]> input_471_pad_0 = const()[name = tensor<string, []>("input_471_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            tensor<string, []> input_471_mode_0 = const()[name = tensor<string, []>("input_471_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_112_to_fp16 = const()[name = tensor<string, []>("const_112_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 512, 196]> input_471_cast_fp16 = pad(constant_val = const_112_to_fp16, mode = input_471_mode_0, pad = input_471_pad_0, x = input_469_cast_fp16)[name = tensor<string, []>("input_471_cast_fp16")];
            tensor<string, []> input_473_pad_type_0 = const()[name = tensor<string, []>("input_473_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, []> input_473_groups_0 = const()[name = tensor<string, []>("input_473_groups_0"), val = tensor<int32, []>(512)];
            tensor<int32, [1]> input_473_strides_0 = const()[name = tensor<string, []>("input_473_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_473_pad_0 = const()[name = tensor<string, []>("input_473_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_473_dilations_0 = const()[name = tensor<string, []>("input_473_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 9]> const_209_to_fp16 = const()[name = tensor<string, []>("const_209_to_fp16"), val = tensor<fp16, [512, 1, 9]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(111333120)))];
            tensor<fp16, [512]> const_210_to_fp16 = const()[name = tensor<string, []>("const_210_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(111342400)))];
            tensor<fp16, [1, 512, 188]> input_475_cast_fp16 = conv(bias = const_210_to_fp16, dilations = input_473_dilations_0, groups = input_473_groups_0, pad = input_473_pad_0, pad_type = input_473_pad_type_0, strides = input_473_strides_0, weight = const_209_to_fp16, x = input_471_cast_fp16)[name = tensor<string, []>("input_475_cast_fp16")];
            tensor<fp16, [1, 512, 188]> input_477_cast_fp16 = silu(x = input_475_cast_fp16)[name = tensor<string, []>("input_477_cast_fp16")];
            tensor<string, []> x_213_pad_type_0 = const()[name = tensor<string, []>("x_213_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> x_213_strides_0 = const()[name = tensor<string, []>("x_213_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_213_pad_0 = const()[name = tensor<string, []>("x_213_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_213_dilations_0 = const()[name = tensor<string, []>("x_213_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> x_213_groups_0 = const()[name = tensor<string, []>("x_213_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [512, 512, 1]> encoder_module_layers_8_conv_pointwise_conv2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_8_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [512, 512, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(111343488)))];
            tensor<fp16, [512]> encoder_module_layers_8_conv_pointwise_conv2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_8_conv_pointwise_conv2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(111867840)))];
            tensor<fp16, [1, 512, 188]> x_213_cast_fp16 = conv(bias = encoder_module_layers_8_conv_pointwise_conv2_bias_to_fp16, dilations = x_213_dilations_0, groups = x_213_groups_0, pad = x_213_pad_0, pad_type = x_213_pad_type_0, strides = x_213_strides_0, weight = encoder_module_layers_8_conv_pointwise_conv2_weight_to_fp16, x = input_477_cast_fp16)[name = tensor<string, []>("x_213_cast_fp16")];
            tensor<int32, [3]> input_479_perm_0 = const()[name = tensor<string, []>("input_479_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 512]> input_479_cast_fp16 = transpose(perm = input_479_perm_0, x = x_213_cast_fp16)[name = tensor<string, []>("transpose_142")];
            tensor<fp16, [1, 188, 512]> input_481_cast_fp16 = add(x = input_463_cast_fp16, y = input_479_cast_fp16)[name = tensor<string, []>("input_481_cast_fp16")];
            tensor<int32, [1]> input_483_axes_0 = const()[name = tensor<string, []>("input_483_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_8_norm_feed_forward2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_8_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(111868928)))];
            tensor<fp16, [512]> encoder_module_layers_8_norm_feed_forward2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_8_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(111870016)))];
            tensor<fp16, [1, 188, 512]> input_483_cast_fp16 = layer_norm(axes = input_483_axes_0, beta = encoder_module_layers_8_norm_feed_forward2_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_8_norm_feed_forward2_weight_to_fp16, x = input_481_cast_fp16)[name = tensor<string, []>("input_483_cast_fp16")];
            tensor<fp16, [2048, 512]> encoder_module_layers_8_feed_forward2_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_8_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [2048, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(111871104)))];
            tensor<fp16, [2048]> encoder_module_layers_8_feed_forward2_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_8_feed_forward2_linear1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(113968320)))];
            tensor<fp16, [1, 188, 2048]> linear_80_cast_fp16 = linear(bias = encoder_module_layers_8_feed_forward2_linear1_bias_to_fp16, weight = encoder_module_layers_8_feed_forward2_linear1_weight_to_fp16, x = input_483_cast_fp16)[name = tensor<string, []>("linear_80_cast_fp16")];
            tensor<fp16, [1, 188, 2048]> input_487_cast_fp16 = silu(x = linear_80_cast_fp16)[name = tensor<string, []>("input_487_cast_fp16")];
            tensor<fp16, [512, 2048]> encoder_module_layers_8_feed_forward2_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_8_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [512, 2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(113972480)))];
            tensor<fp16, [512]> encoder_module_layers_8_feed_forward2_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_8_feed_forward2_linear2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(116069696)))];
            tensor<fp16, [1, 188, 512]> linear_81_cast_fp16 = linear(bias = encoder_module_layers_8_feed_forward2_linear2_bias_to_fp16, weight = encoder_module_layers_8_feed_forward2_linear2_weight_to_fp16, x = input_487_cast_fp16)[name = tensor<string, []>("linear_81_cast_fp16")];
            tensor<fp16, []> var_1884_to_fp16 = const()[name = tensor<string, []>("op_1884_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 512]> var_1885_cast_fp16 = mul(x = linear_81_cast_fp16, y = var_1884_to_fp16)[name = tensor<string, []>("op_1885_cast_fp16")];
            tensor<fp16, [1, 188, 512]> input_493_cast_fp16 = add(x = input_481_cast_fp16, y = var_1885_cast_fp16)[name = tensor<string, []>("input_493_cast_fp16")];
            tensor<int32, [1]> input_495_axes_0 = const()[name = tensor<string, []>("input_495_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_8_norm_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_8_norm_out_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(116070784)))];
            tensor<fp16, [512]> encoder_module_layers_8_norm_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_8_norm_out_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(116071872)))];
            tensor<fp16, [1, 188, 512]> input_495_cast_fp16 = layer_norm(axes = input_495_axes_0, beta = encoder_module_layers_8_norm_out_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_8_norm_out_weight_to_fp16, x = input_493_cast_fp16)[name = tensor<string, []>("input_495_cast_fp16")];
            tensor<int32, [1]> input_497_axes_0 = const()[name = tensor<string, []>("input_497_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_9_norm_feed_forward1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_9_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(116072960)))];
            tensor<fp16, [512]> encoder_module_layers_9_norm_feed_forward1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_9_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(116074048)))];
            tensor<fp16, [1, 188, 512]> input_497_cast_fp16 = layer_norm(axes = input_497_axes_0, beta = encoder_module_layers_9_norm_feed_forward1_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_9_norm_feed_forward1_weight_to_fp16, x = input_495_cast_fp16)[name = tensor<string, []>("input_497_cast_fp16")];
            tensor<fp16, [2048, 512]> encoder_module_layers_9_feed_forward1_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_9_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [2048, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(116075136)))];
            tensor<fp16, [2048]> encoder_module_layers_9_feed_forward1_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_9_feed_forward1_linear1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(118172352)))];
            tensor<fp16, [1, 188, 2048]> linear_82_cast_fp16 = linear(bias = encoder_module_layers_9_feed_forward1_linear1_bias_to_fp16, weight = encoder_module_layers_9_feed_forward1_linear1_weight_to_fp16, x = input_497_cast_fp16)[name = tensor<string, []>("linear_82_cast_fp16")];
            tensor<fp16, [1, 188, 2048]> input_501_cast_fp16 = silu(x = linear_82_cast_fp16)[name = tensor<string, []>("input_501_cast_fp16")];
            tensor<fp16, [512, 2048]> encoder_module_layers_9_feed_forward1_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_9_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [512, 2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(118176512)))];
            tensor<fp16, [512]> encoder_module_layers_9_feed_forward1_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_9_feed_forward1_linear2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(120273728)))];
            tensor<fp16, [1, 188, 512]> linear_83_cast_fp16 = linear(bias = encoder_module_layers_9_feed_forward1_linear2_bias_to_fp16, weight = encoder_module_layers_9_feed_forward1_linear2_weight_to_fp16, x = input_501_cast_fp16)[name = tensor<string, []>("linear_83_cast_fp16")];
            tensor<fp16, []> var_1915_to_fp16 = const()[name = tensor<string, []>("op_1915_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 512]> var_1916_cast_fp16 = mul(x = linear_83_cast_fp16, y = var_1915_to_fp16)[name = tensor<string, []>("op_1916_cast_fp16")];
            tensor<fp16, [1, 188, 512]> input_507_cast_fp16 = add(x = input_495_cast_fp16, y = var_1916_cast_fp16)[name = tensor<string, []>("input_507_cast_fp16")];
            tensor<int32, [1]> query_19_axes_0 = const()[name = tensor<string, []>("query_19_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_9_norm_self_att_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_9_norm_self_att_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(120274816)))];
            tensor<fp16, [512]> encoder_module_layers_9_norm_self_att_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_9_norm_self_att_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(120275904)))];
            tensor<fp16, [1, 188, 512]> query_19_cast_fp16 = layer_norm(axes = query_19_axes_0, beta = encoder_module_layers_9_norm_self_att_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_9_norm_self_att_weight_to_fp16, x = input_507_cast_fp16)[name = tensor<string, []>("query_19_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_9_self_attn_linear_q_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_9_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(120276992)))];
            tensor<fp16, [512]> encoder_module_layers_9_self_attn_linear_q_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_9_self_attn_linear_q_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(120801344)))];
            tensor<fp16, [1, 188, 512]> linear_84_cast_fp16 = linear(bias = encoder_module_layers_9_self_attn_linear_q_bias_to_fp16, weight = encoder_module_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_1933 = const()[name = tensor<string, []>("op_1933"), val = tensor<int32, [4]>([1, -1, 8, 64])];
            tensor<fp16, [1, 188, 8, 64]> q_55_cast_fp16 = reshape(shape = var_1933, x = linear_84_cast_fp16)[name = tensor<string, []>("q_55_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_9_self_attn_linear_k_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_9_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(120802432)))];
            tensor<fp16, [512]> encoder_module_layers_9_self_attn_linear_k_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_9_self_attn_linear_k_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(121326784)))];
            tensor<fp16, [1, 188, 512]> linear_85_cast_fp16 = linear(bias = encoder_module_layers_9_self_attn_linear_k_bias_to_fp16, weight = encoder_module_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_1938 = const()[name = tensor<string, []>("op_1938"), val = tensor<int32, [4]>([1, -1, 8, 64])];
            tensor<fp16, [1, 188, 8, 64]> k_37_cast_fp16 = reshape(shape = var_1938, x = linear_85_cast_fp16)[name = tensor<string, []>("k_37_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_9_self_attn_linear_v_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_9_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(121327872)))];
            tensor<fp16, [512]> encoder_module_layers_9_self_attn_linear_v_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_9_self_attn_linear_v_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(121852224)))];
            tensor<fp16, [1, 188, 512]> linear_86_cast_fp16 = linear(bias = encoder_module_layers_9_self_attn_linear_v_bias_to_fp16, weight = encoder_module_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_1943 = const()[name = tensor<string, []>("op_1943"), val = tensor<int32, [4]>([1, -1, 8, 64])];
            tensor<fp16, [1, 188, 8, 64]> v_19_cast_fp16 = reshape(shape = var_1943, x = linear_86_cast_fp16)[name = tensor<string, []>("v_19_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, 64]> encoder_module_layers_9_self_attn_pos_bias_u_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_9_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(121853312)))];
            tensor<fp16, [1, 188, 8, 64]> var_1955_cast_fp16 = add(x = q_55_cast_fp16, y = encoder_module_layers_9_self_attn_pos_bias_u_to_fp16)[name = tensor<string, []>("op_1955_cast_fp16")];
            tensor<fp16, [8, 64]> encoder_module_layers_9_self_attn_pos_bias_v_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_9_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(121854400)))];
            tensor<fp16, [1, 188, 8, 64]> var_1957_cast_fp16 = add(x = q_55_cast_fp16, y = encoder_module_layers_9_self_attn_pos_bias_v_to_fp16)[name = tensor<string, []>("op_1957_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_221_transpose_x_0 = const()[name = tensor<string, []>("x_221_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_221_transpose_y_0 = const()[name = tensor<string, []>("x_221_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 64, 375]> var_1959_to_fp16 = const()[name = tensor<string, []>("op_1959_to_fp16"), val = tensor<fp16, [1, 8, 64, 375]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(121855488)))];
            tensor<fp16, [1, 8, 188, 64]> q_with_bias_v_19_cast_fp16 = transpose(perm = q_with_bias_v_19_perm_0, x = var_1957_cast_fp16)[name = tensor<string, []>("transpose_140")];
            tensor<fp16, [1, 8, 188, 375]> x_221_cast_fp16 = matmul(transpose_x = x_221_transpose_x_0, transpose_y = x_221_transpose_y_0, x = q_with_bias_v_19_cast_fp16, y = var_1959_to_fp16)[name = tensor<string, []>("x_221_cast_fp16")];
            tensor<int32, [8]> x_223_pad_0 = const()[name = tensor<string, []>("x_223_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            tensor<string, []> x_223_mode_0 = const()[name = tensor<string, []>("x_223_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_119_to_fp16 = const()[name = tensor<string, []>("const_119_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_223_cast_fp16 = pad(constant_val = const_119_to_fp16, mode = x_223_mode_0, pad = x_223_pad_0, x = x_221_cast_fp16)[name = tensor<string, []>("x_223_cast_fp16")];
            tensor<int32, [4]> var_1967 = const()[name = tensor<string, []>("op_1967"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_225_cast_fp16 = reshape(shape = var_1967, x = x_223_cast_fp16)[name = tensor<string, []>("x_225_cast_fp16")];
            tensor<int32, [4]> var_1971_begin_0 = const()[name = tensor<string, []>("op_1971_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_1971_end_0 = const()[name = tensor<string, []>("op_1971_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_1971_end_mask_0 = const()[name = tensor<string, []>("op_1971_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_1971_cast_fp16 = slice_by_index(begin = var_1971_begin_0, end = var_1971_end_0, end_mask = var_1971_end_mask_0, x = x_225_cast_fp16)[name = tensor<string, []>("op_1971_cast_fp16")];
            tensor<int32, [4]> var_1972 = const()[name = tensor<string, []>("op_1972"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_37_cast_fp16 = reshape(shape = var_1972, x = var_1971_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_69_perm_0 = const()[name = tensor<string, []>("transpose_69_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_70_perm_0 = const()[name = tensor<string, []>("transpose_70_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 64, 188]> transpose_70 = transpose(perm = transpose_70_perm_0, x = k_37_cast_fp16)[name = tensor<string, []>("transpose_138")];
            tensor<fp16, [1, 8, 188, 64]> transpose_69 = transpose(perm = transpose_69_perm_0, x = var_1955_cast_fp16)[name = tensor<string, []>("transpose_139")];
            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_69, y = transpose_70)[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_1981_cast_fp16 = add(x = matrix_ac_19_cast_fp16, y = matrix_bd_39_cast_fp16)[name = tensor<string, []>("op_1981_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, []>(0x1p-3)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_37_cast_fp16 = mul(x = var_1981_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_153_to_fp16, b = _inversed_scores_37_cast_fp16, cond = mask_7)[name = tensor<string, []>("scores_39_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_1987_cast_fp16 = softmax(axis = var_138, x = scores_39_cast_fp16)[name = tensor<string, []>("op_1987_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_509_cast_fp16 = select(a = var_154_to_fp16, b = var_1987_cast_fp16, cond = mask_7)[name = tensor<string, []>("input_509_cast_fp16")];
            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, 188, 64]> value_23_cast_fp16 = transpose(perm = value_23_perm_0, x = v_19_cast_fp16)[name = tensor<string, []>("transpose_141")];
            tensor<fp16, [1, 8, 188, 64]> x_227_cast_fp16 = matmul(transpose_x = x_227_transpose_x_0, transpose_y = x_227_transpose_y_0, x = input_509_cast_fp16, y = value_23_cast_fp16)[name = tensor<string, []>("x_227_cast_fp16")];
            tensor<int32, [4]> var_1991_perm_0 = const()[name = tensor<string, []>("op_1991_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_1992 = const()[name = tensor<string, []>("op_1992"), val = tensor<int32, [3]>([1, -1, 512])];
            tensor<fp16, [1, 188, 8, 64]> var_1991_cast_fp16 = transpose(perm = var_1991_perm_0, x = x_227_cast_fp16)[name = tensor<string, []>("transpose_137")];
            tensor<fp16, [1, 188, 512]> input_511_cast_fp16 = reshape(shape = var_1992, x = var_1991_cast_fp16)[name = tensor<string, []>("input_511_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_9_self_attn_linear_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_9_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(122239552)))];
            tensor<fp16, [512]> encoder_module_layers_9_self_attn_linear_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_9_self_attn_linear_out_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(122763904)))];
            tensor<fp16, [1, 188, 512]> linear_88_cast_fp16 = linear(bias = encoder_module_layers_9_self_attn_linear_out_bias_to_fp16, weight = encoder_module_layers_9_self_attn_linear_out_weight_to_fp16, x = input_511_cast_fp16)[name = tensor<string, []>("linear_88_cast_fp16")];
            tensor<fp16, [1, 188, 512]> input_515_cast_fp16 = add(x = input_507_cast_fp16, y = linear_88_cast_fp16)[name = tensor<string, []>("input_515_cast_fp16")];
            tensor<int32, [1]> x_231_axes_0 = const()[name = tensor<string, []>("x_231_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_9_norm_conv_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_9_norm_conv_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(122764992)))];
            tensor<fp16, [512]> encoder_module_layers_9_norm_conv_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_9_norm_conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(122766080)))];
            tensor<fp16, [1, 188, 512]> x_231_cast_fp16 = layer_norm(axes = x_231_axes_0, beta = encoder_module_layers_9_norm_conv_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_9_norm_conv_weight_to_fp16, x = input_515_cast_fp16)[name = tensor<string, []>("x_231_cast_fp16")];
            tensor<int32, [3]> input_517_perm_0 = const()[name = tensor<string, []>("input_517_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> input_519_pad_type_0 = const()[name = tensor<string, []>("input_519_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_519_strides_0 = const()[name = tensor<string, []>("input_519_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_519_pad_0 = const()[name = tensor<string, []>("input_519_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_519_dilations_0 = const()[name = tensor<string, []>("input_519_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_519_groups_0 = const()[name = tensor<string, []>("input_519_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1024, 512, 1]> encoder_module_layers_9_conv_pointwise_conv1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_9_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [1024, 512, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(122767168)))];
            tensor<fp16, [1024]> encoder_module_layers_9_conv_pointwise_conv1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_9_conv_pointwise_conv1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(123815808)))];
            tensor<fp16, [1, 512, 188]> input_517_cast_fp16 = transpose(perm = input_517_perm_0, x = x_231_cast_fp16)[name = tensor<string, []>("transpose_136")];
            tensor<fp16, [1, 1024, 188]> input_519_cast_fp16 = conv(bias = encoder_module_layers_9_conv_pointwise_conv1_bias_to_fp16, dilations = input_519_dilations_0, groups = input_519_groups_0, pad = input_519_pad_0, pad_type = input_519_pad_type_0, strides = input_519_strides_0, weight = encoder_module_layers_9_conv_pointwise_conv1_weight_to_fp16, x = input_517_cast_fp16)[name = tensor<string, []>("input_519_cast_fp16")];
            tensor<int32, []> x_233_split_num_splits_0 = const()[name = tensor<string, []>("x_233_split_num_splits_0"), val = tensor<int32, []>(2)];
            tensor<int32, []> x_233_split_axis_0 = const()[name = tensor<string, []>("x_233_split_axis_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1, 512, 188]> x_233_split_cast_fp16_0, tensor<fp16, [1, 512, 188]> x_233_split_cast_fp16_1 = split(axis = x_233_split_axis_0, num_splits = x_233_split_num_splits_0, x = input_519_cast_fp16)[name = tensor<string, []>("x_233_split_cast_fp16")];
            tensor<fp16, [1, 512, 188]> x_233_split_1_sigmoid_cast_fp16 = sigmoid(x = x_233_split_cast_fp16_1)[name = tensor<string, []>("x_233_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 512, 188]> x_233_cast_fp16 = mul(x = x_233_split_cast_fp16_0, y = x_233_split_1_sigmoid_cast_fp16)[name = tensor<string, []>("x_233_cast_fp16")];
            tensor<fp16, [1, 512, 188]> input_521_cast_fp16 = select(a = var_154_to_fp16, b = x_233_cast_fp16, cond = var_450)[name = tensor<string, []>("input_521_cast_fp16")];
            tensor<int32, [6]> input_523_pad_0 = const()[name = tensor<string, []>("input_523_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            tensor<string, []> input_523_mode_0 = const()[name = tensor<string, []>("input_523_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_122_to_fp16 = const()[name = tensor<string, []>("const_122_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 512, 196]> input_523_cast_fp16 = pad(constant_val = const_122_to_fp16, mode = input_523_mode_0, pad = input_523_pad_0, x = input_521_cast_fp16)[name = tensor<string, []>("input_523_cast_fp16")];
            tensor<string, []> input_525_pad_type_0 = const()[name = tensor<string, []>("input_525_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, []> input_525_groups_0 = const()[name = tensor<string, []>("input_525_groups_0"), val = tensor<int32, []>(512)];
            tensor<int32, [1]> input_525_strides_0 = const()[name = tensor<string, []>("input_525_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_525_pad_0 = const()[name = tensor<string, []>("input_525_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_525_dilations_0 = const()[name = tensor<string, []>("input_525_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 9]> const_211_to_fp16 = const()[name = tensor<string, []>("const_211_to_fp16"), val = tensor<fp16, [512, 1, 9]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(123817920)))];
