program(1.0)
[buildInfo = dict<tensor<string, []>, tensor<string, []>>({{"coremlc-component-MIL", "3500.14.1"}, {"coremlc-version", "3500.32.1"}, {"coremltools-component-torch", "2.8.0"}, {"coremltools-source-dialect", "TorchScript"}, {"coremltools-version", "9.0b1"}})]
{
    func main<ios17>(tensor<fp32, [1, 1, 80000]> audio, tensor<fp32, [1, 63]> weights) {
            tensor<fp32, [1, 400]> _fbank_window = const()[name = tensor<string, []>("_fbank_window"), val = tensor<fp32, [1, 400]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(64)))];
            tensor<fp32, []> _fbank_eps = const()[name = tensor<string, []>("_fbank_eps"), val = tensor<fp32, []>(0x1.b7cdfep-34)];
            tensor<fp32, [400, 1, 400]> _fbank_frame_kernel = const()[name = tensor<string, []>("_fbank_frame_kernel"), val = tensor<fp32, [400, 1, 400]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1728)))];
            tensor<fp32, [256]> resnet_seg_1_bias = const()[name = tensor<string, []>("resnet_seg_1_bias"), val = tensor<fp32, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(641792)))];
            tensor<fp32, [256, 5120]> resnet_seg_1_weight = const()[name = tensor<string, []>("resnet_seg_1_weight"), val = tensor<fp32, [256, 5120]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(642880)))];
            tensor<fp32, []> var_5_promoted = const()[name = tensor<string, []>("op_5_promoted"), val = tensor<fp32, []>(0x1p+15)];
            tensor<fp32, [1, 1, 80000]> waveforms_3 = mul(x = audio, y = var_5_promoted)[name = tensor<string, []>("waveforms_3")];
            tensor<string, []> frames_1_pad_type_0 = const()[name = tensor<string, []>("frames_1_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [1]> frames_1_strides_0 = const()[name = tensor<string, []>("frames_1_strides_0"), val = tensor<int32, [1]>([160])];
            tensor<int32, [2]> frames_1_pad_0 = const()[name = tensor<string, []>("frames_1_pad_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [1]> frames_1_dilations_0 = const()[name = tensor<string, []>("frames_1_dilations_0"), val = tensor<int32, [1]>([1])];
            tensor<int32, []> frames_1_groups_0 = const()[name = tensor<string, []>("frames_1_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp32, [1, 400, 498]> frames_1 = conv(dilations = frames_1_dilations_0, groups = frames_1_groups_0, pad = frames_1_pad_0, pad_type = frames_1_pad_type_0, strides = frames_1_strides_0, weight = _fbank_frame_kernel, x = waveforms_3)[name = tensor<string, []>("frames_1")];
            tensor<int32, [1]> var_45_axes_0 = const()[name = tensor<string, []>("op_45_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp32, [400, 498]> var_45 = squeeze(axes = var_45_axes_0, x = frames_1)[name = tensor<string, []>("op_45")];
            tensor<int32, [2]> frames_3_perm_0 = const()[name = tensor<string, []>("frames_3_perm_0"), val = tensor<int32, [2]>([1, 0])];
            tensor<int32, [1]> var_48_axes_0 = const()[name = tensor<string, []>("op_48_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<bool, []> var_48_keep_dims_0 = const()[name = tensor<string, []>("op_48_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp32, [498, 400]> frames_3 = transpose(perm = frames_3_perm_0, x = var_45)[name = tensor<string, []>("transpose_4")];
            tensor<fp32, [498, 1]> var_48 = reduce_mean(axes = var_48_axes_0, keep_dims = var_48_keep_dims_0, x = frames_3)[name = tensor<string, []>("op_48")];
            tensor<fp32, [498, 400]> frames_5 = sub(x = frames_3, y = var_48)[name = tensor<string, []>("frames_5")];
            tensor<int32, [1]> input_1_axes_0 = const()[name = tensor<string, []>("input_1_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<fp32, [498, 1, 400]> input_1 = expand_dims(axes = input_1_axes_0, x = frames_5)[name = tensor<string, []>("input_1")];
            tensor<fp32, []> const_0 = const()[name = tensor<string, []>("const_0"), val = tensor<fp32, []>(0x0p+0)];
            tensor<int32, [6]> var_52_pad_0 = const()[name = tensor<string, []>("op_52_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 1, 0])];
            tensor<string, []> var_52_mode_0 = const()[name = tensor<string, []>("op_52_mode_0"), val = tensor<string, []>("replicate")];
            tensor<fp32, [498, 1, 401]> var_52 = pad(constant_val = const_0, mode = var_52_mode_0, pad = var_52_pad_0, x = input_1)[name = tensor<string, []>("op_52")];
            tensor<int32, [1]> padded_axes_0 = const()[name = tensor<string, []>("padded_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<fp32, [498, 401]> padded = squeeze(axes = padded_axes_0, x = var_52)[name = tensor<string, []>("padded")];
            tensor<int32, [2]> var_55_begin_0 = const()[name = tensor<string, []>("op_55_begin_0"), val = tensor<int32, [2]>([0, 0])];
            tensor<int32, [2]> var_55_end_0 = const()[name = tensor<string, []>("op_55_end_0"), val = tensor<int32, [2]>([498, 400])];
            tensor<bool, [2]> var_55_end_mask_0 = const()[name = tensor<string, []>("op_55_end_mask_0"), val = tensor<bool, [2]>([true, false])];
            tensor<fp32, [498, 400]> var_55 = slice_by_index(begin = var_55_begin_0, end = var_55_end_0, end_mask = var_55_end_mask_0, x = padded)[name = tensor<string, []>("op_55")];
            tensor<fp32, []> var_56 = const()[name = tensor<string, []>("op_56"), val = tensor<fp32, []>(0x1.f0a3d8p-1)];
            tensor<fp32, [498, 400]> var_57 = mul(x = var_55, y = var_56)[name = tensor<string, []>("op_57")];
            tensor<fp32, [498, 400]> frames_7 = sub(x = frames_5, y = var_57)[name = tensor<string, []>("frames_7")];
            tensor<fp32, [498, 400]> frames_9 = mul(x = frames_7, y = _fbank_window)[name = tensor<string, []>("frames_9")];
            tensor<int32, [1]> input_3_axes_0 = const()[name = tensor<string, []>("input_3_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<fp32, [498, 1, 400]> input_3 = expand_dims(axes = input_3_axes_0, x = frames_9)[name = tensor<string, []>("input_3")];
            tensor<fp32, []> const_1 = const()[name = tensor<string, []>("const_1"), val = tensor<fp32, []>(0x0p+0)];
            tensor<int32, [6]> var_62_pad_0 = const()[name = tensor<string, []>("op_62_pad_0"), val = tensor<int32, [6]>([0, 0, 0, 0, 0, 112])];
            tensor<string, []> var_62_mode_0 = const()[name = tensor<string, []>("op_62_mode_0"), val = tensor<string, []>("constant")];
            tensor<fp32, [498, 1, 512]> var_62 = pad(constant_val = const_1, mode = var_62_mode_0, pad = var_62_pad_0, x = input_3)[name = tensor<string, []>("op_62")];
            tensor<int32, [1]> frames_11_axes_0 = const()[name = tensor<string, []>("frames_11_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<fp32, [498, 512]> frames_11 = squeeze(axes = frames_11_axes_0, x = var_62)[name = tensor<string, []>("frames_11")];
            tensor<fp32, [257, 512]> transpose_0 = const()[name = tensor<string, []>("transpose_0"), val = tensor<fp32, [257, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(5885824)))];
            tensor<fp32, [257]> real_bias_0 = const()[name = tensor<string, []>("real_bias_0"), val = tensor<fp32, [257]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6412224)))];
            tensor<fp32, [498, 257]> real = linear(bias = real_bias_0, weight = transpose_0, x = frames_11)[name = tensor<string, []>("real")];
            tensor<fp32, [257, 512]> transpose_1 = const()[name = tensor<string, []>("transpose_1"), val = tensor<fp32, [257, 512]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6413376)))];
            tensor<fp32, [498, 257]> imag = linear(bias = real_bias_0, weight = transpose_1, x = frames_11)[name = tensor<string, []>("imag")];
            tensor<fp32, []> var_18_promoted = const()[name = tensor<string, []>("op_18_promoted"), val = tensor<fp32, []>(0x1p+1)];
            tensor<fp32, [498, 257]> var_66 = pow(x = real, y = var_18_promoted)[name = tensor<string, []>("op_66")];
            tensor<fp32, []> var_18_promoted_1 = const()[name = tensor<string, []>("op_18_promoted_1"), val = tensor<fp32, []>(0x1p+1)];
            tensor<fp32, [498, 257]> var_67 = pow(x = imag, y = var_18_promoted_1)[name = tensor<string, []>("op_67")];
            tensor<fp32, [498, 257]> power = add(x = var_66, y = var_67)[name = tensor<string, []>("power")];
