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[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, 80, 998]> fbank_features, tensor<fp32, [?, 589]> weights) [FlexibleShapeInformation = tuple<tuple<tensor<string, []>, dict<tensor<string, []>, tensor<int32, [?]>>>, tuple<tensor<string, []>, dict<tensor<string, []>, list<tensor<int32, [2]>, ?>>>>((("DefaultShapes", {{"fbank_features", [1, 1, 80, 998]}, {"weights", [1, 589]}}), ("RangeDims", {{"fbank_features", [[1, 32], [1, 1], [80, 80], [998, 998]]}, {"weights", [[1, 32], [589, 589]]}})))] {
tensor<int32, [1]> weights_1d_axes_0 = const()[name = tensor<string, []>("weights_1d_axes_0"), val = tensor<int32, [1]>([1])];
tensor<string, []> weights_to_fp16_dtype_0 = const()[name = tensor<string, []>("weights_to_fp16_dtype_0"), val = tensor<string, []>("fp16")];
tensor<fp16, [?, 589]> weights_to_fp16 = cast(dtype = weights_to_fp16_dtype_0, x = weights)[name = tensor<string, []>("cast_14")];
tensor<fp16, [?, 1, 589]> weights_1d_cast_fp16 = expand_dims(axes = weights_1d_axes_0, x = weights_to_fp16)[name = tensor<string, []>("weights_1d_cast_fp16")];
tensor<string, []> interpolated_pad_type_0 = const()[name = tensor<string, []>("interpolated_pad_type_0"), val = tensor<string, []>("valid")];
tensor<int32, [1]> interpolated_strides_0 = const()[name = tensor<string, []>("interpolated_strides_0"), val = tensor<int32, [1]>([1])];
tensor<int32, [2]> interpolated_pad_0 = const()[name = tensor<string, []>("interpolated_pad_0"), val = tensor<int32, [2]>([0, 0])];
tensor<int32, [1]> interpolated_dilations_0 = const()[name = tensor<string, []>("interpolated_dilations_0"), val = tensor<int32, [1]>([1])];
tensor<int32, []> interpolated_groups_0 = const()[name = tensor<string, []>("interpolated_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [125, 1, 589]> const_0_to_fp16 = const()[name = tensor<string, []>("const_0_to_fp16"), val = tensor<fp16, [125, 1, 589]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(64)))];
tensor<fp16, [?, 125, 1]> interpolated_cast_fp16 = conv(dilations = interpolated_dilations_0, groups = interpolated_groups_0, pad = interpolated_pad_0, pad_type = interpolated_pad_type_0, strides = interpolated_strides_0, weight = const_0_to_fp16, x = weights_1d_cast_fp16)[name = tensor<string, []>("interpolated_cast_fp16")];
tensor<int32, [1]> weights_3_axes_0 = const()[name = tensor<string, []>("weights_3_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [?, 125]> weights_3_cast_fp16 = squeeze(axes = weights_3_axes_0, x = interpolated_cast_fp16)[name = tensor<string, []>("weights_3_cast_fp16")];
tensor<int32, []> var_33 = const()[name = tensor<string, []>("op_33"), val = tensor<int32, []>(-1)];
tensor<string, []> input_1_pad_type_0 = const()[name = tensor<string, []>("input_1_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [4]> input_1_pad_0 = const()[name = tensor<string, []>("input_1_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
tensor<int32, [2]> input_1_strides_0 = const()[name = tensor<string, []>("input_1_strides_0"), val = tensor<int32, [2]>([1, 1])];
tensor<int32, [2]> input_1_dilations_0 = const()[name = tensor<string, []>("input_1_dilations_0"), val = tensor<int32, [2]>([1, 1])];
tensor<int32, []> input_1_groups_0 = const()[name = tensor<string, []>("input_1_groups_0"), val = tensor<int32, []>(1)];
tensor<string, []> fbank_features_to_fp16_dtype_0 = const()[name = tensor<string, []>("fbank_features_to_fp16_dtype_0"), val = tensor<string, []>("fp16")];
tensor<fp16, [32, 1, 3, 3]> const_3_to_fp16 = const()[name = tensor<string, []>("const_3_to_fp16"), val = tensor<fp16, [32, 1, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(147392)))];
tensor<fp16, [32]> const_4_to_fp16 = const()[name = tensor<string, []>("const_4_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(148032)))];
tensor<fp16, [?, 1, 80, 998]> fbank_features_to_fp16 = cast(dtype = fbank_features_to_fp16_dtype_0, x = fbank_features)[name = tensor<string, []>("cast_13")];
tensor<fp16, [?, 32, 80, 998]> input_3_cast_fp16 = conv(bias = const_4_to_fp16, dilations = input_1_dilations_0, groups = input_1_groups_0, pad = input_1_pad_0, pad_type = input_1_pad_type_0, strides = input_1_strides_0, weight = const_3_to_fp16, x = fbank_features_to_fp16)[name = tensor<string, []>("input_3_cast_fp16")];
tensor<fp16, [?, 32, 80, 998]> input_5_cast_fp16 = relu(x = input_3_cast_fp16)[name = tensor<string, []>("input_5_cast_fp16")];
tensor<string, []> input_7_pad_type_0 = const()[name = tensor<string, []>("input_7_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [4]> input_7_pad_0 = const()[name = tensor<string, []>("input_7_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
tensor<int32, [2]> input_7_strides_0 = const()[name = tensor<string, []>("input_7_strides_0"), val = tensor<int32, [2]>([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<fp16, [32, 32, 3, 3]> const_5_to_fp16 = const()[name = tensor<string, []>("const_5_to_fp16"), val = tensor<fp16, [32, 32, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(148160)))];
tensor<fp16, [32]> const_6_to_fp16 = const()[name = tensor<string, []>("const_6_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(166656)))];
tensor<fp16, [?, 32, 80, 998]> input_9_cast_fp16 = conv(bias = const_6_to_fp16, dilations = input_7_dilations_0, groups = input_7_groups_0, pad = input_7_pad_0, pad_type = input_7_pad_type_0, strides = input_7_strides_0, weight = const_5_to_fp16, x = input_5_cast_fp16)[name = tensor<string, []>("input_9_cast_fp16")];
tensor<fp16, [?, 32, 80, 998]> input_11_cast_fp16 = relu(x = input_9_cast_fp16)[name = tensor<string, []>("input_11_cast_fp16")];
tensor<string, []> input_13_pad_type_0 = const()[name = tensor<string, []>("input_13_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [4]> input_13_pad_0 = const()[name = tensor<string, []>("input_13_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