            tensor<fp16, [512]> const_212_to_fp16 = const()[name = tensor<string, []>("const_212_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(123827200)))];
            tensor<fp16, [1, 512, 188]> input_527_cast_fp16 = conv(bias = const_212_to_fp16, dilations = input_525_dilations_0, groups = input_525_groups_0, pad = input_525_pad_0, pad_type = input_525_pad_type_0, strides = input_525_strides_0, weight = const_211_to_fp16, x = input_523_cast_fp16)[name = tensor<string, []>("input_527_cast_fp16")];
            tensor<fp16, [1, 512, 188]> input_529_cast_fp16 = silu(x = input_527_cast_fp16)[name = tensor<string, []>("input_529_cast_fp16")];
            tensor<string, []> x_235_pad_type_0 = const()[name = tensor<string, []>("x_235_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> x_235_strides_0 = const()[name = tensor<string, []>("x_235_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_235_pad_0 = const()[name = tensor<string, []>("x_235_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_235_dilations_0 = const()[name = tensor<string, []>("x_235_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> x_235_groups_0 = const()[name = tensor<string, []>("x_235_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [512, 512, 1]> encoder_module_layers_9_conv_pointwise_conv2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_9_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [512, 512, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(123828288)))];
            tensor<fp16, [512]> encoder_module_layers_9_conv_pointwise_conv2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_9_conv_pointwise_conv2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(124352640)))];
            tensor<fp16, [1, 512, 188]> x_235_cast_fp16 = conv(bias = encoder_module_layers_9_conv_pointwise_conv2_bias_to_fp16, dilations = x_235_dilations_0, groups = x_235_groups_0, pad = x_235_pad_0, pad_type = x_235_pad_type_0, strides = x_235_strides_0, weight = encoder_module_layers_9_conv_pointwise_conv2_weight_to_fp16, x = input_529_cast_fp16)[name = tensor<string, []>("x_235_cast_fp16")];
            tensor<int32, [3]> input_531_perm_0 = const()[name = tensor<string, []>("input_531_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 512]> input_531_cast_fp16 = transpose(perm = input_531_perm_0, x = x_235_cast_fp16)[name = tensor<string, []>("transpose_135")];
            tensor<fp16, [1, 188, 512]> input_533_cast_fp16 = add(x = input_515_cast_fp16, y = input_531_cast_fp16)[name = tensor<string, []>("input_533_cast_fp16")];
            tensor<int32, [1]> input_535_axes_0 = const()[name = tensor<string, []>("input_535_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_9_norm_feed_forward2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_9_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(124353728)))];
            tensor<fp16, [512]> encoder_module_layers_9_norm_feed_forward2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_9_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(124354816)))];
            tensor<fp16, [1, 188, 512]> input_535_cast_fp16 = layer_norm(axes = input_535_axes_0, beta = encoder_module_layers_9_norm_feed_forward2_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_9_norm_feed_forward2_weight_to_fp16, x = input_533_cast_fp16)[name = tensor<string, []>("input_535_cast_fp16")];
            tensor<fp16, [2048, 512]> encoder_module_layers_9_feed_forward2_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_9_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [2048, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(124355904)))];
            tensor<fp16, [2048]> encoder_module_layers_9_feed_forward2_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_9_feed_forward2_linear1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(126453120)))];
            tensor<fp16, [1, 188, 2048]> linear_89_cast_fp16 = linear(bias = encoder_module_layers_9_feed_forward2_linear1_bias_to_fp16, weight = encoder_module_layers_9_feed_forward2_linear1_weight_to_fp16, x = input_535_cast_fp16)[name = tensor<string, []>("linear_89_cast_fp16")];
            tensor<fp16, [1, 188, 2048]> input_539_cast_fp16 = silu(x = linear_89_cast_fp16)[name = tensor<string, []>("input_539_cast_fp16")];
            tensor<fp16, [512, 2048]> encoder_module_layers_9_feed_forward2_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_9_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [512, 2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(126457280)))];
            tensor<fp16, [512]> encoder_module_layers_9_feed_forward2_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_9_feed_forward2_linear2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(128554496)))];
            tensor<fp16, [1, 188, 512]> linear_90_cast_fp16 = linear(bias = encoder_module_layers_9_feed_forward2_linear2_bias_to_fp16, weight = encoder_module_layers_9_feed_forward2_linear2_weight_to_fp16, x = input_539_cast_fp16)[name = tensor<string, []>("linear_90_cast_fp16")];
            tensor<fp16, []> var_2058_to_fp16 = const()[name = tensor<string, []>("op_2058_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 512]> var_2059_cast_fp16 = mul(x = linear_90_cast_fp16, y = var_2058_to_fp16)[name = tensor<string, []>("op_2059_cast_fp16")];
            tensor<fp16, [1, 188, 512]> input_545_cast_fp16 = add(x = input_533_cast_fp16, y = var_2059_cast_fp16)[name = tensor<string, []>("input_545_cast_fp16")];
            tensor<int32, [1]> input_547_axes_0 = const()[name = tensor<string, []>("input_547_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_9_norm_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_9_norm_out_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(128555584)))];
            tensor<fp16, [512]> encoder_module_layers_9_norm_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_9_norm_out_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(128556672)))];
            tensor<fp16, [1, 188, 512]> input_547_cast_fp16 = layer_norm(axes = input_547_axes_0, beta = encoder_module_layers_9_norm_out_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_9_norm_out_weight_to_fp16, x = input_545_cast_fp16)[name = tensor<string, []>("input_547_cast_fp16")];
            tensor<int32, [1]> input_549_axes_0 = const()[name = tensor<string, []>("input_549_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_10_norm_feed_forward1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_10_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(128557760)))];
            tensor<fp16, [512]> encoder_module_layers_10_norm_feed_forward1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_10_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(128558848)))];
            tensor<fp16, [1, 188, 512]> input_549_cast_fp16 = layer_norm(axes = input_549_axes_0, beta = encoder_module_layers_10_norm_feed_forward1_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_10_norm_feed_forward1_weight_to_fp16, x = input_547_cast_fp16)[name = tensor<string, []>("input_549_cast_fp16")];
            tensor<fp16, [2048, 512]> encoder_module_layers_10_feed_forward1_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_10_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [2048, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(128559936)))];
            tensor<fp16, [2048]> encoder_module_layers_10_feed_forward1_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_10_feed_forward1_linear1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(130657152)))];
            tensor<fp16, [1, 188, 2048]> linear_91_cast_fp16 = linear(bias = encoder_module_layers_10_feed_forward1_linear1_bias_to_fp16, weight = encoder_module_layers_10_feed_forward1_linear1_weight_to_fp16, x = input_549_cast_fp16)[name = tensor<string, []>("linear_91_cast_fp16")];
            tensor<fp16, [1, 188, 2048]> input_553_cast_fp16 = silu(x = linear_91_cast_fp16)[name = tensor<string, []>("input_553_cast_fp16")];
            tensor<fp16, [512, 2048]> encoder_module_layers_10_feed_forward1_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_10_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [512, 2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(130661312)))];
            tensor<fp16, [512]> encoder_module_layers_10_feed_forward1_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_10_feed_forward1_linear2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(132758528)))];
            tensor<fp16, [1, 188, 512]> linear_92_cast_fp16 = linear(bias = encoder_module_layers_10_feed_forward1_linear2_bias_to_fp16, weight = encoder_module_layers_10_feed_forward1_linear2_weight_to_fp16, x = input_553_cast_fp16)[name = tensor<string, []>("linear_92_cast_fp16")];
            tensor<fp16, []> var_2089_to_fp16 = const()[name = tensor<string, []>("op_2089_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 512]> var_2090_cast_fp16 = mul(x = linear_92_cast_fp16, y = var_2089_to_fp16)[name = tensor<string, []>("op_2090_cast_fp16")];
            tensor<fp16, [1, 188, 512]> input_559_cast_fp16 = add(x = input_547_cast_fp16, y = var_2090_cast_fp16)[name = tensor<string, []>("input_559_cast_fp16")];
            tensor<int32, [1]> query_21_axes_0 = const()[name = tensor<string, []>("query_21_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_10_norm_self_att_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_10_norm_self_att_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(132759616)))];
            tensor<fp16, [512]> encoder_module_layers_10_norm_self_att_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_10_norm_self_att_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(132760704)))];
            tensor<fp16, [1, 188, 512]> query_21_cast_fp16 = layer_norm(axes = query_21_axes_0, beta = encoder_module_layers_10_norm_self_att_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_10_norm_self_att_weight_to_fp16, x = input_559_cast_fp16)[name = tensor<string, []>("query_21_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_10_self_attn_linear_q_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_10_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(132761792)))];
            tensor<fp16, [512]> encoder_module_layers_10_self_attn_linear_q_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_10_self_attn_linear_q_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(133286144)))];
            tensor<fp16, [1, 188, 512]> linear_93_cast_fp16 = linear(bias = encoder_module_layers_10_self_attn_linear_q_bias_to_fp16, weight = encoder_module_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_2107 = const()[name = tensor<string, []>("op_2107"), val = tensor<int32, [4]>([1, -1, 8, 64])];
            tensor<fp16, [1, 188, 8, 64]> q_61_cast_fp16 = reshape(shape = var_2107, x = linear_93_cast_fp16)[name = tensor<string, []>("q_61_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_10_self_attn_linear_k_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_10_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(133287232)))];
            tensor<fp16, [512]> encoder_module_layers_10_self_attn_linear_k_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_10_self_attn_linear_k_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(133811584)))];
            tensor<fp16, [1, 188, 512]> linear_94_cast_fp16 = linear(bias = encoder_module_layers_10_self_attn_linear_k_bias_to_fp16, weight = encoder_module_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_2112 = const()[name = tensor<string, []>("op_2112"), val = tensor<int32, [4]>([1, -1, 8, 64])];
            tensor<fp16, [1, 188, 8, 64]> k_41_cast_fp16 = reshape(shape = var_2112, x = linear_94_cast_fp16)[name = tensor<string, []>("k_41_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_10_self_attn_linear_v_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_10_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(133812672)))];
            tensor<fp16, [512]> encoder_module_layers_10_self_attn_linear_v_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_10_self_attn_linear_v_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(134337024)))];
            tensor<fp16, [1, 188, 512]> linear_95_cast_fp16 = linear(bias = encoder_module_layers_10_self_attn_linear_v_bias_to_fp16, weight = encoder_module_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_2117 = const()[name = tensor<string, []>("op_2117"), val = tensor<int32, [4]>([1, -1, 8, 64])];
            tensor<fp16, [1, 188, 8, 64]> v_21_cast_fp16 = reshape(shape = var_2117, x = linear_95_cast_fp16)[name = tensor<string, []>("v_21_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, 64]> encoder_module_layers_10_self_attn_pos_bias_u_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_10_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(134338112)))];
            tensor<fp16, [1, 188, 8, 64]> var_2129_cast_fp16 = add(x = q_61_cast_fp16, y = encoder_module_layers_10_self_attn_pos_bias_u_to_fp16)[name = tensor<string, []>("op_2129_cast_fp16")];
            tensor<fp16, [8, 64]> encoder_module_layers_10_self_attn_pos_bias_v_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_10_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(134339200)))];
            tensor<fp16, [1, 188, 8, 64]> var_2131_cast_fp16 = add(x = q_61_cast_fp16, y = encoder_module_layers_10_self_attn_pos_bias_v_to_fp16)[name = tensor<string, []>("op_2131_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_243_transpose_x_0 = const()[name = tensor<string, []>("x_243_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_243_transpose_y_0 = const()[name = tensor<string, []>("x_243_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 64, 375]> var_2133_to_fp16 = const()[name = tensor<string, []>("op_2133_to_fp16"), val = tensor<fp16, [1, 8, 64, 375]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(134340288)))];
            tensor<fp16, [1, 8, 188, 64]> q_with_bias_v_21_cast_fp16 = transpose(perm = q_with_bias_v_21_perm_0, x = var_2131_cast_fp16)[name = tensor<string, []>("transpose_133")];
            tensor<fp16, [1, 8, 188, 375]> x_243_cast_fp16 = matmul(transpose_x = x_243_transpose_x_0, transpose_y = x_243_transpose_y_0, x = q_with_bias_v_21_cast_fp16, y = var_2133_to_fp16)[name = tensor<string, []>("x_243_cast_fp16")];
            tensor<int32, [8]> x_245_pad_0 = const()[name = tensor<string, []>("x_245_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            tensor<string, []> x_245_mode_0 = const()[name = tensor<string, []>("x_245_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_129_to_fp16 = const()[name = tensor<string, []>("const_129_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_245_cast_fp16 = pad(constant_val = const_129_to_fp16, mode = x_245_mode_0, pad = x_245_pad_0, x = x_243_cast_fp16)[name = tensor<string, []>("x_245_cast_fp16")];
            tensor<int32, [4]> var_2141 = const()[name = tensor<string, []>("op_2141"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_247_cast_fp16 = reshape(shape = var_2141, x = x_245_cast_fp16)[name = tensor<string, []>("x_247_cast_fp16")];
            tensor<int32, [4]> var_2145_begin_0 = const()[name = tensor<string, []>("op_2145_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_2145_end_0 = const()[name = tensor<string, []>("op_2145_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_2145_end_mask_0 = const()[name = tensor<string, []>("op_2145_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_2145_cast_fp16 = slice_by_index(begin = var_2145_begin_0, end = var_2145_end_0, end_mask = var_2145_end_mask_0, x = x_247_cast_fp16)[name = tensor<string, []>("op_2145_cast_fp16")];
            tensor<int32, [4]> var_2146 = const()[name = tensor<string, []>("op_2146"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_41_cast_fp16 = reshape(shape = var_2146, x = var_2145_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_71_perm_0 = const()[name = tensor<string, []>("transpose_71_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_72_perm_0 = const()[name = tensor<string, []>("transpose_72_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 64, 188]> transpose_72 = transpose(perm = transpose_72_perm_0, x = k_41_cast_fp16)[name = tensor<string, []>("transpose_131")];
            tensor<fp16, [1, 8, 188, 64]> transpose_71 = transpose(perm = transpose_71_perm_0, x = var_2129_cast_fp16)[name = tensor<string, []>("transpose_132")];
            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_71, y = transpose_72)[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_2155_cast_fp16 = add(x = matrix_ac_21_cast_fp16, y = matrix_bd_43_cast_fp16)[name = tensor<string, []>("op_2155_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, []>(0x1p-3)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_41_cast_fp16 = mul(x = var_2155_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_153_to_fp16, b = _inversed_scores_41_cast_fp16, cond = mask_7)[name = tensor<string, []>("scores_43_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_2161_cast_fp16 = softmax(axis = var_138, x = scores_43_cast_fp16)[name = tensor<string, []>("op_2161_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_561_cast_fp16 = select(a = var_154_to_fp16, b = var_2161_cast_fp16, cond = mask_7)[name = tensor<string, []>("input_561_cast_fp16")];
            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, 188, 64]> value_25_cast_fp16 = transpose(perm = value_25_perm_0, x = v_21_cast_fp16)[name = tensor<string, []>("transpose_134")];
            tensor<fp16, [1, 8, 188, 64]> x_249_cast_fp16 = matmul(transpose_x = x_249_transpose_x_0, transpose_y = x_249_transpose_y_0, x = input_561_cast_fp16, y = value_25_cast_fp16)[name = tensor<string, []>("x_249_cast_fp16")];
            tensor<int32, [4]> var_2165_perm_0 = const()[name = tensor<string, []>("op_2165_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2166 = const()[name = tensor<string, []>("op_2166"), val = tensor<int32, [3]>([1, -1, 512])];
            tensor<fp16, [1, 188, 8, 64]> var_2165_cast_fp16 = transpose(perm = var_2165_perm_0, x = x_249_cast_fp16)[name = tensor<string, []>("transpose_130")];
            tensor<fp16, [1, 188, 512]> input_563_cast_fp16 = reshape(shape = var_2166, x = var_2165_cast_fp16)[name = tensor<string, []>("input_563_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_10_self_attn_linear_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_10_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(134724352)))];
            tensor<fp16, [512]> encoder_module_layers_10_self_attn_linear_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_10_self_attn_linear_out_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(135248704)))];
            tensor<fp16, [1, 188, 512]> linear_97_cast_fp16 = linear(bias = encoder_module_layers_10_self_attn_linear_out_bias_to_fp16, weight = encoder_module_layers_10_self_attn_linear_out_weight_to_fp16, x = input_563_cast_fp16)[name = tensor<string, []>("linear_97_cast_fp16")];
            tensor<fp16, [1, 188, 512]> input_567_cast_fp16 = add(x = input_559_cast_fp16, y = linear_97_cast_fp16)[name = tensor<string, []>("input_567_cast_fp16")];
            tensor<int32, [1]> x_253_axes_0 = const()[name = tensor<string, []>("x_253_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_10_norm_conv_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_10_norm_conv_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(135249792)))];
            tensor<fp16, [512]> encoder_module_layers_10_norm_conv_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_10_norm_conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(135250880)))];
            tensor<fp16, [1, 188, 512]> x_253_cast_fp16 = layer_norm(axes = x_253_axes_0, beta = encoder_module_layers_10_norm_conv_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_10_norm_conv_weight_to_fp16, x = input_567_cast_fp16)[name = tensor<string, []>("x_253_cast_fp16")];
            tensor<int32, [3]> input_569_perm_0 = const()[name = tensor<string, []>("input_569_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> input_571_pad_type_0 = const()[name = tensor<string, []>("input_571_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_571_strides_0 = const()[name = tensor<string, []>("input_571_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_571_pad_0 = const()[name = tensor<string, []>("input_571_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_571_dilations_0 = const()[name = tensor<string, []>("input_571_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_571_groups_0 = const()[name = tensor<string, []>("input_571_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1024, 512, 1]> encoder_module_layers_10_conv_pointwise_conv1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_10_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [1024, 512, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(135251968)))];
            tensor<fp16, [1024]> encoder_module_layers_10_conv_pointwise_conv1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_10_conv_pointwise_conv1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(136300608)))];
            tensor<fp16, [1, 512, 188]> input_569_cast_fp16 = transpose(perm = input_569_perm_0, x = x_253_cast_fp16)[name = tensor<string, []>("transpose_129")];
            tensor<fp16, [1, 1024, 188]> input_571_cast_fp16 = conv(bias = encoder_module_layers_10_conv_pointwise_conv1_bias_to_fp16, dilations = input_571_dilations_0, groups = input_571_groups_0, pad = input_571_pad_0, pad_type = input_571_pad_type_0, strides = input_571_strides_0, weight = encoder_module_layers_10_conv_pointwise_conv1_weight_to_fp16, x = input_569_cast_fp16)[name = tensor<string, []>("input_571_cast_fp16")];
            tensor<int32, []> x_255_split_num_splits_0 = const()[name = tensor<string, []>("x_255_split_num_splits_0"), val = tensor<int32, []>(2)];
            tensor<int32, []> x_255_split_axis_0 = const()[name = tensor<string, []>("x_255_split_axis_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1, 512, 188]> x_255_split_cast_fp16_0, tensor<fp16, [1, 512, 188]> x_255_split_cast_fp16_1 = split(axis = x_255_split_axis_0, num_splits = x_255_split_num_splits_0, x = input_571_cast_fp16)[name = tensor<string, []>("x_255_split_cast_fp16")];
            tensor<fp16, [1, 512, 188]> x_255_split_1_sigmoid_cast_fp16 = sigmoid(x = x_255_split_cast_fp16_1)[name = tensor<string, []>("x_255_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 512, 188]> x_255_cast_fp16 = mul(x = x_255_split_cast_fp16_0, y = x_255_split_1_sigmoid_cast_fp16)[name = tensor<string, []>("x_255_cast_fp16")];
            tensor<fp16, [1, 512, 188]> input_573_cast_fp16 = select(a = var_154_to_fp16, b = x_255_cast_fp16, cond = var_450)[name = tensor<string, []>("input_573_cast_fp16")];
            tensor<int32, [6]> input_575_pad_0 = const()[name = tensor<string, []>("input_575_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            tensor<string, []> input_575_mode_0 = const()[name = tensor<string, []>("input_575_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_132_to_fp16 = const()[name = tensor<string, []>("const_132_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 512, 196]> input_575_cast_fp16 = pad(constant_val = const_132_to_fp16, mode = input_575_mode_0, pad = input_575_pad_0, x = input_573_cast_fp16)[name = tensor<string, []>("input_575_cast_fp16")];
            tensor<string, []> input_577_pad_type_0 = const()[name = tensor<string, []>("input_577_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, []> input_577_groups_0 = const()[name = tensor<string, []>("input_577_groups_0"), val = tensor<int32, []>(512)];
            tensor<int32, [1]> input_577_strides_0 = const()[name = tensor<string, []>("input_577_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_577_pad_0 = const()[name = tensor<string, []>("input_577_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_577_dilations_0 = const()[name = tensor<string, []>("input_577_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 9]> const_213_to_fp16 = const()[name = tensor<string, []>("const_213_to_fp16"), val = tensor<fp16, [512, 1, 9]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(136302720)))];
            tensor<fp16, [512]> const_214_to_fp16 = const()[name = tensor<string, []>("const_214_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(136312000)))];
            tensor<fp16, [1, 512, 188]> input_579_cast_fp16 = conv(bias = const_214_to_fp16, dilations = input_577_dilations_0, groups = input_577_groups_0, pad = input_577_pad_0, pad_type = input_577_pad_type_0, strides = input_577_strides_0, weight = const_213_to_fp16, x = input_575_cast_fp16)[name = tensor<string, []>("input_579_cast_fp16")];
            tensor<fp16, [1, 512, 188]> input_581_cast_fp16 = silu(x = input_579_cast_fp16)[name = tensor<string, []>("input_581_cast_fp16")];
            tensor<string, []> x_257_pad_type_0 = const()[name = tensor<string, []>("x_257_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> x_257_strides_0 = const()[name = tensor<string, []>("x_257_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_257_pad_0 = const()[name = tensor<string, []>("x_257_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_257_dilations_0 = const()[name = tensor<string, []>("x_257_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> x_257_groups_0 = const()[name = tensor<string, []>("x_257_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [512, 512, 1]> encoder_module_layers_10_conv_pointwise_conv2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_10_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [512, 512, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(136313088)))];