            tensor<fp32, [80, 257]> transpose_2 = const()[name = tensor<string, []>("transpose_2"), val = tensor<fp32, [80, 257]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6939776)))];
            tensor<fp32, [80]> mel_bias_0 = const()[name = tensor<string, []>("mel_bias_0"), val = tensor<fp32, [80]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7022080)))];
            tensor<fp32, [498, 80]> mel = linear(bias = mel_bias_0, weight = transpose_2, x = power)[name = tensor<string, []>("mel")];
            tensor<fp32, []> const_2 = const()[name = tensor<string, []>("const_2"), val = tensor<fp32, []>(0x1.fffffep+127)];
            tensor<fp32, [498, 80]> clip_0 = clip(alpha = _fbank_eps, beta = const_2, x = mel)[name = tensor<string, []>("clip_0")];
            tensor<fp32, []> var_71_epsilon_0 = const()[name = tensor<string, []>("op_71_epsilon_0"), val = tensor<fp32, []>(0x1p-149)];
            tensor<fp32, [498, 80]> var_71 = log(epsilon = var_71_epsilon_0, x = clip_0)[name = tensor<string, []>("op_71")];
            tensor<int32, [1]> var_74_axes_0 = const()[name = tensor<string, []>("op_74_axes_0"), val = tensor<int32, [1]>([0])];
            tensor<fp32, [1, 498, 80]> var_74 = expand_dims(axes = var_74_axes_0, x = var_71)[name = tensor<string, []>("op_74")];
            tensor<int32, [1]> centered_axes_0 = const()[name = tensor<string, []>("centered_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<bool, []> centered_keep_dims_0 = const()[name = tensor<string, []>("centered_keep_dims_0"), val = tensor<bool, []>(true)];
            tensor<fp32, [1, 1, 80]> centered = reduce_mean(axes = centered_axes_0, keep_dims = centered_keep_dims_0, x = var_74)[name = tensor<string, []>("centered")];
            tensor<fp32, [1, 498, 80]> fbank_1 = sub(x = var_74, y = centered)[name = tensor<string, []>("fbank_1")];
            tensor<int32, []> var_91 = const()[name = tensor<string, []>("op_91"), val = tensor<int32, []>(-1)];
            tensor<fp32, []> var_92 = const()[name = tensor<string, []>("op_92"), val = tensor<fp32, []>(0x1.197998p-40)];
            tensor<int32, [3]> var_108 = const()[name = tensor<string, []>("op_108"), val = tensor<int32, [3]>([0, 2, 1])];
            tensor<int32, [1]> input_5_axes_0 = const()[name = tensor<string, []>("input_5_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<fp32, [1, 80, 498]> fbank = transpose(perm = var_108, x = fbank_1)[name = tensor<string, []>("transpose_3")];
            tensor<fp32, [1, 1, 80, 498]> input_5 = expand_dims(axes = input_5_axes_0, x = fbank)[name = tensor<string, []>("input_5")];
            tensor<string, []> input_7_pad_type_0 = const()[name = tensor<string, []>("input_7_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_7_pad_0 = const()[name = tensor<string, []>("input_7_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_7_strides_0 = const()[name = tensor<string, []>("input_7_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_7_dilations_0 = const()[name = tensor<string, []>("input_7_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_7_groups_0 = const()[name = tensor<string, []>("input_7_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp32, [32, 1, 3, 3]> const_8 = const()[name = tensor<string, []>("const_8"), val = tensor<fp32, [32, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7022464)))];
            tensor<fp32, [32]> const_9 = const()[name = tensor<string, []>("const_9"), val = tensor<fp32, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7023680)))];
            tensor<fp32, [1, 32, 80, 498]> input_9 = conv(bias = const_9, dilations = input_7_dilations_0, groups = input_7_groups_0, pad = input_7_pad_0, pad_type = input_7_pad_type_0, strides = input_7_strides_0, weight = const_8, x = input_5)[name = tensor<string, []>("input_9")];
            tensor<fp32, [1, 32, 80, 498]> input_11 = relu(x = input_9)[name = tensor<string, []>("input_11")];
            tensor<string, []> input_13_pad_type_0 = const()[name = tensor<string, []>("input_13_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_13_pad_0 = const()[name = tensor<string, []>("input_13_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_13_strides_0 = const()[name = tensor<string, []>("input_13_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_13_dilations_0 = const()[name = tensor<string, []>("input_13_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_13_groups_0 = const()[name = tensor<string, []>("input_13_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp32, [32, 32, 3, 3]> const_10 = const()[name = tensor<string, []>("const_10"), val = tensor<fp32, [32, 32, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7023872)))];
            tensor<fp32, [32]> const_11 = const()[name = tensor<string, []>("const_11"), val = tensor<fp32, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7060800)))];
            tensor<fp32, [1, 32, 80, 498]> input_15 = conv(bias = const_11, dilations = input_13_dilations_0, groups = input_13_groups_0, pad = input_13_pad_0, pad_type = input_13_pad_type_0, strides = input_13_strides_0, weight = const_10, x = input_11)[name = tensor<string, []>("input_15")];
            tensor<fp32, [1, 32, 80, 498]> input_17 = relu(x = input_15)[name = tensor<string, []>("input_17")];
            tensor<string, []> input_19_pad_type_0 = const()[name = tensor<string, []>("input_19_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_19_pad_0 = const()[name = tensor<string, []>("input_19_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_19_strides_0 = const()[name = tensor<string, []>("input_19_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_19_dilations_0 = const()[name = tensor<string, []>("input_19_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_19_groups_0 = const()[name = tensor<string, []>("input_19_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp32, [32, 32, 3, 3]> const_12 = const()[name = tensor<string, []>("const_12"), val = tensor<fp32, [32, 32, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7060992)))];
            tensor<fp32, [32]> const_13 = const()[name = tensor<string, []>("const_13"), val = tensor<fp32, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7097920)))];
            tensor<fp32, [1, 32, 80, 498]> out_1 = conv(bias = const_13, dilations = input_19_dilations_0, groups = input_19_groups_0, pad = input_19_pad_0, pad_type = input_19_pad_type_0, strides = input_19_strides_0, weight = const_12, x = input_17)[name = tensor<string, []>("out_1")];
            tensor<fp32, [1, 32, 80, 498]> input_21 = add(x = out_1, y = input_11)[name = tensor<string, []>("input_21")];
            tensor<fp32, [1, 32, 80, 498]> input_23 = relu(x = input_21)[name = tensor<string, []>("input_23")];
            tensor<string, []> input_25_pad_type_0 = const()[name = tensor<string, []>("input_25_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_25_pad_0 = const()[name = tensor<string, []>("input_25_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_25_strides_0 = const()[name = tensor<string, []>("input_25_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_25_dilations_0 = const()[name = tensor<string, []>("input_25_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_25_groups_0 = const()[name = tensor<string, []>("input_25_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp32, [32, 32, 3, 3]> const_14 = const()[name = tensor<string, []>("const_14"), val = tensor<fp32, [32, 32, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7098112)))];
            tensor<fp32, [32]> const_15 = const()[name = tensor<string, []>("const_15"), val = tensor<fp32, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7135040)))];
            tensor<fp32, [1, 32, 80, 498]> input_27 = conv(bias = const_15, dilations = input_25_dilations_0, groups = input_25_groups_0, pad = input_25_pad_0, pad_type = input_25_pad_type_0, strides = input_25_strides_0, weight = const_14, x = input_23)[name = tensor<string, []>("input_27")];
            tensor<fp32, [1, 32, 80, 498]> input_29 = relu(x = input_27)[name = tensor<string, []>("input_29")];