tensor<int32, [2]> input_13_strides_0 = const()[name = tensor<string, []>("input_13_strides_0"), val = tensor<int32, [2]>([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<fp16, [32, 32, 3, 3]> const_7_to_fp16 = const()[name = tensor<string, []>("const_7_to_fp16"), val = tensor<fp16, [32, 32, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(166784)))];
tensor<fp16, [32]> const_8_to_fp16 = const()[name = tensor<string, []>("const_8_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(185280)))];
tensor<fp16, [?, 32, 80, 998]> out_1_cast_fp16 = conv(bias = const_8_to_fp16, dilations = input_13_dilations_0, groups = input_13_groups_0, pad = input_13_pad_0, pad_type = input_13_pad_type_0, strides = input_13_strides_0, weight = const_7_to_fp16, x = input_11_cast_fp16)[name = tensor<string, []>("out_1_cast_fp16")];
tensor<fp16, [?, 32, 80, 998]> input_15_cast_fp16 = add(x = out_1_cast_fp16, y = input_5_cast_fp16)[name = tensor<string, []>("input_15_cast_fp16")];
tensor<fp16, [?, 32, 80, 998]> input_17_cast_fp16 = relu(x = input_15_cast_fp16)[name = tensor<string, []>("input_17_cast_fp16")];
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<fp16, [32, 32, 3, 3]> const_9_to_fp16 = const()[name = tensor<string, []>("const_9_to_fp16"), val = tensor<fp16, [32, 32, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(185408)))];
tensor<fp16, [32]> const_10_to_fp16 = const()[name = tensor<string, []>("const_10_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(203904)))];
tensor<fp16, [?, 32, 80, 998]> input_21_cast_fp16 = conv(bias = const_10_to_fp16, 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_9_to_fp16, x = input_17_cast_fp16)[name = tensor<string, []>("input_21_cast_fp16")];
tensor<fp16, [?, 32, 80, 998]> input_23_cast_fp16 = relu(x = input_21_cast_fp16)[name = tensor<string, []>("input_23_cast_fp16")];
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<fp16, [32, 32, 3, 3]> const_11_to_fp16 = const()[name = tensor<string, []>("const_11_to_fp16"), val = tensor<fp16, [32, 32, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(204032)))];
tensor<fp16, [32]> const_12_to_fp16 = const()[name = tensor<string, []>("const_12_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(222528)))];
tensor<fp16, [?, 32, 80, 998]> out_3_cast_fp16 = conv(bias = const_12_to_fp16, 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_11_to_fp16, x = input_23_cast_fp16)[name = tensor<string, []>("out_3_cast_fp16")];
tensor<fp16, [?, 32, 80, 998]> input_27_cast_fp16 = add(x = out_3_cast_fp16, y = input_17_cast_fp16)[name = tensor<string, []>("input_27_cast_fp16")];
tensor<fp16, [?, 32, 80, 998]> input_29_cast_fp16 = relu(x = input_27_cast_fp16)[name = tensor<string, []>("input_29_cast_fp16")];
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<fp16, [32, 32, 3, 3]> const_13_to_fp16 = const()[name = tensor<string, []>("const_13_to_fp16"), val = tensor<fp16, [32, 32, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(222656)))];
tensor<fp16, [32]> const_14_to_fp16 = const()[name = tensor<string, []>("const_14_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(241152)))];
tensor<fp16, [?, 32, 80, 998]> input_33_cast_fp16 = conv(bias = const_14_to_fp16, 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_13_to_fp16, x = input_29_cast_fp16)[name = tensor<string, []>("input_33_cast_fp16")];
tensor<fp16, [?, 32, 80, 998]> input_35_cast_fp16 = relu(x = input_33_cast_fp16)[name = tensor<string, []>("input_35_cast_fp16")];
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<fp16, [32, 32, 3, 3]> const_15_to_fp16 = const()[name = tensor<string, []>("const_15_to_fp16"), val = tensor<fp16, [32, 32, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(241280)))];
tensor<fp16, [32]> const_16_to_fp16 = const()[name = tensor<string, []>("const_16_to_fp16"), val = tensor<fp16, [32]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(259776)))];
tensor<fp16, [?, 32, 80, 998]> out_5_cast_fp16 = conv(bias = const_16_to_fp16, 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_15_to_fp16, x = input_35_cast_fp16)[name = tensor<string, []>("out_5_cast_fp16")];
tensor<fp16, [?, 32, 80, 998]> input_39_cast_fp16 = add(x = out_5_cast_fp16, y = input_29_cast_fp16)[name = tensor<string, []>("input_39_cast_fp16")];
tensor<fp16, [?, 32, 80, 998]> input_41_cast_fp16 = relu(x = input_39_cast_fp16)[name = tensor<string, []>("input_41_cast_fp16")];
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]>([2, 2])];
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<fp16, [64, 32, 3, 3]> const_17_to_fp16 = const()[name = tensor<string, []>("const_17_to_fp16"), val = tensor<fp16, [64, 32, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(259904)))];
tensor<fp16, [64]> const_18_to_fp16 = const()[name = tensor<string, []>("const_18_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(296832)))];
tensor<fp16, [?, 64, 40, 499]> input_45_cast_fp16 = conv(bias = const_18_to_fp16, dilations = input_43_dilations_0, groups = input_43_groups_0, pad = input_43_pad_0, pad_type = input_43_pad_type_0, strides = input_43_strides_0, weight = const_17_to_fp16, x = input_41_cast_fp16)[name = tensor<string, []>("input_45_cast_fp16")];
tensor<fp16, [?, 64, 40, 499]> input_47_cast_fp16 = relu(x = input_45_cast_fp16)[name = tensor<string, []>("input_47_cast_fp16")];
tensor<string, []> input_49_pad_type_0 = const()[name = tensor<string, []>("input_49_pad_type_0"), val = tensor<string, []>("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]>([1, 1])];
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<fp16, [64, 64, 3, 3]> const_19_to_fp16 = const()[name = tensor<string, []>("const_19_to_fp16"), val = tensor<fp16, [64, 64, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(297024)))];
tensor<fp16, [64]> const_20_to_fp16 = const()[name = tensor<string, []>("const_20_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(370816)))];