            tensor<fp16, [512]> encoder_module_layers_10_conv_pointwise_conv2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_10_conv_pointwise_conv2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(136837440)))];
            tensor<fp16, [1, 512, 188]> x_257_cast_fp16 = conv(bias = encoder_module_layers_10_conv_pointwise_conv2_bias_to_fp16, dilations = x_257_dilations_0, groups = x_257_groups_0, pad = x_257_pad_0, pad_type = x_257_pad_type_0, strides = x_257_strides_0, weight = encoder_module_layers_10_conv_pointwise_conv2_weight_to_fp16, x = input_581_cast_fp16)[name = tensor<string, []>("x_257_cast_fp16")];
            tensor<int32, [3]> input_583_perm_0 = const()[name = tensor<string, []>("input_583_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 512]> input_583_cast_fp16 = transpose(perm = input_583_perm_0, x = x_257_cast_fp16)[name = tensor<string, []>("transpose_128")];
            tensor<fp16, [1, 188, 512]> input_585_cast_fp16 = add(x = input_567_cast_fp16, y = input_583_cast_fp16)[name = tensor<string, []>("input_585_cast_fp16")];
            tensor<int32, [1]> input_587_axes_0 = const()[name = tensor<string, []>("input_587_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_10_norm_feed_forward2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_10_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(136838528)))];
            tensor<fp16, [512]> encoder_module_layers_10_norm_feed_forward2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_10_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(136839616)))];
            tensor<fp16, [1, 188, 512]> input_587_cast_fp16 = layer_norm(axes = input_587_axes_0, beta = encoder_module_layers_10_norm_feed_forward2_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_10_norm_feed_forward2_weight_to_fp16, x = input_585_cast_fp16)[name = tensor<string, []>("input_587_cast_fp16")];
            tensor<fp16, [2048, 512]> encoder_module_layers_10_feed_forward2_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_10_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [2048, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(136840704)))];
            tensor<fp16, [2048]> encoder_module_layers_10_feed_forward2_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_10_feed_forward2_linear1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(138937920)))];
            tensor<fp16, [1, 188, 2048]> linear_98_cast_fp16 = linear(bias = encoder_module_layers_10_feed_forward2_linear1_bias_to_fp16, weight = encoder_module_layers_10_feed_forward2_linear1_weight_to_fp16, x = input_587_cast_fp16)[name = tensor<string, []>("linear_98_cast_fp16")];
            tensor<fp16, [1, 188, 2048]> input_591_cast_fp16 = silu(x = linear_98_cast_fp16)[name = tensor<string, []>("input_591_cast_fp16")];
            tensor<fp16, [512, 2048]> encoder_module_layers_10_feed_forward2_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_10_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [512, 2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(138942080)))];
            tensor<fp16, [512]> encoder_module_layers_10_feed_forward2_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_10_feed_forward2_linear2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(141039296)))];
            tensor<fp16, [1, 188, 512]> linear_99_cast_fp16 = linear(bias = encoder_module_layers_10_feed_forward2_linear2_bias_to_fp16, weight = encoder_module_layers_10_feed_forward2_linear2_weight_to_fp16, x = input_591_cast_fp16)[name = tensor<string, []>("linear_99_cast_fp16")];
            tensor<fp16, []> var_2232_to_fp16 = const()[name = tensor<string, []>("op_2232_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 512]> var_2233_cast_fp16 = mul(x = linear_99_cast_fp16, y = var_2232_to_fp16)[name = tensor<string, []>("op_2233_cast_fp16")];
            tensor<fp16, [1, 188, 512]> input_597_cast_fp16 = add(x = input_585_cast_fp16, y = var_2233_cast_fp16)[name = tensor<string, []>("input_597_cast_fp16")];
            tensor<int32, [1]> input_599_axes_0 = const()[name = tensor<string, []>("input_599_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_10_norm_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_10_norm_out_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(141040384)))];
            tensor<fp16, [512]> encoder_module_layers_10_norm_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_10_norm_out_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(141041472)))];
            tensor<fp16, [1, 188, 512]> input_599_cast_fp16 = layer_norm(axes = input_599_axes_0, beta = encoder_module_layers_10_norm_out_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_10_norm_out_weight_to_fp16, x = input_597_cast_fp16)[name = tensor<string, []>("input_599_cast_fp16")];
            tensor<int32, [1]> input_601_axes_0 = const()[name = tensor<string, []>("input_601_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_11_norm_feed_forward1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_11_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(141042560)))];
            tensor<fp16, [512]> encoder_module_layers_11_norm_feed_forward1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_11_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(141043648)))];
            tensor<fp16, [1, 188, 512]> input_601_cast_fp16 = layer_norm(axes = input_601_axes_0, beta = encoder_module_layers_11_norm_feed_forward1_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_11_norm_feed_forward1_weight_to_fp16, x = input_599_cast_fp16)[name = tensor<string, []>("input_601_cast_fp16")];
            tensor<fp16, [2048, 512]> encoder_module_layers_11_feed_forward1_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_11_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [2048, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(141044736)))];
            tensor<fp16, [2048]> encoder_module_layers_11_feed_forward1_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_11_feed_forward1_linear1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(143141952)))];
            tensor<fp16, [1, 188, 2048]> linear_100_cast_fp16 = linear(bias = encoder_module_layers_11_feed_forward1_linear1_bias_to_fp16, weight = encoder_module_layers_11_feed_forward1_linear1_weight_to_fp16, x = input_601_cast_fp16)[name = tensor<string, []>("linear_100_cast_fp16")];
            tensor<fp16, [1, 188, 2048]> input_605_cast_fp16 = silu(x = linear_100_cast_fp16)[name = tensor<string, []>("input_605_cast_fp16")];
            tensor<fp16, [512, 2048]> encoder_module_layers_11_feed_forward1_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_11_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [512, 2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(143146112)))];
            tensor<fp16, [512]> encoder_module_layers_11_feed_forward1_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_11_feed_forward1_linear2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(145243328)))];
            tensor<fp16, [1, 188, 512]> linear_101_cast_fp16 = linear(bias = encoder_module_layers_11_feed_forward1_linear2_bias_to_fp16, weight = encoder_module_layers_11_feed_forward1_linear2_weight_to_fp16, x = input_605_cast_fp16)[name = tensor<string, []>("linear_101_cast_fp16")];
            tensor<fp16, []> var_2263_to_fp16 = const()[name = tensor<string, []>("op_2263_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 512]> var_2264_cast_fp16 = mul(x = linear_101_cast_fp16, y = var_2263_to_fp16)[name = tensor<string, []>("op_2264_cast_fp16")];
            tensor<fp16, [1, 188, 512]> input_611_cast_fp16 = add(x = input_599_cast_fp16, y = var_2264_cast_fp16)[name = tensor<string, []>("input_611_cast_fp16")];
            tensor<int32, [1]> query_23_axes_0 = const()[name = tensor<string, []>("query_23_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_11_norm_self_att_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_11_norm_self_att_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(145244416)))];
            tensor<fp16, [512]> encoder_module_layers_11_norm_self_att_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_11_norm_self_att_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(145245504)))];
            tensor<fp16, [1, 188, 512]> query_23_cast_fp16 = layer_norm(axes = query_23_axes_0, beta = encoder_module_layers_11_norm_self_att_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_11_norm_self_att_weight_to_fp16, x = input_611_cast_fp16)[name = tensor<string, []>("query_23_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_11_self_attn_linear_q_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_11_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(145246592)))];
            tensor<fp16, [512]> encoder_module_layers_11_self_attn_linear_q_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_11_self_attn_linear_q_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(145770944)))];
            tensor<fp16, [1, 188, 512]> linear_102_cast_fp16 = linear(bias = encoder_module_layers_11_self_attn_linear_q_bias_to_fp16, weight = encoder_module_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_2281 = const()[name = tensor<string, []>("op_2281"), val = tensor<int32, [4]>([1, -1, 8, 64])];
            tensor<fp16, [1, 188, 8, 64]> q_67_cast_fp16 = reshape(shape = var_2281, x = linear_102_cast_fp16)[name = tensor<string, []>("q_67_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_11_self_attn_linear_k_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_11_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(145772032)))];
            tensor<fp16, [512]> encoder_module_layers_11_self_attn_linear_k_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_11_self_attn_linear_k_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(146296384)))];
            tensor<fp16, [1, 188, 512]> linear_103_cast_fp16 = linear(bias = encoder_module_layers_11_self_attn_linear_k_bias_to_fp16, weight = encoder_module_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_2286 = const()[name = tensor<string, []>("op_2286"), val = tensor<int32, [4]>([1, -1, 8, 64])];
            tensor<fp16, [1, 188, 8, 64]> k_45_cast_fp16 = reshape(shape = var_2286, x = linear_103_cast_fp16)[name = tensor<string, []>("k_45_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_11_self_attn_linear_v_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_11_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(146297472)))];
            tensor<fp16, [512]> encoder_module_layers_11_self_attn_linear_v_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_11_self_attn_linear_v_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(146821824)))];
            tensor<fp16, [1, 188, 512]> linear_104_cast_fp16 = linear(bias = encoder_module_layers_11_self_attn_linear_v_bias_to_fp16, weight = encoder_module_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_2291 = const()[name = tensor<string, []>("op_2291"), val = tensor<int32, [4]>([1, -1, 8, 64])];
            tensor<fp16, [1, 188, 8, 64]> v_23_cast_fp16 = reshape(shape = var_2291, x = linear_104_cast_fp16)[name = tensor<string, []>("v_23_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, 64]> encoder_module_layers_11_self_attn_pos_bias_u_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_11_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(146822912)))];
            tensor<fp16, [1, 188, 8, 64]> var_2303_cast_fp16 = add(x = q_67_cast_fp16, y = encoder_module_layers_11_self_attn_pos_bias_u_to_fp16)[name = tensor<string, []>("op_2303_cast_fp16")];
            tensor<fp16, [8, 64]> encoder_module_layers_11_self_attn_pos_bias_v_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_11_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(146824000)))];
            tensor<fp16, [1, 188, 8, 64]> var_2305_cast_fp16 = add(x = q_67_cast_fp16, y = encoder_module_layers_11_self_attn_pos_bias_v_to_fp16)[name = tensor<string, []>("op_2305_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_265_transpose_x_0 = const()[name = tensor<string, []>("x_265_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_265_transpose_y_0 = const()[name = tensor<string, []>("x_265_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 64, 375]> var_2307_to_fp16 = const()[name = tensor<string, []>("op_2307_to_fp16"), val = tensor<fp16, [1, 8, 64, 375]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(146825088)))];
            tensor<fp16, [1, 8, 188, 64]> q_with_bias_v_23_cast_fp16 = transpose(perm = q_with_bias_v_23_perm_0, x = var_2305_cast_fp16)[name = tensor<string, []>("transpose_126")];
            tensor<fp16, [1, 8, 188, 375]> x_265_cast_fp16 = matmul(transpose_x = x_265_transpose_x_0, transpose_y = x_265_transpose_y_0, x = q_with_bias_v_23_cast_fp16, y = var_2307_to_fp16)[name = tensor<string, []>("x_265_cast_fp16")];
            tensor<int32, [8]> x_267_pad_0 = const()[name = tensor<string, []>("x_267_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            tensor<string, []> x_267_mode_0 = const()[name = tensor<string, []>("x_267_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_139_to_fp16 = const()[name = tensor<string, []>("const_139_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_267_cast_fp16 = pad(constant_val = const_139_to_fp16, mode = x_267_mode_0, pad = x_267_pad_0, x = x_265_cast_fp16)[name = tensor<string, []>("x_267_cast_fp16")];
            tensor<int32, [4]> var_2315 = const()[name = tensor<string, []>("op_2315"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_269_cast_fp16 = reshape(shape = var_2315, x = x_267_cast_fp16)[name = tensor<string, []>("x_269_cast_fp16")];
            tensor<int32, [4]> var_2319_begin_0 = const()[name = tensor<string, []>("op_2319_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_2319_end_0 = const()[name = tensor<string, []>("op_2319_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_2319_end_mask_0 = const()[name = tensor<string, []>("op_2319_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_2319_cast_fp16 = slice_by_index(begin = var_2319_begin_0, end = var_2319_end_0, end_mask = var_2319_end_mask_0, x = x_269_cast_fp16)[name = tensor<string, []>("op_2319_cast_fp16")];
            tensor<int32, [4]> var_2320 = const()[name = tensor<string, []>("op_2320"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_45_cast_fp16 = reshape(shape = var_2320, x = var_2319_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_73_perm_0 = const()[name = tensor<string, []>("transpose_73_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_74_perm_0 = const()[name = tensor<string, []>("transpose_74_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 64, 188]> transpose_74 = transpose(perm = transpose_74_perm_0, x = k_45_cast_fp16)[name = tensor<string, []>("transpose_124")];
            tensor<fp16, [1, 8, 188, 64]> transpose_73 = transpose(perm = transpose_73_perm_0, x = var_2303_cast_fp16)[name = tensor<string, []>("transpose_125")];
            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_73, y = transpose_74)[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_2329_cast_fp16 = add(x = matrix_ac_23_cast_fp16, y = matrix_bd_47_cast_fp16)[name = tensor<string, []>("op_2329_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, []>(0x1p-3)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_45_cast_fp16 = mul(x = var_2329_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_153_to_fp16, b = _inversed_scores_45_cast_fp16, cond = mask_7)[name = tensor<string, []>("scores_47_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_2335_cast_fp16 = softmax(axis = var_138, x = scores_47_cast_fp16)[name = tensor<string, []>("op_2335_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_613_cast_fp16 = select(a = var_154_to_fp16, b = var_2335_cast_fp16, cond = mask_7)[name = tensor<string, []>("input_613_cast_fp16")];
            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, 188, 64]> value_27_cast_fp16 = transpose(perm = value_27_perm_0, x = v_23_cast_fp16)[name = tensor<string, []>("transpose_127")];
            tensor<fp16, [1, 8, 188, 64]> x_271_cast_fp16 = matmul(transpose_x = x_271_transpose_x_0, transpose_y = x_271_transpose_y_0, x = input_613_cast_fp16, y = value_27_cast_fp16)[name = tensor<string, []>("x_271_cast_fp16")];
            tensor<int32, [4]> var_2339_perm_0 = const()[name = tensor<string, []>("op_2339_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2340 = const()[name = tensor<string, []>("op_2340"), val = tensor<int32, [3]>([1, -1, 512])];
            tensor<fp16, [1, 188, 8, 64]> var_2339_cast_fp16 = transpose(perm = var_2339_perm_0, x = x_271_cast_fp16)[name = tensor<string, []>("transpose_123")];
            tensor<fp16, [1, 188, 512]> input_615_cast_fp16 = reshape(shape = var_2340, x = var_2339_cast_fp16)[name = tensor<string, []>("input_615_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_11_self_attn_linear_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_11_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(147209152)))];
            tensor<fp16, [512]> encoder_module_layers_11_self_attn_linear_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_11_self_attn_linear_out_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(147733504)))];
            tensor<fp16, [1, 188, 512]> linear_106_cast_fp16 = linear(bias = encoder_module_layers_11_self_attn_linear_out_bias_to_fp16, weight = encoder_module_layers_11_self_attn_linear_out_weight_to_fp16, x = input_615_cast_fp16)[name = tensor<string, []>("linear_106_cast_fp16")];
            tensor<fp16, [1, 188, 512]> input_619_cast_fp16 = add(x = input_611_cast_fp16, y = linear_106_cast_fp16)[name = tensor<string, []>("input_619_cast_fp16")];
            tensor<int32, [1]> x_275_axes_0 = const()[name = tensor<string, []>("x_275_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_11_norm_conv_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_11_norm_conv_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(147734592)))];
            tensor<fp16, [512]> encoder_module_layers_11_norm_conv_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_11_norm_conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(147735680)))];
            tensor<fp16, [1, 188, 512]> x_275_cast_fp16 = layer_norm(axes = x_275_axes_0, beta = encoder_module_layers_11_norm_conv_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_11_norm_conv_weight_to_fp16, x = input_619_cast_fp16)[name = tensor<string, []>("x_275_cast_fp16")];
            tensor<int32, [3]> input_621_perm_0 = const()[name = tensor<string, []>("input_621_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> input_623_pad_type_0 = const()[name = tensor<string, []>("input_623_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_623_strides_0 = const()[name = tensor<string, []>("input_623_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_623_pad_0 = const()[name = tensor<string, []>("input_623_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_623_dilations_0 = const()[name = tensor<string, []>("input_623_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_623_groups_0 = const()[name = tensor<string, []>("input_623_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1024, 512, 1]> encoder_module_layers_11_conv_pointwise_conv1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_11_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [1024, 512, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(147736768)))];
            tensor<fp16, [1024]> encoder_module_layers_11_conv_pointwise_conv1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_11_conv_pointwise_conv1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(148785408)))];
            tensor<fp16, [1, 512, 188]> input_621_cast_fp16 = transpose(perm = input_621_perm_0, x = x_275_cast_fp16)[name = tensor<string, []>("transpose_122")];
            tensor<fp16, [1, 1024, 188]> input_623_cast_fp16 = conv(bias = encoder_module_layers_11_conv_pointwise_conv1_bias_to_fp16, dilations = input_623_dilations_0, groups = input_623_groups_0, pad = input_623_pad_0, pad_type = input_623_pad_type_0, strides = input_623_strides_0, weight = encoder_module_layers_11_conv_pointwise_conv1_weight_to_fp16, x = input_621_cast_fp16)[name = tensor<string, []>("input_623_cast_fp16")];
            tensor<int32, []> x_277_split_num_splits_0 = const()[name = tensor<string, []>("x_277_split_num_splits_0"), val = tensor<int32, []>(2)];
            tensor<int32, []> x_277_split_axis_0 = const()[name = tensor<string, []>("x_277_split_axis_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1, 512, 188]> x_277_split_cast_fp16_0, tensor<fp16, [1, 512, 188]> x_277_split_cast_fp16_1 = split(axis = x_277_split_axis_0, num_splits = x_277_split_num_splits_0, x = input_623_cast_fp16)[name = tensor<string, []>("x_277_split_cast_fp16")];
            tensor<fp16, [1, 512, 188]> x_277_split_1_sigmoid_cast_fp16 = sigmoid(x = x_277_split_cast_fp16_1)[name = tensor<string, []>("x_277_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 512, 188]> x_277_cast_fp16 = mul(x = x_277_split_cast_fp16_0, y = x_277_split_1_sigmoid_cast_fp16)[name = tensor<string, []>("x_277_cast_fp16")];
            tensor<fp16, [1, 512, 188]> input_625_cast_fp16 = select(a = var_154_to_fp16, b = x_277_cast_fp16, cond = var_450)[name = tensor<string, []>("input_625_cast_fp16")];
            tensor<int32, [6]> input_627_pad_0 = const()[name = tensor<string, []>("input_627_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            tensor<string, []> input_627_mode_0 = const()[name = tensor<string, []>("input_627_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_142_to_fp16 = const()[name = tensor<string, []>("const_142_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 512, 196]> input_627_cast_fp16 = pad(constant_val = const_142_to_fp16, mode = input_627_mode_0, pad = input_627_pad_0, x = input_625_cast_fp16)[name = tensor<string, []>("input_627_cast_fp16")];
            tensor<string, []> input_629_pad_type_0 = const()[name = tensor<string, []>("input_629_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, []> input_629_groups_0 = const()[name = tensor<string, []>("input_629_groups_0"), val = tensor<int32, []>(512)];
            tensor<int32, [1]> input_629_strides_0 = const()[name = tensor<string, []>("input_629_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_629_pad_0 = const()[name = tensor<string, []>("input_629_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_629_dilations_0 = const()[name = tensor<string, []>("input_629_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 9]> const_215_to_fp16 = const()[name = tensor<string, []>("const_215_to_fp16"), val = tensor<fp16, [512, 1, 9]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(148787520)))];
            tensor<fp16, [512]> const_216_to_fp16 = const()[name = tensor<string, []>("const_216_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(148796800)))];
            tensor<fp16, [1, 512, 188]> input_631_cast_fp16 = conv(bias = const_216_to_fp16, dilations = input_629_dilations_0, groups = input_629_groups_0, pad = input_629_pad_0, pad_type = input_629_pad_type_0, strides = input_629_strides_0, weight = const_215_to_fp16, x = input_627_cast_fp16)[name = tensor<string, []>("input_631_cast_fp16")];
            tensor<fp16, [1, 512, 188]> input_633_cast_fp16 = silu(x = input_631_cast_fp16)[name = tensor<string, []>("input_633_cast_fp16")];
            tensor<string, []> x_279_pad_type_0 = const()[name = tensor<string, []>("x_279_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> x_279_strides_0 = const()[name = tensor<string, []>("x_279_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_279_pad_0 = const()[name = tensor<string, []>("x_279_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_279_dilations_0 = const()[name = tensor<string, []>("x_279_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> x_279_groups_0 = const()[name = tensor<string, []>("x_279_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [512, 512, 1]> encoder_module_layers_11_conv_pointwise_conv2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_11_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [512, 512, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(148797888)))];
            tensor<fp16, [512]> encoder_module_layers_11_conv_pointwise_conv2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_11_conv_pointwise_conv2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(149322240)))];
            tensor<fp16, [1, 512, 188]> x_279_cast_fp16 = conv(bias = encoder_module_layers_11_conv_pointwise_conv2_bias_to_fp16, dilations = x_279_dilations_0, groups = x_279_groups_0, pad = x_279_pad_0, pad_type = x_279_pad_type_0, strides = x_279_strides_0, weight = encoder_module_layers_11_conv_pointwise_conv2_weight_to_fp16, x = input_633_cast_fp16)[name = tensor<string, []>("x_279_cast_fp16")];
            tensor<int32, [3]> input_635_perm_0 = const()[name = tensor<string, []>("input_635_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 512]> input_635_cast_fp16 = transpose(perm = input_635_perm_0, x = x_279_cast_fp16)[name = tensor<string, []>("transpose_121")];