            tensor<string, []> input_31_pad_type_0 = const()[name = tensor<string, []>("input_31_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_31_pad_0 = const()[name = tensor<string, []>("input_31_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_31_strides_0 = const()[name = tensor<string, []>("input_31_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_31_dilations_0 = const()[name = tensor<string, []>("input_31_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_31_groups_0 = const()[name = tensor<string, []>("input_31_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp32, [32, 32, 3, 3]> const_16 = const()[name = tensor<string, []>("const_16"), val = tensor<fp32, [32, 32, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7135232)))];
            tensor<fp32, [32]> const_17 = const()[name = tensor<string, []>("const_17"), val = tensor<fp32, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7172160)))];
            tensor<fp32, [1, 32, 80, 498]> out_3 = conv(bias = const_17, dilations = input_31_dilations_0, groups = input_31_groups_0, pad = input_31_pad_0, pad_type = input_31_pad_type_0, strides = input_31_strides_0, weight = const_16, x = input_29)[name = tensor<string, []>("out_3")];
            tensor<fp32, [1, 32, 80, 498]> input_33 = add(x = out_3, y = input_23)[name = tensor<string, []>("input_33")];
            tensor<fp32, [1, 32, 80, 498]> input_35 = relu(x = input_33)[name = tensor<string, []>("input_35")];
            tensor<string, []> input_37_pad_type_0 = const()[name = tensor<string, []>("input_37_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_37_pad_0 = const()[name = tensor<string, []>("input_37_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_37_strides_0 = const()[name = tensor<string, []>("input_37_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_37_dilations_0 = const()[name = tensor<string, []>("input_37_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_37_groups_0 = const()[name = tensor<string, []>("input_37_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp32, [32, 32, 3, 3]> const_18 = const()[name = tensor<string, []>("const_18"), val = tensor<fp32, [32, 32, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7172352)))];
            tensor<fp32, [32]> const_19 = const()[name = tensor<string, []>("const_19"), val = tensor<fp32, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7209280)))];
            tensor<fp32, [1, 32, 80, 498]> input_39 = conv(bias = const_19, dilations = input_37_dilations_0, groups = input_37_groups_0, pad = input_37_pad_0, pad_type = input_37_pad_type_0, strides = input_37_strides_0, weight = const_18, x = input_35)[name = tensor<string, []>("input_39")];
            tensor<fp32, [1, 32, 80, 498]> input_41 = relu(x = input_39)[name = tensor<string, []>("input_41")];
            tensor<string, []> input_43_pad_type_0 = const()[name = tensor<string, []>("input_43_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_43_pad_0 = const()[name = tensor<string, []>("input_43_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_43_strides_0 = const()[name = tensor<string, []>("input_43_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_43_dilations_0 = const()[name = tensor<string, []>("input_43_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_43_groups_0 = const()[name = tensor<string, []>("input_43_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp32, [32, 32, 3, 3]> const_20 = const()[name = tensor<string, []>("const_20"), val = tensor<fp32, [32, 32, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7209472)))];
            tensor<fp32, [32]> const_21 = const()[name = tensor<string, []>("const_21"), val = tensor<fp32, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7246400)))];
            tensor<fp32, [1, 32, 80, 498]> out_5 = conv(bias = const_21, dilations = input_43_dilations_0, groups = input_43_groups_0, pad = input_43_pad_0, pad_type = input_43_pad_type_0, strides = input_43_strides_0, weight = const_20, x = input_41)[name = tensor<string, []>("out_5")];
            tensor<fp32, [1, 32, 80, 498]> input_45 = add(x = out_5, y = input_35)[name = tensor<string, []>("input_45")];
            tensor<fp32, [1, 32, 80, 498]> input_47 = relu(x = input_45)[name = tensor<string, []>("input_47")];
            tensor<string, []> input_49_pad_type_0 = const()[name = tensor<string, []>("input_49_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_49_pad_0 = const()[name = tensor<string, []>("input_49_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_49_strides_0 = const()[name = tensor<string, []>("input_49_strides_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [2]> input_49_dilations_0 = const()[name = tensor<string, []>("input_49_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_49_groups_0 = const()[name = tensor<string, []>("input_49_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp32, [64, 32, 3, 3]> const_22 = const()[name = tensor<string, []>("const_22"), val = tensor<fp32, [64, 32, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7246592)))];
            tensor<fp32, [64]> const_23 = const()[name = tensor<string, []>("const_23"), val = tensor<fp32, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7320384)))];
            tensor<fp32, [1, 64, 40, 249]> input_51 = conv(bias = const_23, dilations = input_49_dilations_0, groups = input_49_groups_0, pad = input_49_pad_0, pad_type = input_49_pad_type_0, strides = input_49_strides_0, weight = const_22, x = input_47)[name = tensor<string, []>("input_51")];
            tensor<fp32, [1, 64, 40, 249]> input_53 = relu(x = input_51)[name = tensor<string, []>("input_53")];
            tensor<string, []> input_55_pad_type_0 = const()[name = tensor<string, []>("input_55_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_55_pad_0 = const()[name = tensor<string, []>("input_55_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_55_strides_0 = const()[name = tensor<string, []>("input_55_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_55_dilations_0 = const()[name = tensor<string, []>("input_55_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_55_groups_0 = const()[name = tensor<string, []>("input_55_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp32, [64, 64, 3, 3]> const_24 = const()[name = tensor<string, []>("const_24"), val = tensor<fp32, [64, 64, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7320704)))];
            tensor<fp32, [64]> const_25 = const()[name = tensor<string, []>("const_25"), val = tensor<fp32, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7468224)))];
            tensor<fp32, [1, 64, 40, 249]> out_7 = conv(bias = const_25, dilations = input_55_dilations_0, groups = input_55_groups_0, pad = input_55_pad_0, pad_type = input_55_pad_type_0, strides = input_55_strides_0, weight = const_24, x = input_53)[name = tensor<string, []>("out_7")];
            tensor<string, []> input_57_pad_type_0 = const()[name = tensor<string, []>("input_57_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [2]> input_57_strides_0 = const()[name = tensor<string, []>("input_57_strides_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [4]> input_57_pad_0 = const()[name = tensor<string, []>("input_57_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> input_57_dilations_0 = const()[name = tensor<string, []>("input_57_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_57_groups_0 = const()[name = tensor<string, []>("input_57_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp32, [64, 32, 1, 1]> const_26 = const()[name = tensor<string, []>("const_26"), val = tensor<fp32, [64, 32, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7468544)))];
            tensor<fp32, [64]> const_27 = const()[name = tensor<string, []>("const_27"), val = tensor<fp32, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7476800)))];
            tensor<fp32, [1, 64, 40, 249]> var_257 = conv(bias = const_27, 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_26, x = input_47)[name = tensor<string, []>("op_257")];
            tensor<fp32, [1, 64, 40, 249]> input_59 = add(x = out_7, y = var_257)[name = tensor<string, []>("input_59")];
            tensor<fp32, [1, 64, 40, 249]> input_61 = relu(x = input_59)[name = tensor<string, []>("input_61")];
            tensor<string, []> input_63_pad_type_0 = const()[name = tensor<string, []>("input_63_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_63_pad_0 = const()[name = tensor<string, []>("input_63_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_63_strides_0 = const()[name = tensor<string, []>("input_63_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_63_dilations_0 = const()[name = tensor<string, []>("input_63_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_63_groups_0 = const()[name = tensor<string, []>("input_63_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp32, [64, 64, 3, 3]> const_28 = const()[name = tensor<string, []>("const_28"), val = tensor<fp32, [64, 64, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7477120)))];