tensor<fp16, [?, 64, 40, 499]> out_7_cast_fp16 = conv(bias = const_20_to_fp16, dilations = input_49_dilations_0, groups = input_49_groups_0, pad = input_49_pad_0, pad_type = input_49_pad_type_0, strides = input_49_strides_0, weight = const_19_to_fp16, x = input_47_cast_fp16)[name = tensor<string, []>("out_7_cast_fp16")];
tensor<string, []> input_51_pad_type_0 = const()[name = tensor<string, []>("input_51_pad_type_0"), val = tensor<string, []>("valid")];
tensor<int32, [2]> input_51_strides_0 = const()[name = tensor<string, []>("input_51_strides_0"), val = tensor<int32, [2]>([2, 2])];
tensor<int32, [4]> input_51_pad_0 = const()[name = tensor<string, []>("input_51_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
tensor<int32, [2]> input_51_dilations_0 = const()[name = tensor<string, []>("input_51_dilations_0"), val = tensor<int32, [2]>([1, 1])];
tensor<int32, []> input_51_groups_0 = const()[name = tensor<string, []>("input_51_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [64, 32, 1, 1]> const_21_to_fp16 = const()[name = tensor<string, []>("const_21_to_fp16"), val = tensor<fp16, [64, 32, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(371008)))];
tensor<fp16, [64]> const_22_to_fp16 = const()[name = tensor<string, []>("const_22_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(375168)))];
tensor<fp16, [?, 64, 40, 499]> var_196_cast_fp16 = conv(bias = const_22_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 = const_21_to_fp16, x = input_41_cast_fp16)[name = tensor<string, []>("op_196_cast_fp16")];
tensor<fp16, [?, 64, 40, 499]> input_53_cast_fp16 = add(x = out_7_cast_fp16, y = var_196_cast_fp16)[name = tensor<string, []>("input_53_cast_fp16")];
tensor<fp16, [?, 64, 40, 499]> input_55_cast_fp16 = relu(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, []>("custom")];
tensor<int32, [4]> input_57_pad_0 = const()[name = tensor<string, []>("input_57_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
tensor<int32, [2]> input_57_strides_0 = const()[name = tensor<string, []>("input_57_strides_0"), val = tensor<int32, [2]>([1, 1])];
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<fp16, [64, 64, 3, 3]> const_23_to_fp16 = const()[name = tensor<string, []>("const_23_to_fp16"), val = tensor<fp16, [64, 64, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(375360)))];
tensor<fp16, [64]> const_24_to_fp16 = const()[name = tensor<string, []>("const_24_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(449152)))];
tensor<fp16, [?, 64, 40, 499]> input_59_cast_fp16 = conv(bias = const_24_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_23_to_fp16, x = input_55_cast_fp16)[name = tensor<string, []>("input_59_cast_fp16")];
tensor<fp16, [?, 64, 40, 499]> input_61_cast_fp16 = relu(x = input_59_cast_fp16)[name = tensor<string, []>("input_61_cast_fp16")];
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<fp16, [64, 64, 3, 3]> const_25_to_fp16 = const()[name = tensor<string, []>("const_25_to_fp16"), val = tensor<fp16, [64, 64, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(449344)))];
tensor<fp16, [64]> const_26_to_fp16 = const()[name = tensor<string, []>("const_26_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(523136)))];
tensor<fp16, [?, 64, 40, 499]> out_9_cast_fp16 = conv(bias = const_26_to_fp16, 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_25_to_fp16, x = input_61_cast_fp16)[name = tensor<string, []>("out_9_cast_fp16")];
tensor<fp16, [?, 64, 40, 499]> input_65_cast_fp16 = add(x = out_9_cast_fp16, y = input_55_cast_fp16)[name = tensor<string, []>("input_65_cast_fp16")];
tensor<fp16, [?, 64, 40, 499]> input_67_cast_fp16 = relu(x = input_65_cast_fp16)[name = tensor<string, []>("input_67_cast_fp16")];
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<fp16, [64, 64, 3, 3]> const_27_to_fp16 = const()[name = tensor<string, []>("const_27_to_fp16"), val = tensor<fp16, [64, 64, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(523328)))];
tensor<fp16, [64]> const_28_to_fp16 = const()[name = tensor<string, []>("const_28_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(597120)))];
tensor<fp16, [?, 64, 40, 499]> input_71_cast_fp16 = conv(bias = const_28_to_fp16, 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_27_to_fp16, x = input_67_cast_fp16)[name = tensor<string, []>("input_71_cast_fp16")];
tensor<fp16, [?, 64, 40, 499]> input_73_cast_fp16 = relu(x = input_71_cast_fp16)[name = tensor<string, []>("input_73_cast_fp16")];
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<fp16, [64, 64, 3, 3]> const_29_to_fp16 = const()[name = tensor<string, []>("const_29_to_fp16"), val = tensor<fp16, [64, 64, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(597312)))];
tensor<fp16, [64]> const_30_to_fp16 = const()[name = tensor<string, []>("const_30_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(671104)))];
tensor<fp16, [?, 64, 40, 499]> out_11_cast_fp16 = conv(bias = const_30_to_fp16, 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_29_to_fp16, x = input_73_cast_fp16)[name = tensor<string, []>("out_11_cast_fp16")];
tensor<fp16, [?, 64, 40, 499]> input_77_cast_fp16 = add(x = out_11_cast_fp16, y = input_67_cast_fp16)[name = tensor<string, []>("input_77_cast_fp16")];
tensor<fp16, [?, 64, 40, 499]> input_79_cast_fp16 = relu(x = input_77_cast_fp16)[name = tensor<string, []>("input_79_cast_fp16")];
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<fp16, [64, 64, 3, 3]> const_31_to_fp16 = const()[name = tensor<string, []>("const_31_to_fp16"), val = tensor<fp16, [64, 64, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(671296)))];
tensor<fp16, [64]> const_32_to_fp16 = const()[name = tensor<string, []>("const_32_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(745088)))];
tensor<fp16, [?, 64, 40, 499]> input_83_cast_fp16 = conv(bias = const_32_to_fp16, 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_31_to_fp16, x = input_79_cast_fp16)[name = tensor<string, []>("input_83_cast_fp16")];