            tensor<fp16, [1, 188, 512]> input_637_cast_fp16 = add(x = input_619_cast_fp16, y = input_635_cast_fp16)[name = tensor<string, []>("input_637_cast_fp16")];
            tensor<int32, [1]> input_639_axes_0 = const()[name = tensor<string, []>("input_639_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_11_norm_feed_forward2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_11_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(149323328)))];
            tensor<fp16, [512]> encoder_module_layers_11_norm_feed_forward2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_11_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(149324416)))];
            tensor<fp16, [1, 188, 512]> input_639_cast_fp16 = layer_norm(axes = input_639_axes_0, beta = encoder_module_layers_11_norm_feed_forward2_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_11_norm_feed_forward2_weight_to_fp16, x = input_637_cast_fp16)[name = tensor<string, []>("input_639_cast_fp16")];
            tensor<fp16, [2048, 512]> encoder_module_layers_11_feed_forward2_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_11_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [2048, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(149325504)))];
            tensor<fp16, [2048]> encoder_module_layers_11_feed_forward2_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_11_feed_forward2_linear1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(151422720)))];
            tensor<fp16, [1, 188, 2048]> linear_107_cast_fp16 = linear(bias = encoder_module_layers_11_feed_forward2_linear1_bias_to_fp16, weight = encoder_module_layers_11_feed_forward2_linear1_weight_to_fp16, x = input_639_cast_fp16)[name = tensor<string, []>("linear_107_cast_fp16")];
            tensor<fp16, [1, 188, 2048]> input_643_cast_fp16 = silu(x = linear_107_cast_fp16)[name = tensor<string, []>("input_643_cast_fp16")];
            tensor<fp16, [512, 2048]> encoder_module_layers_11_feed_forward2_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_11_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [512, 2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(151426880)))];
            tensor<fp16, [512]> encoder_module_layers_11_feed_forward2_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_11_feed_forward2_linear2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(153524096)))];
            tensor<fp16, [1, 188, 512]> linear_108_cast_fp16 = linear(bias = encoder_module_layers_11_feed_forward2_linear2_bias_to_fp16, weight = encoder_module_layers_11_feed_forward2_linear2_weight_to_fp16, x = input_643_cast_fp16)[name = tensor<string, []>("linear_108_cast_fp16")];
            tensor<fp16, []> var_2406_to_fp16 = const()[name = tensor<string, []>("op_2406_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 512]> var_2407_cast_fp16 = mul(x = linear_108_cast_fp16, y = var_2406_to_fp16)[name = tensor<string, []>("op_2407_cast_fp16")];
            tensor<fp16, [1, 188, 512]> input_649_cast_fp16 = add(x = input_637_cast_fp16, y = var_2407_cast_fp16)[name = tensor<string, []>("input_649_cast_fp16")];
            tensor<int32, [1]> input_651_axes_0 = const()[name = tensor<string, []>("input_651_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_11_norm_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_11_norm_out_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(153525184)))];
            tensor<fp16, [512]> encoder_module_layers_11_norm_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_11_norm_out_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(153526272)))];
            tensor<fp16, [1, 188, 512]> input_651_cast_fp16 = layer_norm(axes = input_651_axes_0, beta = encoder_module_layers_11_norm_out_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_11_norm_out_weight_to_fp16, x = input_649_cast_fp16)[name = tensor<string, []>("input_651_cast_fp16")];
            tensor<int32, [1]> input_653_axes_0 = const()[name = tensor<string, []>("input_653_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_12_norm_feed_forward1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_12_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(153527360)))];
            tensor<fp16, [512]> encoder_module_layers_12_norm_feed_forward1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_12_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(153528448)))];
            tensor<fp16, [1, 188, 512]> input_653_cast_fp16 = layer_norm(axes = input_653_axes_0, beta = encoder_module_layers_12_norm_feed_forward1_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_12_norm_feed_forward1_weight_to_fp16, x = input_651_cast_fp16)[name = tensor<string, []>("input_653_cast_fp16")];
            tensor<fp16, [2048, 512]> encoder_module_layers_12_feed_forward1_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_12_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [2048, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(153529536)))];
            tensor<fp16, [2048]> encoder_module_layers_12_feed_forward1_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_12_feed_forward1_linear1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(155626752)))];
            tensor<fp16, [1, 188, 2048]> linear_109_cast_fp16 = linear(bias = encoder_module_layers_12_feed_forward1_linear1_bias_to_fp16, weight = encoder_module_layers_12_feed_forward1_linear1_weight_to_fp16, x = input_653_cast_fp16)[name = tensor<string, []>("linear_109_cast_fp16")];
            tensor<fp16, [1, 188, 2048]> input_657_cast_fp16 = silu(x = linear_109_cast_fp16)[name = tensor<string, []>("input_657_cast_fp16")];
            tensor<fp16, [512, 2048]> encoder_module_layers_12_feed_forward1_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_12_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [512, 2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(155630912)))];
            tensor<fp16, [512]> encoder_module_layers_12_feed_forward1_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_12_feed_forward1_linear2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(157728128)))];
            tensor<fp16, [1, 188, 512]> linear_110_cast_fp16 = linear(bias = encoder_module_layers_12_feed_forward1_linear2_bias_to_fp16, weight = encoder_module_layers_12_feed_forward1_linear2_weight_to_fp16, x = input_657_cast_fp16)[name = tensor<string, []>("linear_110_cast_fp16")];
            tensor<fp16, []> var_2437_to_fp16 = const()[name = tensor<string, []>("op_2437_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 512]> var_2438_cast_fp16 = mul(x = linear_110_cast_fp16, y = var_2437_to_fp16)[name = tensor<string, []>("op_2438_cast_fp16")];
            tensor<fp16, [1, 188, 512]> input_663_cast_fp16 = add(x = input_651_cast_fp16, y = var_2438_cast_fp16)[name = tensor<string, []>("input_663_cast_fp16")];
            tensor<int32, [1]> query_25_axes_0 = const()[name = tensor<string, []>("query_25_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_12_norm_self_att_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_12_norm_self_att_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(157729216)))];
            tensor<fp16, [512]> encoder_module_layers_12_norm_self_att_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_12_norm_self_att_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(157730304)))];
            tensor<fp16, [1, 188, 512]> query_25_cast_fp16 = layer_norm(axes = query_25_axes_0, beta = encoder_module_layers_12_norm_self_att_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_12_norm_self_att_weight_to_fp16, x = input_663_cast_fp16)[name = tensor<string, []>("query_25_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_12_self_attn_linear_q_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_12_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(157731392)))];
            tensor<fp16, [512]> encoder_module_layers_12_self_attn_linear_q_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_12_self_attn_linear_q_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(158255744)))];
            tensor<fp16, [1, 188, 512]> linear_111_cast_fp16 = linear(bias = encoder_module_layers_12_self_attn_linear_q_bias_to_fp16, weight = encoder_module_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_2455 = const()[name = tensor<string, []>("op_2455"), val = tensor<int32, [4]>([1, -1, 8, 64])];
            tensor<fp16, [1, 188, 8, 64]> q_73_cast_fp16 = reshape(shape = var_2455, x = linear_111_cast_fp16)[name = tensor<string, []>("q_73_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_12_self_attn_linear_k_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_12_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(158256832)))];
            tensor<fp16, [512]> encoder_module_layers_12_self_attn_linear_k_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_12_self_attn_linear_k_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(158781184)))];
            tensor<fp16, [1, 188, 512]> linear_112_cast_fp16 = linear(bias = encoder_module_layers_12_self_attn_linear_k_bias_to_fp16, weight = encoder_module_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_2460 = const()[name = tensor<string, []>("op_2460"), val = tensor<int32, [4]>([1, -1, 8, 64])];
            tensor<fp16, [1, 188, 8, 64]> k_49_cast_fp16 = reshape(shape = var_2460, x = linear_112_cast_fp16)[name = tensor<string, []>("k_49_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_12_self_attn_linear_v_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_12_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(158782272)))];
            tensor<fp16, [512]> encoder_module_layers_12_self_attn_linear_v_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_12_self_attn_linear_v_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(159306624)))];
            tensor<fp16, [1, 188, 512]> linear_113_cast_fp16 = linear(bias = encoder_module_layers_12_self_attn_linear_v_bias_to_fp16, weight = encoder_module_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_2465 = const()[name = tensor<string, []>("op_2465"), val = tensor<int32, [4]>([1, -1, 8, 64])];
            tensor<fp16, [1, 188, 8, 64]> v_25_cast_fp16 = reshape(shape = var_2465, x = linear_113_cast_fp16)[name = tensor<string, []>("v_25_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, 64]> encoder_module_layers_12_self_attn_pos_bias_u_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_12_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(159307712)))];
            tensor<fp16, [1, 188, 8, 64]> var_2477_cast_fp16 = add(x = q_73_cast_fp16, y = encoder_module_layers_12_self_attn_pos_bias_u_to_fp16)[name = tensor<string, []>("op_2477_cast_fp16")];
            tensor<fp16, [8, 64]> encoder_module_layers_12_self_attn_pos_bias_v_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_12_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(159308800)))];
            tensor<fp16, [1, 188, 8, 64]> var_2479_cast_fp16 = add(x = q_73_cast_fp16, y = encoder_module_layers_12_self_attn_pos_bias_v_to_fp16)[name = tensor<string, []>("op_2479_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_287_transpose_x_0 = const()[name = tensor<string, []>("x_287_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_287_transpose_y_0 = const()[name = tensor<string, []>("x_287_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 64, 375]> var_2481_to_fp16 = const()[name = tensor<string, []>("op_2481_to_fp16"), val = tensor<fp16, [1, 8, 64, 375]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(159309888)))];
            tensor<fp16, [1, 8, 188, 64]> q_with_bias_v_25_cast_fp16 = transpose(perm = q_with_bias_v_25_perm_0, x = var_2479_cast_fp16)[name = tensor<string, []>("transpose_119")];
            tensor<fp16, [1, 8, 188, 375]> x_287_cast_fp16 = matmul(transpose_x = x_287_transpose_x_0, transpose_y = x_287_transpose_y_0, x = q_with_bias_v_25_cast_fp16, y = var_2481_to_fp16)[name = tensor<string, []>("x_287_cast_fp16")];
            tensor<int32, [8]> x_289_pad_0 = const()[name = tensor<string, []>("x_289_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            tensor<string, []> x_289_mode_0 = const()[name = tensor<string, []>("x_289_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_149_to_fp16 = const()[name = tensor<string, []>("const_149_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_289_cast_fp16 = pad(constant_val = const_149_to_fp16, mode = x_289_mode_0, pad = x_289_pad_0, x = x_287_cast_fp16)[name = tensor<string, []>("x_289_cast_fp16")];
            tensor<int32, [4]> var_2489 = const()[name = tensor<string, []>("op_2489"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_291_cast_fp16 = reshape(shape = var_2489, x = x_289_cast_fp16)[name = tensor<string, []>("x_291_cast_fp16")];
            tensor<int32, [4]> var_2493_begin_0 = const()[name = tensor<string, []>("op_2493_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_2493_end_0 = const()[name = tensor<string, []>("op_2493_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_2493_end_mask_0 = const()[name = tensor<string, []>("op_2493_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_2493_cast_fp16 = slice_by_index(begin = var_2493_begin_0, end = var_2493_end_0, end_mask = var_2493_end_mask_0, x = x_291_cast_fp16)[name = tensor<string, []>("op_2493_cast_fp16")];
            tensor<int32, [4]> var_2494 = const()[name = tensor<string, []>("op_2494"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_49_cast_fp16 = reshape(shape = var_2494, x = var_2493_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_75_perm_0 = const()[name = tensor<string, []>("transpose_75_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_76_perm_0 = const()[name = tensor<string, []>("transpose_76_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 64, 188]> transpose_76 = transpose(perm = transpose_76_perm_0, x = k_49_cast_fp16)[name = tensor<string, []>("transpose_117")];
            tensor<fp16, [1, 8, 188, 64]> transpose_75 = transpose(perm = transpose_75_perm_0, x = var_2477_cast_fp16)[name = tensor<string, []>("transpose_118")];
            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_75, y = transpose_76)[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_2503_cast_fp16 = add(x = matrix_ac_25_cast_fp16, y = matrix_bd_51_cast_fp16)[name = tensor<string, []>("op_2503_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, []>(0x1p-3)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_49_cast_fp16 = mul(x = var_2503_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_153_to_fp16, b = _inversed_scores_49_cast_fp16, cond = mask_7)[name = tensor<string, []>("scores_51_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_2509_cast_fp16 = softmax(axis = var_138, x = scores_51_cast_fp16)[name = tensor<string, []>("op_2509_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_665_cast_fp16 = select(a = var_154_to_fp16, b = var_2509_cast_fp16, cond = mask_7)[name = tensor<string, []>("input_665_cast_fp16")];
            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, 188, 64]> value_29_cast_fp16 = transpose(perm = value_29_perm_0, x = v_25_cast_fp16)[name = tensor<string, []>("transpose_120")];
            tensor<fp16, [1, 8, 188, 64]> x_293_cast_fp16 = matmul(transpose_x = x_293_transpose_x_0, transpose_y = x_293_transpose_y_0, x = input_665_cast_fp16, y = value_29_cast_fp16)[name = tensor<string, []>("x_293_cast_fp16")];
            tensor<int32, [4]> var_2513_perm_0 = const()[name = tensor<string, []>("op_2513_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2514 = const()[name = tensor<string, []>("op_2514"), val = tensor<int32, [3]>([1, -1, 512])];
            tensor<fp16, [1, 188, 8, 64]> var_2513_cast_fp16 = transpose(perm = var_2513_perm_0, x = x_293_cast_fp16)[name = tensor<string, []>("transpose_116")];
            tensor<fp16, [1, 188, 512]> input_667_cast_fp16 = reshape(shape = var_2514, x = var_2513_cast_fp16)[name = tensor<string, []>("input_667_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_12_self_attn_linear_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_12_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(159693952)))];
            tensor<fp16, [512]> encoder_module_layers_12_self_attn_linear_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_12_self_attn_linear_out_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(160218304)))];
            tensor<fp16, [1, 188, 512]> linear_115_cast_fp16 = linear(bias = encoder_module_layers_12_self_attn_linear_out_bias_to_fp16, weight = encoder_module_layers_12_self_attn_linear_out_weight_to_fp16, x = input_667_cast_fp16)[name = tensor<string, []>("linear_115_cast_fp16")];
            tensor<fp16, [1, 188, 512]> input_671_cast_fp16 = add(x = input_663_cast_fp16, y = linear_115_cast_fp16)[name = tensor<string, []>("input_671_cast_fp16")];
            tensor<int32, [1]> x_297_axes_0 = const()[name = tensor<string, []>("x_297_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_12_norm_conv_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_12_norm_conv_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(160219392)))];
            tensor<fp16, [512]> encoder_module_layers_12_norm_conv_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_12_norm_conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(160220480)))];
            tensor<fp16, [1, 188, 512]> x_297_cast_fp16 = layer_norm(axes = x_297_axes_0, beta = encoder_module_layers_12_norm_conv_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_12_norm_conv_weight_to_fp16, x = input_671_cast_fp16)[name = tensor<string, []>("x_297_cast_fp16")];
            tensor<int32, [3]> input_673_perm_0 = const()[name = tensor<string, []>("input_673_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> input_675_pad_type_0 = const()[name = tensor<string, []>("input_675_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_675_strides_0 = const()[name = tensor<string, []>("input_675_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_675_pad_0 = const()[name = tensor<string, []>("input_675_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_675_dilations_0 = const()[name = tensor<string, []>("input_675_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_675_groups_0 = const()[name = tensor<string, []>("input_675_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1024, 512, 1]> encoder_module_layers_12_conv_pointwise_conv1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_12_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [1024, 512, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(160221568)))];
            tensor<fp16, [1024]> encoder_module_layers_12_conv_pointwise_conv1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_12_conv_pointwise_conv1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(161270208)))];
            tensor<fp16, [1, 512, 188]> input_673_cast_fp16 = transpose(perm = input_673_perm_0, x = x_297_cast_fp16)[name = tensor<string, []>("transpose_115")];
            tensor<fp16, [1, 1024, 188]> input_675_cast_fp16 = conv(bias = encoder_module_layers_12_conv_pointwise_conv1_bias_to_fp16, dilations = input_675_dilations_0, groups = input_675_groups_0, pad = input_675_pad_0, pad_type = input_675_pad_type_0, strides = input_675_strides_0, weight = encoder_module_layers_12_conv_pointwise_conv1_weight_to_fp16, x = input_673_cast_fp16)[name = tensor<string, []>("input_675_cast_fp16")];
            tensor<int32, []> x_299_split_num_splits_0 = const()[name = tensor<string, []>("x_299_split_num_splits_0"), val = tensor<int32, []>(2)];
            tensor<int32, []> x_299_split_axis_0 = const()[name = tensor<string, []>("x_299_split_axis_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1, 512, 188]> x_299_split_cast_fp16_0, tensor<fp16, [1, 512, 188]> x_299_split_cast_fp16_1 = split(axis = x_299_split_axis_0, num_splits = x_299_split_num_splits_0, x = input_675_cast_fp16)[name = tensor<string, []>("x_299_split_cast_fp16")];
            tensor<fp16, [1, 512, 188]> x_299_split_1_sigmoid_cast_fp16 = sigmoid(x = x_299_split_cast_fp16_1)[name = tensor<string, []>("x_299_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 512, 188]> x_299_cast_fp16 = mul(x = x_299_split_cast_fp16_0, y = x_299_split_1_sigmoid_cast_fp16)[name = tensor<string, []>("x_299_cast_fp16")];
            tensor<fp16, [1, 512, 188]> input_677_cast_fp16 = select(a = var_154_to_fp16, b = x_299_cast_fp16, cond = var_450)[name = tensor<string, []>("input_677_cast_fp16")];
            tensor<int32, [6]> input_679_pad_0 = const()[name = tensor<string, []>("input_679_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            tensor<string, []> input_679_mode_0 = const()[name = tensor<string, []>("input_679_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_152_to_fp16 = const()[name = tensor<string, []>("const_152_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 512, 196]> input_679_cast_fp16 = pad(constant_val = const_152_to_fp16, mode = input_679_mode_0, pad = input_679_pad_0, x = input_677_cast_fp16)[name = tensor<string, []>("input_679_cast_fp16")];
            tensor<string, []> input_681_pad_type_0 = const()[name = tensor<string, []>("input_681_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, []> input_681_groups_0 = const()[name = tensor<string, []>("input_681_groups_0"), val = tensor<int32, []>(512)];
            tensor<int32, [1]> input_681_strides_0 = const()[name = tensor<string, []>("input_681_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_681_pad_0 = const()[name = tensor<string, []>("input_681_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_681_dilations_0 = const()[name = tensor<string, []>("input_681_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 9]> const_217_to_fp16 = const()[name = tensor<string, []>("const_217_to_fp16"), val = tensor<fp16, [512, 1, 9]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(161272320)))];
            tensor<fp16, [512]> const_218_to_fp16 = const()[name = tensor<string, []>("const_218_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(161281600)))];
            tensor<fp16, [1, 512, 188]> input_683_cast_fp16 = conv(bias = const_218_to_fp16, dilations = input_681_dilations_0, groups = input_681_groups_0, pad = input_681_pad_0, pad_type = input_681_pad_type_0, strides = input_681_strides_0, weight = const_217_to_fp16, x = input_679_cast_fp16)[name = tensor<string, []>("input_683_cast_fp16")];
            tensor<fp16, [1, 512, 188]> input_685_cast_fp16 = silu(x = input_683_cast_fp16)[name = tensor<string, []>("input_685_cast_fp16")];
            tensor<string, []> x_301_pad_type_0 = const()[name = tensor<string, []>("x_301_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> x_301_strides_0 = const()[name = tensor<string, []>("x_301_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_301_pad_0 = const()[name = tensor<string, []>("x_301_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_301_dilations_0 = const()[name = tensor<string, []>("x_301_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> x_301_groups_0 = const()[name = tensor<string, []>("x_301_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [512, 512, 1]> encoder_module_layers_12_conv_pointwise_conv2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_12_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [512, 512, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(161282688)))];
            tensor<fp16, [512]> encoder_module_layers_12_conv_pointwise_conv2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_12_conv_pointwise_conv2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(161807040)))];
            tensor<fp16, [1, 512, 188]> x_301_cast_fp16 = conv(bias = encoder_module_layers_12_conv_pointwise_conv2_bias_to_fp16, dilations = x_301_dilations_0, groups = x_301_groups_0, pad = x_301_pad_0, pad_type = x_301_pad_type_0, strides = x_301_strides_0, weight = encoder_module_layers_12_conv_pointwise_conv2_weight_to_fp16, x = input_685_cast_fp16)[name = tensor<string, []>("x_301_cast_fp16")];
            tensor<int32, [3]> input_687_perm_0 = const()[name = tensor<string, []>("input_687_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 512]> input_687_cast_fp16 = transpose(perm = input_687_perm_0, x = x_301_cast_fp16)[name = tensor<string, []>("transpose_114")];
            tensor<fp16, [1, 188, 512]> input_689_cast_fp16 = add(x = input_671_cast_fp16, y = input_687_cast_fp16)[name = tensor<string, []>("input_689_cast_fp16")];
            tensor<int32, [1]> input_691_axes_0 = const()[name = tensor<string, []>("input_691_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_12_norm_feed_forward2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_12_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(161808128)))];
            tensor<fp16, [512]> encoder_module_layers_12_norm_feed_forward2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_12_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(161809216)))];
            tensor<fp16, [1, 188, 512]> input_691_cast_fp16 = layer_norm(axes = input_691_axes_0, beta = encoder_module_layers_12_norm_feed_forward2_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_12_norm_feed_forward2_weight_to_fp16, x = input_689_cast_fp16)[name = tensor<string, []>("input_691_cast_fp16")];
            tensor<fp16, [2048, 512]> encoder_module_layers_12_feed_forward2_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_12_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [2048, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(161810304)))];