            tensor<fp32, [64]> const_29 = const()[name = tensor<string, []>("const_29"), val = tensor<fp32, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7624640)))];
            tensor<fp32, [1, 64, 40, 249]> input_65 = conv(bias = const_29, dilations = input_63_dilations_0, groups = input_63_groups_0, pad = input_63_pad_0, pad_type = input_63_pad_type_0, strides = input_63_strides_0, weight = const_28, x = input_61)[name = tensor<string, []>("input_65")];
            tensor<fp32, [1, 64, 40, 249]> input_67 = relu(x = input_65)[name = tensor<string, []>("input_67")];
            tensor<string, []> input_69_pad_type_0 = const()[name = tensor<string, []>("input_69_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_69_pad_0 = const()[name = tensor<string, []>("input_69_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_69_strides_0 = const()[name = tensor<string, []>("input_69_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_69_dilations_0 = const()[name = tensor<string, []>("input_69_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_69_groups_0 = const()[name = tensor<string, []>("input_69_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp32, [64, 64, 3, 3]> const_30 = const()[name = tensor<string, []>("const_30"), val = tensor<fp32, [64, 64, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7624960)))];
            tensor<fp32, [64]> const_31 = const()[name = tensor<string, []>("const_31"), val = tensor<fp32, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7772480)))];
            tensor<fp32, [1, 64, 40, 249]> out_9 = conv(bias = const_31, dilations = input_69_dilations_0, groups = input_69_groups_0, pad = input_69_pad_0, pad_type = input_69_pad_type_0, strides = input_69_strides_0, weight = const_30, x = input_67)[name = tensor<string, []>("out_9")];
            tensor<fp32, [1, 64, 40, 249]> input_71 = add(x = out_9, y = input_61)[name = tensor<string, []>("input_71")];
            tensor<fp32, [1, 64, 40, 249]> input_73 = relu(x = input_71)[name = tensor<string, []>("input_73")];
            tensor<string, []> input_75_pad_type_0 = const()[name = tensor<string, []>("input_75_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_75_pad_0 = const()[name = tensor<string, []>("input_75_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_75_strides_0 = const()[name = tensor<string, []>("input_75_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_75_dilations_0 = const()[name = tensor<string, []>("input_75_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_75_groups_0 = const()[name = tensor<string, []>("input_75_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp32, [64, 64, 3, 3]> const_32 = const()[name = tensor<string, []>("const_32"), val = tensor<fp32, [64, 64, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7772800)))];
            tensor<fp32, [64]> const_33 = const()[name = tensor<string, []>("const_33"), val = tensor<fp32, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7920320)))];
            tensor<fp32, [1, 64, 40, 249]> input_77 = conv(bias = const_33, dilations = input_75_dilations_0, groups = input_75_groups_0, pad = input_75_pad_0, pad_type = input_75_pad_type_0, strides = input_75_strides_0, weight = const_32, x = input_73)[name = tensor<string, []>("input_77")];
            tensor<fp32, [1, 64, 40, 249]> input_79 = relu(x = input_77)[name = tensor<string, []>("input_79")];
            tensor<string, []> input_81_pad_type_0 = const()[name = tensor<string, []>("input_81_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_81_pad_0 = const()[name = tensor<string, []>("input_81_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_81_strides_0 = const()[name = tensor<string, []>("input_81_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_81_dilations_0 = const()[name = tensor<string, []>("input_81_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_81_groups_0 = const()[name = tensor<string, []>("input_81_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp32, [64, 64, 3, 3]> const_34 = const()[name = tensor<string, []>("const_34"), val = tensor<fp32, [64, 64, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7920640)))];
            tensor<fp32, [64]> const_35 = const()[name = tensor<string, []>("const_35"), val = tensor<fp32, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8068160)))];
            tensor<fp32, [1, 64, 40, 249]> out_11 = conv(bias = const_35, dilations = input_81_dilations_0, groups = input_81_groups_0, pad = input_81_pad_0, pad_type = input_81_pad_type_0, strides = input_81_strides_0, weight = const_34, x = input_79)[name = tensor<string, []>("out_11")];
            tensor<fp32, [1, 64, 40, 249]> input_83 = add(x = out_11, y = input_73)[name = tensor<string, []>("input_83")];
            tensor<fp32, [1, 64, 40, 249]> input_85 = relu(x = input_83)[name = tensor<string, []>("input_85")];
            tensor<string, []> input_87_pad_type_0 = const()[name = tensor<string, []>("input_87_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_87_pad_0 = const()[name = tensor<string, []>("input_87_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_87_strides_0 = const()[name = tensor<string, []>("input_87_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_87_dilations_0 = const()[name = tensor<string, []>("input_87_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_87_groups_0 = const()[name = tensor<string, []>("input_87_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp32, [64, 64, 3, 3]> const_36 = const()[name = tensor<string, []>("const_36"), val = tensor<fp32, [64, 64, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8068480)))];
            tensor<fp32, [64]> const_37 = const()[name = tensor<string, []>("const_37"), val = tensor<fp32, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8216000)))];
            tensor<fp32, [1, 64, 40, 249]> input_89 = conv(bias = const_37, dilations = input_87_dilations_0, groups = input_87_groups_0, pad = input_87_pad_0, pad_type = input_87_pad_type_0, strides = input_87_strides_0, weight = const_36, x = input_85)[name = tensor<string, []>("input_89")];
            tensor<fp32, [1, 64, 40, 249]> input_91 = relu(x = input_89)[name = tensor<string, []>("input_91")];
            tensor<string, []> input_93_pad_type_0 = const()[name = tensor<string, []>("input_93_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_93_pad_0 = const()[name = tensor<string, []>("input_93_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_93_strides_0 = const()[name = tensor<string, []>("input_93_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_93_dilations_0 = const()[name = tensor<string, []>("input_93_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_93_groups_0 = const()[name = tensor<string, []>("input_93_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp32, [64, 64, 3, 3]> const_38 = const()[name = tensor<string, []>("const_38"), val = tensor<fp32, [64, 64, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8216320)))];
            tensor<fp32, [64]> const_39 = const()[name = tensor<string, []>("const_39"), val = tensor<fp32, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8363840)))];
            tensor<fp32, [1, 64, 40, 249]> out_13 = conv(bias = const_39, dilations = input_93_dilations_0, groups = input_93_groups_0, pad = input_93_pad_0, pad_type = input_93_pad_type_0, strides = input_93_strides_0, weight = const_38, x = input_91)[name = tensor<string, []>("out_13")];
            tensor<fp32, [1, 64, 40, 249]> input_95 = add(x = out_13, y = input_85)[name = tensor<string, []>("input_95")];
            tensor<fp32, [1, 64, 40, 249]> input_97 = relu(x = input_95)[name = tensor<string, []>("input_97")];