tensor<fp16, [?, 64, 40, 499]> input_85_cast_fp16 = relu(x = input_83_cast_fp16)[name = tensor<string, []>("input_85_cast_fp16")];
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<fp16, [64, 64, 3, 3]> const_33_to_fp16 = const()[name = tensor<string, []>("const_33_to_fp16"), val = tensor<fp16, [64, 64, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(745280)))];
tensor<fp16, [64]> const_34_to_fp16 = const()[name = tensor<string, []>("const_34_to_fp16"), val = tensor<fp16, [64]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(819072)))];
tensor<fp16, [?, 64, 40, 499]> out_13_cast_fp16 = conv(bias = const_34_to_fp16, 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_33_to_fp16, x = input_85_cast_fp16)[name = tensor<string, []>("out_13_cast_fp16")];
tensor<fp16, [?, 64, 40, 499]> input_89_cast_fp16 = add(x = out_13_cast_fp16, y = input_79_cast_fp16)[name = tensor<string, []>("input_89_cast_fp16")];
tensor<fp16, [?, 64, 40, 499]> input_91_cast_fp16 = relu(x = input_89_cast_fp16)[name = tensor<string, []>("input_91_cast_fp16")];
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]>([2, 2])];
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<fp16, [128, 64, 3, 3]> const_35_to_fp16 = const()[name = tensor<string, []>("const_35_to_fp16"), val = tensor<fp16, [128, 64, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(819264)))];
tensor<fp16, [128]> const_36_to_fp16 = const()[name = tensor<string, []>("const_36_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(966784)))];
tensor<fp16, [?, 128, 20, 250]> input_95_cast_fp16 = conv(bias = const_36_to_fp16, 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_35_to_fp16, x = input_91_cast_fp16)[name = tensor<string, []>("input_95_cast_fp16")];
tensor<fp16, [?, 128, 20, 250]> input_97_cast_fp16 = relu(x = input_95_cast_fp16)[name = tensor<string, []>("input_97_cast_fp16")];
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]>([1, 1])];
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<fp16, [128, 128, 3, 3]> const_37_to_fp16 = const()[name = tensor<string, []>("const_37_to_fp16"), val = tensor<fp16, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(967104)))];
tensor<fp16, [128]> const_38_to_fp16 = const()[name = tensor<string, []>("const_38_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1262080)))];
tensor<fp16, [?, 128, 20, 250]> out_15_cast_fp16 = conv(bias = const_38_to_fp16, 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_37_to_fp16, x = input_97_cast_fp16)[name = tensor<string, []>("out_15_cast_fp16")];
tensor<string, []> input_101_pad_type_0 = const()[name = tensor<string, []>("input_101_pad_type_0"), val = tensor<string, []>("valid")];
tensor<int32, [2]> input_101_strides_0 = const()[name = tensor<string, []>("input_101_strides_0"), val = tensor<int32, [2]>([2, 2])];
tensor<int32, [4]> input_101_pad_0 = const()[name = tensor<string, []>("input_101_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
tensor<int32, [2]> input_101_dilations_0 = const()[name = tensor<string, []>("input_101_dilations_0"), val = tensor<int32, [2]>([1, 1])];
tensor<int32, []> input_101_groups_0 = const()[name = tensor<string, []>("input_101_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [128, 64, 1, 1]> const_39_to_fp16 = const()[name = tensor<string, []>("const_39_to_fp16"), val = tensor<fp16, [128, 64, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1262400)))];
tensor<fp16, [128]> const_40_to_fp16 = const()[name = tensor<string, []>("const_40_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1278848)))];
tensor<fp16, [?, 128, 20, 250]> var_332_cast_fp16 = conv(bias = const_40_to_fp16, dilations = input_101_dilations_0, groups = input_101_groups_0, pad = input_101_pad_0, pad_type = input_101_pad_type_0, strides = input_101_strides_0, weight = const_39_to_fp16, x = input_91_cast_fp16)[name = tensor<string, []>("op_332_cast_fp16")];
tensor<fp16, [?, 128, 20, 250]> input_103_cast_fp16 = add(x = out_15_cast_fp16, y = var_332_cast_fp16)[name = tensor<string, []>("input_103_cast_fp16")];
tensor<fp16, [?, 128, 20, 250]> input_105_cast_fp16 = relu(x = input_103_cast_fp16)[name = tensor<string, []>("input_105_cast_fp16")];
tensor<string, []> input_107_pad_type_0 = const()[name = tensor<string, []>("input_107_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [4]> input_107_pad_0 = const()[name = tensor<string, []>("input_107_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
tensor<int32, [2]> input_107_strides_0 = const()[name = tensor<string, []>("input_107_strides_0"), val = tensor<int32, [2]>([1, 1])];
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<fp16, [128, 128, 3, 3]> const_41_to_fp16 = const()[name = tensor<string, []>("const_41_to_fp16"), val = tensor<fp16, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1279168)))];
tensor<fp16, [128]> const_42_to_fp16 = const()[name = tensor<string, []>("const_42_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1574144)))];
tensor<fp16, [?, 128, 20, 250]> input_109_cast_fp16 = conv(bias = const_42_to_fp16, 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_41_to_fp16, x = input_105_cast_fp16)[name = tensor<string, []>("input_109_cast_fp16")];
tensor<fp16, [?, 128, 20, 250]> input_111_cast_fp16 = relu(x = input_109_cast_fp16)[name = tensor<string, []>("input_111_cast_fp16")];
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<fp16, [128, 128, 3, 3]> const_43_to_fp16 = const()[name = tensor<string, []>("const_43_to_fp16"), val = tensor<fp16, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1574464)))];
tensor<fp16, [128]> const_44_to_fp16 = const()[name = tensor<string, []>("const_44_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1869440)))];
tensor<fp16, [?, 128, 20, 250]> out_17_cast_fp16 = conv(bias = const_44_to_fp16, 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_43_to_fp16, x = input_111_cast_fp16)[name = tensor<string, []>("out_17_cast_fp16")];
tensor<fp16, [?, 128, 20, 250]> input_115_cast_fp16 = add(x = out_17_cast_fp16, y = input_105_cast_fp16)[name = tensor<string, []>("input_115_cast_fp16")];