            tensor<fp16, [2048]> encoder_module_layers_12_feed_forward2_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_12_feed_forward2_linear1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(163907520)))];
            tensor<fp16, [1, 188, 2048]> linear_116_cast_fp16 = linear(bias = encoder_module_layers_12_feed_forward2_linear1_bias_to_fp16, weight = encoder_module_layers_12_feed_forward2_linear1_weight_to_fp16, x = input_691_cast_fp16)[name = tensor<string, []>("linear_116_cast_fp16")];
            tensor<fp16, [1, 188, 2048]> input_695_cast_fp16 = silu(x = linear_116_cast_fp16)[name = tensor<string, []>("input_695_cast_fp16")];
            tensor<fp16, [512, 2048]> encoder_module_layers_12_feed_forward2_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_12_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [512, 2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(163911680)))];
            tensor<fp16, [512]> encoder_module_layers_12_feed_forward2_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_12_feed_forward2_linear2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(166008896)))];
            tensor<fp16, [1, 188, 512]> linear_117_cast_fp16 = linear(bias = encoder_module_layers_12_feed_forward2_linear2_bias_to_fp16, weight = encoder_module_layers_12_feed_forward2_linear2_weight_to_fp16, x = input_695_cast_fp16)[name = tensor<string, []>("linear_117_cast_fp16")];
            tensor<fp16, []> var_2580_to_fp16 = const()[name = tensor<string, []>("op_2580_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 512]> var_2581_cast_fp16 = mul(x = linear_117_cast_fp16, y = var_2580_to_fp16)[name = tensor<string, []>("op_2581_cast_fp16")];
            tensor<fp16, [1, 188, 512]> input_701_cast_fp16 = add(x = input_689_cast_fp16, y = var_2581_cast_fp16)[name = tensor<string, []>("input_701_cast_fp16")];
            tensor<int32, [1]> input_703_axes_0 = const()[name = tensor<string, []>("input_703_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_12_norm_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_12_norm_out_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(166009984)))];
            tensor<fp16, [512]> encoder_module_layers_12_norm_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_12_norm_out_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(166011072)))];
            tensor<fp16, [1, 188, 512]> input_703_cast_fp16 = layer_norm(axes = input_703_axes_0, beta = encoder_module_layers_12_norm_out_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_12_norm_out_weight_to_fp16, x = input_701_cast_fp16)[name = tensor<string, []>("input_703_cast_fp16")];
            tensor<int32, [1]> input_705_axes_0 = const()[name = tensor<string, []>("input_705_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_13_norm_feed_forward1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_13_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(166012160)))];
            tensor<fp16, [512]> encoder_module_layers_13_norm_feed_forward1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_13_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(166013248)))];
            tensor<fp16, [1, 188, 512]> input_705_cast_fp16 = layer_norm(axes = input_705_axes_0, beta = encoder_module_layers_13_norm_feed_forward1_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_13_norm_feed_forward1_weight_to_fp16, x = input_703_cast_fp16)[name = tensor<string, []>("input_705_cast_fp16")];
            tensor<fp16, [2048, 512]> encoder_module_layers_13_feed_forward1_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_13_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [2048, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(166014336)))];
            tensor<fp16, [2048]> encoder_module_layers_13_feed_forward1_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_13_feed_forward1_linear1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(168111552)))];
            tensor<fp16, [1, 188, 2048]> linear_118_cast_fp16 = linear(bias = encoder_module_layers_13_feed_forward1_linear1_bias_to_fp16, weight = encoder_module_layers_13_feed_forward1_linear1_weight_to_fp16, x = input_705_cast_fp16)[name = tensor<string, []>("linear_118_cast_fp16")];
            tensor<fp16, [1, 188, 2048]> input_709_cast_fp16 = silu(x = linear_118_cast_fp16)[name = tensor<string, []>("input_709_cast_fp16")];
            tensor<fp16, [512, 2048]> encoder_module_layers_13_feed_forward1_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_13_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [512, 2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(168115712)))];
            tensor<fp16, [512]> encoder_module_layers_13_feed_forward1_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_13_feed_forward1_linear2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(170212928)))];
            tensor<fp16, [1, 188, 512]> linear_119_cast_fp16 = linear(bias = encoder_module_layers_13_feed_forward1_linear2_bias_to_fp16, weight = encoder_module_layers_13_feed_forward1_linear2_weight_to_fp16, x = input_709_cast_fp16)[name = tensor<string, []>("linear_119_cast_fp16")];
            tensor<fp16, []> var_2611_to_fp16 = const()[name = tensor<string, []>("op_2611_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 512]> var_2612_cast_fp16 = mul(x = linear_119_cast_fp16, y = var_2611_to_fp16)[name = tensor<string, []>("op_2612_cast_fp16")];
            tensor<fp16, [1, 188, 512]> input_715_cast_fp16 = add(x = input_703_cast_fp16, y = var_2612_cast_fp16)[name = tensor<string, []>("input_715_cast_fp16")];
            tensor<int32, [1]> query_27_axes_0 = const()[name = tensor<string, []>("query_27_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_13_norm_self_att_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_13_norm_self_att_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(170214016)))];
            tensor<fp16, [512]> encoder_module_layers_13_norm_self_att_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_13_norm_self_att_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(170215104)))];
            tensor<fp16, [1, 188, 512]> query_27_cast_fp16 = layer_norm(axes = query_27_axes_0, beta = encoder_module_layers_13_norm_self_att_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_13_norm_self_att_weight_to_fp16, x = input_715_cast_fp16)[name = tensor<string, []>("query_27_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_13_self_attn_linear_q_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_13_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(170216192)))];
            tensor<fp16, [512]> encoder_module_layers_13_self_attn_linear_q_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_13_self_attn_linear_q_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(170740544)))];
            tensor<fp16, [1, 188, 512]> linear_120_cast_fp16 = linear(bias = encoder_module_layers_13_self_attn_linear_q_bias_to_fp16, weight = encoder_module_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_2629 = const()[name = tensor<string, []>("op_2629"), val = tensor<int32, [4]>([1, -1, 8, 64])];
            tensor<fp16, [1, 188, 8, 64]> q_79_cast_fp16 = reshape(shape = var_2629, x = linear_120_cast_fp16)[name = tensor<string, []>("q_79_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_13_self_attn_linear_k_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_13_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(170741632)))];
            tensor<fp16, [512]> encoder_module_layers_13_self_attn_linear_k_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_13_self_attn_linear_k_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(171265984)))];
            tensor<fp16, [1, 188, 512]> linear_121_cast_fp16 = linear(bias = encoder_module_layers_13_self_attn_linear_k_bias_to_fp16, weight = encoder_module_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_2634 = const()[name = tensor<string, []>("op_2634"), val = tensor<int32, [4]>([1, -1, 8, 64])];
            tensor<fp16, [1, 188, 8, 64]> k_53_cast_fp16 = reshape(shape = var_2634, x = linear_121_cast_fp16)[name = tensor<string, []>("k_53_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_13_self_attn_linear_v_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_13_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(171267072)))];
            tensor<fp16, [512]> encoder_module_layers_13_self_attn_linear_v_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_13_self_attn_linear_v_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(171791424)))];
            tensor<fp16, [1, 188, 512]> linear_122_cast_fp16 = linear(bias = encoder_module_layers_13_self_attn_linear_v_bias_to_fp16, weight = encoder_module_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_2639 = const()[name = tensor<string, []>("op_2639"), val = tensor<int32, [4]>([1, -1, 8, 64])];
            tensor<fp16, [1, 188, 8, 64]> v_27_cast_fp16 = reshape(shape = var_2639, x = linear_122_cast_fp16)[name = tensor<string, []>("v_27_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, 64]> encoder_module_layers_13_self_attn_pos_bias_u_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_13_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(171792512)))];
            tensor<fp16, [1, 188, 8, 64]> var_2651_cast_fp16 = add(x = q_79_cast_fp16, y = encoder_module_layers_13_self_attn_pos_bias_u_to_fp16)[name = tensor<string, []>("op_2651_cast_fp16")];
            tensor<fp16, [8, 64]> encoder_module_layers_13_self_attn_pos_bias_v_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_13_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(171793600)))];
            tensor<fp16, [1, 188, 8, 64]> var_2653_cast_fp16 = add(x = q_79_cast_fp16, y = encoder_module_layers_13_self_attn_pos_bias_v_to_fp16)[name = tensor<string, []>("op_2653_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_309_transpose_x_0 = const()[name = tensor<string, []>("x_309_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_309_transpose_y_0 = const()[name = tensor<string, []>("x_309_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 64, 375]> var_2655_to_fp16 = const()[name = tensor<string, []>("op_2655_to_fp16"), val = tensor<fp16, [1, 8, 64, 375]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(171794688)))];
            tensor<fp16, [1, 8, 188, 64]> q_with_bias_v_27_cast_fp16 = transpose(perm = q_with_bias_v_27_perm_0, x = var_2653_cast_fp16)[name = tensor<string, []>("transpose_112")];
            tensor<fp16, [1, 8, 188, 375]> x_309_cast_fp16 = matmul(transpose_x = x_309_transpose_x_0, transpose_y = x_309_transpose_y_0, x = q_with_bias_v_27_cast_fp16, y = var_2655_to_fp16)[name = tensor<string, []>("x_309_cast_fp16")];
            tensor<int32, [8]> x_311_pad_0 = const()[name = tensor<string, []>("x_311_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            tensor<string, []> x_311_mode_0 = const()[name = tensor<string, []>("x_311_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_159_to_fp16 = const()[name = tensor<string, []>("const_159_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_311_cast_fp16 = pad(constant_val = const_159_to_fp16, mode = x_311_mode_0, pad = x_311_pad_0, x = x_309_cast_fp16)[name = tensor<string, []>("x_311_cast_fp16")];
            tensor<int32, [4]> var_2663 = const()[name = tensor<string, []>("op_2663"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_313_cast_fp16 = reshape(shape = var_2663, x = x_311_cast_fp16)[name = tensor<string, []>("x_313_cast_fp16")];
            tensor<int32, [4]> var_2667_begin_0 = const()[name = tensor<string, []>("op_2667_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_2667_end_0 = const()[name = tensor<string, []>("op_2667_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_2667_end_mask_0 = const()[name = tensor<string, []>("op_2667_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_2667_cast_fp16 = slice_by_index(begin = var_2667_begin_0, end = var_2667_end_0, end_mask = var_2667_end_mask_0, x = x_313_cast_fp16)[name = tensor<string, []>("op_2667_cast_fp16")];
            tensor<int32, [4]> var_2668 = const()[name = tensor<string, []>("op_2668"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_53_cast_fp16 = reshape(shape = var_2668, x = var_2667_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_77_perm_0 = const()[name = tensor<string, []>("transpose_77_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_78_perm_0 = const()[name = tensor<string, []>("transpose_78_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 64, 188]> transpose_78 = transpose(perm = transpose_78_perm_0, x = k_53_cast_fp16)[name = tensor<string, []>("transpose_110")];
            tensor<fp16, [1, 8, 188, 64]> transpose_77 = transpose(perm = transpose_77_perm_0, x = var_2651_cast_fp16)[name = tensor<string, []>("transpose_111")];
            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_77, y = transpose_78)[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_2677_cast_fp16 = add(x = matrix_ac_27_cast_fp16, y = matrix_bd_55_cast_fp16)[name = tensor<string, []>("op_2677_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, []>(0x1p-3)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_53_cast_fp16 = mul(x = var_2677_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_153_to_fp16, b = _inversed_scores_53_cast_fp16, cond = mask_7)[name = tensor<string, []>("scores_55_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_2683_cast_fp16 = softmax(axis = var_138, x = scores_55_cast_fp16)[name = tensor<string, []>("op_2683_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_717_cast_fp16 = select(a = var_154_to_fp16, b = var_2683_cast_fp16, cond = mask_7)[name = tensor<string, []>("input_717_cast_fp16")];
            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, 188, 64]> value_31_cast_fp16 = transpose(perm = value_31_perm_0, x = v_27_cast_fp16)[name = tensor<string, []>("transpose_113")];
            tensor<fp16, [1, 8, 188, 64]> x_315_cast_fp16 = matmul(transpose_x = x_315_transpose_x_0, transpose_y = x_315_transpose_y_0, x = input_717_cast_fp16, y = value_31_cast_fp16)[name = tensor<string, []>("x_315_cast_fp16")];
            tensor<int32, [4]> var_2687_perm_0 = const()[name = tensor<string, []>("op_2687_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2688 = const()[name = tensor<string, []>("op_2688"), val = tensor<int32, [3]>([1, -1, 512])];
            tensor<fp16, [1, 188, 8, 64]> var_2687_cast_fp16 = transpose(perm = var_2687_perm_0, x = x_315_cast_fp16)[name = tensor<string, []>("transpose_109")];
            tensor<fp16, [1, 188, 512]> input_719_cast_fp16 = reshape(shape = var_2688, x = var_2687_cast_fp16)[name = tensor<string, []>("input_719_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_13_self_attn_linear_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_13_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(172178752)))];
            tensor<fp16, [512]> encoder_module_layers_13_self_attn_linear_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_13_self_attn_linear_out_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(172703104)))];
            tensor<fp16, [1, 188, 512]> linear_124_cast_fp16 = linear(bias = encoder_module_layers_13_self_attn_linear_out_bias_to_fp16, weight = encoder_module_layers_13_self_attn_linear_out_weight_to_fp16, x = input_719_cast_fp16)[name = tensor<string, []>("linear_124_cast_fp16")];
            tensor<fp16, [1, 188, 512]> input_723_cast_fp16 = add(x = input_715_cast_fp16, y = linear_124_cast_fp16)[name = tensor<string, []>("input_723_cast_fp16")];
            tensor<int32, [1]> x_319_axes_0 = const()[name = tensor<string, []>("x_319_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_13_norm_conv_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_13_norm_conv_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(172704192)))];
            tensor<fp16, [512]> encoder_module_layers_13_norm_conv_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_13_norm_conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(172705280)))];
            tensor<fp16, [1, 188, 512]> x_319_cast_fp16 = layer_norm(axes = x_319_axes_0, beta = encoder_module_layers_13_norm_conv_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_13_norm_conv_weight_to_fp16, x = input_723_cast_fp16)[name = tensor<string, []>("x_319_cast_fp16")];
            tensor<int32, [3]> input_725_perm_0 = const()[name = tensor<string, []>("input_725_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> input_727_pad_type_0 = const()[name = tensor<string, []>("input_727_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_727_strides_0 = const()[name = tensor<string, []>("input_727_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_727_pad_0 = const()[name = tensor<string, []>("input_727_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_727_dilations_0 = const()[name = tensor<string, []>("input_727_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_727_groups_0 = const()[name = tensor<string, []>("input_727_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1024, 512, 1]> encoder_module_layers_13_conv_pointwise_conv1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_13_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [1024, 512, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(172706368)))];
            tensor<fp16, [1024]> encoder_module_layers_13_conv_pointwise_conv1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_13_conv_pointwise_conv1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(173755008)))];
            tensor<fp16, [1, 512, 188]> input_725_cast_fp16 = transpose(perm = input_725_perm_0, x = x_319_cast_fp16)[name = tensor<string, []>("transpose_108")];
            tensor<fp16, [1, 1024, 188]> input_727_cast_fp16 = conv(bias = encoder_module_layers_13_conv_pointwise_conv1_bias_to_fp16, dilations = input_727_dilations_0, groups = input_727_groups_0, pad = input_727_pad_0, pad_type = input_727_pad_type_0, strides = input_727_strides_0, weight = encoder_module_layers_13_conv_pointwise_conv1_weight_to_fp16, x = input_725_cast_fp16)[name = tensor<string, []>("input_727_cast_fp16")];
            tensor<int32, []> x_321_split_num_splits_0 = const()[name = tensor<string, []>("x_321_split_num_splits_0"), val = tensor<int32, []>(2)];
            tensor<int32, []> x_321_split_axis_0 = const()[name = tensor<string, []>("x_321_split_axis_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1, 512, 188]> x_321_split_cast_fp16_0, tensor<fp16, [1, 512, 188]> x_321_split_cast_fp16_1 = split(axis = x_321_split_axis_0, num_splits = x_321_split_num_splits_0, x = input_727_cast_fp16)[name = tensor<string, []>("x_321_split_cast_fp16")];
            tensor<fp16, [1, 512, 188]> x_321_split_1_sigmoid_cast_fp16 = sigmoid(x = x_321_split_cast_fp16_1)[name = tensor<string, []>("x_321_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 512, 188]> x_321_cast_fp16 = mul(x = x_321_split_cast_fp16_0, y = x_321_split_1_sigmoid_cast_fp16)[name = tensor<string, []>("x_321_cast_fp16")];
            tensor<fp16, [1, 512, 188]> input_729_cast_fp16 = select(a = var_154_to_fp16, b = x_321_cast_fp16, cond = var_450)[name = tensor<string, []>("input_729_cast_fp16")];
            tensor<int32, [6]> input_731_pad_0 = const()[name = tensor<string, []>("input_731_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            tensor<string, []> input_731_mode_0 = const()[name = tensor<string, []>("input_731_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_162_to_fp16 = const()[name = tensor<string, []>("const_162_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 512, 196]> input_731_cast_fp16 = pad(constant_val = const_162_to_fp16, mode = input_731_mode_0, pad = input_731_pad_0, x = input_729_cast_fp16)[name = tensor<string, []>("input_731_cast_fp16")];
            tensor<string, []> input_733_pad_type_0 = const()[name = tensor<string, []>("input_733_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, []> input_733_groups_0 = const()[name = tensor<string, []>("input_733_groups_0"), val = tensor<int32, []>(512)];
            tensor<int32, [1]> input_733_strides_0 = const()[name = tensor<string, []>("input_733_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_733_pad_0 = const()[name = tensor<string, []>("input_733_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_733_dilations_0 = const()[name = tensor<string, []>("input_733_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 9]> const_219_to_fp16 = const()[name = tensor<string, []>("const_219_to_fp16"), val = tensor<fp16, [512, 1, 9]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(173757120)))];
            tensor<fp16, [512]> const_220_to_fp16 = const()[name = tensor<string, []>("const_220_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(173766400)))];
            tensor<fp16, [1, 512, 188]> input_735_cast_fp16 = conv(bias = const_220_to_fp16, dilations = input_733_dilations_0, groups = input_733_groups_0, pad = input_733_pad_0, pad_type = input_733_pad_type_0, strides = input_733_strides_0, weight = const_219_to_fp16, x = input_731_cast_fp16)[name = tensor<string, []>("input_735_cast_fp16")];
            tensor<fp16, [1, 512, 188]> input_737_cast_fp16 = silu(x = input_735_cast_fp16)[name = tensor<string, []>("input_737_cast_fp16")];
            tensor<string, []> x_323_pad_type_0 = const()[name = tensor<string, []>("x_323_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> x_323_strides_0 = const()[name = tensor<string, []>("x_323_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_323_pad_0 = const()[name = tensor<string, []>("x_323_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_323_dilations_0 = const()[name = tensor<string, []>("x_323_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> x_323_groups_0 = const()[name = tensor<string, []>("x_323_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [512, 512, 1]> encoder_module_layers_13_conv_pointwise_conv2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_13_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [512, 512, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(173767488)))];
            tensor<fp16, [512]> encoder_module_layers_13_conv_pointwise_conv2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_13_conv_pointwise_conv2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(174291840)))];
            tensor<fp16, [1, 512, 188]> x_323_cast_fp16 = conv(bias = encoder_module_layers_13_conv_pointwise_conv2_bias_to_fp16, dilations = x_323_dilations_0, groups = x_323_groups_0, pad = x_323_pad_0, pad_type = x_323_pad_type_0, strides = x_323_strides_0, weight = encoder_module_layers_13_conv_pointwise_conv2_weight_to_fp16, x = input_737_cast_fp16)[name = tensor<string, []>("x_323_cast_fp16")];
            tensor<int32, [3]> input_739_perm_0 = const()[name = tensor<string, []>("input_739_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 512]> input_739_cast_fp16 = transpose(perm = input_739_perm_0, x = x_323_cast_fp16)[name = tensor<string, []>("transpose_107")];
            tensor<fp16, [1, 188, 512]> input_741_cast_fp16 = add(x = input_723_cast_fp16, y = input_739_cast_fp16)[name = tensor<string, []>("input_741_cast_fp16")];
            tensor<int32, [1]> input_743_axes_0 = const()[name = tensor<string, []>("input_743_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_13_norm_feed_forward2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_13_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(174292928)))];
            tensor<fp16, [512]> encoder_module_layers_13_norm_feed_forward2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_13_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(174294016)))];
            tensor<fp16, [1, 188, 512]> input_743_cast_fp16 = layer_norm(axes = input_743_axes_0, beta = encoder_module_layers_13_norm_feed_forward2_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_13_norm_feed_forward2_weight_to_fp16, x = input_741_cast_fp16)[name = tensor<string, []>("input_743_cast_fp16")];
            tensor<fp16, [2048, 512]> encoder_module_layers_13_feed_forward2_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_13_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [2048, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(174295104)))];
            tensor<fp16, [2048]> encoder_module_layers_13_feed_forward2_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_13_feed_forward2_linear1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(176392320)))];
            tensor<fp16, [1, 188, 2048]> linear_125_cast_fp16 = linear(bias = encoder_module_layers_13_feed_forward2_linear1_bias_to_fp16, weight = encoder_module_layers_13_feed_forward2_linear1_weight_to_fp16, x = input_743_cast_fp16)[name = tensor<string, []>("linear_125_cast_fp16")];
            tensor<fp16, [1, 188, 2048]> input_747_cast_fp16 = silu(x = linear_125_cast_fp16)[name = tensor<string, []>("input_747_cast_fp16")];
            tensor<fp16, [512, 2048]> encoder_module_layers_13_feed_forward2_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_13_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [512, 2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(176396480)))];
            tensor<fp16, [512]> encoder_module_layers_13_feed_forward2_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_13_feed_forward2_linear2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(178493696)))];