            tensor<string, []> input_99_pad_type_0 = const()[name = tensor<string, []>("input_99_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_99_pad_0 = const()[name = tensor<string, []>("input_99_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_99_strides_0 = const()[name = tensor<string, []>("input_99_strides_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [2]> input_99_dilations_0 = const()[name = tensor<string, []>("input_99_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_99_groups_0 = const()[name = tensor<string, []>("input_99_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp32, [128, 64, 3, 3]> const_40 = const()[name = tensor<string, []>("const_40"), val = tensor<fp32, [128, 64, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8364160)))];
            tensor<fp32, [128]> const_41 = const()[name = tensor<string, []>("const_41"), val = tensor<fp32, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8659136)))];
            tensor<fp32, [1, 128, 20, 125]> input_101 = conv(bias = const_41, dilations = input_99_dilations_0, groups = input_99_groups_0, pad = input_99_pad_0, pad_type = input_99_pad_type_0, strides = input_99_strides_0, weight = const_40, x = input_97)[name = tensor<string, []>("input_101")];
            tensor<fp32, [1, 128, 20, 125]> input_103 = relu(x = input_101)[name = tensor<string, []>("input_103")];
            tensor<string, []> input_105_pad_type_0 = const()[name = tensor<string, []>("input_105_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_105_pad_0 = const()[name = tensor<string, []>("input_105_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_105_strides_0 = const()[name = tensor<string, []>("input_105_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_105_dilations_0 = const()[name = tensor<string, []>("input_105_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_105_groups_0 = const()[name = tensor<string, []>("input_105_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp32, [128, 128, 3, 3]> const_42 = const()[name = tensor<string, []>("const_42"), val = tensor<fp32, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8659712)))];
            tensor<fp32, [128]> const_43 = const()[name = tensor<string, []>("const_43"), val = tensor<fp32, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9249600)))];
            tensor<fp32, [1, 128, 20, 125]> out_15 = conv(bias = const_43, dilations = input_105_dilations_0, groups = input_105_groups_0, pad = input_105_pad_0, pad_type = input_105_pad_type_0, strides = input_105_strides_0, weight = const_42, x = input_103)[name = tensor<string, []>("out_15")];
            tensor<string, []> input_107_pad_type_0 = const()[name = tensor<string, []>("input_107_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [2]> input_107_strides_0 = const()[name = tensor<string, []>("input_107_strides_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [4]> input_107_pad_0 = const()[name = tensor<string, []>("input_107_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> input_107_dilations_0 = const()[name = tensor<string, []>("input_107_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_107_groups_0 = const()[name = tensor<string, []>("input_107_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp32, [128, 64, 1, 1]> const_44 = const()[name = tensor<string, []>("const_44"), val = tensor<fp32, [128, 64, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9250176)))];
            tensor<fp32, [128]> const_45 = const()[name = tensor<string, []>("const_45"), val = tensor<fp32, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9283008)))];
            tensor<fp32, [1, 128, 20, 125]> var_393 = conv(bias = const_45, dilations = input_107_dilations_0, groups = input_107_groups_0, pad = input_107_pad_0, pad_type = input_107_pad_type_0, strides = input_107_strides_0, weight = const_44, x = input_97)[name = tensor<string, []>("op_393")];
            tensor<fp32, [1, 128, 20, 125]> input_109 = add(x = out_15, y = var_393)[name = tensor<string, []>("input_109")];
            tensor<fp32, [1, 128, 20, 125]> input_111 = relu(x = input_109)[name = tensor<string, []>("input_111")];
            tensor<string, []> input_113_pad_type_0 = const()[name = tensor<string, []>("input_113_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_113_pad_0 = const()[name = tensor<string, []>("input_113_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_113_strides_0 = const()[name = tensor<string, []>("input_113_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_113_dilations_0 = const()[name = tensor<string, []>("input_113_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_113_groups_0 = const()[name = tensor<string, []>("input_113_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp32, [128, 128, 3, 3]> const_46 = const()[name = tensor<string, []>("const_46"), val = tensor<fp32, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9283584)))];
            tensor<fp32, [128]> const_47 = const()[name = tensor<string, []>("const_47"), val = tensor<fp32, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9873472)))];
            tensor<fp32, [1, 128, 20, 125]> input_115 = conv(bias = const_47, dilations = input_113_dilations_0, groups = input_113_groups_0, pad = input_113_pad_0, pad_type = input_113_pad_type_0, strides = input_113_strides_0, weight = const_46, x = input_111)[name = tensor<string, []>("input_115")];
            tensor<fp32, [1, 128, 20, 125]> input_117 = relu(x = input_115)[name = tensor<string, []>("input_117")];
            tensor<string, []> input_119_pad_type_0 = const()[name = tensor<string, []>("input_119_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_119_pad_0 = const()[name = tensor<string, []>("input_119_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_119_strides_0 = const()[name = tensor<string, []>("input_119_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_119_dilations_0 = const()[name = tensor<string, []>("input_119_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_119_groups_0 = const()[name = tensor<string, []>("input_119_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp32, [128, 128, 3, 3]> const_48 = const()[name = tensor<string, []>("const_48"), val = tensor<fp32, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9874048)))];
            tensor<fp32, [128]> const_49 = const()[name = tensor<string, []>("const_49"), val = tensor<fp32, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10463936)))];
            tensor<fp32, [1, 128, 20, 125]> out_17 = conv(bias = const_49, dilations = input_119_dilations_0, groups = input_119_groups_0, pad = input_119_pad_0, pad_type = input_119_pad_type_0, strides = input_119_strides_0, weight = const_48, x = input_117)[name = tensor<string, []>("out_17")];
            tensor<fp32, [1, 128, 20, 125]> input_121 = add(x = out_17, y = input_111)[name = tensor<string, []>("input_121")];
            tensor<fp32, [1, 128, 20, 125]> input_123 = relu(x = input_121)[name = tensor<string, []>("input_123")];
            tensor<string, []> input_125_pad_type_0 = const()[name = tensor<string, []>("input_125_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_125_pad_0 = const()[name = tensor<string, []>("input_125_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_125_strides_0 = const()[name = tensor<string, []>("input_125_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_125_dilations_0 = const()[name = tensor<string, []>("input_125_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_125_groups_0 = const()[name = tensor<string, []>("input_125_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp32, [128, 128, 3, 3]> const_50 = const()[name = tensor<string, []>("const_50"), val = tensor<fp32, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10464512)))];
            tensor<fp32, [128]> const_51 = const()[name = tensor<string, []>("const_51"), val = tensor<fp32, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11054400)))];
            tensor<fp32, [1, 128, 20, 125]> input_127 = conv(bias = const_51, dilations = input_125_dilations_0, groups = input_125_groups_0, pad = input_125_pad_0, pad_type = input_125_pad_type_0, strides = input_125_strides_0, weight = const_50, x = input_123)[name = tensor<string, []>("input_127")];
            tensor<fp32, [1, 128, 20, 125]> input_129 = relu(x = input_127)[name = tensor<string, []>("input_129")];
            tensor<string, []> input_131_pad_type_0 = const()[name = tensor<string, []>("input_131_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_131_pad_0 = const()[name = tensor<string, []>("input_131_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_131_strides_0 = const()[name = tensor<string, []>("input_131_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_131_dilations_0 = const()[name = tensor<string, []>("input_131_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_131_groups_0 = const()[name = tensor<string, []>("input_131_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp32, [128, 128, 3, 3]> const_52 = const()[name = tensor<string, []>("const_52"), val = tensor<fp32, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11054976)))];