tensor<fp16, [?, 128, 20, 250]> input_117_cast_fp16 = relu(x = input_115_cast_fp16)[name = tensor<string, []>("input_117_cast_fp16")];
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<fp16, [128, 128, 3, 3]> const_45_to_fp16 = const()[name = tensor<string, []>("const_45_to_fp16"), val = tensor<fp16, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(1869760)))];
tensor<fp16, [128]> const_46_to_fp16 = const()[name = tensor<string, []>("const_46_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2164736)))];
tensor<fp16, [?, 128, 20, 250]> input_121_cast_fp16 = conv(bias = const_46_to_fp16, 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_45_to_fp16, x = input_117_cast_fp16)[name = tensor<string, []>("input_121_cast_fp16")];
tensor<fp16, [?, 128, 20, 250]> input_123_cast_fp16 = relu(x = input_121_cast_fp16)[name = tensor<string, []>("input_123_cast_fp16")];
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<fp16, [128, 128, 3, 3]> const_47_to_fp16 = const()[name = tensor<string, []>("const_47_to_fp16"), val = tensor<fp16, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2165056)))];
tensor<fp16, [128]> const_48_to_fp16 = const()[name = tensor<string, []>("const_48_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2460032)))];
tensor<fp16, [?, 128, 20, 250]> out_19_cast_fp16 = conv(bias = const_48_to_fp16, 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_47_to_fp16, x = input_123_cast_fp16)[name = tensor<string, []>("out_19_cast_fp16")];
tensor<fp16, [?, 128, 20, 250]> input_127_cast_fp16 = add(x = out_19_cast_fp16, y = input_117_cast_fp16)[name = tensor<string, []>("input_127_cast_fp16")];
tensor<fp16, [?, 128, 20, 250]> input_129_cast_fp16 = relu(x = input_127_cast_fp16)[name = tensor<string, []>("input_129_cast_fp16")];
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<fp16, [128, 128, 3, 3]> const_49_to_fp16 = const()[name = tensor<string, []>("const_49_to_fp16"), val = tensor<fp16, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2460352)))];
tensor<fp16, [128]> const_50_to_fp16 = const()[name = tensor<string, []>("const_50_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2755328)))];
tensor<fp16, [?, 128, 20, 250]> input_133_cast_fp16 = conv(bias = const_50_to_fp16, 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_49_to_fp16, x = input_129_cast_fp16)[name = tensor<string, []>("input_133_cast_fp16")];
tensor<fp16, [?, 128, 20, 250]> input_135_cast_fp16 = relu(x = input_133_cast_fp16)[name = tensor<string, []>("input_135_cast_fp16")];
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<fp16, [128, 128, 3, 3]> const_51_to_fp16 = const()[name = tensor<string, []>("const_51_to_fp16"), val = tensor<fp16, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(2755648)))];
tensor<fp16, [128]> const_52_to_fp16 = const()[name = tensor<string, []>("const_52_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3050624)))];
tensor<fp16, [?, 128, 20, 250]> out_21_cast_fp16 = conv(bias = const_52_to_fp16, 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_51_to_fp16, x = input_135_cast_fp16)[name = tensor<string, []>("out_21_cast_fp16")];
tensor<fp16, [?, 128, 20, 250]> input_139_cast_fp16 = add(x = out_21_cast_fp16, y = input_129_cast_fp16)[name = tensor<string, []>("input_139_cast_fp16")];
tensor<fp16, [?, 128, 20, 250]> input_141_cast_fp16 = relu(x = input_139_cast_fp16)[name = tensor<string, []>("input_141_cast_fp16")];
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<fp16, [128, 128, 3, 3]> const_53_to_fp16 = const()[name = tensor<string, []>("const_53_to_fp16"), val = tensor<fp16, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3050944)))];
tensor<fp16, [128]> const_54_to_fp16 = const()[name = tensor<string, []>("const_54_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3345920)))];
tensor<fp16, [?, 128, 20, 250]> input_145_cast_fp16 = conv(bias = const_54_to_fp16, 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_53_to_fp16, x = input_141_cast_fp16)[name = tensor<string, []>("input_145_cast_fp16")];
tensor<fp16, [?, 128, 20, 250]> input_147_cast_fp16 = relu(x = input_145_cast_fp16)[name = tensor<string, []>("input_147_cast_fp16")];
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<fp16, [128, 128, 3, 3]> const_55_to_fp16 = const()[name = tensor<string, []>("const_55_to_fp16"), val = tensor<fp16, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3346240)))];
tensor<fp16, [128]> const_56_to_fp16 = const()[name = tensor<string, []>("const_56_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3641216)))];
tensor<fp16, [?, 128, 20, 250]> out_23_cast_fp16 = conv(bias = const_56_to_fp16, 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_55_to_fp16, x = input_147_cast_fp16)[name = tensor<string, []>("out_23_cast_fp16")];
tensor<fp16, [?, 128, 20, 250]> input_151_cast_fp16 = add(x = out_23_cast_fp16, y = input_141_cast_fp16)[name = tensor<string, []>("input_151_cast_fp16")];
tensor<fp16, [?, 128, 20, 250]> input_153_cast_fp16 = relu(x = input_151_cast_fp16)[name = tensor<string, []>("input_153_cast_fp16")];
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<fp16, [128, 128, 3, 3]> const_57_to_fp16 = const()[name = tensor<string, []>("const_57_to_fp16"), val = tensor<fp16, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3641536)))];
tensor<fp16, [128]> const_58_to_fp16 = const()[name = tensor<string, []>("const_58_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3936512)))];
tensor<fp16, [?, 128, 20, 250]> input_157_cast_fp16 = conv(bias = const_58_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 = const_57_to_fp16, x = input_153_cast_fp16)[name = tensor<string, []>("input_157_cast_fp16")];
tensor<fp16, [?, 128, 20, 250]> input_159_cast_fp16 = relu(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, []>("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<fp16, [128, 128, 3, 3]> const_59_to_fp16 = const()[name = tensor<string, []>("const_59_to_fp16"), val = tensor<fp16, [128, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(3936832)))];