            tensor<fp16, [1, 188, 512]> linear_126_cast_fp16 = linear(bias = encoder_module_layers_13_feed_forward2_linear2_bias_to_fp16, weight = encoder_module_layers_13_feed_forward2_linear2_weight_to_fp16, x = input_747_cast_fp16)[name = tensor<string, []>("linear_126_cast_fp16")];
            tensor<fp16, []> var_2754_to_fp16 = const()[name = tensor<string, []>("op_2754_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 512]> var_2755_cast_fp16 = mul(x = linear_126_cast_fp16, y = var_2754_to_fp16)[name = tensor<string, []>("op_2755_cast_fp16")];
            tensor<fp16, [1, 188, 512]> input_753_cast_fp16 = add(x = input_741_cast_fp16, y = var_2755_cast_fp16)[name = tensor<string, []>("input_753_cast_fp16")];
            tensor<int32, [1]> input_755_axes_0 = const()[name = tensor<string, []>("input_755_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_13_norm_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_13_norm_out_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(178494784)))];
            tensor<fp16, [512]> encoder_module_layers_13_norm_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_13_norm_out_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(178495872)))];
            tensor<fp16, [1, 188, 512]> input_755_cast_fp16 = layer_norm(axes = input_755_axes_0, beta = encoder_module_layers_13_norm_out_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_13_norm_out_weight_to_fp16, x = input_753_cast_fp16)[name = tensor<string, []>("input_755_cast_fp16")];
            tensor<int32, [1]> input_757_axes_0 = const()[name = tensor<string, []>("input_757_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_14_norm_feed_forward1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_14_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(178496960)))];
            tensor<fp16, [512]> encoder_module_layers_14_norm_feed_forward1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_14_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(178498048)))];
            tensor<fp16, [1, 188, 512]> input_757_cast_fp16 = layer_norm(axes = input_757_axes_0, beta = encoder_module_layers_14_norm_feed_forward1_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_14_norm_feed_forward1_weight_to_fp16, x = input_755_cast_fp16)[name = tensor<string, []>("input_757_cast_fp16")];
            tensor<fp16, [2048, 512]> encoder_module_layers_14_feed_forward1_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_14_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [2048, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(178499136)))];
            tensor<fp16, [2048]> encoder_module_layers_14_feed_forward1_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_14_feed_forward1_linear1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(180596352)))];
            tensor<fp16, [1, 188, 2048]> linear_127_cast_fp16 = linear(bias = encoder_module_layers_14_feed_forward1_linear1_bias_to_fp16, weight = encoder_module_layers_14_feed_forward1_linear1_weight_to_fp16, x = input_757_cast_fp16)[name = tensor<string, []>("linear_127_cast_fp16")];
            tensor<fp16, [1, 188, 2048]> input_761_cast_fp16 = silu(x = linear_127_cast_fp16)[name = tensor<string, []>("input_761_cast_fp16")];
            tensor<fp16, [512, 2048]> encoder_module_layers_14_feed_forward1_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_14_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [512, 2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(180600512)))];
            tensor<fp16, [512]> encoder_module_layers_14_feed_forward1_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_14_feed_forward1_linear2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(182697728)))];
            tensor<fp16, [1, 188, 512]> linear_128_cast_fp16 = linear(bias = encoder_module_layers_14_feed_forward1_linear2_bias_to_fp16, weight = encoder_module_layers_14_feed_forward1_linear2_weight_to_fp16, x = input_761_cast_fp16)[name = tensor<string, []>("linear_128_cast_fp16")];
            tensor<fp16, []> var_2785_to_fp16 = const()[name = tensor<string, []>("op_2785_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 512]> var_2786_cast_fp16 = mul(x = linear_128_cast_fp16, y = var_2785_to_fp16)[name = tensor<string, []>("op_2786_cast_fp16")];
            tensor<fp16, [1, 188, 512]> input_767_cast_fp16 = add(x = input_755_cast_fp16, y = var_2786_cast_fp16)[name = tensor<string, []>("input_767_cast_fp16")];
            tensor<int32, [1]> query_29_axes_0 = const()[name = tensor<string, []>("query_29_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_14_norm_self_att_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_14_norm_self_att_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(182698816)))];
            tensor<fp16, [512]> encoder_module_layers_14_norm_self_att_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_14_norm_self_att_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(182699904)))];
            tensor<fp16, [1, 188, 512]> query_29_cast_fp16 = layer_norm(axes = query_29_axes_0, beta = encoder_module_layers_14_norm_self_att_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_14_norm_self_att_weight_to_fp16, x = input_767_cast_fp16)[name = tensor<string, []>("query_29_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_14_self_attn_linear_q_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_14_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(182700992)))];
            tensor<fp16, [512]> encoder_module_layers_14_self_attn_linear_q_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_14_self_attn_linear_q_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(183225344)))];
            tensor<fp16, [1, 188, 512]> linear_129_cast_fp16 = linear(bias = encoder_module_layers_14_self_attn_linear_q_bias_to_fp16, weight = encoder_module_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_2803 = const()[name = tensor<string, []>("op_2803"), val = tensor<int32, [4]>([1, -1, 8, 64])];
            tensor<fp16, [1, 188, 8, 64]> q_85_cast_fp16 = reshape(shape = var_2803, x = linear_129_cast_fp16)[name = tensor<string, []>("q_85_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_14_self_attn_linear_k_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_14_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(183226432)))];
            tensor<fp16, [512]> encoder_module_layers_14_self_attn_linear_k_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_14_self_attn_linear_k_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(183750784)))];
            tensor<fp16, [1, 188, 512]> linear_130_cast_fp16 = linear(bias = encoder_module_layers_14_self_attn_linear_k_bias_to_fp16, weight = encoder_module_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_2808 = const()[name = tensor<string, []>("op_2808"), val = tensor<int32, [4]>([1, -1, 8, 64])];
            tensor<fp16, [1, 188, 8, 64]> k_57_cast_fp16 = reshape(shape = var_2808, x = linear_130_cast_fp16)[name = tensor<string, []>("k_57_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_14_self_attn_linear_v_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_14_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(183751872)))];
            tensor<fp16, [512]> encoder_module_layers_14_self_attn_linear_v_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_14_self_attn_linear_v_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(184276224)))];
            tensor<fp16, [1, 188, 512]> linear_131_cast_fp16 = linear(bias = encoder_module_layers_14_self_attn_linear_v_bias_to_fp16, weight = encoder_module_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_2813 = const()[name = tensor<string, []>("op_2813"), val = tensor<int32, [4]>([1, -1, 8, 64])];
            tensor<fp16, [1, 188, 8, 64]> v_29_cast_fp16 = reshape(shape = var_2813, x = linear_131_cast_fp16)[name = tensor<string, []>("v_29_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, 64]> encoder_module_layers_14_self_attn_pos_bias_u_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_14_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(184277312)))];
            tensor<fp16, [1, 188, 8, 64]> var_2825_cast_fp16 = add(x = q_85_cast_fp16, y = encoder_module_layers_14_self_attn_pos_bias_u_to_fp16)[name = tensor<string, []>("op_2825_cast_fp16")];
            tensor<fp16, [8, 64]> encoder_module_layers_14_self_attn_pos_bias_v_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_14_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(184278400)))];
            tensor<fp16, [1, 188, 8, 64]> var_2827_cast_fp16 = add(x = q_85_cast_fp16, y = encoder_module_layers_14_self_attn_pos_bias_v_to_fp16)[name = tensor<string, []>("op_2827_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_331_transpose_x_0 = const()[name = tensor<string, []>("x_331_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_331_transpose_y_0 = const()[name = tensor<string, []>("x_331_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 64, 375]> var_2829_to_fp16 = const()[name = tensor<string, []>("op_2829_to_fp16"), val = tensor<fp16, [1, 8, 64, 375]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(184279488)))];
            tensor<fp16, [1, 8, 188, 64]> q_with_bias_v_29_cast_fp16 = transpose(perm = q_with_bias_v_29_perm_0, x = var_2827_cast_fp16)[name = tensor<string, []>("transpose_105")];
            tensor<fp16, [1, 8, 188, 375]> x_331_cast_fp16 = matmul(transpose_x = x_331_transpose_x_0, transpose_y = x_331_transpose_y_0, x = q_with_bias_v_29_cast_fp16, y = var_2829_to_fp16)[name = tensor<string, []>("x_331_cast_fp16")];
            tensor<int32, [8]> x_333_pad_0 = const()[name = tensor<string, []>("x_333_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            tensor<string, []> x_333_mode_0 = const()[name = tensor<string, []>("x_333_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_169_to_fp16 = const()[name = tensor<string, []>("const_169_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_333_cast_fp16 = pad(constant_val = const_169_to_fp16, mode = x_333_mode_0, pad = x_333_pad_0, x = x_331_cast_fp16)[name = tensor<string, []>("x_333_cast_fp16")];
            tensor<int32, [4]> var_2837 = const()[name = tensor<string, []>("op_2837"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_335_cast_fp16 = reshape(shape = var_2837, x = x_333_cast_fp16)[name = tensor<string, []>("x_335_cast_fp16")];
            tensor<int32, [4]> var_2841_begin_0 = const()[name = tensor<string, []>("op_2841_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_2841_end_0 = const()[name = tensor<string, []>("op_2841_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_2841_end_mask_0 = const()[name = tensor<string, []>("op_2841_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_2841_cast_fp16 = slice_by_index(begin = var_2841_begin_0, end = var_2841_end_0, end_mask = var_2841_end_mask_0, x = x_335_cast_fp16)[name = tensor<string, []>("op_2841_cast_fp16")];
            tensor<int32, [4]> var_2842 = const()[name = tensor<string, []>("op_2842"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_57_cast_fp16 = reshape(shape = var_2842, x = var_2841_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_79_perm_0 = const()[name = tensor<string, []>("transpose_79_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_80_perm_0 = const()[name = tensor<string, []>("transpose_80_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 64, 188]> transpose_80 = transpose(perm = transpose_80_perm_0, x = k_57_cast_fp16)[name = tensor<string, []>("transpose_103")];
            tensor<fp16, [1, 8, 188, 64]> transpose_79 = transpose(perm = transpose_79_perm_0, x = var_2825_cast_fp16)[name = tensor<string, []>("transpose_104")];
            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_79, y = transpose_80)[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_2851_cast_fp16 = add(x = matrix_ac_29_cast_fp16, y = matrix_bd_59_cast_fp16)[name = tensor<string, []>("op_2851_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, []>(0x1p-3)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_57_cast_fp16 = mul(x = var_2851_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_153_to_fp16, b = _inversed_scores_57_cast_fp16, cond = mask_7)[name = tensor<string, []>("scores_59_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_2857_cast_fp16 = softmax(axis = var_138, x = scores_59_cast_fp16)[name = tensor<string, []>("op_2857_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_769_cast_fp16 = select(a = var_154_to_fp16, b = var_2857_cast_fp16, cond = mask_7)[name = tensor<string, []>("input_769_cast_fp16")];
            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, 188, 64]> value_33_cast_fp16 = transpose(perm = value_33_perm_0, x = v_29_cast_fp16)[name = tensor<string, []>("transpose_106")];
            tensor<fp16, [1, 8, 188, 64]> x_337_cast_fp16 = matmul(transpose_x = x_337_transpose_x_0, transpose_y = x_337_transpose_y_0, x = input_769_cast_fp16, y = value_33_cast_fp16)[name = tensor<string, []>("x_337_cast_fp16")];
            tensor<int32, [4]> var_2861_perm_0 = const()[name = tensor<string, []>("op_2861_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_2862 = const()[name = tensor<string, []>("op_2862"), val = tensor<int32, [3]>([1, -1, 512])];
            tensor<fp16, [1, 188, 8, 64]> var_2861_cast_fp16 = transpose(perm = var_2861_perm_0, x = x_337_cast_fp16)[name = tensor<string, []>("transpose_102")];
            tensor<fp16, [1, 188, 512]> input_771_cast_fp16 = reshape(shape = var_2862, x = var_2861_cast_fp16)[name = tensor<string, []>("input_771_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_14_self_attn_linear_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_14_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(184663552)))];
            tensor<fp16, [512]> encoder_module_layers_14_self_attn_linear_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_14_self_attn_linear_out_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(185187904)))];
            tensor<fp16, [1, 188, 512]> linear_133_cast_fp16 = linear(bias = encoder_module_layers_14_self_attn_linear_out_bias_to_fp16, weight = encoder_module_layers_14_self_attn_linear_out_weight_to_fp16, x = input_771_cast_fp16)[name = tensor<string, []>("linear_133_cast_fp16")];
            tensor<fp16, [1, 188, 512]> input_775_cast_fp16 = add(x = input_767_cast_fp16, y = linear_133_cast_fp16)[name = tensor<string, []>("input_775_cast_fp16")];
            tensor<int32, [1]> x_341_axes_0 = const()[name = tensor<string, []>("x_341_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_14_norm_conv_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_14_norm_conv_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(185188992)))];
            tensor<fp16, [512]> encoder_module_layers_14_norm_conv_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_14_norm_conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(185190080)))];
            tensor<fp16, [1, 188, 512]> x_341_cast_fp16 = layer_norm(axes = x_341_axes_0, beta = encoder_module_layers_14_norm_conv_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_14_norm_conv_weight_to_fp16, x = input_775_cast_fp16)[name = tensor<string, []>("x_341_cast_fp16")];
            tensor<int32, [3]> input_777_perm_0 = const()[name = tensor<string, []>("input_777_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> input_779_pad_type_0 = const()[name = tensor<string, []>("input_779_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_779_strides_0 = const()[name = tensor<string, []>("input_779_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_779_pad_0 = const()[name = tensor<string, []>("input_779_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_779_dilations_0 = const()[name = tensor<string, []>("input_779_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_779_groups_0 = const()[name = tensor<string, []>("input_779_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1024, 512, 1]> encoder_module_layers_14_conv_pointwise_conv1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_14_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [1024, 512, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(185191168)))];
            tensor<fp16, [1024]> encoder_module_layers_14_conv_pointwise_conv1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_14_conv_pointwise_conv1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(186239808)))];
            tensor<fp16, [1, 512, 188]> input_777_cast_fp16 = transpose(perm = input_777_perm_0, x = x_341_cast_fp16)[name = tensor<string, []>("transpose_101")];
            tensor<fp16, [1, 1024, 188]> input_779_cast_fp16 = conv(bias = encoder_module_layers_14_conv_pointwise_conv1_bias_to_fp16, dilations = input_779_dilations_0, groups = input_779_groups_0, pad = input_779_pad_0, pad_type = input_779_pad_type_0, strides = input_779_strides_0, weight = encoder_module_layers_14_conv_pointwise_conv1_weight_to_fp16, x = input_777_cast_fp16)[name = tensor<string, []>("input_779_cast_fp16")];
            tensor<int32, []> x_343_split_num_splits_0 = const()[name = tensor<string, []>("x_343_split_num_splits_0"), val = tensor<int32, []>(2)];
            tensor<int32, []> x_343_split_axis_0 = const()[name = tensor<string, []>("x_343_split_axis_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1, 512, 188]> x_343_split_cast_fp16_0, tensor<fp16, [1, 512, 188]> x_343_split_cast_fp16_1 = split(axis = x_343_split_axis_0, num_splits = x_343_split_num_splits_0, x = input_779_cast_fp16)[name = tensor<string, []>("x_343_split_cast_fp16")];
            tensor<fp16, [1, 512, 188]> x_343_split_1_sigmoid_cast_fp16 = sigmoid(x = x_343_split_cast_fp16_1)[name = tensor<string, []>("x_343_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 512, 188]> x_343_cast_fp16 = mul(x = x_343_split_cast_fp16_0, y = x_343_split_1_sigmoid_cast_fp16)[name = tensor<string, []>("x_343_cast_fp16")];
            tensor<fp16, [1, 512, 188]> input_781_cast_fp16 = select(a = var_154_to_fp16, b = x_343_cast_fp16, cond = var_450)[name = tensor<string, []>("input_781_cast_fp16")];
            tensor<int32, [6]> input_783_pad_0 = const()[name = tensor<string, []>("input_783_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            tensor<string, []> input_783_mode_0 = const()[name = tensor<string, []>("input_783_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_172_to_fp16 = const()[name = tensor<string, []>("const_172_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 512, 196]> input_783_cast_fp16 = pad(constant_val = const_172_to_fp16, mode = input_783_mode_0, pad = input_783_pad_0, x = input_781_cast_fp16)[name = tensor<string, []>("input_783_cast_fp16")];
            tensor<string, []> input_785_pad_type_0 = const()[name = tensor<string, []>("input_785_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, []> input_785_groups_0 = const()[name = tensor<string, []>("input_785_groups_0"), val = tensor<int32, []>(512)];
            tensor<int32, [1]> input_785_strides_0 = const()[name = tensor<string, []>("input_785_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_785_pad_0 = const()[name = tensor<string, []>("input_785_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_785_dilations_0 = const()[name = tensor<string, []>("input_785_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 9]> const_221_to_fp16 = const()[name = tensor<string, []>("const_221_to_fp16"), val = tensor<fp16, [512, 1, 9]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(186241920)))];
            tensor<fp16, [512]> const_222_to_fp16 = const()[name = tensor<string, []>("const_222_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(186251200)))];
            tensor<fp16, [1, 512, 188]> input_787_cast_fp16 = conv(bias = const_222_to_fp16, dilations = input_785_dilations_0, groups = input_785_groups_0, pad = input_785_pad_0, pad_type = input_785_pad_type_0, strides = input_785_strides_0, weight = const_221_to_fp16, x = input_783_cast_fp16)[name = tensor<string, []>("input_787_cast_fp16")];
            tensor<fp16, [1, 512, 188]> input_789_cast_fp16 = silu(x = input_787_cast_fp16)[name = tensor<string, []>("input_789_cast_fp16")];
            tensor<string, []> x_345_pad_type_0 = const()[name = tensor<string, []>("x_345_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> x_345_strides_0 = const()[name = tensor<string, []>("x_345_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_345_pad_0 = const()[name = tensor<string, []>("x_345_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_345_dilations_0 = const()[name = tensor<string, []>("x_345_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> x_345_groups_0 = const()[name = tensor<string, []>("x_345_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [512, 512, 1]> encoder_module_layers_14_conv_pointwise_conv2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_14_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [512, 512, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(186252288)))];
            tensor<fp16, [512]> encoder_module_layers_14_conv_pointwise_conv2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_14_conv_pointwise_conv2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(186776640)))];
            tensor<fp16, [1, 512, 188]> x_345_cast_fp16 = conv(bias = encoder_module_layers_14_conv_pointwise_conv2_bias_to_fp16, dilations = x_345_dilations_0, groups = x_345_groups_0, pad = x_345_pad_0, pad_type = x_345_pad_type_0, strides = x_345_strides_0, weight = encoder_module_layers_14_conv_pointwise_conv2_weight_to_fp16, x = input_789_cast_fp16)[name = tensor<string, []>("x_345_cast_fp16")];
            tensor<int32, [3]> input_791_perm_0 = const()[name = tensor<string, []>("input_791_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 512]> input_791_cast_fp16 = transpose(perm = input_791_perm_0, x = x_345_cast_fp16)[name = tensor<string, []>("transpose_100")];
            tensor<fp16, [1, 188, 512]> input_793_cast_fp16 = add(x = input_775_cast_fp16, y = input_791_cast_fp16)[name = tensor<string, []>("input_793_cast_fp16")];
            tensor<int32, [1]> input_795_axes_0 = const()[name = tensor<string, []>("input_795_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_14_norm_feed_forward2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_14_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(186777728)))];
            tensor<fp16, [512]> encoder_module_layers_14_norm_feed_forward2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_14_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(186778816)))];
            tensor<fp16, [1, 188, 512]> input_795_cast_fp16 = layer_norm(axes = input_795_axes_0, beta = encoder_module_layers_14_norm_feed_forward2_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_14_norm_feed_forward2_weight_to_fp16, x = input_793_cast_fp16)[name = tensor<string, []>("input_795_cast_fp16")];
            tensor<fp16, [2048, 512]> encoder_module_layers_14_feed_forward2_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_14_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [2048, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(186779904)))];
            tensor<fp16, [2048]> encoder_module_layers_14_feed_forward2_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_14_feed_forward2_linear1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(188877120)))];
            tensor<fp16, [1, 188, 2048]> linear_134_cast_fp16 = linear(bias = encoder_module_layers_14_feed_forward2_linear1_bias_to_fp16, weight = encoder_module_layers_14_feed_forward2_linear1_weight_to_fp16, x = input_795_cast_fp16)[name = tensor<string, []>("linear_134_cast_fp16")];
            tensor<fp16, [1, 188, 2048]> input_799_cast_fp16 = silu(x = linear_134_cast_fp16)[name = tensor<string, []>("input_799_cast_fp16")];
            tensor<fp16, [512, 2048]> encoder_module_layers_14_feed_forward2_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_14_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [512, 2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(188881280)))];
            tensor<fp16, [512]> encoder_module_layers_14_feed_forward2_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_14_feed_forward2_linear2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(190978496)))];
            tensor<fp16, [1, 188, 512]> linear_135_cast_fp16 = linear(bias = encoder_module_layers_14_feed_forward2_linear2_bias_to_fp16, weight = encoder_module_layers_14_feed_forward2_linear2_weight_to_fp16, x = input_799_cast_fp16)[name = tensor<string, []>("linear_135_cast_fp16")];
            tensor<fp16, []> var_2928_to_fp16 = const()[name = tensor<string, []>("op_2928_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 512]> var_2929_cast_fp16 = mul(x = linear_135_cast_fp16, y = var_2928_to_fp16)[name = tensor<string, []>("op_2929_cast_fp16")];
            tensor<fp16, [1, 188, 512]> input_805_cast_fp16 = add(x = input_793_cast_fp16, y = var_2929_cast_fp16)[name = tensor<string, []>("input_805_cast_fp16")];
            tensor<int32, [1]> input_807_axes_0 = const()[name = tensor<string, []>("input_807_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_14_norm_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_14_norm_out_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(190979584)))];
            tensor<fp16, [512]> encoder_module_layers_14_norm_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_14_norm_out_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(190980672)))];