            tensor<fp32, [128]> const_53 = const()[name = tensor<string, []>("const_53"), val = tensor<fp32, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11644864)))];
            tensor<fp32, [1, 128, 20, 125]> out_19 = conv(bias = const_53, dilations = input_131_dilations_0, groups = input_131_groups_0, pad = input_131_pad_0, pad_type = input_131_pad_type_0, strides = input_131_strides_0, weight = const_52, x = input_129)[name = tensor<string, []>("out_19")];
            tensor<fp32, [1, 128, 20, 125]> input_133 = add(x = out_19, y = input_123)[name = tensor<string, []>("input_133")];
            tensor<fp32, [1, 128, 20, 125]> input_135 = relu(x = input_133)[name = tensor<string, []>("input_135")];
            tensor<string, []> input_137_pad_type_0 = const()[name = tensor<string, []>("input_137_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_137_pad_0 = const()[name = tensor<string, []>("input_137_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_137_strides_0 = const()[name = tensor<string, []>("input_137_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_137_dilations_0 = const()[name = tensor<string, []>("input_137_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_137_groups_0 = const()[name = tensor<string, []>("input_137_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp32, [128, 128, 3, 3]> const_54 = const()[name = tensor<string, []>("const_54"), val = tensor<fp32, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(11645440)))];
            tensor<fp32, [128]> const_55 = const()[name = tensor<string, []>("const_55"), val = tensor<fp32, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12235328)))];
            tensor<fp32, [1, 128, 20, 125]> input_139 = conv(bias = const_55, dilations = input_137_dilations_0, groups = input_137_groups_0, pad = input_137_pad_0, pad_type = input_137_pad_type_0, strides = input_137_strides_0, weight = const_54, x = input_135)[name = tensor<string, []>("input_139")];
            tensor<fp32, [1, 128, 20, 125]> input_141 = relu(x = input_139)[name = tensor<string, []>("input_141")];
            tensor<string, []> input_143_pad_type_0 = const()[name = tensor<string, []>("input_143_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_143_pad_0 = const()[name = tensor<string, []>("input_143_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_143_strides_0 = const()[name = tensor<string, []>("input_143_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_143_dilations_0 = const()[name = tensor<string, []>("input_143_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_143_groups_0 = const()[name = tensor<string, []>("input_143_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp32, [128, 128, 3, 3]> const_56 = const()[name = tensor<string, []>("const_56"), val = tensor<fp32, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12235904)))];
            tensor<fp32, [128]> const_57 = const()[name = tensor<string, []>("const_57"), val = tensor<fp32, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12825792)))];
            tensor<fp32, [1, 128, 20, 125]> out_21 = conv(bias = const_57, dilations = input_143_dilations_0, groups = input_143_groups_0, pad = input_143_pad_0, pad_type = input_143_pad_type_0, strides = input_143_strides_0, weight = const_56, x = input_141)[name = tensor<string, []>("out_21")];
            tensor<fp32, [1, 128, 20, 125]> input_145 = add(x = out_21, y = input_135)[name = tensor<string, []>("input_145")];
            tensor<fp32, [1, 128, 20, 125]> input_147 = relu(x = input_145)[name = tensor<string, []>("input_147")];
            tensor<string, []> input_149_pad_type_0 = const()[name = tensor<string, []>("input_149_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_149_pad_0 = const()[name = tensor<string, []>("input_149_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_149_strides_0 = const()[name = tensor<string, []>("input_149_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_149_dilations_0 = const()[name = tensor<string, []>("input_149_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_149_groups_0 = const()[name = tensor<string, []>("input_149_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp32, [128, 128, 3, 3]> const_58 = const()[name = tensor<string, []>("const_58"), val = tensor<fp32, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(12826368)))];
            tensor<fp32, [128]> const_59 = const()[name = tensor<string, []>("const_59"), val = tensor<fp32, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13416256)))];
            tensor<fp32, [1, 128, 20, 125]> input_151 = conv(bias = const_59, dilations = input_149_dilations_0, groups = input_149_groups_0, pad = input_149_pad_0, pad_type = input_149_pad_type_0, strides = input_149_strides_0, weight = const_58, x = input_147)[name = tensor<string, []>("input_151")];
            tensor<fp32, [1, 128, 20, 125]> input_153 = relu(x = input_151)[name = tensor<string, []>("input_153")];
            tensor<string, []> input_155_pad_type_0 = const()[name = tensor<string, []>("input_155_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_155_pad_0 = const()[name = tensor<string, []>("input_155_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_155_strides_0 = const()[name = tensor<string, []>("input_155_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_155_dilations_0 = const()[name = tensor<string, []>("input_155_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_155_groups_0 = const()[name = tensor<string, []>("input_155_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp32, [128, 128, 3, 3]> const_60 = const()[name = tensor<string, []>("const_60"), val = tensor<fp32, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13416832)))];
            tensor<fp32, [128]> const_61 = const()[name = tensor<string, []>("const_61"), val = tensor<fp32, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14006720)))];
            tensor<fp32, [1, 128, 20, 125]> out_23 = conv(bias = const_61, 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 = const_60, x = input_153)[name = tensor<string, []>("out_23")];
            tensor<fp32, [1, 128, 20, 125]> input_157 = add(x = out_23, y = input_147)[name = tensor<string, []>("input_157")];
            tensor<fp32, [1, 128, 20, 125]> input_159 = relu(x = input_157)[name = tensor<string, []>("input_159")];
            tensor<string, []> input_161_pad_type_0 = const()[name = tensor<string, []>("input_161_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_161_pad_0 = const()[name = tensor<string, []>("input_161_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_161_strides_0 = const()[name = tensor<string, []>("input_161_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_161_dilations_0 = const()[name = tensor<string, []>("input_161_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_161_groups_0 = const()[name = tensor<string, []>("input_161_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp32, [128, 128, 3, 3]> const_62 = const()[name = tensor<string, []>("const_62"), val = tensor<fp32, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14007296)))];
            tensor<fp32, [128]> const_63 = const()[name = tensor<string, []>("const_63"), val = tensor<fp32, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14597184)))];
            tensor<fp32, [1, 128, 20, 125]> input_163 = conv(bias = const_63, 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_62, x = input_159)[name = tensor<string, []>("input_163")];
            tensor<fp32, [1, 128, 20, 125]> input_165 = relu(x = input_163)[name = tensor<string, []>("input_165")];
            tensor<string, []> input_167_pad_type_0 = const()[name = tensor<string, []>("input_167_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_167_pad_0 = const()[name = tensor<string, []>("input_167_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_167_strides_0 = const()[name = tensor<string, []>("input_167_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_167_dilations_0 = const()[name = tensor<string, []>("input_167_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_167_groups_0 = const()[name = tensor<string, []>("input_167_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp32, [128, 128, 3, 3]> const_64 = const()[name = tensor<string, []>("const_64"), val = tensor<fp32, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(14597760)))];