tensor<fp16, [128]> const_60_to_fp16 = const()[name = tensor<string, []>("const_60_to_fp16"), val = tensor<fp16, [128]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4231808)))];
tensor<fp16, [?, 128, 20, 250]> out_25_cast_fp16 = conv(bias = const_60_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_59_to_fp16, x = input_159_cast_fp16)[name = tensor<string, []>("out_25_cast_fp16")];
tensor<fp16, [?, 128, 20, 250]> input_163_cast_fp16 = add(x = out_25_cast_fp16, y = input_153_cast_fp16)[name = tensor<string, []>("input_163_cast_fp16")];
tensor<fp16, [?, 128, 20, 250]> input_165_cast_fp16 = relu(x = input_163_cast_fp16)[name = tensor<string, []>("input_165_cast_fp16")];
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]>([2, 2])];
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<fp16, [256, 128, 3, 3]> const_61_to_fp16 = const()[name = tensor<string, []>("const_61_to_fp16"), val = tensor<fp16, [256, 128, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4232128)))];
tensor<fp16, [256]> const_62_to_fp16 = const()[name = tensor<string, []>("const_62_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4822016)))];
tensor<fp16, [?, 256, 10, 125]> input_169_cast_fp16 = conv(bias = const_62_to_fp16, dilations = input_167_dilations_0, groups = input_167_groups_0, pad = input_167_pad_0, pad_type = input_167_pad_type_0, strides = input_167_strides_0, weight = const_61_to_fp16, x = input_165_cast_fp16)[name = tensor<string, []>("input_169_cast_fp16")];
tensor<fp16, [?, 256, 10, 125]> input_171_cast_fp16 = relu(x = input_169_cast_fp16)[name = tensor<string, []>("input_171_cast_fp16")];
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]>([1, 1])];
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<fp16, [256, 256, 3, 3]> const_63_to_fp16 = const()[name = tensor<string, []>("const_63_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(4822592)))];
tensor<fp16, [256]> const_64_to_fp16 = const()[name = tensor<string, []>("const_64_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6002304)))];
tensor<fp16, [?, 256, 10, 125]> out_27_cast_fp16 = conv(bias = const_64_to_fp16, 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_63_to_fp16, x = input_171_cast_fp16)[name = tensor<string, []>("out_27_cast_fp16")];
tensor<string, []> input_175_pad_type_0 = const()[name = tensor<string, []>("input_175_pad_type_0"), val = tensor<string, []>("valid")];
tensor<int32, [2]> input_175_strides_0 = const()[name = tensor<string, []>("input_175_strides_0"), val = tensor<int32, [2]>([2, 2])];
tensor<int32, [4]> input_175_pad_0 = const()[name = tensor<string, []>("input_175_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
tensor<int32, [2]> input_175_dilations_0 = const()[name = tensor<string, []>("input_175_dilations_0"), val = tensor<int32, [2]>([1, 1])];
tensor<int32, []> input_175_groups_0 = const()[name = tensor<string, []>("input_175_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [256, 128, 1, 1]> const_65_to_fp16 = const()[name = tensor<string, []>("const_65_to_fp16"), val = tensor<fp16, [256, 128, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6002880)))];
tensor<fp16, [256]> const_66_to_fp16 = const()[name = tensor<string, []>("const_66_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6068480)))];
tensor<fp16, [?, 256, 10, 125]> var_523_cast_fp16 = conv(bias = const_66_to_fp16, dilations = input_175_dilations_0, groups = input_175_groups_0, pad = input_175_pad_0, pad_type = input_175_pad_type_0, strides = input_175_strides_0, weight = const_65_to_fp16, x = input_165_cast_fp16)[name = tensor<string, []>("op_523_cast_fp16")];
tensor<fp16, [?, 256, 10, 125]> input_177_cast_fp16 = add(x = out_27_cast_fp16, y = var_523_cast_fp16)[name = tensor<string, []>("input_177_cast_fp16")];
tensor<fp16, [?, 256, 10, 125]> input_179_cast_fp16 = relu(x = input_177_cast_fp16)[name = tensor<string, []>("input_179_cast_fp16")];
tensor<string, []> input_181_pad_type_0 = const()[name = tensor<string, []>("input_181_pad_type_0"), val = tensor<string, []>("custom")];
tensor<int32, [4]> input_181_pad_0 = const()[name = tensor<string, []>("input_181_pad_0"), val = tensor<int32, [4]>([1, 1, 1, 1])];
tensor<int32, [2]> input_181_strides_0 = const()[name = tensor<string, []>("input_181_strides_0"), val = tensor<int32, [2]>([1, 1])];
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<fp16, [256, 256, 3, 3]> const_67_to_fp16 = const()[name = tensor<string, []>("const_67_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(6069056)))];
tensor<fp16, [256]> const_68_to_fp16 = const()[name = tensor<string, []>("const_68_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7248768)))];
tensor<fp16, [?, 256, 10, 125]> input_183_cast_fp16 = conv(bias = const_68_to_fp16, 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_67_to_fp16, x = input_179_cast_fp16)[name = tensor<string, []>("input_183_cast_fp16")];
tensor<fp16, [?, 256, 10, 125]> input_185_cast_fp16 = relu(x = input_183_cast_fp16)[name = tensor<string, []>("input_185_cast_fp16")];
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<fp16, [256, 256, 3, 3]> const_69_to_fp16 = const()[name = tensor<string, []>("const_69_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(7249344)))];
tensor<fp16, [256]> const_70_to_fp16 = const()[name = tensor<string, []>("const_70_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8429056)))];
tensor<fp16, [?, 256, 10, 125]> out_29_cast_fp16 = conv(bias = const_70_to_fp16, 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_69_to_fp16, x = input_185_cast_fp16)[name = tensor<string, []>("out_29_cast_fp16")];
tensor<fp16, [?, 256, 10, 125]> input_189_cast_fp16 = add(x = out_29_cast_fp16, y = input_179_cast_fp16)[name = tensor<string, []>("input_189_cast_fp16")];