            tensor<fp16, [1, 188, 512]> input_807_cast_fp16 = layer_norm(axes = input_807_axes_0, beta = encoder_module_layers_14_norm_out_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_14_norm_out_weight_to_fp16, x = input_805_cast_fp16)[name = tensor<string, []>("input_807_cast_fp16")];
            tensor<int32, [1]> input_809_axes_0 = const()[name = tensor<string, []>("input_809_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_15_norm_feed_forward1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_15_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(190981760)))];
            tensor<fp16, [512]> encoder_module_layers_15_norm_feed_forward1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_15_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(190982848)))];
            tensor<fp16, [1, 188, 512]> input_809_cast_fp16 = layer_norm(axes = input_809_axes_0, beta = encoder_module_layers_15_norm_feed_forward1_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_15_norm_feed_forward1_weight_to_fp16, x = input_807_cast_fp16)[name = tensor<string, []>("input_809_cast_fp16")];
            tensor<fp16, [2048, 512]> encoder_module_layers_15_feed_forward1_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_15_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [2048, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(190983936)))];
            tensor<fp16, [2048]> encoder_module_layers_15_feed_forward1_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_15_feed_forward1_linear1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(193081152)))];
            tensor<fp16, [1, 188, 2048]> linear_136_cast_fp16 = linear(bias = encoder_module_layers_15_feed_forward1_linear1_bias_to_fp16, weight = encoder_module_layers_15_feed_forward1_linear1_weight_to_fp16, x = input_809_cast_fp16)[name = tensor<string, []>("linear_136_cast_fp16")];
            tensor<fp16, [1, 188, 2048]> input_813_cast_fp16 = silu(x = linear_136_cast_fp16)[name = tensor<string, []>("input_813_cast_fp16")];
            tensor<fp16, [512, 2048]> encoder_module_layers_15_feed_forward1_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_15_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [512, 2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(193085312)))];
            tensor<fp16, [512]> encoder_module_layers_15_feed_forward1_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_15_feed_forward1_linear2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(195182528)))];
            tensor<fp16, [1, 188, 512]> linear_137_cast_fp16 = linear(bias = encoder_module_layers_15_feed_forward1_linear2_bias_to_fp16, weight = encoder_module_layers_15_feed_forward1_linear2_weight_to_fp16, x = input_813_cast_fp16)[name = tensor<string, []>("linear_137_cast_fp16")];
            tensor<fp16, []> var_2959_to_fp16 = const()[name = tensor<string, []>("op_2959_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 512]> var_2960_cast_fp16 = mul(x = linear_137_cast_fp16, y = var_2959_to_fp16)[name = tensor<string, []>("op_2960_cast_fp16")];
            tensor<fp16, [1, 188, 512]> input_819_cast_fp16 = add(x = input_807_cast_fp16, y = var_2960_cast_fp16)[name = tensor<string, []>("input_819_cast_fp16")];
            tensor<int32, [1]> query_31_axes_0 = const()[name = tensor<string, []>("query_31_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_15_norm_self_att_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_15_norm_self_att_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(195183616)))];
            tensor<fp16, [512]> encoder_module_layers_15_norm_self_att_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_15_norm_self_att_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(195184704)))];
            tensor<fp16, [1, 188, 512]> query_31_cast_fp16 = layer_norm(axes = query_31_axes_0, beta = encoder_module_layers_15_norm_self_att_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_15_norm_self_att_weight_to_fp16, x = input_819_cast_fp16)[name = tensor<string, []>("query_31_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_15_self_attn_linear_q_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_15_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(195185792)))];
            tensor<fp16, [512]> encoder_module_layers_15_self_attn_linear_q_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_15_self_attn_linear_q_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(195710144)))];
            tensor<fp16, [1, 188, 512]> linear_138_cast_fp16 = linear(bias = encoder_module_layers_15_self_attn_linear_q_bias_to_fp16, weight = encoder_module_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_2977 = const()[name = tensor<string, []>("op_2977"), val = tensor<int32, [4]>([1, -1, 8, 64])];
            tensor<fp16, [1, 188, 8, 64]> q_91_cast_fp16 = reshape(shape = var_2977, x = linear_138_cast_fp16)[name = tensor<string, []>("q_91_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_15_self_attn_linear_k_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_15_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(195711232)))];
            tensor<fp16, [512]> encoder_module_layers_15_self_attn_linear_k_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_15_self_attn_linear_k_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(196235584)))];
            tensor<fp16, [1, 188, 512]> linear_139_cast_fp16 = linear(bias = encoder_module_layers_15_self_attn_linear_k_bias_to_fp16, weight = encoder_module_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_2982 = const()[name = tensor<string, []>("op_2982"), val = tensor<int32, [4]>([1, -1, 8, 64])];
            tensor<fp16, [1, 188, 8, 64]> k_61_cast_fp16 = reshape(shape = var_2982, x = linear_139_cast_fp16)[name = tensor<string, []>("k_61_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_15_self_attn_linear_v_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_15_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(196236672)))];
            tensor<fp16, [512]> encoder_module_layers_15_self_attn_linear_v_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_15_self_attn_linear_v_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(196761024)))];
            tensor<fp16, [1, 188, 512]> linear_140_cast_fp16 = linear(bias = encoder_module_layers_15_self_attn_linear_v_bias_to_fp16, weight = encoder_module_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_2987 = const()[name = tensor<string, []>("op_2987"), val = tensor<int32, [4]>([1, -1, 8, 64])];
            tensor<fp16, [1, 188, 8, 64]> v_31_cast_fp16 = reshape(shape = var_2987, x = linear_140_cast_fp16)[name = tensor<string, []>("v_31_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, 64]> encoder_module_layers_15_self_attn_pos_bias_u_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_15_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(196762112)))];
            tensor<fp16, [1, 188, 8, 64]> var_2999_cast_fp16 = add(x = q_91_cast_fp16, y = encoder_module_layers_15_self_attn_pos_bias_u_to_fp16)[name = tensor<string, []>("op_2999_cast_fp16")];
            tensor<fp16, [8, 64]> encoder_module_layers_15_self_attn_pos_bias_v_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_15_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(196763200)))];
            tensor<fp16, [1, 188, 8, 64]> var_3001_cast_fp16 = add(x = q_91_cast_fp16, y = encoder_module_layers_15_self_attn_pos_bias_v_to_fp16)[name = tensor<string, []>("op_3001_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_353_transpose_x_0 = const()[name = tensor<string, []>("x_353_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_353_transpose_y_0 = const()[name = tensor<string, []>("x_353_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 64, 375]> var_3003_to_fp16 = const()[name = tensor<string, []>("op_3003_to_fp16"), val = tensor<fp16, [1, 8, 64, 375]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(196764288)))];
            tensor<fp16, [1, 8, 188, 64]> q_with_bias_v_31_cast_fp16 = transpose(perm = q_with_bias_v_31_perm_0, x = var_3001_cast_fp16)[name = tensor<string, []>("transpose_98")];
            tensor<fp16, [1, 8, 188, 375]> x_353_cast_fp16 = matmul(transpose_x = x_353_transpose_x_0, transpose_y = x_353_transpose_y_0, x = q_with_bias_v_31_cast_fp16, y = var_3003_to_fp16)[name = tensor<string, []>("x_353_cast_fp16")];
            tensor<int32, [8]> x_355_pad_0 = const()[name = tensor<string, []>("x_355_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            tensor<string, []> x_355_mode_0 = const()[name = tensor<string, []>("x_355_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_179_to_fp16 = const()[name = tensor<string, []>("const_179_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_355_cast_fp16 = pad(constant_val = const_179_to_fp16, mode = x_355_mode_0, pad = x_355_pad_0, x = x_353_cast_fp16)[name = tensor<string, []>("x_355_cast_fp16")];
            tensor<int32, [4]> var_3011 = const()[name = tensor<string, []>("op_3011"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_357_cast_fp16 = reshape(shape = var_3011, x = x_355_cast_fp16)[name = tensor<string, []>("x_357_cast_fp16")];
            tensor<int32, [4]> var_3015_begin_0 = const()[name = tensor<string, []>("op_3015_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_3015_end_0 = const()[name = tensor<string, []>("op_3015_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_3015_end_mask_0 = const()[name = tensor<string, []>("op_3015_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_3015_cast_fp16 = slice_by_index(begin = var_3015_begin_0, end = var_3015_end_0, end_mask = var_3015_end_mask_0, x = x_357_cast_fp16)[name = tensor<string, []>("op_3015_cast_fp16")];
            tensor<int32, [4]> var_3016 = const()[name = tensor<string, []>("op_3016"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_61_cast_fp16 = reshape(shape = var_3016, x = var_3015_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_81_perm_0 = const()[name = tensor<string, []>("transpose_81_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_82_perm_0 = const()[name = tensor<string, []>("transpose_82_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 64, 188]> transpose_82 = transpose(perm = transpose_82_perm_0, x = k_61_cast_fp16)[name = tensor<string, []>("transpose_96")];
            tensor<fp16, [1, 8, 188, 64]> transpose_81 = transpose(perm = transpose_81_perm_0, x = var_2999_cast_fp16)[name = tensor<string, []>("transpose_97")];
            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_81, y = transpose_82)[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_3025_cast_fp16 = add(x = matrix_ac_31_cast_fp16, y = matrix_bd_63_cast_fp16)[name = tensor<string, []>("op_3025_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, []>(0x1p-3)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_61_cast_fp16 = mul(x = var_3025_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_153_to_fp16, b = _inversed_scores_61_cast_fp16, cond = mask_7)[name = tensor<string, []>("scores_63_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_3031_cast_fp16 = softmax(axis = var_138, x = scores_63_cast_fp16)[name = tensor<string, []>("op_3031_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_821_cast_fp16 = select(a = var_154_to_fp16, b = var_3031_cast_fp16, cond = mask_7)[name = tensor<string, []>("input_821_cast_fp16")];
            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, 188, 64]> value_35_cast_fp16 = transpose(perm = value_35_perm_0, x = v_31_cast_fp16)[name = tensor<string, []>("transpose_99")];
            tensor<fp16, [1, 8, 188, 64]> x_359_cast_fp16 = matmul(transpose_x = x_359_transpose_x_0, transpose_y = x_359_transpose_y_0, x = input_821_cast_fp16, y = value_35_cast_fp16)[name = tensor<string, []>("x_359_cast_fp16")];
            tensor<int32, [4]> var_3035_perm_0 = const()[name = tensor<string, []>("op_3035_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_3036 = const()[name = tensor<string, []>("op_3036"), val = tensor<int32, [3]>([1, -1, 512])];
            tensor<fp16, [1, 188, 8, 64]> var_3035_cast_fp16 = transpose(perm = var_3035_perm_0, x = x_359_cast_fp16)[name = tensor<string, []>("transpose_95")];
            tensor<fp16, [1, 188, 512]> input_823_cast_fp16 = reshape(shape = var_3036, x = var_3035_cast_fp16)[name = tensor<string, []>("input_823_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_15_self_attn_linear_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_15_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(197148352)))];
            tensor<fp16, [512]> encoder_module_layers_15_self_attn_linear_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_15_self_attn_linear_out_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(197672704)))];
            tensor<fp16, [1, 188, 512]> linear_142_cast_fp16 = linear(bias = encoder_module_layers_15_self_attn_linear_out_bias_to_fp16, weight = encoder_module_layers_15_self_attn_linear_out_weight_to_fp16, x = input_823_cast_fp16)[name = tensor<string, []>("linear_142_cast_fp16")];
            tensor<fp16, [1, 188, 512]> input_827_cast_fp16 = add(x = input_819_cast_fp16, y = linear_142_cast_fp16)[name = tensor<string, []>("input_827_cast_fp16")];
            tensor<int32, [1]> x_363_axes_0 = const()[name = tensor<string, []>("x_363_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_15_norm_conv_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_15_norm_conv_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(197673792)))];
            tensor<fp16, [512]> encoder_module_layers_15_norm_conv_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_15_norm_conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(197674880)))];
            tensor<fp16, [1, 188, 512]> x_363_cast_fp16 = layer_norm(axes = x_363_axes_0, beta = encoder_module_layers_15_norm_conv_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_15_norm_conv_weight_to_fp16, x = input_827_cast_fp16)[name = tensor<string, []>("x_363_cast_fp16")];
            tensor<int32, [3]> input_829_perm_0 = const()[name = tensor<string, []>("input_829_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> input_831_pad_type_0 = const()[name = tensor<string, []>("input_831_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_831_strides_0 = const()[name = tensor<string, []>("input_831_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_831_pad_0 = const()[name = tensor<string, []>("input_831_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_831_dilations_0 = const()[name = tensor<string, []>("input_831_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_831_groups_0 = const()[name = tensor<string, []>("input_831_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1024, 512, 1]> encoder_module_layers_15_conv_pointwise_conv1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_15_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [1024, 512, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(197675968)))];
            tensor<fp16, [1024]> encoder_module_layers_15_conv_pointwise_conv1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_15_conv_pointwise_conv1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(198724608)))];
            tensor<fp16, [1, 512, 188]> input_829_cast_fp16 = transpose(perm = input_829_perm_0, x = x_363_cast_fp16)[name = tensor<string, []>("transpose_94")];
            tensor<fp16, [1, 1024, 188]> input_831_cast_fp16 = conv(bias = encoder_module_layers_15_conv_pointwise_conv1_bias_to_fp16, dilations = input_831_dilations_0, groups = input_831_groups_0, pad = input_831_pad_0, pad_type = input_831_pad_type_0, strides = input_831_strides_0, weight = encoder_module_layers_15_conv_pointwise_conv1_weight_to_fp16, x = input_829_cast_fp16)[name = tensor<string, []>("input_831_cast_fp16")];
            tensor<int32, []> x_365_split_num_splits_0 = const()[name = tensor<string, []>("x_365_split_num_splits_0"), val = tensor<int32, []>(2)];
            tensor<int32, []> x_365_split_axis_0 = const()[name = tensor<string, []>("x_365_split_axis_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1, 512, 188]> x_365_split_cast_fp16_0, tensor<fp16, [1, 512, 188]> x_365_split_cast_fp16_1 = split(axis = x_365_split_axis_0, num_splits = x_365_split_num_splits_0, x = input_831_cast_fp16)[name = tensor<string, []>("x_365_split_cast_fp16")];
            tensor<fp16, [1, 512, 188]> x_365_split_1_sigmoid_cast_fp16 = sigmoid(x = x_365_split_cast_fp16_1)[name = tensor<string, []>("x_365_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 512, 188]> x_365_cast_fp16 = mul(x = x_365_split_cast_fp16_0, y = x_365_split_1_sigmoid_cast_fp16)[name = tensor<string, []>("x_365_cast_fp16")];
            tensor<fp16, [1, 512, 188]> input_833_cast_fp16 = select(a = var_154_to_fp16, b = x_365_cast_fp16, cond = var_450)[name = tensor<string, []>("input_833_cast_fp16")];
            tensor<int32, [6]> input_835_pad_0 = const()[name = tensor<string, []>("input_835_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            tensor<string, []> input_835_mode_0 = const()[name = tensor<string, []>("input_835_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_182_to_fp16 = const()[name = tensor<string, []>("const_182_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 512, 196]> input_835_cast_fp16 = pad(constant_val = const_182_to_fp16, mode = input_835_mode_0, pad = input_835_pad_0, x = input_833_cast_fp16)[name = tensor<string, []>("input_835_cast_fp16")];
            tensor<string, []> input_837_pad_type_0 = const()[name = tensor<string, []>("input_837_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, []> input_837_groups_0 = const()[name = tensor<string, []>("input_837_groups_0"), val = tensor<int32, []>(512)];
            tensor<int32, [1]> input_837_strides_0 = const()[name = tensor<string, []>("input_837_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_837_pad_0 = const()[name = tensor<string, []>("input_837_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_837_dilations_0 = const()[name = tensor<string, []>("input_837_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 9]> const_223_to_fp16 = const()[name = tensor<string, []>("const_223_to_fp16"), val = tensor<fp16, [512, 1, 9]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(198726720)))];
            tensor<fp16, [512]> const_224_to_fp16 = const()[name = tensor<string, []>("const_224_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(198736000)))];
            tensor<fp16, [1, 512, 188]> input_839_cast_fp16 = conv(bias = const_224_to_fp16, dilations = input_837_dilations_0, groups = input_837_groups_0, pad = input_837_pad_0, pad_type = input_837_pad_type_0, strides = input_837_strides_0, weight = const_223_to_fp16, x = input_835_cast_fp16)[name = tensor<string, []>("input_839_cast_fp16")];
            tensor<fp16, [1, 512, 188]> input_841_cast_fp16 = silu(x = input_839_cast_fp16)[name = tensor<string, []>("input_841_cast_fp16")];
            tensor<string, []> x_367_pad_type_0 = const()[name = tensor<string, []>("x_367_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> x_367_strides_0 = const()[name = tensor<string, []>("x_367_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_367_pad_0 = const()[name = tensor<string, []>("x_367_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_367_dilations_0 = const()[name = tensor<string, []>("x_367_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> x_367_groups_0 = const()[name = tensor<string, []>("x_367_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [512, 512, 1]> encoder_module_layers_15_conv_pointwise_conv2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_15_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [512, 512, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(198737088)))];
            tensor<fp16, [512]> encoder_module_layers_15_conv_pointwise_conv2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_15_conv_pointwise_conv2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(199261440)))];
            tensor<fp16, [1, 512, 188]> x_367_cast_fp16 = conv(bias = encoder_module_layers_15_conv_pointwise_conv2_bias_to_fp16, dilations = x_367_dilations_0, groups = x_367_groups_0, pad = x_367_pad_0, pad_type = x_367_pad_type_0, strides = x_367_strides_0, weight = encoder_module_layers_15_conv_pointwise_conv2_weight_to_fp16, x = input_841_cast_fp16)[name = tensor<string, []>("x_367_cast_fp16")];
            tensor<int32, [3]> input_843_perm_0 = const()[name = tensor<string, []>("input_843_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 512]> input_843_cast_fp16 = transpose(perm = input_843_perm_0, x = x_367_cast_fp16)[name = tensor<string, []>("transpose_93")];
            tensor<fp16, [1, 188, 512]> input_845_cast_fp16 = add(x = input_827_cast_fp16, y = input_843_cast_fp16)[name = tensor<string, []>("input_845_cast_fp16")];
            tensor<int32, [1]> input_847_axes_0 = const()[name = tensor<string, []>("input_847_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_15_norm_feed_forward2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_15_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(199262528)))];
            tensor<fp16, [512]> encoder_module_layers_15_norm_feed_forward2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_15_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(199263616)))];
            tensor<fp16, [1, 188, 512]> input_847_cast_fp16 = layer_norm(axes = input_847_axes_0, beta = encoder_module_layers_15_norm_feed_forward2_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_15_norm_feed_forward2_weight_to_fp16, x = input_845_cast_fp16)[name = tensor<string, []>("input_847_cast_fp16")];
            tensor<fp16, [2048, 512]> encoder_module_layers_15_feed_forward2_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_15_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [2048, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(199264704)))];
            tensor<fp16, [2048]> encoder_module_layers_15_feed_forward2_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_15_feed_forward2_linear1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(201361920)))];
            tensor<fp16, [1, 188, 2048]> linear_143_cast_fp16 = linear(bias = encoder_module_layers_15_feed_forward2_linear1_bias_to_fp16, weight = encoder_module_layers_15_feed_forward2_linear1_weight_to_fp16, x = input_847_cast_fp16)[name = tensor<string, []>("linear_143_cast_fp16")];
            tensor<fp16, [1, 188, 2048]> input_851_cast_fp16 = silu(x = linear_143_cast_fp16)[name = tensor<string, []>("input_851_cast_fp16")];
            tensor<fp16, [512, 2048]> encoder_module_layers_15_feed_forward2_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_15_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [512, 2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(201366080)))];
            tensor<fp16, [512]> encoder_module_layers_15_feed_forward2_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_15_feed_forward2_linear2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(203463296)))];
            tensor<fp16, [1, 188, 512]> linear_144_cast_fp16 = linear(bias = encoder_module_layers_15_feed_forward2_linear2_bias_to_fp16, weight = encoder_module_layers_15_feed_forward2_linear2_weight_to_fp16, x = input_851_cast_fp16)[name = tensor<string, []>("linear_144_cast_fp16")];
            tensor<fp16, []> var_3102_to_fp16 = const()[name = tensor<string, []>("op_3102_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 512]> var_3103_cast_fp16 = mul(x = linear_144_cast_fp16, y = var_3102_to_fp16)[name = tensor<string, []>("op_3103_cast_fp16")];
            tensor<fp16, [1, 188, 512]> input_857_cast_fp16 = add(x = input_845_cast_fp16, y = var_3103_cast_fp16)[name = tensor<string, []>("input_857_cast_fp16")];
            tensor<int32, [1]> input_859_axes_0 = const()[name = tensor<string, []>("input_859_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_15_norm_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_15_norm_out_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(203464384)))];
            tensor<fp16, [512]> encoder_module_layers_15_norm_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_15_norm_out_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(203465472)))];
            tensor<fp16, [1, 188, 512]> input_859_cast_fp16 = layer_norm(axes = input_859_axes_0, beta = encoder_module_layers_15_norm_out_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_15_norm_out_weight_to_fp16, x = input_857_cast_fp16)[name = tensor<string, []>("input_859_cast_fp16")];
            tensor<int32, [1]> input_861_axes_0 = const()[name = tensor<string, []>("input_861_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_16_norm_feed_forward1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_16_norm_feed_forward1_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(203466560)))];
            tensor<fp16, [512]> encoder_module_layers_16_norm_feed_forward1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_16_norm_feed_forward1_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(203467648)))];
            tensor<fp16, [1, 188, 512]> input_861_cast_fp16 = layer_norm(axes = input_861_axes_0, beta = encoder_module_layers_16_norm_feed_forward1_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_16_norm_feed_forward1_weight_to_fp16, x = input_859_cast_fp16)[name = tensor<string, []>("input_861_cast_fp16")];