            tensor<fp32, [128]> const_65 = const()[name = tensor<string, []>("const_65"), val = tensor<fp32, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15187648)))];
            tensor<fp32, [1, 128, 20, 125]> out_25 = conv(bias = const_65, dilations = input_167_dilations_0, groups = input_167_groups_0, pad = input_167_pad_0, pad_type = input_167_pad_type_0, strides = input_167_strides_0, weight = const_64, x = input_165)[name = tensor<string, []>("out_25")];
            tensor<fp32, [1, 128, 20, 125]> input_169 = add(x = out_25, y = input_159)[name = tensor<string, []>("input_169")];
            tensor<fp32, [1, 128, 20, 125]> input_171 = relu(x = input_169)[name = tensor<string, []>("input_171")];
            tensor<string, []> input_173_pad_type_0 = const()[name = tensor<string, []>("input_173_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_173_pad_0 = const()[name = tensor<string, []>("input_173_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_173_strides_0 = const()[name = tensor<string, []>("input_173_strides_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [2]> input_173_dilations_0 = const()[name = tensor<string, []>("input_173_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_173_groups_0 = const()[name = tensor<string, []>("input_173_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp32, [256, 128, 3, 3]> const_66 = const()[name = tensor<string, []>("const_66"), val = tensor<fp32, [256, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(15188224)))];
            tensor<fp32, [256]> const_67 = const()[name = tensor<string, []>("const_67"), val = tensor<fp32, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(16367936)))];
            tensor<fp32, [1, 256, 10, 63]> input_175 = conv(bias = const_67, dilations = input_173_dilations_0, groups = input_173_groups_0, pad = input_173_pad_0, pad_type = input_173_pad_type_0, strides = input_173_strides_0, weight = const_66, x = input_171)[name = tensor<string, []>("input_175")];
            tensor<fp32, [1, 256, 10, 63]> input_177 = relu(x = input_175)[name = tensor<string, []>("input_177")];
            tensor<string, []> input_179_pad_type_0 = const()[name = tensor<string, []>("input_179_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_179_pad_0 = const()[name = tensor<string, []>("input_179_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_179_strides_0 = const()[name = tensor<string, []>("input_179_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_179_dilations_0 = const()[name = tensor<string, []>("input_179_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_179_groups_0 = const()[name = tensor<string, []>("input_179_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp32, [256, 256, 3, 3]> const_68 = const()[name = tensor<string, []>("const_68"), val = tensor<fp32, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(16369024)))];
            tensor<fp32, [256]> const_69 = const()[name = tensor<string, []>("const_69"), val = tensor<fp32, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(18728384)))];
            tensor<fp32, [1, 256, 10, 63]> out_27 = conv(bias = const_69, dilations = input_179_dilations_0, groups = input_179_groups_0, pad = input_179_pad_0, pad_type = input_179_pad_type_0, strides = input_179_strides_0, weight = const_68, x = input_177)[name = tensor<string, []>("out_27")];
            tensor<string, []> input_181_pad_type_0 = const()[name = tensor<string, []>("input_181_pad_type_0"), val = tensor<string, []>("valid")];
            tensor<int32, [2]> input_181_strides_0 = const()[name = tensor<string, []>("input_181_strides_0"), val = tensor<int32, [2]>([2, 2])];
            tensor<int32, [4]> input_181_pad_0 = const()[name = tensor<string, []>("input_181_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
            tensor<int32, [2]> input_181_dilations_0 = const()[name = tensor<string, []>("input_181_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_181_groups_0 = const()[name = tensor<string, []>("input_181_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp32, [256, 128, 1, 1]> const_70 = const()[name = tensor<string, []>("const_70"), val = tensor<fp32, [256, 128, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(18729472)))];
            tensor<fp32, [256]> const_71 = const()[name = tensor<string, []>("const_71"), val = tensor<fp32, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(18860608)))];
            tensor<fp32, [1, 256, 10, 63]> var_584 = conv(bias = const_71, dilations = input_181_dilations_0, groups = input_181_groups_0, pad = input_181_pad_0, pad_type = input_181_pad_type_0, strides = input_181_strides_0, weight = const_70, x = input_171)[name = tensor<string, []>("op_584")];
            tensor<fp32, [1, 256, 10, 63]> input_183 = add(x = out_27, y = var_584)[name = tensor<string, []>("input_183")];
            tensor<fp32, [1, 256, 10, 63]> input_185 = relu(x = input_183)[name = tensor<string, []>("input_185")];
            tensor<string, []> input_187_pad_type_0 = const()[name = tensor<string, []>("input_187_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_187_pad_0 = const()[name = tensor<string, []>("input_187_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_187_strides_0 = const()[name = tensor<string, []>("input_187_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_187_dilations_0 = const()[name = tensor<string, []>("input_187_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_187_groups_0 = const()[name = tensor<string, []>("input_187_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp32, [256, 256, 3, 3]> const_72 = const()[name = tensor<string, []>("const_72"), val = tensor<fp32, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(18861696)))];
            tensor<fp32, [256]> const_73 = const()[name = tensor<string, []>("const_73"), val = tensor<fp32, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(21221056)))];
            tensor<fp32, [1, 256, 10, 63]> input_189 = conv(bias = const_73, dilations = input_187_dilations_0, groups = input_187_groups_0, pad = input_187_pad_0, pad_type = input_187_pad_type_0, strides = input_187_strides_0, weight = const_72, x = input_185)[name = tensor<string, []>("input_189")];
            tensor<fp32, [1, 256, 10, 63]> input_191 = relu(x = input_189)[name = tensor<string, []>("input_191")];
            tensor<string, []> input_193_pad_type_0 = const()[name = tensor<string, []>("input_193_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_193_pad_0 = const()[name = tensor<string, []>("input_193_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_193_strides_0 = const()[name = tensor<string, []>("input_193_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_193_dilations_0 = const()[name = tensor<string, []>("input_193_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_193_groups_0 = const()[name = tensor<string, []>("input_193_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp32, [256, 256, 3, 3]> const_74 = const()[name = tensor<string, []>("const_74"), val = tensor<fp32, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(21222144)))];
            tensor<fp32, [256]> const_75 = const()[name = tensor<string, []>("const_75"), val = tensor<fp32, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(23581504)))];
            tensor<fp32, [1, 256, 10, 63]> out_29 = conv(bias = const_75, dilations = input_193_dilations_0, groups = input_193_groups_0, pad = input_193_pad_0, pad_type = input_193_pad_type_0, strides = input_193_strides_0, weight = const_74, x = input_191)[name = tensor<string, []>("out_29")];
            tensor<fp32, [1, 256, 10, 63]> input_195 = add(x = out_29, y = input_185)[name = tensor<string, []>("input_195")];
            tensor<fp32, [1, 256, 10, 63]> input_197 = relu(x = input_195)[name = tensor<string, []>("input_197")];