tensor<fp16, [?, 256, 10, 125]> input_191_cast_fp16 = relu(x = input_189_cast_fp16)[name = tensor<string, []>("input_191_cast_fp16")];
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<fp16, [256, 256, 3, 3]> const_71_to_fp16 = const()[name = tensor<string, []>("const_71_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(8429632)))];
tensor<fp16, [256]> const_72_to_fp16 = const()[name = tensor<string, []>("const_72_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9609344)))];
tensor<fp16, [?, 256, 10, 125]> input_195_cast_fp16 = conv(bias = const_72_to_fp16, 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_71_to_fp16, x = input_191_cast_fp16)[name = tensor<string, []>("input_195_cast_fp16")];
tensor<fp16, [?, 256, 10, 125]> input_197_cast_fp16 = relu(x = input_195_cast_fp16)[name = tensor<string, []>("input_197_cast_fp16")];
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<fp16, [256, 256, 3, 3]> const_73_to_fp16 = const()[name = tensor<string, []>("const_73_to_fp16"), val = tensor<fp16, [256, 256, 3, 3]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(9609920)))];
tensor<fp16, [256]> const_74_to_fp16 = const()[name = tensor<string, []>("const_74_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10789632)))];
tensor<fp16, [?, 256, 10, 125]> out_cast_fp16 = conv(bias = const_74_to_fp16, dilations = input_199_dilations_0, groups = input_199_groups_0, pad = input_199_pad_0, pad_type = input_199_pad_type_0, strides = input_199_strides_0, weight = const_73_to_fp16, x = input_197_cast_fp16)[name = tensor<string, []>("out_cast_fp16")];
tensor<fp16, [?, 256, 10, 125]> input_201_cast_fp16 = add(x = out_cast_fp16, y = input_191_cast_fp16)[name = tensor<string, []>("input_201_cast_fp16")];
tensor<fp16, [?, 256, 10, 125]> features_cast_fp16 = relu(x = input_201_cast_fp16)[name = tensor<string, []>("features_cast_fp16")];
tensor<int32, [3]> concat_0x = const()[name = tensor<string, []>("concat_0x"), val = tensor<int32, [3]>([-1, 2560, 125])];
tensor<fp16, [?, 2560, 125]> sequences_1_cast_fp16 = reshape(shape = concat_0x, x = features_cast_fp16)[name = tensor<string, []>("sequences_1_cast_fp16")];
tensor<int32, [1]> weights_fp32_axes_0 = const()[name = tensor<string, []>("weights_fp32_axes_0"), val = tensor<int32, [1]>([1])];
tensor<fp16, [?, 1, 125]> weights_fp32_cast_fp16 = expand_dims(axes = weights_fp32_axes_0, x = weights_3_cast_fp16)[name = tensor<string, []>("weights_fp32_cast_fp16")];
tensor<int32, [1]> weights_expanded_axes_0 = const()[name = tensor<string, []>("weights_expanded_axes_0"), val = tensor<int32, [1]>([2])];
tensor<fp16, [?, 1, 1, 125]> weights_expanded_cast_fp16 = expand_dims(axes = weights_expanded_axes_0, x = weights_fp32_cast_fp16)[name = tensor<string, []>("weights_expanded_cast_fp16")];
tensor<int32, [1]> var_599_axes_0 = const()[name = tensor<string, []>("op_599_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<bool, []> var_599_keep_dims_0 = const()[name = tensor<string, []>("op_599_keep_dims_0"), val = tensor<bool, []>(false)];
tensor<fp16, [?, 1, 1]> var_599_cast_fp16 = reduce_sum(axes = var_599_axes_0, keep_dims = var_599_keep_dims_0, x = weights_expanded_cast_fp16)[name = tensor<string, []>("op_599_cast_fp16")];
tensor<fp16, []> var_600_to_fp16 = const()[name = tensor<string, []>("op_600_to_fp16"), val = tensor<fp16, []>(0x1.a38p-14)];
tensor<fp16, [?, 1, 1]> v1_cast_fp16 = add(x = var_599_cast_fp16, y = var_600_to_fp16)[name = tensor<string, []>("v1_cast_fp16")];
tensor<int32, [1]> var_602_axes_0 = const()[name = tensor<string, []>("op_602_axes_0"), val = tensor<int32, [1]>([1])];
tensor<fp16, [?, 1, 2560, 125]> var_602_cast_fp16 = expand_dims(axes = var_602_axes_0, x = sequences_1_cast_fp16)[name = tensor<string, []>("op_602_cast_fp16")];
tensor<fp16, [?, 1, 2560, 125]> weighted_cast_fp16 = mul(x = var_602_cast_fp16, y = weights_expanded_cast_fp16)[name = tensor<string, []>("weighted_cast_fp16")];
tensor<int32, [1]> var_605_axes_0 = const()[name = tensor<string, []>("op_605_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<bool, []> var_605_keep_dims_0 = const()[name = tensor<string, []>("op_605_keep_dims_0"), val = tensor<bool, []>(false)];
tensor<fp16, [?, 1, 2560]> var_605_cast_fp16 = reduce_sum(axes = var_605_axes_0, keep_dims = var_605_keep_dims_0, x = weighted_cast_fp16)[name = tensor<string, []>("op_605_cast_fp16")];
tensor<fp16, [?, 1, 2560]> mean_cast_fp16 = real_div(x = var_605_cast_fp16, y = v1_cast_fp16)[name = tensor<string, []>("mean_cast_fp16")];
tensor<int32, [1]> var_608_axes_0 = const()[name = tensor<string, []>("op_608_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [?, 1, 2560, 1]> var_608_cast_fp16 = expand_dims(axes = var_608_axes_0, x = mean_cast_fp16)[name = tensor<string, []>("op_608_cast_fp16")];
tensor<fp16, [?, 1, 2560, 125]> diff_cast_fp16 = sub(x = var_602_cast_fp16, y = var_608_cast_fp16)[name = tensor<string, []>("diff_cast_fp16")];
tensor<fp16, [?, 1, 1, 125]> var_610_cast_fp16 = mul(x = weights_expanded_cast_fp16, y = weights_expanded_cast_fp16)[name = tensor<string, []>("op_610_cast_fp16")];
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<fp16, [?, 1, 1]> v2_cast_fp16 = reduce_sum(axes = v2_axes_0, keep_dims = v2_keep_dims_0, x = var_610_cast_fp16)[name = tensor<string, []>("v2_cast_fp16")];
tensor<fp16, [?, 1, 1]> var_613_cast_fp16 = real_div(x = v2_cast_fp16, y = v1_cast_fp16)[name = tensor<string, []>("op_613_cast_fp16")];
tensor<fp16, [?, 1, 1]> var_614_cast_fp16 = sub(x = v1_cast_fp16, y = var_613_cast_fp16)[name = tensor<string, []>("op_614_cast_fp16")];
tensor<fp16, []> var_615_to_fp16 = const()[name = tensor<string, []>("op_615_to_fp16"), val = tensor<fp16, []>(0x1.a38p-14)];
tensor<fp16, [?, 1, 1]> denom_cast_fp16 = add(x = var_614_cast_fp16, y = var_615_to_fp16)[name = tensor<string, []>("denom_cast_fp16")];
tensor<fp16, [?, 1, 2560, 125]> var_617_cast_fp16 = mul(x = diff_cast_fp16, y = diff_cast_fp16)[name = tensor<string, []>("op_617_cast_fp16")];