            tensor<fp16, [2048, 512]> encoder_module_layers_16_feed_forward1_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_16_feed_forward1_linear1_weight_to_fp16"), val = tensor<fp16, [2048, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(203468736)))];
            tensor<fp16, [2048]> encoder_module_layers_16_feed_forward1_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_16_feed_forward1_linear1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(205565952)))];
            tensor<fp16, [1, 188, 2048]> linear_145_cast_fp16 = linear(bias = encoder_module_layers_16_feed_forward1_linear1_bias_to_fp16, weight = encoder_module_layers_16_feed_forward1_linear1_weight_to_fp16, x = input_861_cast_fp16)[name = tensor<string, []>("linear_145_cast_fp16")];
            tensor<fp16, [1, 188, 2048]> input_865_cast_fp16 = silu(x = linear_145_cast_fp16)[name = tensor<string, []>("input_865_cast_fp16")];
            tensor<fp16, [512, 2048]> encoder_module_layers_16_feed_forward1_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_16_feed_forward1_linear2_weight_to_fp16"), val = tensor<fp16, [512, 2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(205570112)))];
            tensor<fp16, [512]> encoder_module_layers_16_feed_forward1_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_16_feed_forward1_linear2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(207667328)))];
            tensor<fp16, [1, 188, 512]> linear_146_cast_fp16 = linear(bias = encoder_module_layers_16_feed_forward1_linear2_bias_to_fp16, weight = encoder_module_layers_16_feed_forward1_linear2_weight_to_fp16, x = input_865_cast_fp16)[name = tensor<string, []>("linear_146_cast_fp16")];
            tensor<fp16, []> var_3133_to_fp16 = const()[name = tensor<string, []>("op_3133_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 512]> var_3134_cast_fp16 = mul(x = linear_146_cast_fp16, y = var_3133_to_fp16)[name = tensor<string, []>("op_3134_cast_fp16")];
            tensor<fp16, [1, 188, 512]> input_871_cast_fp16 = add(x = input_859_cast_fp16, y = var_3134_cast_fp16)[name = tensor<string, []>("input_871_cast_fp16")];
            tensor<int32, [1]> query_axes_0 = const()[name = tensor<string, []>("query_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_16_norm_self_att_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_16_norm_self_att_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(207668416)))];
            tensor<fp16, [512]> encoder_module_layers_16_norm_self_att_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_16_norm_self_att_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(207669504)))];
            tensor<fp16, [1, 188, 512]> query_cast_fp16 = layer_norm(axes = query_axes_0, beta = encoder_module_layers_16_norm_self_att_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_16_norm_self_att_weight_to_fp16, x = input_871_cast_fp16)[name = tensor<string, []>("query_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_16_self_attn_linear_q_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_16_self_attn_linear_q_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(207670592)))];
            tensor<fp16, [512]> encoder_module_layers_16_self_attn_linear_q_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_16_self_attn_linear_q_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(208194944)))];
            tensor<fp16, [1, 188, 512]> linear_147_cast_fp16 = linear(bias = encoder_module_layers_16_self_attn_linear_q_bias_to_fp16, weight = encoder_module_layers_16_self_attn_linear_q_weight_to_fp16, x = query_cast_fp16)[name = tensor<string, []>("linear_147_cast_fp16")];
            tensor<int32, [4]> var_3151 = const()[name = tensor<string, []>("op_3151"), val = tensor<int32, [4]>([1, -1, 8, 64])];
            tensor<fp16, [1, 188, 8, 64]> q_97_cast_fp16 = reshape(shape = var_3151, x = linear_147_cast_fp16)[name = tensor<string, []>("q_97_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_16_self_attn_linear_k_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_16_self_attn_linear_k_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(208196032)))];
            tensor<fp16, [512]> encoder_module_layers_16_self_attn_linear_k_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_16_self_attn_linear_k_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(208720384)))];
            tensor<fp16, [1, 188, 512]> linear_148_cast_fp16 = linear(bias = encoder_module_layers_16_self_attn_linear_k_bias_to_fp16, weight = encoder_module_layers_16_self_attn_linear_k_weight_to_fp16, x = query_cast_fp16)[name = tensor<string, []>("linear_148_cast_fp16")];
            tensor<int32, [4]> var_3156 = const()[name = tensor<string, []>("op_3156"), val = tensor<int32, [4]>([1, -1, 8, 64])];
            tensor<fp16, [1, 188, 8, 64]> k_65_cast_fp16 = reshape(shape = var_3156, x = linear_148_cast_fp16)[name = tensor<string, []>("k_65_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_16_self_attn_linear_v_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_16_self_attn_linear_v_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(208721472)))];
            tensor<fp16, [512]> encoder_module_layers_16_self_attn_linear_v_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_16_self_attn_linear_v_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(209245824)))];
            tensor<fp16, [1, 188, 512]> linear_149_cast_fp16 = linear(bias = encoder_module_layers_16_self_attn_linear_v_bias_to_fp16, weight = encoder_module_layers_16_self_attn_linear_v_weight_to_fp16, x = query_cast_fp16)[name = tensor<string, []>("linear_149_cast_fp16")];
            tensor<int32, [4]> var_3161 = const()[name = tensor<string, []>("op_3161"), val = tensor<int32, [4]>([1, -1, 8, 64])];
            tensor<fp16, [1, 188, 8, 64]> v_cast_fp16 = reshape(shape = var_3161, x = linear_149_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, 64]> encoder_module_layers_16_self_attn_pos_bias_u_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_16_self_attn_pos_bias_u_to_fp16"), val = tensor<fp16, [8, 64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(209246912)))];
            tensor<fp16, [1, 188, 8, 64]> var_3173_cast_fp16 = add(x = q_97_cast_fp16, y = encoder_module_layers_16_self_attn_pos_bias_u_to_fp16)[name = tensor<string, []>("op_3173_cast_fp16")];
            tensor<fp16, [8, 64]> encoder_module_layers_16_self_attn_pos_bias_v_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_16_self_attn_pos_bias_v_to_fp16"), val = tensor<fp16, [8, 64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(209248000)))];
            tensor<fp16, [1, 188, 8, 64]> var_3175_cast_fp16 = add(x = q_97_cast_fp16, y = encoder_module_layers_16_self_attn_pos_bias_v_to_fp16)[name = tensor<string, []>("op_3175_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_375_transpose_x_0 = const()[name = tensor<string, []>("x_375_transpose_x_0"), val = tensor<bool, []>(false)];
            tensor<bool, []> x_375_transpose_y_0 = const()[name = tensor<string, []>("x_375_transpose_y_0"), val = tensor<bool, []>(false)];
            tensor<fp16, [1, 8, 64, 375]> var_3177_to_fp16 = const()[name = tensor<string, []>("op_3177_to_fp16"), val = tensor<fp16, [1, 8, 64, 375]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(209249088)))];
            tensor<fp16, [1, 8, 188, 64]> q_with_bias_v_cast_fp16 = transpose(perm = q_with_bias_v_perm_0, x = var_3175_cast_fp16)[name = tensor<string, []>("transpose_91")];
            tensor<fp16, [1, 8, 188, 375]> x_375_cast_fp16 = matmul(transpose_x = x_375_transpose_x_0, transpose_y = x_375_transpose_y_0, x = q_with_bias_v_cast_fp16, y = var_3177_to_fp16)[name = tensor<string, []>("x_375_cast_fp16")];
            tensor<int32, [8]> x_377_pad_0 = const()[name = tensor<string, []>("x_377_pad_0"), val = tensor<int32, [8]>([0, 0, 0, 0, 0, 0, 1, 0])];
            tensor<string, []> x_377_mode_0 = const()[name = tensor<string, []>("x_377_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_189_to_fp16 = const()[name = tensor<string, []>("const_189_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 8, 188, 376]> x_377_cast_fp16 = pad(constant_val = const_189_to_fp16, mode = x_377_mode_0, pad = x_377_pad_0, x = x_375_cast_fp16)[name = tensor<string, []>("x_377_cast_fp16")];
            tensor<int32, [4]> var_3185 = const()[name = tensor<string, []>("op_3185"), val = tensor<int32, [4]>([1, 8, -1, 188])];
            tensor<fp16, [1, 8, 376, 188]> x_379_cast_fp16 = reshape(shape = var_3185, x = x_377_cast_fp16)[name = tensor<string, []>("x_379_cast_fp16")];
            tensor<int32, [4]> var_3189_begin_0 = const()[name = tensor<string, []>("op_3189_begin_0"), val = tensor<int32, [4]>([0, 0, 1, 0])];
            tensor<int32, [4]> var_3189_end_0 = const()[name = tensor<string, []>("op_3189_end_0"), val = tensor<int32, [4]>([1, 8, 376, 188])];
            tensor<bool, [4]> var_3189_end_mask_0 = const()[name = tensor<string, []>("op_3189_end_mask_0"), val = tensor<bool, [4]>([true, true, true, true])];
            tensor<fp16, [1, 8, 375, 188]> var_3189_cast_fp16 = slice_by_index(begin = var_3189_begin_0, end = var_3189_end_0, end_mask = var_3189_end_mask_0, x = x_379_cast_fp16)[name = tensor<string, []>("op_3189_cast_fp16")];
            tensor<int32, [4]> var_3190 = const()[name = tensor<string, []>("op_3190"), val = tensor<int32, [4]>([1, 8, 188, 375])];
            tensor<fp16, [1, 8, 188, 375]> matrix_bd_65_cast_fp16 = reshape(shape = var_3190, x = var_3189_cast_fp16)[name = tensor<string, []>("matrix_bd_65_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_83_perm_0 = const()[name = tensor<string, []>("transpose_83_perm_0"), val = tensor<int32, [4]>([0, 2, -3, -1])];
            tensor<int32, [4]> transpose_84_perm_0 = const()[name = tensor<string, []>("transpose_84_perm_0"), val = tensor<int32, [4]>([0, 2, -1, -3])];
            tensor<fp16, [1, 8, 64, 188]> transpose_84 = transpose(perm = transpose_84_perm_0, x = k_65_cast_fp16)[name = tensor<string, []>("transpose_89")];
            tensor<fp16, [1, 8, 188, 64]> transpose_83 = transpose(perm = transpose_83_perm_0, x = var_3173_cast_fp16)[name = tensor<string, []>("transpose_90")];
            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_83, y = transpose_84)[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_65_cast_fp16)[name = tensor<string, []>("matrix_bd_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_3199_cast_fp16 = add(x = matrix_ac_cast_fp16, y = matrix_bd_cast_fp16)[name = tensor<string, []>("op_3199_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, []>(0x1p-3)];
            tensor<fp16, [1, 8, 188, 188]> _inversed_scores_65_cast_fp16 = mul(x = var_3199_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_cast_fp16 = select(a = var_153_to_fp16, b = _inversed_scores_65_cast_fp16, cond = mask_7)[name = tensor<string, []>("scores_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> var_3205_cast_fp16 = softmax(axis = var_138, x = scores_cast_fp16)[name = tensor<string, []>("op_3205_cast_fp16")];
            tensor<fp16, [1, 8, 188, 188]> input_873_cast_fp16 = select(a = var_154_to_fp16, b = var_3205_cast_fp16, cond = mask_7)[name = tensor<string, []>("input_873_cast_fp16")];
            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, 188, 64]> value_cast_fp16 = transpose(perm = value_perm_0, x = v_cast_fp16)[name = tensor<string, []>("transpose_92")];
            tensor<fp16, [1, 8, 188, 64]> x_381_cast_fp16 = matmul(transpose_x = x_381_transpose_x_0, transpose_y = x_381_transpose_y_0, x = input_873_cast_fp16, y = value_cast_fp16)[name = tensor<string, []>("x_381_cast_fp16")];
            tensor<int32, [4]> var_3209_perm_0 = const()[name = tensor<string, []>("op_3209_perm_0"), val = tensor<int32, [4]>([0, 2, 1, 3])];
            tensor<int32, [3]> var_3210 = const()[name = tensor<string, []>("op_3210"), val = tensor<int32, [3]>([1, -1, 512])];
            tensor<fp16, [1, 188, 8, 64]> var_3209_cast_fp16 = transpose(perm = var_3209_perm_0, x = x_381_cast_fp16)[name = tensor<string, []>("transpose_88")];
            tensor<fp16, [1, 188, 512]> input_875_cast_fp16 = reshape(shape = var_3210, x = var_3209_cast_fp16)[name = tensor<string, []>("input_875_cast_fp16")];
            tensor<fp16, [512, 512]> encoder_module_layers_16_self_attn_linear_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_16_self_attn_linear_out_weight_to_fp16"), val = tensor<fp16, [512, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(209633152)))];
            tensor<fp16, [512]> encoder_module_layers_16_self_attn_linear_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_16_self_attn_linear_out_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(210157504)))];
            tensor<fp16, [1, 188, 512]> linear_151_cast_fp16 = linear(bias = encoder_module_layers_16_self_attn_linear_out_bias_to_fp16, weight = encoder_module_layers_16_self_attn_linear_out_weight_to_fp16, x = input_875_cast_fp16)[name = tensor<string, []>("linear_151_cast_fp16")];
            tensor<fp16, [1, 188, 512]> input_879_cast_fp16 = add(x = input_871_cast_fp16, y = linear_151_cast_fp16)[name = tensor<string, []>("input_879_cast_fp16")];
            tensor<int32, [1]> x_385_axes_0 = const()[name = tensor<string, []>("x_385_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_16_norm_conv_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_16_norm_conv_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(210158592)))];
            tensor<fp16, [512]> encoder_module_layers_16_norm_conv_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_16_norm_conv_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(210159680)))];
            tensor<fp16, [1, 188, 512]> x_385_cast_fp16 = layer_norm(axes = x_385_axes_0, beta = encoder_module_layers_16_norm_conv_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_16_norm_conv_weight_to_fp16, x = input_879_cast_fp16)[name = tensor<string, []>("x_385_cast_fp16")];
            tensor<int32, [3]> input_881_perm_0 = const()[name = tensor<string, []>("input_881_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> input_883_pad_type_0 = const()[name = tensor<string, []>("input_883_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> input_883_strides_0 = const()[name = tensor<string, []>("input_883_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_883_pad_0 = const()[name = tensor<string, []>("input_883_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_883_dilations_0 = const()[name = tensor<string, []>("input_883_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> input_883_groups_0 = const()[name = tensor<string, []>("input_883_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1024, 512, 1]> encoder_module_layers_16_conv_pointwise_conv1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_16_conv_pointwise_conv1_weight_to_fp16"), val = tensor<fp16, [1024, 512, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(210160768)))];
            tensor<fp16, [1024]> encoder_module_layers_16_conv_pointwise_conv1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_16_conv_pointwise_conv1_bias_to_fp16"), val = tensor<fp16, [1024]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(211209408)))];
            tensor<fp16, [1, 512, 188]> input_881_cast_fp16 = transpose(perm = input_881_perm_0, x = x_385_cast_fp16)[name = tensor<string, []>("transpose_87")];
            tensor<fp16, [1, 1024, 188]> input_883_cast_fp16 = conv(bias = encoder_module_layers_16_conv_pointwise_conv1_bias_to_fp16, dilations = input_883_dilations_0, groups = input_883_groups_0, pad = input_883_pad_0, pad_type = input_883_pad_type_0, strides = input_883_strides_0, weight = encoder_module_layers_16_conv_pointwise_conv1_weight_to_fp16, x = input_881_cast_fp16)[name = tensor<string, []>("input_883_cast_fp16")];
            tensor<int32, []> x_387_split_num_splits_0 = const()[name = tensor<string, []>("x_387_split_num_splits_0"), val = tensor<int32, []>(2)];
            tensor<int32, []> x_387_split_axis_0 = const()[name = tensor<string, []>("x_387_split_axis_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [1, 512, 188]> x_387_split_cast_fp16_0, tensor<fp16, [1, 512, 188]> x_387_split_cast_fp16_1 = split(axis = x_387_split_axis_0, num_splits = x_387_split_num_splits_0, x = input_883_cast_fp16)[name = tensor<string, []>("x_387_split_cast_fp16")];
            tensor<fp16, [1, 512, 188]> x_387_split_1_sigmoid_cast_fp16 = sigmoid(x = x_387_split_cast_fp16_1)[name = tensor<string, []>("x_387_split_1_sigmoid_cast_fp16")];
            tensor<fp16, [1, 512, 188]> x_387_cast_fp16 = mul(x = x_387_split_cast_fp16_0, y = x_387_split_1_sigmoid_cast_fp16)[name = tensor<string, []>("x_387_cast_fp16")];
            tensor<fp16, [1, 512, 188]> input_885_cast_fp16 = select(a = var_154_to_fp16, b = x_387_cast_fp16, cond = var_450)[name = tensor<string, []>("input_885_cast_fp16")];
            tensor<int32, [6]> input_887_pad_0 = const()[name = tensor<string, []>("input_887_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 4, 4])];
            tensor<string, []> input_887_mode_0 = const()[name = tensor<string, []>("input_887_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp16, []> const_192_to_fp16 = const()[name = tensor<string, []>("const_192_to_fp16"), val = tensor<fp16, []>(0x0p+0)];
            tensor<fp16, [1, 512, 196]> input_887_cast_fp16 = pad(constant_val = const_192_to_fp16, mode = input_887_mode_0, pad = input_887_pad_0, x = input_885_cast_fp16)[name = tensor<string, []>("input_887_cast_fp16")];
            tensor<string, []> input_889_pad_type_0 = const()[name = tensor<string, []>("input_889_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, []> input_889_groups_0 = const()[name = tensor<string, []>("input_889_groups_0"), val = tensor<int32, []>(512)];
            tensor<int32, [1]> input_889_strides_0 = const()[name = tensor<string, []>("input_889_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> input_889_pad_0 = const()[name = tensor<string, []>("input_889_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> input_889_dilations_0 = const()[name = tensor<string, []>("input_889_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<fp16, [512, 1, 9]> const_225_to_fp16 = const()[name = tensor<string, []>("const_225_to_fp16"), val = tensor<fp16, [512, 1, 9]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(211211520)))];
            tensor<fp16, [512]> const_226_to_fp16 = const()[name = tensor<string, []>("const_226_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(211220800)))];
            tensor<fp16, [1, 512, 188]> input_891_cast_fp16 = conv(bias = const_226_to_fp16, dilations = input_889_dilations_0, groups = input_889_groups_0, pad = input_889_pad_0, pad_type = input_889_pad_type_0, strides = input_889_strides_0, weight = const_225_to_fp16, x = input_887_cast_fp16)[name = tensor<string, []>("input_891_cast_fp16")];
            tensor<fp16, [1, 512, 188]> input_893_cast_fp16 = silu(x = input_891_cast_fp16)[name = tensor<string, []>("input_893_cast_fp16")];
            tensor<string, []> x_389_pad_type_0 = const()[name = tensor<string, []>("x_389_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> x_389_strides_0 = const()[name = tensor<string, []>("x_389_strides_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, [2]> x_389_pad_0 = const()[name = tensor<string, []>("x_389_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> x_389_dilations_0 = const()[name = tensor<string, []>("x_389_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> x_389_groups_0 = const()[name = tensor<string, []>("x_389_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp16, [512, 512, 1]> encoder_module_layers_16_conv_pointwise_conv2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_16_conv_pointwise_conv2_weight_to_fp16"), val = tensor<fp16, [512, 512, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(211221888)))];
            tensor<fp16, [512]> encoder_module_layers_16_conv_pointwise_conv2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_16_conv_pointwise_conv2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(211746240)))];
            tensor<fp16, [1, 512, 188]> x_389_cast_fp16 = conv(bias = encoder_module_layers_16_conv_pointwise_conv2_bias_to_fp16, dilations = x_389_dilations_0, groups = x_389_groups_0, pad = x_389_pad_0, pad_type = x_389_pad_type_0, strides = x_389_strides_0, weight = encoder_module_layers_16_conv_pointwise_conv2_weight_to_fp16, x = input_893_cast_fp16)[name = tensor<string, []>("x_389_cast_fp16")];
            tensor<int32, [3]> input_895_perm_0 = const()[name = tensor<string, []>("input_895_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<fp16, [1, 188, 512]> input_895_cast_fp16 = transpose(perm = input_895_perm_0, x = x_389_cast_fp16)[name = tensor<string, []>("transpose_86")];
            tensor<fp16, [1, 188, 512]> input_897_cast_fp16 = add(x = input_879_cast_fp16, y = input_895_cast_fp16)[name = tensor<string, []>("input_897_cast_fp16")];
            tensor<int32, [1]> input_899_axes_0 = const()[name = tensor<string, []>("input_899_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp16, [512]> encoder_module_layers_16_norm_feed_forward2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_16_norm_feed_forward2_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(211747328)))];
            tensor<fp16, [512]> encoder_module_layers_16_norm_feed_forward2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_16_norm_feed_forward2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(211748416)))];
            tensor<fp16, [1, 188, 512]> input_899_cast_fp16 = layer_norm(axes = input_899_axes_0, beta = encoder_module_layers_16_norm_feed_forward2_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_16_norm_feed_forward2_weight_to_fp16, x = input_897_cast_fp16)[name = tensor<string, []>("input_899_cast_fp16")];
            tensor<fp16, [2048, 512]> encoder_module_layers_16_feed_forward2_linear1_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_16_feed_forward2_linear1_weight_to_fp16"), val = tensor<fp16, [2048, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(211749504)))];
            tensor<fp16, [2048]> encoder_module_layers_16_feed_forward2_linear1_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_16_feed_forward2_linear1_bias_to_fp16"), val = tensor<fp16, [2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(213846720)))];
            tensor<fp16, [1, 188, 2048]> linear_152_cast_fp16 = linear(bias = encoder_module_layers_16_feed_forward2_linear1_bias_to_fp16, weight = encoder_module_layers_16_feed_forward2_linear1_weight_to_fp16, x = input_899_cast_fp16)[name = tensor<string, []>("linear_152_cast_fp16")];
            tensor<fp16, [1, 188, 2048]> input_903_cast_fp16 = silu(x = linear_152_cast_fp16)[name = tensor<string, []>("input_903_cast_fp16")];
            tensor<fp16, [512, 2048]> encoder_module_layers_16_feed_forward2_linear2_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_16_feed_forward2_linear2_weight_to_fp16"), val = tensor<fp16, [512, 2048]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(213850880)))];
            tensor<fp16, [512]> encoder_module_layers_16_feed_forward2_linear2_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_16_feed_forward2_linear2_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(215948096)))];
            tensor<fp16, [1, 188, 512]> linear_153_cast_fp16 = linear(bias = encoder_module_layers_16_feed_forward2_linear2_bias_to_fp16, weight = encoder_module_layers_16_feed_forward2_linear2_weight_to_fp16, x = input_903_cast_fp16)[name = tensor<string, []>("linear_153_cast_fp16")];
            tensor<fp16, []> var_3276_to_fp16 = const()[name = tensor<string, []>("op_3276_to_fp16"), val = tensor<fp16, []>(0x1p-1)];
            tensor<fp16, [1, 188, 512]> var_3277_cast_fp16 = mul(x = linear_153_cast_fp16, y = var_3276_to_fp16)[name = tensor<string, []>("op_3277_cast_fp16")];
            tensor<fp16, [1, 188, 512]> input_cast_fp16 = add(x = input_897_cast_fp16, y = var_3277_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, [512]> encoder_module_layers_16_norm_out_weight_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_16_norm_out_weight_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(215949184)))];
            tensor<fp16, [512]> encoder_module_layers_16_norm_out_bias_to_fp16 = const()[name = tensor<string, []>("encoder_module_layers_16_norm_out_bias_to_fp16"), val = tensor<fp16, [512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(215950272)))];
            tensor<fp16, [1, 188, 512]> audio_signal_cast_fp16 = layer_norm(axes = audio_signal_axes_0, beta = encoder_module_layers_16_norm_out_bias_to_fp16, epsilon = var_156_to_fp16, gamma = encoder_module_layers_16_norm_out_weight_to_fp16, x = input_cast_fp16)[name = tensor<string, []>("audio_signal_cast_fp16")];
            tensor<int32, [3]> obj_3_perm_0 = const()[name = tensor<string, []>("obj_3_perm_0"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<string, []> obj_3_cast_fp16_to_fp32_dtype_0 = const()[name = tensor<string, []>("obj_3_cast_fp16_to_fp32_dtype_0"), val = tensor<string, []>("fp32")];
            tensor<fp16, [1, 512, 188]> obj_3_cast_fp16 = transpose(perm = obj_3_perm_0, x = audio_signal_cast_fp16)[name = tensor<string, []>("transpose_85")];
            tensor<fp32, [1, 512, 188]> encoder = cast(dtype = obj_3_cast_fp16_to_fp32_dtype_0, x = obj_3_cast_fp16)[name = tensor<string, []>("cast_175")];
        } -> (encoder, encoder_length);
}