            tensor<string, []> input_199_pad_type_0 = const()[name = tensor<string, []>("input_199_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_199_pad_0 = const()[name = tensor<string, []>("input_199_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_199_strides_0 = const()[name = tensor<string, []>("input_199_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_199_dilations_0 = const()[name = tensor<string, []>("input_199_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_199_groups_0 = const()[name = tensor<string, []>("input_199_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp32, [256, 256, 3, 3]> const_76 = const()[name = tensor<string, []>("const_76"), val = tensor<fp32, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(23582592)))];
            tensor<fp32, [256]> const_77 = const()[name = tensor<string, []>("const_77"), val = tensor<fp32, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(25941952)))];
            tensor<fp32, [1, 256, 10, 63]> input_201 = conv(bias = const_77, dilations = input_199_dilations_0, groups = input_199_groups_0, pad = input_199_pad_0, pad_type = input_199_pad_type_0, strides = input_199_strides_0, weight = const_76, x = input_197)[name = tensor<string, []>("input_201")];
            tensor<fp32, [1, 256, 10, 63]> input_203 = relu(x = input_201)[name = tensor<string, []>("input_203")];
            tensor<string, []> input_205_pad_type_0 = const()[name = tensor<string, []>("input_205_pad_type_0"), val = tensor<string, []>("custom")];
            tensor<int32, [4]> input_205_pad_0 = const()[name = tensor<string, []>("input_205_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
            tensor<int32, [2]> input_205_strides_0 = const()[name = tensor<string, []>("input_205_strides_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, [2]> input_205_dilations_0 = const()[name = tensor<string, []>("input_205_dilations_0"), val = tensor<int32, [2]>([1, 1])];
            tensor<int32, []> input_205_groups_0 = const()[name = tensor<string, []>("input_205_groups_0"), val = tensor<int32, []>(1)];
            tensor<fp32, [256, 256, 3, 3]> const_78 = const()[name = tensor<string, []>("const_78"), val = tensor<fp32, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(25943040)))];
            tensor<fp32, [256]> const_79 = const()[name = tensor<string, []>("const_79"), val = tensor<fp32, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(28302400)))];
            tensor<fp32, [1, 256, 10, 63]> out = conv(bias = const_79, dilations = input_205_dilations_0, groups = input_205_groups_0, pad = input_205_pad_0, pad_type = input_205_pad_type_0, strides = input_205_strides_0, weight = const_78, x = input_203)[name = tensor<string, []>("out")];
            tensor<fp32, [1, 256, 10, 63]> input_207 = add(x = out, y = input_197)[name = tensor<string, []>("input_207")];
            tensor<fp32, [1, 256, 10, 63]> features = relu(x = input_207)[name = tensor<string, []>("features")];
            tensor<int32, [3]> var_653 = const()[name = tensor<string, []>("op_653"), val = tensor<int32, [3]>([1, 2560, 63])];
            tensor<fp32, [1, 2560, 63]> sequences = reshape(shape = var_653, x = features)[name = tensor<string, []>("sequences")];
            tensor<int32, [1]> weights_3_axes_0 = const()[name = tensor<string, []>("weights_3_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<fp32, [1, 1, 63]> weights_3 = expand_dims(axes = weights_3_axes_0, x = weights)[name = tensor<string, []>("weights_3")];
            tensor<int32, [1]> weights_axes_0 = const()[name = tensor<string, []>("weights_axes_0"), val = tensor<int32, [1]>([2])];
            tensor<fp32, [1, 1, 1, 63]> weights_1 = expand_dims(axes = weights_axes_0, x = weights_3)[name = tensor<string, []>("weights")];
            tensor<int32, [1]> var_658_axes_0 = const()[name = tensor<string, []>("op_658_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_658_keep_dims_0 = const()[name = tensor<string, []>("op_658_keep_dims_0"), val = tensor<bool, []>(false)];
            tensor<fp32, [1, 1, 1]> var_658 = reduce_sum(axes = var_658_axes_0, keep_dims = var_658_keep_dims_0, x = weights_1)[name = tensor<string, []>("op_658")];
            tensor<fp32, []> var_659 = const()[name = tensor<string, []>("op_659"), val = tensor<fp32, []>(0x1.5798eep-27)];
            tensor<fp32, [1, 1, 1]> v1 = add(x = var_658, y = var_659)[name = tensor<string, []>("v1")];
            tensor<int32, [1]> var_661_axes_0 = const()[name = tensor<string, []>("op_661_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<fp32, [1, 1, 2560, 63]> var_661 = expand_dims(axes = var_661_axes_0, x = sequences)[name = tensor<string, []>("op_661")];
            tensor<fp32, [1, 1, 2560, 63]> weighted = mul(x = var_661, y = weights_1)[name = tensor<string, []>("weighted")];
            tensor<int32, [1]> var_664_axes_0 = const()[name = tensor<string, []>("op_664_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_664_keep_dims_0 = const()[name = tensor<string, []>("op_664_keep_dims_0"), val = tensor<bool, []>(false)];
            tensor<fp32, [1, 1, 2560]> var_664 = reduce_sum(axes = var_664_axes_0, keep_dims = var_664_keep_dims_0, x = weighted)[name = tensor<string, []>("op_664")];
            tensor<fp32, [1, 1, 2560]> mean = real_div(x = var_664, y = v1)[name = tensor<string, []>("mean")];
            tensor<int32, [1]> var_667_axes_0 = const()[name = tensor<string, []>("op_667_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<fp32, [1, 1, 2560, 1]> var_667 = expand_dims(axes = var_667_axes_0, x = mean)[name = tensor<string, []>("op_667")];
            tensor<fp32, [1, 1, 2560, 63]> diff = sub(x = var_661, y = var_667)[name = tensor<string, []>("diff")];
            tensor<fp32, [1, 1, 1, 63]> var_669 = mul(x = weights_1, y = weights_1)[name = tensor<string, []>("op_669")];
            tensor<int32, [1]> v2_axes_0 = const()[name = tensor<string, []>("v2_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> v2_keep_dims_0 = const()[name = tensor<string, []>("v2_keep_dims_0"), val = tensor<bool, []>(false)];
            tensor<fp32, [1, 1, 1]> v2 = reduce_sum(axes = v2_axes_0, keep_dims = v2_keep_dims_0, x = var_669)[name = tensor<string, []>("v2")];
            tensor<fp32, [1, 1, 1]> var_672 = real_div(x = v2, y = v1)[name = tensor<string, []>("op_672")];
            tensor<fp32, [1, 1, 1]> var_673 = sub(x = v1, y = var_672)[name = tensor<string, []>("op_673")];
            tensor<fp32, []> var_674 = const()[name = tensor<string, []>("op_674"), val = tensor<fp32, []>(0x1.5798eep-27)];
            tensor<fp32, [1, 1, 1]> denom = add(x = var_673, y = var_674)[name = tensor<string, []>("denom")];
            tensor<fp32, [1, 1, 2560, 63]> var_676 = mul(x = diff, y = diff)[name = tensor<string, []>("op_676")];
            tensor<fp32, [1, 1, 2560, 63]> var_677 = mul(x = var_676, y = weights_1)[name = tensor<string, []>("op_677")];
            tensor<int32, [1]> var_679_axes_0 = const()[name = tensor<string, []>("op_679_axes_0"), val = tensor<int32, [1]>([-1])];
            tensor<bool, []> var_679_keep_dims_0 = const()[name = tensor<string, []>("op_679_keep_dims_0"), val = tensor<bool, []>(false)];
            tensor<fp32, [1, 1, 2560]> var_679 = reduce_sum(axes = var_679_axes_0, keep_dims = var_679_keep_dims_0, x = var_677)[name = tensor<string, []>("op_679")];
            tensor<fp32, [1, 1, 2560]> var = real_div(x = var_679, y = denom)[name = tensor<string, []>("var")];
            tensor<fp32, []> const_7 = const()[name = tensor<string, []>("const_7"), val = tensor<fp32, []>(0x1.fffffep+127)];
            tensor<fp32, [1, 1, 2560]> clip_1 = clip(alpha = var_92, beta = const_7, x = var)[name = tensor<string, []>("clip_1")];
            tensor<fp32, [1, 1, 2560]> std = sqrt(x = clip_1)[name = tensor<string, []>("std")];
            tensor<bool, []> output_interleave_0 = const()[name = tensor<string, []>("output_interleave_0"), val = tensor<bool, []>(false)];
            tensor<fp32, [1, 1, 5120]> output = concat(axis = var_91, interleave = output_interleave_0, values = (mean, std))[name = tensor<string, []>("output")];
            tensor<int32, [1]> input_axes_0 = const()[name = tensor<string, []>("input_axes_0"), val = tensor<int32, [1]>([1])];
            tensor<fp32, [1, 5120]> input = squeeze(axes = input_axes_0, x = output)[name = tensor<string, []>("input")];
            tensor<fp32, [1, 256]> embedding = linear(bias = resnet_seg_1_bias, weight = resnet_seg_1_weight, x = input)[name = tensor<string, []>("linear_0")];
        } -> (embedding);
}