tensor<fp16, [?, 1, 2560, 125]> var_618_cast_fp16 = mul(x = var_617_cast_fp16, y = weights_expanded_cast_fp16)[name = tensor<string, []>("op_618_cast_fp16")];
tensor<int32, [1]> var_620_axes_0 = const()[name = tensor<string, []>("op_620_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<bool, []> var_620_keep_dims_0 = const()[name = tensor<string, []>("op_620_keep_dims_0"), val = tensor<bool, []>(false)];
tensor<fp16, [?, 1, 2560]> var_620_cast_fp16 = reduce_sum(axes = var_620_axes_0, keep_dims = var_620_keep_dims_0, x = var_618_cast_fp16)[name = tensor<string, []>("op_620_cast_fp16")];
tensor<fp16, [?, 1, 2560]> var_cast_fp16 = real_div(x = var_620_cast_fp16, y = denom_cast_fp16)[name = tensor<string, []>("var_cast_fp16")];
tensor<fp16, []> var_34_to_fp16 = const()[name = tensor<string, []>("op_34_to_fp16"), val = tensor<fp16, []>(0x1.1p-20)];
tensor<fp16, []> const_1_to_fp16 = const()[name = tensor<string, []>("const_1_to_fp16"), val = tensor<fp16, []>(inf)];
tensor<fp16, [?, 1, 2560]> clip_0_cast_fp16 = clip(alpha = var_34_to_fp16, beta = const_1_to_fp16, x = var_cast_fp16)[name = tensor<string, []>("clip_0_cast_fp16")];
tensor<fp16, [?, 1, 2560]> std_cast_fp16 = sqrt(x = clip_0_cast_fp16)[name = tensor<string, []>("std_cast_fp16")];
tensor<bool, []> output_interleave_0 = const()[name = tensor<string, []>("output_interleave_0"), val = tensor<bool, []>(false)];
tensor<fp16, [?, 1, 5120]> output_cast_fp16 = concat(axis = var_33, interleave = output_interleave_0, values = (mean_cast_fp16, std_cast_fp16))[name = tensor<string, []>("output_cast_fp16")];
tensor<int32, [1]> var_626_axes_0 = const()[name = tensor<string, []>("op_626_axes_0"), val = tensor<int32, [1]>([1])];
tensor<fp16, [?, 5120]> var_626_cast_fp16 = squeeze(axes = var_626_axes_0, x = output_cast_fp16)[name = tensor<string, []>("op_626_cast_fp16")];
tensor<int32, [1]> var_628_axes_0 = const()[name = tensor<string, []>("op_628_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [?, 5120, 1]> var_628_cast_fp16 = expand_dims(axes = var_628_axes_0, x = var_626_cast_fp16)[name = tensor<string, []>("op_628_cast_fp16")];
tensor<int32, [1]> input_203_axes_0 = const()[name = tensor<string, []>("input_203_axes_0"), val = tensor<int32, [1]>([-1])];
tensor<fp16, [?, 5120, 1, 1]> input_203_cast_fp16 = expand_dims(axes = input_203_axes_0, x = var_628_cast_fp16)[name = tensor<string, []>("input_203_cast_fp16")];
tensor<string, []> var_636_pad_type_0 = const()[name = tensor<string, []>("op_636_pad_type_0"), val = tensor<string, []>("valid")];
tensor<int32, [2]> var_636_strides_0 = const()[name = tensor<string, []>("op_636_strides_0"), val = tensor<int32, [2]>([1, 1])];
tensor<int32, [4]> var_636_pad_0 = const()[name = tensor<string, []>("op_636_pad_0"), val = tensor<int32, [4]>([0, 0, 0, 0])];
tensor<int32, [2]> var_636_dilations_0 = const()[name = tensor<string, []>("op_636_dilations_0"), val = tensor<int32, [2]>([1, 1])];
tensor<int32, []> var_636_groups_0 = const()[name = tensor<string, []>("op_636_groups_0"), val = tensor<int32, []>(1)];
tensor<fp16, [256, 5120, 1, 1]> resnet_seg_1_weight_to_fp16 = const()[name = tensor<string, []>("resnet_seg_1_weight_to_fp16"), val = tensor<fp16, [256, 5120, 1, 1]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(10790208)))];
tensor<fp16, [256]> resnet_seg_1_bias_to_fp16 = const()[name = tensor<string, []>("resnet_seg_1_bias_to_fp16"), val = tensor<fp16, [256]>(BLOBFILE(path = tensor<string, []>("@model_path/weights/weight.bin"), offset = tensor<uint64, []>(13411712)))];
tensor<fp16, [?, 256, 1, 1]> var_636_cast_fp16 = conv(bias = resnet_seg_1_bias_to_fp16, dilations = var_636_dilations_0, groups = var_636_groups_0, pad = var_636_pad_0, pad_type = var_636_pad_type_0, strides = var_636_strides_0, weight = resnet_seg_1_weight_to_fp16, x = input_203_cast_fp16)[name = tensor<string, []>("op_636_cast_fp16")];
tensor<int32, [2]> concat_1x = const()[name = tensor<string, []>("concat_1x"), val = tensor<int32, [2]>([-1, 256])];
tensor<fp16, [?, 256]> input_cast_fp16 = reshape(shape = concat_1x, x = var_636_cast_fp16)[name = tensor<string, []>("input_cast_fp16")];
tensor<string, []> input_cast_fp16_to_fp32_dtype_0 = const()[name = tensor<string, []>("input_cast_fp16_to_fp32_dtype_0"), val = tensor<string, []>("fp32")];
tensor<int32, [1]> var_640 = const()[name = tensor<string, []>("op_640"), val = tensor<int32, [1]>([-1])];
tensor<bool, []> var_641 = const()[name = tensor<string, []>("op_641"), val = tensor<bool, []>(true)];
tensor<fp32, [?, 256]> input_cast_fp16_to_fp32 = cast(dtype = input_cast_fp16_to_fp32_dtype_0, x = input_cast_fp16)[name = tensor<string, []>("cast_12")];
tensor<fp32, [?, 1]> norms_1 = reduce_l2_norm(axes = var_640, keep_dims = var_641, x = input_cast_fp16_to_fp32)[name = tensor<string, []>("norms_1")];
tensor<string, []> norms_1_to_fp16_dtype_0 = const()[name = tensor<string, []>("norms_1_to_fp16_dtype_0"), val = tensor<string, []>("fp16")];
tensor<fp16, []> var_644_to_fp16 = const()[name = tensor<string, []>("op_644_to_fp16"), val = tensor<fp16, []>(0x1.a38p-14)];
tensor<fp16, []> const_2_to_fp16 = const()[name = tensor<string, []>("const_2_to_fp16"), val = tensor<fp16, []>(inf)];
tensor<fp16, [?, 1]> norms_1_to_fp16 = cast(dtype = norms_1_to_fp16_dtype_0, x = norms_1)[name = tensor<string, []>("cast_11")];
tensor<fp16, [?, 1]> clip_1_cast_fp16 = clip(alpha = var_644_to_fp16, beta = const_2_to_fp16, x = norms_1_to_fp16)[name = tensor<string, []>("clip_1_cast_fp16")];
tensor<fp16, [?, 256]> var_647_cast_fp16 = real_div(x = input_cast_fp16, y = clip_1_cast_fp16)[name = tensor<string, []>("op_647_cast_fp16")];
tensor<string, []> var_647_cast_fp16_to_fp32_dtype_0 = const()[name = tensor<string, []>("op_647_cast_fp16_to_fp32_dtype_0"), val = tensor<string, []>("fp32")];
tensor<fp32, [?, 256]> embedding = cast(dtype = var_647_cast_fp16_to_fp32_dtype_0, x = var_647_cast_fp16)[name = tensor<string, []>("cast_10")];
} -> (embedding);
}